{"paper_id":"43919745-6031-463a-bb67-10fe2a5a3f5a","body_text":"A Review Report on Real Time Health Condition Monitoring of Devices in Solar Power Transmission Systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Review Report on Real Time Health Condition Monitoring of Devices in Solar Power Transmission Systems Venkata Govardhan Rao Kambhampati, Venkata Sai Kalyani Thalanki, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4336932/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As renewable energy generation grows globally, real-time asset management is crucial, particularly for offshore and remote systems. Electric grids are rapidly adopting renewable energy generation. Currently, there is no cost-effective condition monitoring method for real-time assessment of renewable energy sources, enabling intelligent asset management decisions to optimise utilisation and prevent unforeseen problems. Transformers are key assets that connect renewable generation plants to the grid. If one fails, generation can be lost for a lengthy time. The transformer in an on-grid system steps up or down voltage as needed. Transformer monitoring is crucial to Smart Grids. Transformer monitoring also allows demand analysis—what each family, business, or commercial institution consumes, where it consumes more, and when demand peaks. By its nature most renewable generation is intermittent, which places increased stress on transformers. To achieve an efficient, better and reliable generation of solar energy, it is necessary to monitor the transformers and solar generation system continuously. Hence in this work, real time health condition monitoring of devices in solar power transmission systems is presented. This system monitors the devices in real time with the help of IoT. Understanding transformer health and performance with real-time monitoring allows developing and optimizing proactive maintenance strategies for improving the performance of solar power transmission systems. Renewable Energy Smart Grid Transformer Solar Energy and Internet of Things I. INTRODUCTION Deploying renewable energy in India aims to promote economic development, enhance energy security, increase energy access, and address climate change concerns. Given the decline in fossil fuel availability, it is crucial to transition to renewable energy sources to meet our energy needs. Solar, wind, tidal, biomass, and geothermal energy are all promising alternatives that can help reduce our reliance on fossil fuels [ 1 ]. There has been a significant increase in the recent focus and development of renewable energy sources (RESs). Renewable energy sources are receiving a lot of research attention because of their cost-effective and environmentally friendly qualities. These days, solar power, wind farms, and battery energy storage have been getting a lot of attention. In many cases, RESs are typically installed in remote locations or offshore [ 2 ]. Renewable energy is projected to experience rapid growth in the electricity sector, with wind and solar PV being well-established and cost-effective options, according to the International Energy Agency (IEA). However, the global demand for energy continues to rise. Embracing renewable energy technologies is a highly effective method for minimising our environmental footprint [ 3 ]. Renewable energy sources have been widely recognised as dependable and are considered the most effective solution to address our increasing energy demands. The growing fascination with solar power, rising expenses, and the need for energy monitoring have led to several compelling reasons for its necessity [ 4 ]. Today, Solar Photovoltaic (PV) power is a cutting-edge development in the renewable energy market that helps to decrease the reliance on fossil fuel by-products. For optimal utilisation of solar power generation, it is crucial to focus on its storage and consumption. The power generated by the RES is directly sent to the loads or storage units. Meanwhile, the batteries are charged or discharged based on the real-time production values of RESs and the demands of the loads. Efficiently harnessing renewable electrical power is crucial. It has the potential to enhance system efficiency and alleviate strain on the power grid [ 5 ]. Solar power stations are highly regarded as a viable option for renewable energy systems in various locations. They offer a more cost-effective and low-maintenance alternative to conventional systems, while also requiring less space. Equipment is typically placed on an open terrace to control space occupancy in small generating stations [ 6 ]. The use of solar energy is easily available all around the world and has the potential to lessen dependency on energy that is imported. It is intriguing to think that the energy requirements of the entire world can be satisfied by just ninety minutes of sunlight lasting for an entire year. The functioning of solar photovoltaic (PV) systems does not result in the release of greenhouse gases (GHG) or any other pollutants. Solar energy provides a multitude of benefits, including the easy deployment of solar systems, the optimisation of operational methods, the precise forecasting of renewable energy, and the effective scheduling of power plants. In addition to this, it supports investments in flexible resources such as demand-side resources, grid infrastructure, power storage, and flexible generation. Electrical networks need energy storage systems (ESSs) to handle renewable energies (REs)' unpredictability and generate stable, high-quality electricity. Standard energy storage systems use static power converters to connect storage mediums to the grid. Based on application needs, the storage medium must absorb, store, and deliver electrical energy. Renewable energy is practical and necessary in current society. Renewable energy, like hydroelectric, thermoelectric, and nuclear power, uses a grid system to efficiently distribute and manage electrical energy [ 7 ]. Generator, grid, and customer make up the electric energy system. All three must be balanced and monitored. The smart grid is essential for bringing together all parties [ 8 ]. The smart grid is described as a groundbreaking endeavour that involves the implementation of advanced communication and control systems, diverse energy sources, innovative generation methods, and compliance with regulatory frameworks across different jurisdictions. One of the goals in the Enhancing Aquatic Renewable Energy project is to seamlessly incorporate the Renewable Energy source into the smart grid. Smart Grid (SG) offers the energy industry a chance to enter a new era of improved reliability and efficiency [ 9 ]. Electricity equipment is vital to the electricity grid's operation. Internet of Things technology is being adopted in the power business, so monitoring power equipment status via IoT has great research potential [ 10 ]. Most grid power comes from fossil fuels. A Smart Grid is necessary for a new era. A successful renewable microgrid system needs accessible sources. Understanding availability and properly controlling load on different sources helps improve system reliability. It works well with a good monitoring system. Managing energy sources and integrating them into the grid is difficult [ 11 ]. Smart grids improve power system efficiency and renewable energy management. An advanced smart grid uses sensors and controllers to monitor the electricity system and make real-time adjustments. For two-way data flow, a smart grid includes distributed energy resources (DERs), distributed computation, and communication networks. This balances power supply and demand and maximises socioeconomic benefits [ 12 ]. On-grid solar systems produce electricity solely when the utility power grid is accessible and linked directly to the utility feed. When you have an excess of power, on-grid systems will send it back to the utility grid. These systems are incredibly efficient and easy to install. These systems can easily cover their own costs by reducing energy bills within a span of 3–8 years. On-grid systems can be implemented with or without net metering. Solar power systems connected to the utility grid generate power on-grid. These devices distribute excess solar power to the utility grid, compensating users. They work with the electrical grid. When there's not enough sunshine for your business, the system uses grid power. When you have excessive power use and wish to minimise your electricity expenses, these methods work best. Since they depend on the grid, these systems fail during power outages. Power transfer between the power grid, battery, and load usually needs rectification, inversion, or frequency conversion. The converter permits electricity flow in both directions [ 13 ]. Independent off-grid systems store solar electricity in batteries. Solar panels, battery, charge controller, grid box, inverter, mounting structure, and balance of systems are typical. The solar panels can store enough sunlight during the day and use it at night. Off-grid systems store and use solar electricity through batteries, assuring power during grid outages. Designed to be self-sufficient. Off-grid solar plants can power crucial loads during power outages. These systems can power crucial loads without a power grid. However, these systems require special equipment and are costly to install. These are ideal for enterprises that can run without power. Many solar developers suggest installing an on-grid solar system and considering a backup DG if needed. However, for remote areas without access to a reliable grid, an off-grid system may be a suitable alternative. Given the rising peak demand and the necessity to enhance grid infrastructure for efficient operation and reliable management, the distribution smart grid plays a crucial role in expediting the modernization of the ageing power system. Smart technologies have a significant impact on the distribution grid. Implementing remote control and automation of the grid can lead to cost savings, improved data accuracy, and efficient troubleshooting of electricity system issues [ 14 ]. As the IOT (internet of things) grows, grids may easily connect customers and suppliers for two-way communication. This allows remote energy control and real-time monitoring. Distributed energy resource (DER) aggregation and control are handled by these systems [ 15 ]. Solar PV systems need an inverter to convert DC power into AC power at grid voltage. Grid-connected PV system inverter architecture must be efficient and cost-effective [ 16 ]. Transformers are essential to solar energy production and distribution. Transformers have been used to boost or decrease non-renewable energy. Solar transformer design must prioritise durability, stability, and long-term operation. Transformers with low input voltage. High-order harmonics and DC components from transportation can impair solar inverters and panels. Solar transformers can be distribution, station, substation, pad-mounted, or grounding. PV cells convert solar energy into DC to generate electricity. Inverters convert DC to AC and connect this to the electrical grid via a step-up transformer. For substations to supply power to nearby locations, transformers must work properly. It is the heart of any transmission. It clarifies power production decisions and boosts power consumption. Power transformers are precious, thus condition monitoring is vital for maintenance. Critical transformer failure in a transmission grid could threaten energy security. Different loads can degrade a power transformer's insulation, reducing its lifespan. Thermal, electrical, mechanical, and environmental loads are included. PV cells produce DC power, which an inverter converts to AC power. This AC power can be paralleled to the grid using a step-up transformer. However, the inverter adds DC and harmonic components when it converts PV panel DC output to AC. This reduces power quality and increases transformer vibration and noise, especially with amorphous alloy transformers. Furthermore, DC and harmonic components increase transformer no-load losses. The distribution transformer serves as the final element in the power grid for voltage transformation. It is utilised for transforming medium voltage into low voltage, which is suitable for residential or commercial purposes. Distribution transformers play a crucial role in the distribution power system. Distribution transformers (DT’s) are vital components in electrical distribution networks, serving as central hubs. Ensuring their proper function is crucial for maintaining a reliable power supply to consumers. If a critical transformer were to fail catastrophically, it would lead to power outages in the downstream network and potentially create substantial economic and environmental difficulties. DTs are typically found on the feeders below the substation, with a majority of them being mounted on poles. There are numerous elements that contribute to suboptimal performance and have a negative impact on the lifespan of DT. Each HV/MV primary substation has many subordinate substations. Distribution transformers number around 1,000 in a medium-sized city with 40 HV/MV primary stations. Many fall into decay each year for various reasons. Oil leakage, overloading, uneven loading, and harmonics increase distribution transformer degradation and failure. Over time, electrical, mechanical, and thermal strains on power transformer components cause most failures. Transformers are frequently used in power supply systems to convert AC voltage and provide galvanic isolation for components. Smart grids have become a topic of great interest among researchers in recent times. They possess unique power-generating capabilities and can provide electricity, particularly to conscientious customers during critical situations. Electricity can be generated from a variety of sources, such as nuclear power plants, autonomous diesel electric units, large batteries, wind farms, solar panels, and hydrogen fuel cells. When integrating various energy sources into smart grids, it is crucial to effectively coordinate different stress levels. It becomes more complex when dealing with electrical energy, as it is generated or stored in both DC and AC systems. If the input voltage is asymmetrical and there are variations in frequency, it will have a negative impact on the output voltage of the classic transformer, as there are no enhancements or alterations to mitigate these effects. These transformers rarely possess the intelligence and communication capabilities. Insufficient data regarding the loading of the transformer is a major factor contributing to the inefficiency of the distribution network. Whenever there is an issue with these transformers, customers promptly inform the authorities. Transformers should be carefully monitored on a regular basis to prevent any unexpected interruptions and anticipate potential issues. Developing reliable and cost-effective remote monitoring systems has been crucial for the evolution of the smart grid, particularly in electricity distribution. Several techniques have been devised to assess the condition of transformers. As transformers get older, their internal insulation breaks down. This can heighten their chances of experiencing failure and becoming more susceptible to severe circumstances like lightning strikes and short-circuits. Insulation degradation is primarily caused by overloading and excessive temperatures, thorough, and ongoing monitoring is necessary. Typically, diagnostic methods for distribution transformers were traditionally conducted offline, requiring the transformer to be taken out of service. Thanks to advancements in information technology and smart sensor devices, it is now possible to assess the status of transformers in real-time. The monitoring process is conducted online and in real-time, which significantly enhances the accuracy of the condition analysis for the transformer. Monitoring distribution transformers in real-time can provide valuable insights into potential failure risks. Therefore, additional analysis can be conducted to easily identify the development trend of risks and make timely decisions to prevent unexpected and catastrophic equipment shut-downs. Monitoring transformers allows for real-time analysis of their condition, which in turn helps assess the potential risks to their availability. To effectively assess the condition of the transformer and identify potential issues, the monitoring system needs to conduct physical measurements and analyse the data within the relevant environmental conditions. Implementing efficient techniques to monitor the condition and well-being of distribution transformers can assist utilities in taking proactive measures to prevent failures and deterioration. The Internet of Things (IoT) connects nearby things via wired and wireless networks without user participation [ 17 ]. Through IoT, items communicate and exchange information to provide advanced intelligent services. With the proliferation of sensors and communication modules in modern mobile devices and sophisticated network technologies like Wi-Fi, LTE, and 5G, the Internet of Things (IoT) has garnered academic and industry attention. By connecting things to the Internet, IoT senses, activates, collects, stores, and processes data. IoT services such object tracking, environmental monitoring, healthcare, traffic management, smart security, smart home, and smart city are being researched. Transformer monitoring is crucial due to smart grid technologies and IoT-based smart grids. II. LITERATURE SURVEY Munish Kumar, Ahmad Faiz Minai, Akhlaque A. Khan, Satish Kumar, et al. [ 18 ] discusses an IoT-based energy management system designed for smart grids. This paper explores the utilisation of IoT in conjunction with Smart Grid to enhance power efficiency, reduce losses, and minimise energy wastage, resulting in economic benefits. IoT is also utilised for the transmission of real-time data to the Smart Grid, enabling energy conservation when demand fluctuates. Communication between users and suppliers has been facilitated by IoT for this system. R. Govindarajan, S. Meikandasivam, D. Vijayakumar et al. [ 19 ] exhibit real-time smart energy monitoring system performance analysis. Performance is analysed for smart real-time energy monitoring system design and implementation. Advanced wireless technologies like Zigbee, IoT, Android Mobile Apps, and cloud computing connect metres to consumers in the proposed systems. A digital power metre in the main panel interfaces with a communication gateway to measure voltage, current, power, power factor, and household appliance harmonics in real time. Cheng-Yu Tang and Jun-Ting Lin et al. [ 20 ] explain Energy Storage System Multi Input Converter Bidirectional Power Flow Control. This work shows a multi-input DC-DC converter with bidirectional power flow control. The Multi-Input Converter (MIC) reduces components and circuit cost compared to the power converter. Bidirectional power flow control and independent input current control are possible with the proposed MIC circuit. This technique will give detailed circuit analysis and mathematical derivation of the suggested MIC. Mr. Adinath S. Satpute, Prof. Dr. G. U Kharat, Prof. R. S Bansode et al. [ 21 ] discuss WoT-based Smart Grid System to Monitor and Control Renewable Energy Source. This article describes a basic electric and smart grid system for renewable energy sources based on WoT, including different methodologies, its basic working system and specifications, and a control panel GUI for easy access and strategy that appeals to advanced digital technology and information management practices and appropriate base modernization electrical delivery infrastructure. Maisagalla Gopal, T Chandra Prakash, N Venkata Ramakrishna, Bonthala Prabhanjan Yadav et al. [ 22 ] propose IoT-Based Solar Power Monitoring System. IoT-supervised solar energy can improve plant performance and monitoring. It monitors solar panel dust to maximise active power. Radiation hits the solar cell, determining solar panel output power. The central controller monitors the panels and loads with all panels attached and sensors perfectly connected. Thus, user may see current, voltage, and sunshine. Doha's Photo-Voltaic (PV) Monitoring System, Performance Analysis, and Power Prediction Models are explained by Farid Touati, Amith Khandakar, Muhammad E.H. Chowdhury, Antonio Jr. S.P. Gonazales, Christian Kim Sorino, and Kamel Benh This work customises data collection for harsh climate solar systems utilising off-the-shelf components and data analytics for performance evaluation and prediction. Custom signal conditioning for extreme temperatures, microcontroller Development Board with interface shields, and wireless data transmission to icloud IoT platforms. We created an automatically changeable in-house electronic load to measure the PV system's maximum power. Hongchang Ke, Jian Wang, Hui Wang, Yuming Ge et al. [ 24 ] improve IoT device data offloading and resource allocation using Deep Reinforcement Learning. Their model offloads data and considers renewable energy for a MEC (Mobile Edge Computing) server with several stochastic computing jobs and time-varying wireless channels. Their deep reinforcement learning (JODRBRL)-based joint optimisation solution for data offloading, renewable energy aware, and bandwidth allocation for IoT devices can manage the continuous action space and escape the curse of dimensionality caused by its complexity. Arturo Garcia, Hélia Guerra et al. describe a cheap IoT device for CIVISA's multiparameter remote stations' renewable energy system monitoring [ 25 ]. They developed a low-cost voltage metre prototype with data logging, LAN transmission, and IoT for several sites. Prototype testing was successful, and network stations can replicate the product. Sanwar Hossain, Mostafizur Rahman, Tuhin Sarker, Ershadul Haque, and Abu Jahid et al. [ 26 ] present a Smart IoT-Based System for Monitoring and Controlling Sub-Station Equipment. This paper shows an IoT-based network strategy for monitoring and regulating sub-station equipment to optimise time and resources. The IoT-based system allows objects to be sensed or controlled remotely across existing network infrastructure, enabling more direct integration of the physical world into computer-based systems and improving efficiency, accuracy, and economic benefit with minimal human intervention. Supriya Ghodake, Priyanka Ghadage, Neha Patil, Prof. Akshay Jadhav et al. [ 27 ] presented Arduino-based Remote Solar Power System Health Monitoring. This project uses IoT to remotely monitor a solar facility for performance evaluation using new cost actual technique. This will simplify preventive maintenance, solar panel defect detection, and real-time monitoring. This technology is used in solar cities, smart villages, micro grids, and street lights. Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua, “Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua et. al., [ 28 ] describes a Research on characteristics of bidirectional CLLC DC–DC transformer used in DC microgrid. Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua, “Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua, “Research on characteristics of bidirectional CLLC DC–DC transformer used in DC microgrid. This work verifies a bidirectional full-bridge CLLC resonant converter for high-frequency galvanic isolation of a 380 V DC microgrid system and controls bidirectional power flow. The converter can operate in ZVS (Zero Voltage Switching) under soft switching of the main switch and output rectifier. In addition, the converter does not need any clamp and buffer circuit to reduce the voltage stress of the power switch. Chang-Sic Choi, Jin-Doo Jeong, Il-Woo Lee, Wan-Ki Park et. al., [ 29 ] presents LoRa based Renewable Energy Monitoring System with Open IoT Platform. The authors describe the implementation of monitoring system for renewable energy generation facilities with the system architecture, implementation method, and analysis program. We use various open IoT platform such as Arduino, Raspberry Pi and low-cost LoRa network. In the future, we will carry out research result on the performance analysis and improvement solutions after operating on the testbed site for a long time. J.E. Shuda, A.J. Rix; M.J. Booysen et. al., [ 30 ] discussed Towards Module-Level Performance and Health Monitoring of Solar PV Plants Using LoRa Wireless Sensor Networks. LoRa was chosen as the wireless technology due to its long range and low power consumption. A couple of sensor nodes and a gateway was designed built and tested. Range test were conducted to ensure that the chosen wireless technology meets the range requirements found on a typical PV plant. Module-level measurements were taken on different solar modules over a period of a few weeks. Range and Measurement test results shows that the sensor nodes and wireless technology is a sufficient solution for a WSN that is capable of measuring module-level performance parameters on a utility scale PV plant. K Sai Chandu, Macharla Bharath et. al., [ 31 ] demonstrates Bidirectional Hybrid Coupled Transformer for Battery Energy Storage System. A novel 3phase-inverter, which consists of multiple distributed BBCs and a Voltage Doubler using PV and wind source, for the battery energy storage system has been proposed in this paper.The proposed 3phase-inverter has individual power control capability for each battery module while fulfills the functions of battery charging and discharging by using pulsating current. Eventually, the equalization, lifetime extension, and capacity flexibility of the battery energy storage system can be achieved. Suprita M. Patil, Vijayalashmi M, Rakesh Tapaskar et. al., [ 32 ] presents IoT based Solar Energy Monitoring System. This system refers to the online display of the power usage of solar energy as a renewable energy. This monitoring is done through raspberry pi using flask framework. Smart Monitoring displays daily usage of renewable energy. This helps the user to analysis of energy usage. Analysis impacts on the renewable energy usage and electricity issues. Yu Jianyang, Muhammad Qasim Khan, ZhangYanwen, Muhammad Mansoor Khan, Muhammad Ali et. al., [ 33 ] demonstrates HVDC Bidirectional Power Flow Using Solid State Transformer. A new topology was presented to control DC power flow through an Interline DC Power flow controller (IDCPFC) with Solid State Transformer (SST). In the proposed method, the boost converter is used to achieve increased output voltage from the input voltage and its current is regulated through the duty cycle of the converter. The control algorithm of this technique is smooth and easy to deploy. Prutha M. Badave, B. Karthikeyan, S. M. Badave, S. B. Mahajan, P. Sanjeevikumar & Gurjit Singh Gill et. al., [ 34 ] presents health Monitoring System of Solar Photovoltaic Panel: An Internet of Things Application. A wireless remote monitoring system for solar photovoltaic (PV) plant is proposed in this paper. It is an Internet of Things (IoT) application implemented with an objective to offer a cost-effective solution of monitoring system, which continuously presents remote energy yields and its performance either on computer or on handheld gadgets such as smart phones. On board Wi-Fi, wireless communication enhances the system performance with reduced area and facilitates to monitor system parameters. Jayaharsha Kandimalla, Dr. D. Ravi Kishore et. al., [ 35 ] demonstrates Web Based Monitoring of Solar Power Plant Using Open Source IOT Platform Thing speak and Arduino. They developed a prototype for implementation of new cost-effective methodology based on IoT to monitor a solar photovoltaic plant for performance evaluation using open-source tools and resources like Arduino and Thing speak. Thing speak is a SaaS (Software as a Service) platform which provides space on Web to monitor our parameters. Thing speak provides all services for free of cost. Which saves lot of investment on Website designing and maintenance. We focussed on low-cost system with easy interface so that common people who installs roof top solar plants also monitors easily without depending on service providing companies. Eugene Y. Song, Gerald J. FitzPatrick, and Kang B. Lee et. al., [ 36 ] demonstrates Smart Sensors and Standard-Based Interoperability in Smart Grids. This work describes sensing, timing, intelligence, and communication requirements of sensors for the SGs (Smart Grids) and describes a general model of the SSs (Smart Sensors) for SGs based on these requirements. Then it illustrates, how the model works with phasor measurement unit (PMU)- and merging unit-based SSs deployed in the SGs with standardized interfaces to support the interoperability of the SSs. This work describes sensor interface standards used in the SGs and the need for interoperability testing and proposes a passive interoperability test method for the SSs to achieve and assure sensor data interoperability. To verify this test method, an interoperability test system for the PMU-based SSs was developed and presented. Jaswinder Singh, and S.K. Aggarwal et. al., [ 37 ] presents Distribution Transformer Monitoring for Smart Gridin India. This paper introduces the Distributed Transformer Monitoring System using Field Programmable Gate Array based technology integrated with wireless communication modules and its utilization for a smart grid. It consists of network of sensors and energy meters. The whole architecture and the hardware & software flow of the system have been explained. The developed approach effectively monitors the network of transformers operating state, dispatches the critical information, thus helps utility operator to keep transformer in service for long life. It is also having the advantages of significant cost savings and greater reliability. Jaswinder Singh, and S.K. Aggarwal et. al., [ 38 ] presents Distribution Transformer Monitoring for Smart Grid in India. This paper introduces the Distributed Transformer Monitoring System (DTMS) using FPGA based technology integrated with communication modules and its utilization for Smart Grid. It consists of network of sensors and energy meters and communication over wireless network. A trail was given on the implemented system for testing and results came out as expected. Diogo Varajao, Lu´ıs M. Miranda, Rui E. Araujo, J. Pec¸as Lopes et. al., [ 39 ] describes Power Transformer for a Single-stage Bidirectional and Isolated AC-DC Matrix Converter for Energy Storage Systems. This paper presents an approach to design the transformer and the link inductor for the high-frequency link matrix converter. The proposed method aims to systematize the design process of the HF-link using analytic and software tools. A 10 kW / 20 kHz transformer plus a link inductor are designed using this strategy achieving a combined efficiency of 99.32%. P. Pounraj, D. Prince Winston, S. Cynthia Christabel, R. Ramaraj et. al., [ 40 ] demonstrates A Continuous Health Monitoring System for Photovoltaic Array Using Arduino Microcontroller. In this paper new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This technique can classify the health status into four categories such as Healthy, Low Fault, Medium Fault and High Fault. By this classification faulty operation can be rectified and power generation may be improved. In case of high faults, PV panels can be protected. The cost requirement for the implementation is very low. Mr. Vikas S. Chandre, Prof. Ravindre G.Dabhade et. al., [ 41 ] presents Smart Grid System To Monitor and Control Renewable Energy Source Based on Web of Things. This system consist of three major subsystems namely power generation and storage, power monitoring and billing and power control and managing by using WoT. WoT technology can effectively combine the infrastructure resources in increase the quality of power system information and increases the utilization efficiency of infrastructures in the existing power system. The part of vision of a smart grid is its ability to enable informed participation by customers making them an integral part of the electrical power. Mayorkinos Papaelias Liang Cheng, Maria Kogia, Abbas Mohimi Vassilios Kappatos, Cem Selcuk, Louis Constantinou, Carlos Quiterio Gómez Muñoz, Fausto Pedro GarciaMarquez, Tat-HeanGan et. al., [ 42 ] presents Inspection and Structural Health Monitoring techniques for Concentrated Solar Power plants. This work discusses the non-destructive evaluation techniques that can be employed to inspect solar receivers and insulated pipes as well as relevant research and development work in this field. With the increased use of solar tower technology, the accurate evaluation of the structural integrity of volumetric solar receivers after they are manufactured but also during their in-service lifetime will become more necessary. P. Pounraj, D. Prince Winston, S. Cynthia Christabel, R. Ramaraj et. al., [ 43 ] describes A Continuous Health Monitoring System for Photovoltaic Array Using Arduino Microcontroller. In this work, new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This technique can classify the health status into four categories such as Healthy, Low Fault, Medium Fault and High Fault. By this classification faulty operation can be rectified and power generation may be improved. In case of high faults, PV panels can be protected. The cost requirement for the implementation is very low. The proposed technique is implemented in MATLAB Simulation and hardware. The array considered in this paper is 2 × 2 Series Parallel. Carlos R. Baier, Miguel Torres, Javier A. Muñoz, Marco Rivera, Eduardo Espinosa N, Pablo Acuña et. al., [ 44 ] describes Bidirectional Power Flow Control of a Single-Phase Current-Source Grid-Tie Battery Energy Storage System. This paper presents the modelling and control of a battery energy storage system (BESS) connected to the grid by a single-phase current source inverter. A bidirectional DC/DC converter connects the battery bank to the dc bus of the inverter allowing power flow in both directions. An integrated non-linear control strategy is proposed to control both converters and to manage the power flow direction between the BESS and a stiff grid. Kouhei Hayashia, Ryosuke Katoa, Ryosuke Toriia, Hisao Taokaa and Rikiya Abe et. al., [ 45 ] demonstrates Bi-directional power flow through a digital grid router. They demonstrate a control method of bi-directional power flow. We verify its possibility by doing an experiment. Through this method, one can control the direction of current flow through a ‘leg’ and the value of current by hysteresis control. Hysteresis control is a method which controls the switching of an insulated gate bipolar transistor ‘IGBT’ by comparing output current and reference current having constant width of the amplitude of reference current. Mohd Nafis Akram; Saeed Lotfifard, et. al., [ 46 ] demonstrates Modelling and Health Monitoring of DC Side of Photovoltaic Array. To implement and validate the presented method in computer programs, a new approach for modelling PV systems is demonstrated that only requires information from manufacturers datasheet reported under normal-operating cell temperature (NOCT) conditions and standard-operating test conditions (STCs). This model precisely represents characteristics of PV systems at different temperatures, as the temperature dependency of parameters such as duality factor, series resistance, and thermal voltage is considered in the proposed model. Shruti Tiwari, R N Patel et. al., [ 47 ] demonstrates Real time monitoring of solar power plant and automatic load control. The objective of this work is to develop a power management system for optimum utilization of generated power from Solar PV power plants. This is to alleviate the existing situation wherein the net solar power utilization is effectively only about 50%. Some of the features of this scheme are automatic load switching, advanced remote metering & control, and priority-based switching. Wen Yen Lin, Kuang Po Hsueh, Wang Hsin Hsu; Liew Gha Yie, Wei Chen Tai et. al., [ 48 ] demonstrates the Design and Implementation of Health Monitoring System for Solar Panel in IPv6 Network. They describe a remote monitoring system of solar panels via IPv6 wireless network, in which the parameters of environment and panel voltage would be sent to the Smart Analysis Database System. Then we can monitor the health of the Solar Plant by using the Android mobile platform anywhere and anytime. The administrator not only can use a mobile device to maintain the solar plant and smart home device via IPv6 Network without NAT transformation, but also receive the message immediately when the status of solar panel or home device is abnormal. Priyanka Biradar, Shruthi. M et. al., [ 49 ] describes New Intelligent Semiconductor Transformer with Bidirectional Power-Flow Capability. This work demonstrates a new intelligent semiconductor transformer (IST) which consists of a bidirectional ac/dc resonant converter, dc/dc converter, and dc/ac converter. This structure pro-vides good voltage-balancing performance on the high-voltage side and a simple control method for bidirectional power flow. A three-phase transformer can be implemented with three units of the demonstrated IST. Salvador Alepuz, Francisco González-Molina, Jacinto Martin-Arnedoc, Juan A. Martinez-Velasco et. al., [ 50 ] describes Development and testing of a bidirectional distribution electronic power transformer model. A model for a bidirectional high-frequency power electronic transformer is presented. Several case studies have been carried out in order to evaluate the behaviour of the transformer under different operating conditions and test the impact on the power quality. The results show that the electronic power transformer, also known as solid-state transformer, not only matches the functions of a conventional power transformer, but also provides additional capabilities to mitigate dynamic power quality problems. III. REAL TIME HEALTH CONDITION MONITORING In this section, Real time health condition monitoring of devices in solar power transmission systems is presented. The monitoring system has three modules. The first one is the real-time monitoring to the overall system; this is the dashboard that gives the user the general information in real-time about the energy grid. The second module monitors transformer in real-time. The electrical and environmental variables of the node (generator or load) can be monitored if needed. The third component is the reporting function. PV systems whose power is directly fed into the utility or electric grid are generally known as grid-connected PV systems. These are also called on-grid or grid-tied PV systems. These PV systems are capable of only feeding energy into the grid. A typical grid-connected PV system consists of components of PV modules, an inverter, a transformer, and a utility meter. PV systems that generate electricity to be used locally at the generation centre without being injected into a utility grid are called stand-alone PV systems. Here, mostly the energy generated is consumed and any available excess will be stored in batteries. A few examples of such systems are solar streetlights, solar water pumping, and rooftop home solar PV systems. A solar power transformer is used in solar power applications. A solar panel transformer has to convert the DC voltage coming out of the photovoltaic systems and step it up to the rated output. This can also be called as a solar inverter transformer because it inverts DC to AC. Photovoltaic power generation can be divided into two types according to how it is connected to the grid: off-grid and grid-connected. The majority of PV plants are currently grid-connected, i.e. connected in parallel to the existing power supply network to maximise the use of the electricity generated by the plant. The Fig. 1 shows the schematic of IMWP solar PV system connected to the utility grid. Inverters and transformers used in photovoltaic power stations are one of the important nuclear components of photovoltaic power stations. Inverters realise the conversion from DC to AC, and transformers realise the transmission and utilisation of electrical energy. In order to reduce line transmission losses and increase transmission distances, the voltage of 270V or 400V at the outlet of the PV inverter needs to be raised and then output, i.e. a step-up transformer is installed to raise the voltage to l0kV or 3kV depending on the capacity of the power station, which reduces transmission line losses while also making the system electrically physically isolated. Photovoltaic power generation network in normal operation, must have measurement, safety protection, control, remote communication and other functions, detect the operation of the power distribution system, judge the state and make the necessary control instructions, but also all the information will be transmitted to the monitoring in a timely manner also, the degree has the basic requirements of intelligent photovoltaic pad mounted transformer. Considering the particularity of photovoltaic power generation, that is, power generation during the day, no matter whether the power generation device outputs power or not, as long as the transformer is connected to the system, the transformer will always produce no-load loss. The load loss of the transformer is required to be as low as possible. If the transformer runs at night, the no-load loss is also required to be low; It is necessary to consider the dependency of the studied methods on the load condition, temperature, and the effect of transformer aging over time. The primary function of transformer oil is to protect the winding and core of the transformer. It helps dissipate heat i.e. act as a coolant, prevents arcing and corona, protects the insulation, and stops any kind of oxidation to take place within the transformer tank. The dielectric breakdown test on the insulating oil of a transformer can help determine its level of contamination. If in-service oil testing is performed, it can help determine the remaining life and operational safety of the transformer and help prevent equipment res. For in service equipment, it is recommended to test the oil at least once a year. Modern PV inverters usually produce the sinusoidal voltage, and the current waveform is similar to the ideal sine wave. So, grid-tie transformers generally do not need to be large in the event that solar power inverters operate them. General-purpose transformers are typically specifically designed. Non-linear loads could cause the voltage and current to cause Total Harmonic Distortion (THD) which could impact the transformer's performance and cause an increase in heating. The environmental conditions, like ambient temperature, must also be taken into consideration. Grid-tie transformers typically don't experience a maximum load or, if they do, it will last less than an hour, based on typical load curves for solar facilities. Partial discharge monitoring is a commonly recognized method for early fault diagnosis. PD monitoring is a promising, rapidly developing method for high-voltage equipment condition monitoring. PD intensity is an important diagnostic feature of oil and solid insulation condition. Partial discharge as a localized electrical discharge that only partially bridges the insulation between conductors. In practice, PDs are both symptoms and causes of insulation aging, and they can cause equipment failure in the long term. PD monitoring helps prevent early aging of insulation. Meanwhile, it is crucial to know the characteristics of the discharge itself for the purposes of monitoring, PD power, usually reduced to PDI-Partial Discharge Intensity. This parameter is defined as the total energy of discharges divided by the time of their summation, which is why it has the same dimensionality as power. The parameter describes the power and intensity of PD and is determined by the dependency. $$PDI=\\frac{1}{T}\\sum _{i=1}^{m}{Q}_{i}{U}_{d} \\left(1\\right)$$ 1 Where m is the number of pulses recorded over the observation time T; Ud is the effective voltage. A drastic increase in Q02 and PDI is an unambiguous sign of insulation destruction. If these values change significantly over 3–4 observations, or at least double over a year, then the insulation has an expanding. When the applied voltage to a transformer is sinusoidal, the core flux rises from -Φm to + Φm during the positive half cycle of the applied voltage. If the transformer is switched ON at an instant when the instantaneous value of applied voltage is at its positive peak, then the flux would rise from its natural zero value up to + Φm during the next quarter cycle (Magnetizing lags voltage by 90deg). The magnetising current required would remain normal and the switching of the transformer would be trouble free. However, if the instantaneous value of applied voltage at switching instant is zero and going towards positive, then the core flux would rise from its natural zero value to + 2Φm in the next half cycle. This phenomenon is also known as doubling effect. This flux doubling is accompanied by a huge magnetizing inrush current which may reach 5 times the full load current or higher, leading to massive winding forces and a possible dip in the system. Magnetizing inrush is highly unsymmetrical and stays for quite a few cycles, decaying according to the time constant of the system. The inrush current is expected to delay quickly if the system is switched on resistive load or capacitive loads. However, it would delay slowly if switched on NO load or with inductive load (which is the case for most Grid connected Solar Power Plants). Inrush current curve: Inrush current is a form of transient over current present during the energization of transformers. It depends on the residual flux of the transformer, magnetic characteristic of the core & voltage waveform at the time of switching. The individual harmonic voltage distortion levels can be established by performing this calculation for the p.u. current associated with each harmonic number. The Voltage Total Harmonic Distortion (THD) is then calculated by establishing the square root of the sum of the squares of these individual Voltage harmonics. When a sinusoidal signal of frequency ω passes through a non-ideal, non-linear device, additional content is added at multiples nω (harmonics) of the original frequency. THD is a measure of that additional signal content present in the input signal $${THD}_{F}=\\frac{\\sqrt{{V}_{2}^{2}+{V}_{3}^{2}+{V}_{4}^{2}\\dots }}{{V}_{1}}$$ 2 Where THD is total harmonic distortion and Vn = RMS voltage of nth harmonic IoT is the network of physical devices embedded with electronics, software, sensors, actuators and network connectivity which have the ability to identify, collect and exchange the data. Each thing is uniquely identifiable through its embedded computing system and able to interoperate within the existing internet infrastructure. Various sensors are installed on the transmission line to collect environmental data information (Parameters such as temperature, relative humidity, transformer characteristics, air pressure, rainfall, light radiation, etc.), in real time and perform analysis and processing to realize the real time monitoring of the operating environment of power equipment. As said before, one of the main objectives of the sensing system is to enhance the use of renewable energy, so all the data gathered by the system must be analyzed to generate models to enhance the control and the performance of the grid. The Communication Module (CMM) handles the exchange of information between different modules and devices. The basic components used in this monitoring system are sensors that measure the parameters in a PV system in actual conditions. The signal processing unit is another significant unit. This unit amplifies and clears signals for subsequent processing. Also, this unit includes a processor that sends the signal processing unit outputs to a PC through a dedicated protocol in real time. The PC is applied for analyzing, saving, and showing data. According to data analysis and user commands, information is transmitted to the control unit for subsequent operation. Sensor selection depends on the monitoring objectives and location. The main sensors used in this monitoring system to evaluate the aforementioned parameters are current sensors, voltage sensors, solar irradiance sensors, temperature sensors, anemometer wind speed sensors, hygrometer sensors, and barometer pressure sensors. The data acquisition system (DAS) plays an important role in any monitoring system and is used to collect data from different sensors of a PV system. Then, this data is digitalized for storage and the DAS sends data to the control center for processing and presentation. The Thing Speak IoT platform enables clients to update and receive updates from channel feeds via the Thing Speak MQTT (Message Queuing Telemetry Transport) broker. MQTT is a publish/subscribe communication protocol that uses TCP/IP sockets or Web Sockets. MQTT over Web Sockets can be secured with SSL (secure sockets layer). Features of Thing Speak include real-time data collection, data processing, visualizations, apps, and plugins. At the heart of Thing Speak is a Thing Speak Channel. A channel is where one can send their data to be stored. Each channel includes 8 fields for any type of data, 3 location fields, and 1 status field. The secondary module provides all the information to operator to inspect whether transformers work correctly. The operator can visualize the entire network using the interactive graphical interface and easily navigate from one window to other. Control center receives the information from each transformer in a fixed time, the information is presented in the useful format, and operator can see the various data i.e. any transformer violating the threshold limits, over loading, unbalancing etc. In the event of a system quantity crossing the predefined threshold, an alarm is automatic generated for operator intervention and SMS is sent to concern field engineer. The operator can visualize the entire network using the interactive graphical interface. If the condition of transformer is measured accurately then the efficiency of solar power plant will be improved. IV. RESULT ANALYSIS In this section, real time health condition monitoring of devices in solar power transmission systems is implemented. The real time health condition monitoring of devices is performed using IoT. The main cause behind the altered performance of transformer in the presence of solar panel is its associated inverters that are used to supply linear loads. A higher temperature rise will occur in the windings and cores of the transformer due to voltage and current harmonics, resulting in extra losses. The temperature and hot spot calculation and aging rate of transformer are calculated from international standards. The average ambient temperature for a transformer over a 24-hour period should not exceed 30 degrees Celsius. For instance, if the transformer ambient temperature was 40 o C for 12 hours, then the transformer must not exceed 20 o C for the remaining 12 hours to average a 30 o ambient temperature. If the average ambient temperature exceeds 30 degrees Celsius, the derating factor is 0.4% reduction of VA for every degree Celsius above 30 degrees Celsius per IEEE C57 12.96. The IEEE formula that is used to derive the 0.4% factor is valid only up to an AVERAGE of 50 degrees Celsius. Also, using transformers above their listed ambient temperature can shorten the life of the transformer. Due to the number of other factors involved, such as loading, frequency of use, and humidity, no data exists on how high ambient temperatures affect the life of a transformer. The transformer life is established as a function of hot spot temperature (noted as 𝜃 𝐻 ) which is computed by ambient temperature and load. Then, 𝜃 𝐻 is provided as an input variable to acquire the thermal aging acceleration factor 𝐹 AA $${F}_{AA}=\\text{exp}\\left(\\frac{15000}{383}-\\frac{15000}{{\\theta }_{H}+273}\\right)$$ 3 When 𝜃 𝐻 is the reference temperature. 𝐹AA is equal to 1. Based on this definition, the loss of life in a given time period is presented as $${F}_{EQA}=\\frac{{\\sum }_{n=1}^{N}{F}_{AA}\\varDelta {t}_{n}}{{\\sum }_{n=1}^{N}\\varDelta {t}_{n}}$$ 4 $$\\% Loss of life=\\frac{{F}_{EQA}\\times t\\times 100}{Normal Insulation life}$$ 5 Where 𝐹EQA is the equivalent aging factor in the total time period, 𝐹 AA𝑛 is the aging acceleration factor during the time interval Δ𝑡 𝑛 , 𝑁 is the total number of time intervals, and “Normal insulation life” is the value of transformer life at the reference temperature 110 o C. Temperature is one of the prime factors that affect a transformer's life. In fact, increased temperature is the major cause of reduced transformer life. The Fig. 3 shows the transformer efficiency with respect to the temperature variations. Further, the cause of most transformer failures is a breakdown of the insulation system, so anything that adversely affects the insulating properties inside the transformer reduces transformer life. Such things as overloading the transformer, moisture in the transformer, poor quality oil or insulating paper, and extreme temperatures affect the insulating properties of the transformer. Most transformers are designed to operate for a minimum of 20–30 years at the nameplate load, if properly sized, installed and maintained. Transformers loaded above the nameplate rating over an extended period of time may have reduced life expectancy. The annual mean temperature is defined as the approximate average/mean of the maximum and minimum temperatures of the hottest and coldest months of the year. The relationship between transformer life and temperature is shown in Fig. 4 . The working status of transformer is measured in real time and the performance efficiency of solar power system is monitored in real time using IoT. There by the performance of solar plant system will be high. The performance of the PV system is graded on the basis of (i) Capacity Utilisation Factor (CUF) and (ii) Performance Ratio (PR). PR is a measure of the quality of a PV system independent of its location while CUF mainly dependent on GHI of the location of the PV system and module efficiency and hence it depends on the location. The PR, CUF and module efficiency varies with weather condition of the location. The capacity factor for a grid connected PV system is also represented by $$CUF=\\left(\\frac{peak sun hours}{day}\\right)/24h/day$$ 6 If a system delivers full rated power continuously, its CUF would be unity i.e. 100%. CUF is dependent on the location of the PV system. The higher the capacity factor, the better the PV system. Performance ratio is defined as the ratio of the energy fed to the grid (final yield) to the energy that the system could have, Performance ratio is defined as the ratio of the energy fed to the grid (final yield) to the energy that the system could have. $$PR=\\frac{{Y}_{F}}{{Y}_{R}}$$ 7 The CUF and PR of presented solar power transmission system using IoT system are tabulated as follows: Table 1 Performance Comparison Different methods Capacity Utilisation Factor Performance Ratio (%) Traditional solar power transmission systems 7% 70% Solar power transmission systems using IoT 17% 92% Compared to traditional solar power transmission systems, presented solar power transmission systems using IoT has better performance in terms of CUF and PR. In general, the capacity utilisation factor of all roof top solar PV system in India is 16–17%. CUF is location specific, and it is 13–15% in Massachusetts (USA) and 19% in Arizona (USA). Hence this system has effectively monitored the devices of solar power transmission systems. V. CONCLUSION In this work, real time health condition monitoring of devices in solar power transmission systems is presented. Internet of Things is used here to control and monitor the devices of solar power transmission systems. This monitoring system has three main modules. The first one is the real-time monitoring to the overall system and second one is used for transformer real time monitoring and third module is to provide the system health report to the user. Among different components, transformer is the most crucial one. The performance of transformer which is connected to on-grid is measured with respect to temperature variations. The performance of presented system is measured in terms of Performance ratio and C Capacity Utilisation Factor. Compared to traditional systems, this real time health condition monitoring of solar power transmission systems has better CUF and PR. 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Shruti Tiwari, R N Patel, “Real time monitoring of solar power plant and automatic load control”, 2015 IEEE Students Conference on Engineering and Systems (SCES), ISBN:978-1-4673-8597-8, DOI: 10.1109/SCES.2015.7506453 . Wen Yen Lin; Kuang Po Hsueh; Wang Hsin Hsu; Liew Gha Yie; Wei Chen Tai, “Design and Implementation of Health Monitoring System for Solar Panel in IPv6 Network”, 2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, DOI: 10.1109/IIH-MSP.2014.21 . Priyanka Biradar, Shruthi. M, “New Intelligent Semiconductor Transformer with Bidirectional Power-Flow Capability”, 4 International Journal of Engineering Research & Technology (IJERT) IJERT ISSN: 2278 – 0181, Vol. 3 Issue 4, April – 2014. Salvador Alepuz, Francisco González-Molina, Jacinto Martin-Arnedoc, Juan A. Martinez-Velasco, “Development and testing of a bidirectional distribution electronic power transformer model”, Electric Power Systems Research 107 (2014) 230–239, doi: 10.1016/j.epsr.2013.10.010 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4336932\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":298873630,\"identity\":\"88f80652-7666-4fbe-8798-c99e6c5c5190\",\"order_by\":0,\"name\":\"Venkata Govardhan Rao Kambhampati\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYBACCTjrBoSSAxEHHpCixRisJYEULYkNIBKfFskZCcwvPrbZ5fPdbn72uKLGJn1+2OGHQFvs5HQbsGuRlkhgs5zZlmw5884xc8Mzx9JyN95OMwBqSTY2O4BdixzPATZjnjPMBgY3EswkG9gO526cnQDSciBxG34t9UAt6d8kG/4dTjecnf4BrxZp9gbmxzwVh4FacswkG9sOJ8hL5+C3RbK9sY1xRsVxA8kbOWWSjX1phhukcwoOJBjg9ovEYebDHz4YVBvw3UjfJtnwzUZefnb65g8fKuzkcGlhYGBsk0DhG4BVGuBSDgbMH1C48g14VY+CUTAKRsEIBAChHGJhEEn5rQAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"St. Martin’s Engineering College\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Venkata\",\"middleName\":\"Govardhan Rao\",\"lastName\":\"Kambhampati\",\"suffix\":\"\"},{\"id\":298873632,\"identity\":\"b6899357-ab10-455a-a9b3-c1de51e53cd9\",\"order_by\":1,\"name\":\"Venkata Sai Kalyani Thalanki\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"St. Martin’s Engineering College\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Venkata\",\"middleName\":\"Sai Kalyani\",\"lastName\":\"Thalanki\",\"suffix\":\"\"},{\"id\":298873633,\"identity\":\"3eba16ab-0b49-4d7b-a190-e935711486ca\",\"order_by\":2,\"name\":\"Ramchandra Nittala\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"St. Martin’s Engineering College\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ramchandra\",\"middleName\":\"\",\"lastName\":\"Nittala\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-04-28 08:21:53\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4336932/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4336932/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":59334901,\"identity\":\"724c44bf-ba2f-4c00-9010-3e7517100624\",\"added_by\":\"auto\",\"created_at\":\"2024-06-29 21:31:32\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":424287,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4336932/v1/bd25eae0-9400-48f0-aa57-bdbea5737d86.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"A Review Report on Real Time Health Condition Monitoring of Devices in Solar Power Transmission Systems\",\"fulltext\":[{\"header\":\"I. INTRODUCTION\",\"content\":\"\\u003cp\\u003eDeploying renewable energy in India aims to promote economic development, enhance energy security, increase energy access, and address climate change concerns. Given the decline in fossil fuel availability, it is crucial to transition to renewable energy sources to meet our energy needs. Solar, wind, tidal, biomass, and geothermal energy are all promising alternatives that can help reduce our reliance on fossil fuels [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. There has been a significant increase in the recent focus and development of renewable energy sources (RESs). Renewable energy sources are receiving a lot of research attention because of their cost-effective and environmentally friendly qualities. These days, solar power, wind farms, and battery energy storage have been getting a lot of attention. In many cases, RESs are typically installed in remote locations or offshore [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Renewable energy is projected to experience rapid growth in the electricity sector, with wind and solar PV being well-established and cost-effective options, according to the International Energy Agency (IEA). However, the global demand for energy continues to rise. Embracing renewable energy technologies is a highly effective method for minimising our environmental footprint [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eRenewable energy sources have been widely recognised as dependable and are considered the most effective solution to address our increasing energy demands. The growing fascination with solar power, rising expenses, and the need for energy monitoring have led to several compelling reasons for its necessity [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. Today, Solar Photovoltaic (PV) power is a cutting-edge development in the renewable energy market that helps to decrease the reliance on fossil fuel by-products. For optimal utilisation of solar power generation, it is crucial to focus on its storage and consumption. The power generated by the RES is directly sent to the loads or storage units. Meanwhile, the batteries are charged or discharged based on the real-time production values of RESs and the demands of the loads.\\u003c/p\\u003e \\u003cp\\u003eEfficiently harnessing renewable electrical power is crucial. It has the potential to enhance system efficiency and alleviate strain on the power grid [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Solar power stations are highly regarded as a viable option for renewable energy systems in various locations. They offer a more cost-effective and low-maintenance alternative to conventional systems, while also requiring less space. Equipment is typically placed on an open terrace to control space occupancy in small generating stations [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe use of solar energy is easily available all around the world and has the potential to lessen dependency on energy that is imported. It is intriguing to think that the energy requirements of the entire world can be satisfied by just ninety minutes of sunlight lasting for an entire year. The functioning of solar photovoltaic (PV) systems does not result in the release of greenhouse gases (GHG) or any other pollutants. Solar energy provides a multitude of benefits, including the easy deployment of solar systems, the optimisation of operational methods, the precise forecasting of renewable energy, and the effective scheduling of power plants. In addition to this, it supports investments in flexible resources such as demand-side resources, grid infrastructure, power storage, and flexible generation.\\u003c/p\\u003e \\u003cp\\u003eElectrical networks need energy storage systems (ESSs) to handle renewable energies (REs)' unpredictability and generate stable, high-quality electricity. Standard energy storage systems use static power converters to connect storage mediums to the grid. Based on application needs, the storage medium must absorb, store, and deliver electrical energy.\\u003c/p\\u003e \\u003cp\\u003eRenewable energy is practical and necessary in current society. Renewable energy, like hydroelectric, thermoelectric, and nuclear power, uses a grid system to efficiently distribute and manage electrical energy [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. Generator, grid, and customer make up the electric energy system. All three must be balanced and monitored. The smart grid is essential for bringing together all parties [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe smart grid is described as a groundbreaking endeavour that involves the implementation of advanced communication and control systems, diverse energy sources, innovative generation methods, and compliance with regulatory frameworks across different jurisdictions. One of the goals in the Enhancing Aquatic Renewable Energy project is to seamlessly incorporate the Renewable Energy source into the smart grid. Smart Grid (SG) offers the energy industry a chance to enter a new era of improved reliability and efficiency [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eElectricity equipment is vital to the electricity grid's operation. Internet of Things technology is being adopted in the power business, so monitoring power equipment status via IoT has great research potential [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Most grid power comes from fossil fuels. A Smart Grid is necessary for a new era. A successful renewable microgrid system needs accessible sources. Understanding availability and properly controlling load on different sources helps improve system reliability. It works well with a good monitoring system. Managing energy sources and integrating them into the grid is difficult [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSmart grids improve power system efficiency and renewable energy management. An advanced smart grid uses sensors and controllers to monitor the electricity system and make real-time adjustments. For two-way data flow, a smart grid includes distributed energy resources (DERs), distributed computation, and communication networks. This balances power supply and demand and maximises socioeconomic benefits [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eOn-grid solar systems produce electricity solely when the utility power grid is accessible and linked directly to the utility feed. When you have an excess of power, on-grid systems will send it back to the utility grid. These systems are incredibly efficient and easy to install. These systems can easily cover their own costs by reducing energy bills within a span of 3\\u0026ndash;8 years. On-grid systems can be implemented with or without net metering.\\u003c/p\\u003e \\u003cp\\u003eSolar power systems connected to the utility grid generate power on-grid. These devices distribute excess solar power to the utility grid, compensating users. They work with the electrical grid. When there's not enough sunshine for your business, the system uses grid power. When you have excessive power use and wish to minimise your electricity expenses, these methods work best. Since they depend on the grid, these systems fail during power outages. Power transfer between the power grid, battery, and load usually needs rectification, inversion, or frequency conversion. The converter permits electricity flow in both directions [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eIndependent off-grid systems store solar electricity in batteries. Solar panels, battery, charge controller, grid box, inverter, mounting structure, and balance of systems are typical. The solar panels can store enough sunlight during the day and use it at night. Off-grid systems store and use solar electricity through batteries, assuring power during grid outages. Designed to be self-sufficient. Off-grid solar plants can power crucial loads during power outages. These systems can power crucial loads without a power grid. However, these systems require special equipment and are costly to install. These are ideal for enterprises that can run without power.\\u003c/p\\u003e \\u003cp\\u003eMany solar developers suggest installing an on-grid solar system and considering a backup DG if needed. However, for remote areas without access to a reliable grid, an off-grid system may be a suitable alternative. Given the rising peak demand and the necessity to enhance grid infrastructure for efficient operation and reliable management, the distribution smart grid plays a crucial role in expediting the modernization of the ageing power system. Smart technologies have a significant impact on the distribution grid. Implementing remote control and automation of the grid can lead to cost savings, improved data accuracy, and efficient troubleshooting of electricity system issues [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAs the IOT (internet of things) grows, grids may easily connect customers and suppliers for two-way communication. This allows remote energy control and real-time monitoring. Distributed energy resource (DER) aggregation and control are handled by these systems [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Solar PV systems need an inverter to convert DC power into AC power at grid voltage. Grid-connected PV system inverter architecture must be efficient and cost-effective [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eTransformers are essential to solar energy production and distribution. Transformers have been used to boost or decrease non-renewable energy. Solar transformer design must prioritise durability, stability, and long-term operation. Transformers with low input voltage. High-order harmonics and DC components from transportation can impair solar inverters and panels. Solar transformers can be distribution, station, substation, pad-mounted, or grounding. PV cells convert solar energy into DC to generate electricity. Inverters convert DC to AC and connect this to the electrical grid via a step-up transformer. For substations to supply power to nearby locations, transformers must work properly. It is the heart of any transmission. It clarifies power production decisions and boosts power consumption. Power transformers are precious, thus condition monitoring is vital for maintenance. Critical transformer failure in a transmission grid could threaten energy security. Different loads can degrade a power transformer's insulation, reducing its lifespan. Thermal, electrical, mechanical, and environmental loads are included.\\u003c/p\\u003e \\u003cp\\u003ePV cells produce DC power, which an inverter converts to AC power. This AC power can be paralleled to the grid using a step-up transformer. However, the inverter adds DC and harmonic components when it converts PV panel DC output to AC. This reduces power quality and increases transformer vibration and noise, especially with amorphous alloy transformers. Furthermore, DC and harmonic components increase transformer no-load losses.\\u003c/p\\u003e \\u003cp\\u003eThe distribution transformer serves as the final element in the power grid for voltage transformation. It is utilised for transforming medium voltage into low voltage, which is suitable for residential or commercial purposes. Distribution transformers play a crucial role in the distribution power system. Distribution transformers (DT\\u0026rsquo;s) are vital components in electrical distribution networks, serving as central hubs. Ensuring their proper function is crucial for maintaining a reliable power supply to consumers. If a critical transformer were to fail catastrophically, it would lead to power outages in the downstream network and potentially create substantial economic and environmental difficulties. DTs are typically found on the feeders below the substation, with a majority of them being mounted on poles. There are numerous elements that contribute to suboptimal performance and have a negative impact on the lifespan of DT.\\u003c/p\\u003e \\u003cp\\u003eEach HV/MV primary substation has many subordinate substations. Distribution transformers number around 1,000 in a medium-sized city with 40 HV/MV primary stations. Many fall into decay each year for various reasons. Oil leakage, overloading, uneven loading, and harmonics increase distribution transformer degradation and failure. Over time, electrical, mechanical, and thermal strains on power transformer components cause most failures.\\u003c/p\\u003e \\u003cp\\u003eTransformers are frequently used in power supply systems to convert AC voltage and provide galvanic isolation for components. Smart grids have become a topic of great interest among researchers in recent times. They possess unique power-generating capabilities and can provide electricity, particularly to conscientious customers during critical situations. Electricity can be generated from a variety of sources, such as nuclear power plants, autonomous diesel electric units, large batteries, wind farms, solar panels, and hydrogen fuel cells. When integrating various energy sources into smart grids, it is crucial to effectively coordinate different stress levels. It becomes more complex when dealing with electrical energy, as it is generated or stored in both DC and AC systems. If the input voltage is asymmetrical and there are variations in frequency, it will have a negative impact on the output voltage of the classic transformer, as there are no enhancements or alterations to mitigate these effects.\\u003c/p\\u003e \\u003cp\\u003eThese transformers rarely possess the intelligence and communication capabilities. Insufficient data regarding the loading of the transformer is a major factor contributing to the inefficiency of the distribution network. Whenever there is an issue with these transformers, customers promptly inform the authorities. Transformers should be carefully monitored on a regular basis to prevent any unexpected interruptions and anticipate potential issues. Developing reliable and cost-effective remote monitoring systems has been crucial for the evolution of the smart grid, particularly in electricity distribution. Several techniques have been devised to assess the condition of transformers. As transformers get older, their internal insulation breaks down. This can heighten their chances of experiencing failure and becoming more susceptible to severe circumstances like lightning strikes and short-circuits. Insulation degradation is primarily caused by overloading and excessive temperatures, thorough, and ongoing monitoring is necessary. Typically, diagnostic methods for distribution transformers were traditionally conducted offline, requiring the transformer to be taken out of service. Thanks to advancements in information technology and smart sensor devices, it is now possible to assess the status of transformers in real-time. The monitoring process is conducted online and in real-time, which significantly enhances the accuracy of the condition analysis for the transformer.\\u003c/p\\u003e \\u003cp\\u003eMonitoring distribution transformers in real-time can provide valuable insights into potential failure risks. Therefore, additional analysis can be conducted to easily identify the development trend of risks and make timely decisions to prevent unexpected and catastrophic equipment shut-downs. Monitoring transformers allows for real-time analysis of their condition, which in turn helps assess the potential risks to their availability. To effectively assess the condition of the transformer and identify potential issues, the monitoring system needs to conduct physical measurements and analyse the data within the relevant environmental conditions. Implementing efficient techniques to monitor the condition and well-being of distribution transformers can assist utilities in taking proactive measures to prevent failures and deterioration.\\u003c/p\\u003e \\u003cp\\u003eThe Internet of Things (IoT) connects nearby things via wired and wireless networks without user participation [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Through IoT, items communicate and exchange information to provide advanced intelligent services. With the proliferation of sensors and communication modules in modern mobile devices and sophisticated network technologies like Wi-Fi, LTE, and 5G, the Internet of Things (IoT) has garnered academic and industry attention. By connecting things to the Internet, IoT senses, activates, collects, stores, and processes data. IoT services such object tracking, environmental monitoring, healthcare, traffic management, smart security, smart home, and smart city are being researched. Transformer monitoring is crucial due to smart grid technologies and IoT-based smart grids.\\u003c/p\\u003e\"},{\"header\":\"II. LITERATURE SURVEY\",\"content\":\"\\u003cp\\u003eMunish Kumar, Ahmad Faiz Minai, Akhlaque A. Khan, Satish Kumar, et al. [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e] discusses an IoT-based energy management system designed for smart grids. This paper explores the utilisation of IoT in conjunction with Smart Grid to enhance power efficiency, reduce losses, and minimise energy wastage, resulting in economic benefits. IoT is also utilised for the transmission of real-time data to the Smart Grid, enabling energy conservation when demand fluctuates. Communication between users and suppliers has been facilitated by IoT for this system.\\u003c/p\\u003e \\u003cp\\u003eR. Govindarajan, S. Meikandasivam, D. Vijayakumar et al. [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e] exhibit real-time smart energy monitoring system performance analysis. Performance is analysed for smart real-time energy monitoring system design and implementation. Advanced wireless technologies like Zigbee, IoT, Android Mobile Apps, and cloud computing connect metres to consumers in the proposed systems. A digital power metre in the main panel interfaces with a communication gateway to measure voltage, current, power, power factor, and household appliance harmonics in real time.\\u003c/p\\u003e \\u003cp\\u003eCheng-Yu Tang and Jun-Ting Lin et al. [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] explain Energy Storage System Multi Input Converter Bidirectional Power Flow Control. This work shows a multi-input DC-DC converter with bidirectional power flow control. The Multi-Input Converter (MIC) reduces components and circuit cost compared to the power converter. Bidirectional power flow control and independent input current control are possible with the proposed MIC circuit. This technique will give detailed circuit analysis and mathematical derivation of the suggested MIC.\\u003c/p\\u003e \\u003cp\\u003eMr. Adinath S. Satpute, Prof. Dr. G. U Kharat, Prof. R. S Bansode et al. [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] discuss WoT-based Smart Grid System to Monitor and Control Renewable Energy Source. This article describes a basic electric and smart grid system for renewable energy sources based on WoT, including different methodologies, its basic working system and specifications, and a control panel GUI for easy access and strategy that appeals to advanced digital technology and information management practices and appropriate base modernization electrical delivery infrastructure.\\u003c/p\\u003e \\u003cp\\u003eMaisagalla Gopal, T Chandra Prakash, N Venkata Ramakrishna, Bonthala Prabhanjan Yadav et al. [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e] propose IoT-Based Solar Power Monitoring System. IoT-supervised solar energy can improve plant performance and monitoring. It monitors solar panel dust to maximise active power. Radiation hits the solar cell, determining solar panel output power. The central controller monitors the panels and loads with all panels attached and sensors perfectly connected. Thus, user may see current, voltage, and sunshine.\\u003c/p\\u003e \\u003cp\\u003eDoha's Photo-Voltaic (PV) Monitoring System, Performance Analysis, and Power Prediction Models are explained by Farid Touati, Amith Khandakar, Muhammad E.H. Chowdhury, Antonio Jr. S.P. Gonazales, Christian Kim Sorino, and Kamel Benh This work customises data collection for harsh climate solar systems utilising off-the-shelf components and data analytics for performance evaluation and prediction. Custom signal conditioning for extreme temperatures, microcontroller Development Board with interface shields, and wireless data transmission to icloud IoT platforms. We created an automatically changeable in-house electronic load to measure the PV system's maximum power.\\u003c/p\\u003e \\u003cp\\u003eHongchang Ke, Jian Wang, Hui Wang, Yuming Ge et al. [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e] improve IoT device data offloading and resource allocation using Deep Reinforcement Learning. Their model offloads data and considers renewable energy for a MEC (Mobile Edge Computing) server with several stochastic computing jobs and time-varying wireless channels. Their deep reinforcement learning (JODRBRL)-based joint optimisation solution for data offloading, renewable energy aware, and bandwidth allocation for IoT devices can manage the continuous action space and escape the curse of dimensionality caused by its complexity.\\u003c/p\\u003e \\u003cp\\u003eArturo Garcia, H\\u0026eacute;lia Guerra et al. describe a cheap IoT device for CIVISA's multiparameter remote stations' renewable energy system monitoring [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. They developed a low-cost voltage metre prototype with data logging, LAN transmission, and IoT for several sites. Prototype testing was successful, and network stations can replicate the product.\\u003c/p\\u003e \\u003cp\\u003eSanwar Hossain, Mostafizur Rahman, Tuhin Sarker, Ershadul Haque, and Abu Jahid et al. [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e] present a Smart IoT-Based System for Monitoring and Controlling Sub-Station Equipment. This paper shows an IoT-based network strategy for monitoring and regulating sub-station equipment to optimise time and resources. The IoT-based system allows objects to be sensed or controlled remotely across existing network infrastructure, enabling more direct integration of the physical world into computer-based systems and improving efficiency, accuracy, and economic benefit with minimal human intervention.\\u003c/p\\u003e \\u003cp\\u003eSupriya Ghodake, Priyanka Ghadage, Neha Patil, Prof. Akshay Jadhav et al. [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e] presented Arduino-based Remote Solar Power System Health Monitoring. This project uses IoT to remotely monitor a solar facility for performance evaluation using new cost actual technique. This will simplify preventive maintenance, solar panel defect detection, and real-time monitoring. This technology is used in solar cities, smart villages, micro grids, and street lights.\\u003c/p\\u003e \\u003cp\\u003eWen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua, \\u0026ldquo;Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua et. al., [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e] describes a Research on characteristics of bidirectional CLLC DC\\u0026ndash;DC transformer used in DC microgrid. Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua, \\u0026ldquo;Wen Chunxue, Hu Mingming, Hu Changbin, Piao Zhengguo, Zhou Jinghua, \\u0026ldquo;Research on characteristics of bidirectional CLLC DC\\u0026ndash;DC transformer used in DC microgrid. This work verifies a bidirectional full-bridge CLLC resonant converter for high-frequency galvanic isolation of a 380 V DC microgrid system and controls bidirectional power flow. The converter can operate in ZVS (Zero Voltage Switching) under soft switching of the main switch and output rectifier. In addition, the converter does not need any clamp and buffer circuit to reduce the voltage stress of the power switch.\\u003c/p\\u003e \\u003cp\\u003eChang-Sic Choi, Jin-Doo Jeong, Il-Woo Lee, Wan-Ki Park et. al., [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e] presents LoRa based Renewable Energy Monitoring System with Open IoT Platform. The authors describe the implementation of monitoring system for renewable energy generation facilities with the system architecture, implementation method, and analysis program. We use various open IoT platform such as Arduino, Raspberry Pi and low-cost LoRa network. In the future, we will carry out research result on the performance analysis and improvement solutions after operating on the testbed site for a long time.\\u003c/p\\u003e \\u003cp\\u003eJ.E. Shuda, A.J. Rix; M.J. Booysen et. al., [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e] discussed Towards Module-Level Performance and Health Monitoring of Solar PV Plants Using LoRa Wireless Sensor Networks. LoRa was chosen as the wireless technology due to its long range and low power consumption. A couple of sensor nodes and a gateway was designed built and tested. Range test were conducted to ensure that the chosen wireless technology meets the range requirements found on a typical PV plant. Module-level measurements were taken on different solar modules over a period of a few weeks. Range and Measurement test results shows that the sensor nodes and wireless technology is a sufficient solution for a WSN that is capable of measuring module-level performance parameters on a utility scale PV plant.\\u003c/p\\u003e \\u003cp\\u003eK Sai Chandu, Macharla Bharath et. al., [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e] demonstrates Bidirectional Hybrid Coupled Transformer for Battery Energy Storage System. A novel 3phase-inverter, which consists of multiple distributed BBCs and a Voltage Doubler using PV and wind source, for the battery energy storage system has been proposed in this paper.The proposed 3phase-inverter has individual power control capability for each battery module while fulfills the functions of battery charging and discharging by using pulsating current. Eventually, the equalization, lifetime extension, and capacity flexibility of the battery energy storage system can be achieved.\\u003c/p\\u003e \\u003cp\\u003eSuprita M. Patil, Vijayalashmi M, Rakesh Tapaskar et. al., [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e] presents IoT based Solar Energy Monitoring System. This system refers to the online display of the power usage of solar energy as a renewable energy. This monitoring is done through raspberry pi using flask framework. Smart Monitoring displays daily usage of renewable energy. This helps the user to analysis of energy usage. Analysis impacts on the renewable energy usage and electricity issues.\\u003c/p\\u003e \\u003cp\\u003eYu Jianyang, Muhammad Qasim Khan, ZhangYanwen, Muhammad Mansoor Khan, Muhammad Ali et. al., [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e] demonstrates HVDC Bidirectional Power Flow Using Solid State Transformer. A new topology was presented to control DC power flow through an Interline DC Power flow controller (IDCPFC) with Solid State Transformer (SST). In the proposed method, the boost converter is used to achieve increased output voltage from the input voltage and its current is regulated through the duty cycle of the converter. The control algorithm of this technique is smooth and easy to deploy.\\u003c/p\\u003e \\u003cp\\u003ePrutha M. Badave, B. Karthikeyan, S. M. Badave, S. B. Mahajan, P. Sanjeevikumar \\u0026amp; Gurjit Singh Gill et. al., [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e] presents health Monitoring System of Solar Photovoltaic Panel: An Internet of Things Application. A wireless remote monitoring system for solar photovoltaic (PV) plant is proposed in this paper. It is an Internet of Things (IoT) application implemented with an objective to offer a cost-effective solution of monitoring system, which continuously presents remote energy yields and its performance either on computer or on handheld gadgets such as smart phones. On board Wi-Fi, wireless communication enhances the system performance with reduced area and facilitates to monitor system parameters.\\u003c/p\\u003e \\u003cp\\u003eJayaharsha Kandimalla, Dr. D. Ravi Kishore et. al., [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e] demonstrates Web Based Monitoring of Solar Power Plant Using Open Source IOT Platform Thing speak and Arduino. They developed a prototype for implementation of new cost-effective methodology based on IoT to monitor a solar photovoltaic plant for performance evaluation using open-source tools and resources like Arduino and Thing speak. Thing speak is a SaaS (Software as a Service) platform which provides space on Web to monitor our parameters. Thing speak provides all services for free of cost. Which saves lot of investment on Website designing and maintenance. We focussed on low-cost system with easy interface so that common people who installs roof top solar plants also monitors easily without depending on service providing companies.\\u003c/p\\u003e \\u003cp\\u003eEugene Y. Song, Gerald J. FitzPatrick, and Kang B. Lee et. al., [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e] demonstrates Smart Sensors and Standard-Based Interoperability in Smart Grids. This work describes sensing, timing, intelligence, and communication requirements of sensors for the SGs (Smart Grids) and describes a general model of the SSs (Smart Sensors) for SGs based on these requirements. Then it illustrates, how the model works with phasor measurement unit (PMU)- and merging unit-based SSs deployed in the SGs with standardized interfaces to support the interoperability of the SSs. This work describes sensor interface standards used in the SGs and the need for interoperability testing and proposes a passive interoperability test method for the SSs to achieve and assure sensor data interoperability. To verify this test method, an interoperability test system for the PMU-based SSs was developed and presented.\\u003c/p\\u003e \\u003cp\\u003eJaswinder Singh, and S.K. Aggarwal et. al., [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e] presents Distribution Transformer Monitoring for Smart Gridin India. This paper introduces the Distributed Transformer Monitoring System using Field Programmable Gate Array based technology integrated with wireless communication modules and its utilization for a smart grid. It consists of network of sensors and energy meters. The whole architecture and the hardware \\u0026amp; software flow of the system have been explained. The developed approach effectively monitors the network of transformers operating state, dispatches the critical information, thus helps utility operator to keep transformer in service for long life. It is also having the advantages of significant cost savings and greater reliability.\\u003c/p\\u003e \\u003cp\\u003eJaswinder Singh, and S.K. Aggarwal et. al., [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e] presents Distribution Transformer Monitoring for Smart Grid in India. This paper introduces the Distributed Transformer Monitoring System (DTMS) using FPGA based technology integrated with communication modules and its utilization for Smart Grid. It consists of network of sensors and energy meters and communication over wireless network. A trail was given on the implemented system for testing and results came out as expected.\\u003c/p\\u003e \\u003cp\\u003eDiogo Varajao, Lu\\u0026acute;ıs M. Miranda, Rui E. Araujo, J. Pec\\u0026cedil;as Lopes et. al., [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e] describes Power Transformer for a Single-stage Bidirectional and Isolated AC-DC Matrix Converter for Energy Storage Systems. This paper presents an approach to design the transformer and the link inductor for the high-frequency link matrix converter. The proposed method aims to systematize the design process of the HF-link using analytic and software tools. A 10 kW / 20 kHz transformer plus a link inductor are designed using this strategy achieving a combined efficiency of 99.32%.\\u003c/p\\u003e \\u003cp\\u003eP. Pounraj, D. Prince Winston, S. Cynthia Christabel, R. Ramaraj et. al., [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e] demonstrates A Continuous Health Monitoring System for Photovoltaic Array Using Arduino Microcontroller. In this paper new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This technique can classify the health status into four categories such as Healthy, Low Fault, Medium Fault and High Fault. By this classification faulty operation can be rectified and power generation may be improved. In case of high faults, PV panels can be protected. The cost requirement for the implementation is very low.\\u003c/p\\u003e \\u003cp\\u003eMr. Vikas S. Chandre, Prof. Ravindre G.Dabhade et. al., [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e] presents Smart Grid System To Monitor and Control Renewable Energy Source Based on Web of Things. This system consist of three major subsystems namely power generation and storage, power monitoring and billing and power control and managing by using WoT. WoT technology can effectively combine the infrastructure resources in increase the quality of power system information and increases the utilization efficiency of infrastructures in the existing power system. The part of vision of a smart grid is its ability to enable informed participation by customers making them an integral part of the electrical power.\\u003c/p\\u003e \\u003cp\\u003eMayorkinos Papaelias Liang Cheng, Maria Kogia, Abbas Mohimi Vassilios Kappatos, Cem Selcuk, Louis Constantinou, Carlos Quiterio G\\u0026oacute;mez Mu\\u0026ntilde;oz, Fausto Pedro GarciaMarquez, Tat-HeanGan et. al., [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e] presents Inspection and Structural Health Monitoring techniques for Concentrated Solar Power plants. This work discusses the non-destructive evaluation techniques that can be employed to inspect solar receivers and insulated pipes as well as relevant research and development work in this field. With the increased use of solar tower technology, the accurate evaluation of the structural integrity of volumetric solar receivers after they are manufactured but also during their in-service lifetime will become more necessary.\\u003c/p\\u003e \\u003cp\\u003eP. Pounraj, D. Prince Winston, S. Cynthia Christabel, R. Ramaraj et. al., [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e] describes A Continuous Health Monitoring System for Photovoltaic Array Using Arduino Microcontroller. In this work, new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This technique can classify the health status into four categories such as Healthy, Low Fault, Medium Fault and High Fault. By this classification faulty operation can be rectified and power generation may be improved. In case of high faults, PV panels can be protected. The cost requirement for the implementation is very low. The proposed technique is implemented in MATLAB Simulation and hardware. The array considered in this paper is 2 \\u0026times; 2 Series Parallel.\\u003c/p\\u003e \\u003cp\\u003eCarlos R. Baier, Miguel Torres, Javier A. Mu\\u0026ntilde;oz, Marco Rivera, Eduardo Espinosa N, Pablo Acu\\u0026ntilde;a et. al., [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e] describes Bidirectional Power Flow Control of a Single-Phase Current-Source Grid-Tie Battery Energy Storage System. This paper presents the modelling and control of a battery energy storage system (BESS) connected to the grid by a single-phase current source inverter. A bidirectional DC/DC converter connects the battery bank to the dc bus of the inverter allowing power flow in both directions. An integrated non-linear control strategy is proposed to control both converters and to manage the power flow direction between the BESS and a stiff grid.\\u003c/p\\u003e \\u003cp\\u003eKouhei Hayashia, Ryosuke Katoa, Ryosuke Toriia, Hisao Taokaa and Rikiya Abe et. al., [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e] demonstrates Bi-directional power flow through a digital grid router. They demonstrate a control method of bi-directional power flow. We verify its possibility by doing an experiment. Through this method, one can control the direction of current flow through a \\u0026lsquo;leg\\u0026rsquo; and the value of current by hysteresis control. Hysteresis control is a method which controls the switching of an insulated gate bipolar transistor \\u0026lsquo;IGBT\\u0026rsquo; by comparing output current and reference current having constant width of the amplitude of reference current.\\u003c/p\\u003e \\u003cp\\u003eMohd Nafis Akram; Saeed Lotfifard, et. al., [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e] demonstrates Modelling and Health Monitoring of DC Side of Photovoltaic Array. To implement and validate the presented method in computer programs, a new approach for modelling PV systems is demonstrated that only requires information from manufacturers datasheet reported under normal-operating cell temperature (NOCT) conditions and standard-operating test conditions (STCs). This model precisely represents characteristics of PV systems at different temperatures, as the temperature dependency of parameters such as duality factor, series resistance, and thermal voltage is considered in the proposed model.\\u003c/p\\u003e \\u003cp\\u003eShruti Tiwari, R N Patel et. al., [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e] demonstrates Real time monitoring of solar power plant and automatic load control. The objective of this work is to develop a power management system for optimum utilization of generated power from Solar PV power plants. This is to alleviate the existing situation wherein the net solar power utilization is effectively only about 50%. Some of the features of this scheme are automatic load switching, advanced remote metering \\u0026amp; control, and priority-based switching.\\u003c/p\\u003e \\u003cp\\u003eWen Yen Lin, Kuang Po Hsueh, Wang Hsin Hsu; Liew Gha Yie, Wei Chen Tai et. al., [\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e] demonstrates the Design and Implementation of Health Monitoring System for Solar Panel in IPv6 Network. They describe a remote monitoring system of solar panels via IPv6 wireless network, in which the parameters of environment and panel voltage would be sent to the Smart Analysis Database System. Then we can monitor the health of the Solar Plant by using the Android mobile platform anywhere and anytime. The administrator not only can use a mobile device to maintain the solar plant and smart home device via IPv6 Network without NAT transformation, but also receive the message immediately when the status of solar panel or home device is abnormal.\\u003c/p\\u003e \\u003cp\\u003ePriyanka Biradar, Shruthi. M et. al., [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e] describes New Intelligent Semiconductor Transformer with Bidirectional Power-Flow Capability. This work demonstrates a new intelligent semiconductor transformer (IST) which consists of a bidirectional ac/dc resonant converter, dc/dc converter, and dc/ac converter. This structure pro-vides good voltage-balancing performance on the high-voltage side and a simple control method for bidirectional power flow. A three-phase transformer can be implemented with three units of the demonstrated IST.\\u003c/p\\u003e \\u003cp\\u003eSalvador Alepuz, Francisco Gonz\\u0026aacute;lez-Molina, Jacinto Martin-Arnedoc, Juan A. Martinez-Velasco et. al., [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e] describes Development and testing of a bidirectional distribution electronic power transformer model. A model for a bidirectional high-frequency power electronic transformer is presented. Several case studies have been carried out in order to evaluate the behaviour of the transformer under different operating conditions and test the impact on the power quality. The results show that the electronic power transformer, also known as solid-state transformer, not only matches the functions of a conventional power transformer, but also provides additional capabilities to mitigate dynamic power quality problems.\\u003c/p\\u003e\"},{\"header\":\"III. REAL TIME HEALTH CONDITION MONITORING\",\"content\":\"\\u003cp\\u003eIn this section, Real time health condition monitoring of devices in solar power transmission systems is presented. The monitoring system has three modules. The first one is the real-time monitoring to the overall system; this is the dashboard that gives the user the general information in real-time about the energy grid. The second module monitors transformer in real-time. The electrical and environmental variables of the node (generator or load) can be monitored if needed. The third component is the reporting function.\\u003c/p\\u003e \\u003cp\\u003ePV systems whose power is directly fed into the utility or electric grid are generally known as grid-connected PV systems. These are also called on-grid or grid-tied PV systems. These PV systems are capable of only feeding energy into the grid. A typical grid-connected PV system consists of components of PV modules, an inverter, a transformer, and a utility meter. PV systems that generate electricity to be used locally at the generation centre without being injected into a utility grid are called stand-alone PV systems. Here, mostly the energy generated is consumed and any available excess will be stored in batteries. A few examples of such systems are solar streetlights, solar water pumping, and rooftop home solar PV systems.\\u003c/p\\u003e \\u003cp\\u003eA solar power transformer is used in solar power applications. A solar panel transformer has to convert the DC voltage coming out of the photovoltaic systems and step it up to the rated output. This can also be called as a solar inverter transformer because it inverts DC to AC. Photovoltaic power generation can be divided into two types according to how it is connected to the grid: off-grid and grid-connected. The majority of PV plants are currently grid-connected, i.e. connected in parallel to the existing power supply network to maximise the use of the electricity generated by the plant. The Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e shows the schematic of IMWP solar PV system connected to the utility grid.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eInverters and transformers used in photovoltaic power stations are one of the important nuclear components of photovoltaic power stations. Inverters realise the conversion from DC to AC, and transformers realise the transmission and utilisation of electrical energy. In order to reduce line transmission losses and increase transmission distances, the voltage of 270V or 400V at the outlet of the PV inverter needs to be raised and then output, i.e. a step-up transformer is installed to raise the voltage to l0kV or 3kV depending on the capacity of the power station, which reduces transmission line losses while also making the system electrically physically isolated.\\u003c/p\\u003e \\u003cp\\u003ePhotovoltaic power generation network in normal operation, must have measurement, safety protection, control, remote communication and other functions, detect the operation of the power distribution system, judge the state and make the necessary control instructions, but also all the information will be transmitted to the monitoring in a timely manner also, the degree has the basic requirements of intelligent photovoltaic pad mounted transformer.\\u003c/p\\u003e \\u003cp\\u003eConsidering the particularity of photovoltaic power generation, that is, power generation during the day, no matter whether the power generation device outputs power or not, as long as the transformer is connected to the system, the transformer will always produce no-load loss. The load loss of the transformer is required to be as low as possible. If the transformer runs at night, the no-load loss is also required to be low; It is necessary to consider the dependency of the studied methods on the load condition, temperature, and the effect of transformer aging over time.\\u003c/p\\u003e \\u003cp\\u003eThe primary function of transformer oil is to protect the winding and core of the transformer. It helps dissipate heat i.e. act as a coolant, prevents arcing and corona, protects the insulation, and stops any kind of oxidation to take place within the transformer tank. The dielectric breakdown test on the insulating oil of a transformer can help determine its level of contamination. If in-service oil testing is performed, it can help determine the remaining life and operational safety of the transformer and help prevent equipment res. For in service equipment, it is recommended to test the oil at least once a year.\\u003c/p\\u003e \\u003cp\\u003eModern PV inverters usually produce the sinusoidal voltage, and the current waveform is similar to the ideal sine wave. So, grid-tie transformers generally do not need to be large in the event that solar power inverters operate them. General-purpose transformers are typically specifically designed. Non-linear loads could cause the voltage and current to cause Total Harmonic Distortion (THD) which could impact the transformer's performance and cause an increase in heating. The environmental conditions, like ambient temperature, must also be taken into consideration. Grid-tie transformers typically don't experience a maximum load or, if they do, it will last less than an hour, based on typical load curves for solar facilities.\\u003c/p\\u003e \\u003cp\\u003ePartial discharge monitoring is a commonly recognized method for early fault diagnosis. PD monitoring is a promising, rapidly developing method for high-voltage equipment condition monitoring. PD intensity is an important diagnostic feature of oil and solid insulation condition. Partial discharge as a localized electrical discharge that only partially bridges the insulation between conductors. In practice, PDs are both symptoms and causes of insulation aging, and they can cause equipment failure in the long term. PD monitoring helps prevent early aging of insulation. Meanwhile, it is crucial to know the characteristics of the discharge itself for the purposes of monitoring, PD power, usually reduced to PDI-Partial Discharge Intensity. This parameter is defined as the total energy of discharges divided by the time of their summation, which is why it has the same dimensionality as power. The parameter describes the power and intensity of PD and is determined by the dependency.\\u003cdiv id=\\\"Equ1\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ1\\\" name=\\\"EquationSource\\\"\\u003e\\n$$PDI=\\\\frac{1}{T}\\\\sum _{i=1}^{m}{Q}_{i}{U}_{d} \\\\left(1\\\\right)$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e1\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eWhere m is the number of pulses recorded over the observation time T; Ud is the effective voltage. A drastic increase in Q02 and PDI is an unambiguous sign of insulation destruction. If these values change significantly over 3\\u0026ndash;4 observations, or at least double over a year, then the insulation has an expanding.\\u003c/p\\u003e \\u003cp\\u003eWhen the applied voltage to a transformer is sinusoidal, the core flux rises from -Φm to\\u0026thinsp;+\\u0026thinsp;Φm during the positive half cycle of the applied voltage. If the transformer is switched ON at an instant when the instantaneous value of applied voltage is at its positive peak, then the flux would rise from its natural zero value up to\\u0026thinsp;+\\u0026thinsp;Φm during the next quarter cycle (Magnetizing lags voltage by 90deg). The magnetising current required would remain normal and the switching of the transformer would be trouble free. However, if the instantaneous value of applied voltage at switching instant is zero and going towards positive, then the core flux would rise from its natural zero value to +\\u0026thinsp;2Φm in the next half cycle. This phenomenon is also known as doubling effect. This flux doubling is accompanied by a huge magnetizing inrush current which may reach 5 times the full load current or higher, leading to massive winding forces and a possible dip in the system. Magnetizing inrush is highly unsymmetrical and stays for quite a few cycles, decaying according to the time constant of the system. The inrush current is expected to delay quickly if the system is switched on resistive load or capacitive loads. However, it would delay slowly if switched on NO load or with inductive load (which is the case for most Grid connected Solar Power Plants).\\u003c/p\\u003e \\u003cp\\u003eInrush current curve: Inrush current is a form of transient over current present during the energization of transformers. It depends on the residual flux of the transformer, magnetic characteristic of the core \\u0026amp; voltage waveform at the time of switching. The individual harmonic voltage distortion levels can be established by performing this calculation for the p.u. current associated with each harmonic number. The Voltage Total Harmonic Distortion (THD) is then calculated by establishing the square root of the sum of the squares of these individual Voltage harmonics. When a sinusoidal signal of frequency ω passes through a non-ideal, non-linear device, additional content is added at multiples nω (harmonics) of the original frequency. THD is a measure of that additional signal content present in the input signal\\u003cdiv id=\\\"Equ2\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ2\\\" name=\\\"EquationSource\\\"\\u003e\\n$${THD}_{F}=\\\\frac{\\\\sqrt{{V}_{2}^{2}+{V}_{3}^{2}+{V}_{4}^{2}\\\\dots }}{{V}_{1}}$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e2\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eWhere THD is total harmonic distortion and Vn\\u0026thinsp;=\\u0026thinsp;RMS voltage of nth harmonic\\u003c/p\\u003e \\u003cp\\u003eIoT is the network of physical devices embedded with electronics, software, sensors, actuators and network connectivity which have the ability to identify, collect and exchange the data. Each thing is uniquely identifiable through its embedded computing system and able to interoperate within the existing internet infrastructure. Various sensors are installed on the transmission line to collect environmental data information (Parameters such as temperature, relative humidity, transformer characteristics, air pressure, rainfall, light radiation, etc.), in real time and perform analysis and processing to realize the real time monitoring of the operating environment of power equipment. As said before, one of the main objectives of the sensing system is to enhance the use of renewable energy, so all the data gathered by the system must be analyzed to generate models to enhance the control and the performance of the grid. The Communication Module (CMM) handles the exchange of information between different modules and devices.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe basic components used in this monitoring system are sensors that measure the parameters in a PV system in actual conditions. The signal processing unit is another significant unit. This unit amplifies and clears signals for subsequent processing. Also, this unit includes a processor that sends the signal processing unit outputs to a PC through a dedicated protocol in real time. The PC is applied for analyzing, saving, and showing data. According to data analysis and user commands, information is transmitted to the control unit for subsequent operation.\\u003c/p\\u003e \\u003cp\\u003eSensor selection depends on the monitoring objectives and location. The main sensors used in this monitoring system to evaluate the aforementioned parameters are current sensors, voltage sensors, solar irradiance sensors, temperature sensors, anemometer wind speed sensors, hygrometer sensors, and barometer pressure sensors. The data acquisition system (DAS) plays an important role in any monitoring system and is used to collect data from different sensors of a PV system. Then, this data is digitalized for storage and the DAS sends data to the control center for processing and presentation.\\u003c/p\\u003e \\u003cp\\u003eThe Thing Speak IoT platform enables clients to update and receive updates from channel feeds via the Thing Speak MQTT (Message Queuing Telemetry Transport) broker. MQTT is a publish/subscribe communication protocol that uses TCP/IP sockets or Web Sockets. MQTT over Web Sockets can be secured with SSL (secure sockets layer). Features of Thing Speak include real-time data collection, data processing, visualizations, apps, and plugins. At the heart of Thing Speak is a Thing Speak Channel. A channel is where one can send their data to be stored. Each channel includes 8 fields for any type of data, 3 location fields, and 1 status field.\\u003c/p\\u003e \\u003cp\\u003eThe secondary module provides all the information to operator to inspect whether transformers work correctly. The operator can visualize the entire network using the interactive graphical interface and easily navigate from one window to other. Control center receives the information from each transformer in a fixed time, the information is presented in the useful format, and operator can see the various data i.e. any transformer violating the threshold limits, over loading, unbalancing etc. In the event of a system quantity crossing the predefined threshold, an alarm is automatic generated for operator intervention and SMS is sent to concern field engineer. The operator can visualize the entire network using the interactive graphical interface. If the condition of transformer is measured accurately then the efficiency of solar power plant will be improved.\\u003c/p\\u003e\"},{\"header\":\"IV. RESULT ANALYSIS\",\"content\":\"\\u003cp\\u003eIn this section, real time health condition monitoring of devices in solar power transmission systems is implemented. The real time health condition monitoring of devices is performed using IoT. The main cause behind the altered performance of transformer in the presence of solar panel is its associated inverters that are used to supply linear loads. A higher temperature rise will occur in the windings and cores of the transformer due to voltage and current harmonics, resulting in extra losses. The temperature and hot spot calculation and aging rate of transformer are calculated from international standards.\\u003c/p\\u003e \\u003cp\\u003eThe average ambient temperature for a transformer over a 24-hour period should not exceed 30 degrees Celsius. For instance, if the transformer ambient temperature was 40\\u003csup\\u003eo\\u003c/sup\\u003eC for 12 hours, then the transformer must not exceed 20\\u003csup\\u003eo\\u003c/sup\\u003eC for the remaining 12 hours to average a 30\\u003csup\\u003eo\\u003c/sup\\u003e ambient temperature. If the average ambient temperature exceeds 30 degrees Celsius, the derating factor is 0.4% reduction of VA for every degree Celsius above 30 degrees Celsius per IEEE C57 12.96. The IEEE formula that is used to derive the 0.4% factor is valid only up to an AVERAGE of 50 degrees Celsius. Also, using transformers above their listed ambient temperature can shorten the life of the transformer. Due to the number of other factors involved, such as loading, frequency of use, and humidity, no data exists on how high ambient temperatures affect the life of a transformer.\\u003c/p\\u003e \\u003cp\\u003eThe transformer life is established as a function of hot spot temperature (noted as \\u0026#120579;\\u003csub\\u003e\\u0026#119867;\\u003c/sub\\u003e) which is computed by ambient temperature and load. Then, \\u0026#120579;\\u003csub\\u003e\\u0026#119867;\\u003c/sub\\u003e is provided as an input variable to acquire the thermal aging acceleration factor \\u0026#119865;\\u003csub\\u003eAA\\u003c/sub\\u003e\\u003cdiv id=\\\"Equ3\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ3\\\" name=\\\"EquationSource\\\"\\u003e\\n$${F}_{AA}=\\\\text{exp}\\\\left(\\\\frac{15000}{383}-\\\\frac{15000}{{\\\\theta }_{H}+273}\\\\right)$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e3\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eWhen \\u0026#120579;\\u003csub\\u003e\\u0026#119867;\\u003c/sub\\u003e is the reference temperature. \\u0026#119865;AA is equal to 1. Based on this definition, the loss of life in a given time period is presented as\\u003cdiv id=\\\"Equ4\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ4\\\" name=\\\"EquationSource\\\"\\u003e\\n$${F}_{EQA}=\\\\frac{{\\\\sum }_{n=1}^{N}{F}_{AA}\\\\varDelta {t}_{n}}{{\\\\sum }_{n=1}^{N}\\\\varDelta {t}_{n}}$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e4\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Equ5\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ5\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\% Loss of life=\\\\frac{{F}_{EQA}\\\\times t\\\\times 100}{Normal Insulation life}$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e5\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eWhere \\u0026#119865;EQA is the equivalent aging factor in the total time period, \\u0026#119865;\\u003csub\\u003eAA\\u0026#119899;\\u003c/sub\\u003e is the aging acceleration factor during the time interval Δ\\u0026#119905;\\u003csub\\u003e\\u0026#119899;\\u003c/sub\\u003e, \\u0026#119873; is the total number of time intervals, and \\u0026ldquo;Normal insulation life\\u0026rdquo; is the value of transformer life at the reference temperature 110\\u003csup\\u003eo\\u003c/sup\\u003eC. Temperature is one of the prime factors that affect a transformer's life. In fact, increased temperature is the major cause of reduced transformer life. The Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e shows the transformer efficiency with respect to the temperature variations.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eFurther, the cause of most transformer failures is a breakdown of the insulation system, so anything that adversely affects the insulating properties inside the transformer reduces transformer life. Such things as overloading the transformer, moisture in the transformer, poor quality oil or insulating paper, and extreme temperatures affect the insulating properties of the transformer. Most transformers are designed to operate for a minimum of 20\\u0026ndash;30 years at the nameplate load, if properly sized, installed and maintained. Transformers loaded above the nameplate rating over an extended period of time may have reduced life expectancy.\\u003c/p\\u003e \\u003cp\\u003eThe annual mean temperature is defined as the approximate average/mean of the maximum and minimum temperatures of the hottest and coldest months of the year. The relationship between transformer life and temperature is shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe working status of transformer is measured in real time and the performance efficiency of solar power system is monitored in real time using IoT. There by the performance of solar plant system will be high. The performance of the PV system is graded on the basis of (i) Capacity Utilisation Factor (CUF) and (ii) Performance Ratio (PR). PR is a measure of the quality of a PV system independent of its location while CUF mainly dependent on GHI of the location of the PV system and module efficiency and hence it depends on the location. The PR, CUF and module efficiency varies with weather condition of the location.\\u003c/p\\u003e \\u003cp\\u003eThe capacity factor for a grid connected PV system is also represented by\\u003cdiv id=\\\"Equ6\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ6\\\" name=\\\"EquationSource\\\"\\u003e\\n$$CUF=\\\\left(\\\\frac{peak sun hours}{day}\\\\right)/24h/day$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e6\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eIf a system delivers full rated power continuously, its CUF would be unity i.e. 100%. CUF is dependent on the location of the PV system. The higher the capacity factor, the better the PV system. Performance ratio is defined as the ratio of the energy fed to the grid (final yield) to the energy that the system could have, Performance ratio is defined as the ratio of the energy fed to the grid (final yield) to the energy that the system could have.\\u003cdiv id=\\\"Equ7\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equ7\\\" name=\\\"EquationSource\\\"\\u003e\\n$$PR=\\\\frac{{Y}_{F}}{{Y}_{R}}$$\\u003c/div\\u003e\\u003cdiv class=\\\"EquationNumber\\\"\\u003e7\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eThe CUF and PR of presented solar power transmission system using IoT system are tabulated as follows:\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003ePerformance Comparison\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDifferent methods\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCapacity Utilisation Factor\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePerformance Ratio (%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTraditional solar power transmission systems\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e70%\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSolar power transmission systems using IoT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e17%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e92%\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eCompared to traditional solar power transmission systems, presented solar power transmission systems using IoT has better performance in terms of CUF and PR. In general, the capacity utilisation factor of all roof top solar PV system in India is 16\\u0026ndash;17%. CUF is location specific, and it is 13\\u0026ndash;15% in Massachusetts (USA) and 19% in Arizona (USA). Hence this system has effectively monitored the devices of solar power transmission systems.\\u003c/p\\u003e\"},{\"header\":\"V. CONCLUSION\",\"content\":\"\\u003cp\\u003eIn this work, real time health condition monitoring of devices in solar power transmission systems is presented. Internet of Things is used here to control and monitor the devices of solar power transmission systems. This monitoring system has three main modules. The first one is the real-time monitoring to the overall system and second one is used for transformer real time monitoring and third module is to provide the system health report to the user. Among different components, transformer is the most crucial one. The performance of transformer which is connected to on-grid is measured with respect to temperature variations. The performance of presented system is measured in terms of Performance ratio and C Capacity Utilisation Factor. Compared to traditional systems, this real time health condition monitoring of solar power transmission systems has better CUF and PR.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eKVGNR and NRC: Conceptualization, Data curation, Formal analysis, Methodology, Resources, Software, Validation, Visualisation, Writing\\u0026mdash;original draft. TVSK: Data curation, Investigation, Supervision., KVGR, NRC and TVSK: Writing\\u0026mdash;review and editing. All authors have read and agreed to the published version of the manuscript.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eS. Sivaranjani; S. Logashri; C.K. Pavithra; T. 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Eng. Sci., 2021; 10(2), 563\\u0026ndash;568, doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.28948/ngmuh.911764\\u003c/span\\u003e\\u003cspan address=\\\"10.28948/ngmuh.911764\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRavi Kishore Kodali, Jeswin John, \\u0026ldquo;Smart Monitoring of Solar Panels Using AWS\\u0026rdquo;, 2020 International Conference on Power Electronics \\u0026amp; IoT Applications in Renewable Energy and its Control (PARC) GLA University, Mathura, UP, India. Feb 28\\u0026ndash;29, 2020.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMunish Kumar, Ahmad Faiz Minai, Akhlaque A. Khan; Satish Kumar, \\u0026ldquo;IoT based Energy Management System for Smart Grid\\u0026rdquo;, 2020 International Conference on Advances in Computing, Communication \\u0026amp; Materials (ICACCM), ISBN:978-1-7281-9785-2, doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1109/ICACCM50413.2020.9213061\\u003c/span\\u003e\\u003cspan address=\\\"10.1109/ICACCM50413.2020.9213061\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eR. Govindarajan, S. Meikandasivam, D. Vijayakumar, \\u0026ldquo;Performance Analysis of Smart Energy Monitoring Systems in Real-time\\u0026rdquo;, Engineering, Technology \\u0026amp; Applied Science Research Vol. 10, No. 3, 2020, 5808\\u0026ndash;5813.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMr. Adinath S. Satpute, Prof. /Dr. G. U Kharat, Prof. R. S Bansode, \\u0026ldquo;Smart Grid System to Monitor \\u0026amp; Control Renewable Energy Source based on WoT\\u0026rdquo;, International Journal of Engineering Research \\u0026amp; Technology (IJERT) \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.ijert.org\\u003c/span\\u003e\\u003cspan address=\\\"http://www.ijert.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e ISSN: 2278\\u0026thinsp;\\u0026ndash;\\u0026thinsp;0181 IJERTV9IS060358, Vol. 9 Issue 06, June-2020.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMaisagalla Gopal, T Chandra Prakash, N Venkata Ramakrishna,Bonthala Prabhanjan Yadav, \\u0026ldquo;IoT Based Solar Power Monitoring System\\u0026rdquo;, IOP Conf. 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Gonazales, Christian Kim Sorino and Kamel Benhmed, \\u0026ldquo; Photo-Voltaic (PV) Monitoring System, Performance Analysis and Power Prediction Models in Doha, Qatar, 2020, Renewable energy, Technologies and Applications, 2020, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.5772/intechopen.92632\\u003c/span\\u003e\\u003cspan address=\\\"10.5772/intechopen.92632\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHongchang Ke, Jian Wang, Hui Wang, Yuming Ge, \\u0026ldquo;Joint Optimization of Data Offloading and Resource Allocation With Renewable Energy Aware for IoT Devices: A Deep Reinforcement Learning Approach\\u0026rdquo;, IEEE Access (Volume: 7), 2019, ISSN: 2169\\u0026ndash;3536, DOI: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1109/ACCESS.2019.2959348\\u003c/span\\u003e\\u003cspan address=\\\"10.1109/ACCESS.2019.2959348\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eArturo Garcia, H\\u0026eacute;lia Guerra, \\u0026ldquo;Affordable IoT device for renewable energy systems monitoring of the CIVISA\\u0026rsquo;s multiparameter remote stations\\u0026rdquo;, 2019 International Conference in Engineering Applications (ICEA), ISBN: 978-1-7281-2962-4,DOI: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1109/CEAP.2019.8883497\\u003c/span\\u003e\\u003cspan address=\\\"10.1109/CEAP.2019.8883497\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCheng-Yu Tang, and Jun-Ting Lin, \\u0026ldquo;Bidirectional Power Flow Control of a Multi Input Converter for Energy Storage System\\u0026rdquo;, Energies 2019, 12, 3756; doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3390/en12193756\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/en12193756\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMd. 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M, \\u0026ldquo;New Intelligent Semiconductor Transformer with Bidirectional Power-Flow Capability\\u0026rdquo;, 4 International Journal of Engineering Research \\u0026amp; Technology (IJERT) IJERT ISSN: 2278\\u0026thinsp;\\u0026ndash;\\u0026thinsp;0181, Vol. 3 Issue 4, April \\u0026ndash; 2014.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSalvador Alepuz, Francisco Gonz\\u0026aacute;lez-Molina, Jacinto Martin-Arnedoc, Juan A. Martinez-Velasco, \\u0026ldquo;Development and testing of a bidirectional distribution electronic power transformer model\\u0026rdquo;, Electric Power Systems Research 107 (2014) 230\\u0026ndash;239, doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.epsr.2013.10.010\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.epsr.2013.10.010\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Renewable Energy, Smart Grid, Transformer, Solar Energy, and Internet of Things\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4336932/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4336932/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eAs renewable energy generation grows globally, real-time asset management is crucial, particularly for offshore and remote systems. Electric grids are rapidly adopting renewable energy generation. Currently, there is no cost-effective condition monitoring method for real-time assessment of renewable energy sources, enabling intelligent asset management decisions to optimise utilisation and prevent unforeseen problems. Transformers are key assets that connect renewable generation plants to the grid. If one fails, generation can be lost for a lengthy time. The transformer in an on-grid system steps up or down voltage as needed. Transformer monitoring is crucial to Smart Grids. Transformer monitoring also allows demand analysis\\u0026mdash;what each family, business, or commercial institution consumes, where it consumes more, and when demand peaks. By its nature most renewable generation is intermittent, which places increased stress on transformers. To achieve an efficient, better and reliable generation of solar energy, it is necessary to monitor the transformers and solar generation system continuously. Hence in this work, real time health condition monitoring of devices in solar power transmission systems is presented. This system monitors the devices in real time with the help of IoT. Understanding transformer health and performance with real-time monitoring allows developing and optimizing proactive maintenance strategies for improving the performance of solar power transmission systems.\\u003c/p\\u003e\",\"manuscriptTitle\":\"A Review Report on Real Time Health Condition Monitoring of Devices in Solar Power Transmission Systems\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-05-07 10:54:24\",\"doi\":\"10.21203/rs.3.rs-4336932/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"1cad4226-f40b-455c-b52d-fa507553c7c8\",\"owner\":[],\"postedDate\":\"May 7th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-06-29T21:23:24+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-05-07 10:54:24\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4336932\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4336932\",\"identity\":\"rs-4336932\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}