Evaluating Renewable Energy from the Sea: A Study of OTEC Feasibility in the Banda Sea, Indonesia

Evaluating Renewable Energy from the Sea: A Study of OTEC Feasibility in the Banda Sea, Indonesia | 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 Case Report Evaluating Renewable Energy from the Sea: A Study of OTEC Feasibility in the Banda Sea, Indonesia Muhammad Akbar Sunandi, Isnaini Prihatiningsih, Amron Amron This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6581259/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 The growing global demand for electricity, which is driven by rapid technological and infrastructure developments, has intensified the need to transition from fossil fuels to renewable energy sources. Indonesia holds significant potential for Ocean Thermal Energy Conversion (OTEC) with its abundant marine resources, particularly in Banda Sea. Therefore, this research aimed to explore the seasonal and spatial distribution of OTEC potential using temperature data from Marine Copernicus model, validated with Argo Float measurements. The validation produced a Mean Absolute Percentage Error (MAPE) of 2.814% and an R² value of 0.9945, indicating high model accuracy. Moreover, seasonal variations showed that Carnot efficiency values between 7.60–7.70% were achievable at depths of 643–1,245 meters, depending on sea surface temperature (SST) fluctuations. Station 2, which was located 9 km from the coast, indicated the most consistent and optimal conditions for year-round OTEC operation with net power output ranging 63.85–75.79 MW. This research showed the viability of OTEC in Banda Sea and indicated the importance of continuous monitoring and accurate modeling to support renewable energy transition in Indonesia. Ocean Thermal Energy Conversion Banda Sea Renewable Energy Oceanographic Modeling Temperature Gradient Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The increasing global demand for electricity is driven by rapid technological advancements and infrastructure development, impacting all sectors, including households, industries, as well as government operations. As electricity becomes a fundamental necessity for daily life, its importance continues to grow (Jaiswal et al., 2022 ; Maka & Alabid, 2022 ; Strielkowski et al., 2021 ). Currently, many nations heavily rely on fossil fuels as the primary energy source, which significantly contributes to rising carbon dioxide (CO2) emissions. This reliance on fossil fuels is a major factor in climate change, inspiring urgent calls for a transition to renewable energy sources. Various countries including Indonesia have started making changes to reduce greenhouse gas emissions and achieve net-zero targets. This marks a significant shift in energy policies and practices of the countries (Kusuma et al., 2024 ; Nasir & Bengi, 2024 ; Resosudarmo et al., 2023 ; Tiwari et al., 2024 ). The detrimental environmental impacts associated with fossil fuel use, particularly greenhouse gas emissions, have raised alarms about global warming. Increased temperatures and rising sea levels pose severe threats to ecosystems and human settlements worldwide (Griggs & Reguero, 2021 ; Isiaka et al., 2023 ; Roy et al., 2023 ; Tebaldi et al., 2021 ). In response, governments globally are making commitments to reduce carbon emissions and promote cleaner energy alternatives. This is evident in the national energy policies of Indonesia, which set ambitious targets for renewable energy usage, aiming for 23% by 2025 and 31% by 2050, respectively (Kanugrahan et al., 2022 ; Raihan, 2023 ). The targets reflect the commitment of the country to a sustainable energy future, while also addressing the pressing issue of climate change. Despite these commitments, Indonesia faces significant challenges in transitioning to renewable energy. High costs associated with renewable technologies and the slow pace of development have hindered progress, with only 11.31% of total energy consumption coming from renewable sources as of 2020 (MEMR-RI, 2021 ). The continued dependence on fossil fuels, particularly coal, which accounts for over 40% of the national electricity supply, shows the urgency of accelerating renewable energy initiatives (MEMR-RI, 2023 ). Addressing the challenges is crucial for the country to meet its energy needs sustainably while also reducing carbon footprint. A promising avenue for renewable energy development in Indonesia lies in its vast marine resources. The country has significant potential to harness ocean energy, particularly through Ocean Thermal Energy Conversion (OTEC) with the second-longest coastline in the world. Research indicates that thermal ocean potential of Indonesia is estimated at approximately 2.5 x 10²³ joules, with the capacity to generate around 0.1–451.7 GW of power (Langer et al., 2021 , 2022 ; Suprijo et al., 2021 ). This potential positions OTEC as a viable option for improving the renewable energy mix in the country and supports international efforts to transition to cleaner energy sources. Banda Sea has surfaced as a particularly promising site for renewable energy development due to its favorable characteristics, including depths exceeding 2,000 meters and stable sea surface temperatures (SST) ranging from 26–30°C throughout the year (Gordon & Susanto, 2001 ; Iskandar, 2010 ; Tadjuddah, 2016 ). The combination of warm surface waters and cooler deep ocean temperatures creates ideal conditions for OTEC, allowing efficient energy conversion. Therefore, further investigation into the thermal dynamics of Banda Sea is essential for optimizing the development and implementation of renewable energy technologies in this region. Accurate temperature measurements are critical for the successful application of OTEC and other renewable energy technologies. These measurements can be obtained through various methods, including direct sampling and modeling procedures. The use of oceanographic models, such as those provided by the Copernicus Marine Environment Monitoring Service (CMEMS), offers a practical solution for monitoring sea temperatures across extensive areas (Sanchez-Arcilla et al., 2021 ; Sotillo et al., 2021 ; von Schuckmann et al., 2018 ). The accuracy of these models is influenced by numerous factors such as the algorithms used and the data quality, signifying the need for strong as well as up-to-date modeling to support renewable energy transition effectively in Indonesia. Moreover, the country can improve its understanding of marine resources and increase the feasibility of renewable energy projects by leveraging these advanced modeling methods, contributing to a sustainable energy future. Material and Methods The research employs a combination of hardware and software tools for comprehensive data analysis. The primary equipment included a personal computer with an Intel Core i7 processor, which was essential for processing image data and conducting in-depth analyses of the results. Additionally, major software used in this research included Anaconda for Python programming, ArcGIS for advanced data visualization, Ocean Data View (ODV) for extracting and visualizing temperature data, and Microsoft Excel for tabulation and further data analysis. The data for the analysis comprised Marine Copernicus model data with a horizontal resolution of 9 km, aimed at analyzing temperature concentration in Banda Sea, alongside Argo Float data from 2023, which served as a critical reference for validating temperature concentration measurements. The method applied during the research was fundamentally observational, engaging in systematic observation and recording of phenomena using specialized instruments to gather scientific facts (Dehalwar & Sharma, 2023 ; Schwing, 2023 ). This research leveraged secondary data sourced from Marine Copernicus website and in-situ measurements obtained from Argo Floats accessible via Coriolis website. The analysis process proceeded through stages of data collection, processing, and analysis, with a concentrated focus on Banda Sea region, particularly around stations known for high population density in Maluku. This method supported modern oceanographic research that showed the importance of incorporating diverse data sources to improve the accuracy of environmental assessments (Schwing, 2023 ). The fieldwork was scheduled between October and December 2024, taking place at Oceanography and Marine Technology Laboratory at Jenderal Soedirman University. The research area comprised Banda Sea, with specific coordinates ranging from 2°S to 4°S and 125°E to 131°E (Fig. 1 ). During the process, three research stations were strategically identified based on geographic significance, particularly in regions such as Seram Bagian Barat, Ambon, and Maluku Tengah, which were characterized by high population density as well as ecological diversity. This selection process reflected current trends in marine research that prioritized locations with significant human impact and ecological importance (Pittman et al., 2021 ). Marine Copernicus model data was initially downloaded in .nc format and subsequently converted to .txt format using ODV software for data processing. Initial preprocessing in Microsoft Excel was conducted to remove erroneous measurement values and to combine the data with reference values obtained from Argo. Relating to the analysis, the processed data was then exported for visualization at each coordinate of the research station using ODV software. The handling of Argo Float temperature data followed a similar method, ensuring that it followed the temperature data derived from Copernicus model, thereby facilitating a comprehensive analysis that supported best Data analysis incorporated both statistical and descriptive methods during the research. The validation of model data was thoroughly analyzed by comparing it with in-situ data from Argo Floats, specifically focusing on temperature data for the year 2023. Methods such as Mean Absolute Percentage Error (MAPE) and simple linear regression were used to assess model accuracy. In the context of the research, MAPE served as a critical measure of forecasting accuracy by calculating the average absolute error relative to actual observed values, with lower MAPE values indicating superior model performance (Chicco et al., 2021 ). Additionally, simple linear regression was used to elucidate the relationships between independent and dependent variables, offering an understanding of how fluctuations in one variable influenced another (Montgomery et al., 2021 ). The identification of OTEC potential was conducted seasonally, examining data from various periods throughout 2023. The net power potential was calculated by assessing the warm water intake at a depth of 15 meters, alongside the cold-water intake at depths that complied with Carnot efficiency standards. Moreover, the Carnot efficiency was calculated to optimize energy conversion, based on specific temperature differentials and operational parameters (Chen et al., 2023 ). The research identified potential OTEC installation sites by considering underwater topography, specifically targeting locations with depths greater than 700 meters and proximity to shorelines in 30 km, ensuring compliance with the efficiency criteria necessary for effective OTEC operations. This methodological framework supported contemporary research that showed the importance of incorporating thermodynamic principles with oceanographic data to assess renewable energy potential effectively (Fan et al., 2023 ). Results and discussion Validity of Coppernicus model The validation of Marine Copernicus model data against Argo data represented a significant advancement in the understanding and application of oceanographic models. The use of MAPE as a metric for assessing prediction accuracy provided a strong framework for evaluating model performance. Following the discussion, the model indicated a high level of accuracy with a MAPE value of 2.814%, as it was less than the 10% threshold by Chicco et al. ( 2021 ). This low error margin showed that Marine Copernicus model could be confidently used in decision-making processes, particularly in marine resource management and climate change research, where precise temperature data was critical (Drenkard et al., 2021 ). The application of simple linear regression analysis to quantify the relationship between model data and in-situ measurements improved the credibility of the findings (Fig. 2 ). The regression equation 𝑦=0.9941𝑥−0.2144 indicated a nearly one-to-one relationship between the model and observed temperatures, reinforcing the reliability of the model. Relating to the discussion, a coefficient of determination (R²) of 0.9945 signified an exceptional fit, with 99.45% of the variability in model temperature data explained by Argo temperature data. This strong correlation was crucial for validating the predictive capabilities of the model, which was essential for applications in fields such as oceanographic research and climate modeling (Haghbin et al., 2021 ). The implications of these findings extended beyond validation, showing the potential of Marine Copernicus model as a crucial tool for assessing oceanic conditions. Accurate temperature data was essential for understanding marine ecosystems, influencing biological productivity, and managing fisheries sustainably. As explained by Brodie et al. ( 2022 ), reliable models could aid in predicting shifts in marine species distribution in response to changing ocean temperatures, thereby informing conservation strategies and policy decisions. The ability to accurately model temperature dynamics played an essential role in addressing the challenges posed by climate change in marine environments. High accuracy of Marine Copernicus model supports its incorporation into broader oceanographic frameworks, where the method complemented other data sources. The findings showed that combining satellite-based models with in-situ measurements from platforms such as Argo improved the understanding of complex ocean dynamics. This incorporated method was increasingly recognized as necessary for effective ocean monitoring and management (Gacutan et al., 2022 ). Research could acquire a more comprehensive view of oceanic conditions and the fluctuations over time by leveraging both remote sensing and in-situ data. The results from this research could inform future research directions in oceanography. The reliability shown reliability of Marine Copernicus model inspired further exploration into its applications, such as in climate change impact assessments and the development of renewable energy resources such as OTEC. Research by Martínez et al. ( 2024 ) described that understanding thermal gradients in ocean water was essential for optimizing OTEC systems, and Marine Copernicus model could provide valuable data for such initiatives. This opened avenues for interdisciplinary research that combined oceanography, renewable energy, and environmental science. The validation of Marine Copernicus model against Argo data confirmed its accuracy and showed the significance as a tool for scientific inquiry as well as practical applications. The strong correlation between modeled and observed temperatures indicated that this model could effectively inform decision-making in marine and environmental management. As the challenges posed by climate change continued to change, the reliance on strong models such as Marine Copernicus became crucial for developing effective strategies to mitigate impacts on marine ecosystems and ensure sustainable resource use. Spatial and temporal distribution of OTEC potential The potential for OTEC in Banda Sea was significantly influenced by seasonal variations in SST and corresponding thermal gradients at various depths (Fig. 3 , and Table 1 ). During the west season, the warm water intake at a depth of 15 meters showed temperatures ranging from 29–30°C, which was conducive for OTEC installations (Fig. 3 A). The minimum installation depth of 643 meters across all research stations indicated that the thermal gradient was sufficient to achieve Carnot efficiencies between 7.60–7.70%. These efficiencies were critical for the economic viability of OTEC systems, directly correlating with the energy output that could be harnessed from the temperature differential between warm surface and cold deep water (Khan et al., 2022 ; Langer et al., 2022 ). The results supported previous research that showed the importance of thermal gradients in optimizing OTEC systems (Aresti et al., 2023 ). The stability of SST led to a consistent distribution of potential depths for OTEC installations in Transition 1 Season, which spanned from March to May (Fig. 3 B). The warm water intake temperatures remained relatively high, ranging from 29.40-29.75°C, allowing the same minimum installation depth of 643 meters. The Carnot efficiencies achieved during this season were comparable to those in the west season, indicating that the thermal conditions remained favorable for energy conversion. However, the slight decline in SST during this period showed that continuous monitoring was essential to adapt to changing thermal conditions, as even minor fluctuations could impact the efficiency of OTEC systems (Nakib et al., 2024 ). This signified the need for adaptive management strategies in the deployment of OTEC technologies. The East Season, which occurred from June to August, presented a different scenario where the potential for OTEC installations was significantly affected by cooler SST, ranging from 27.74–28.93°C (Fig. 3 C). This necessitated deeper installations which exceeded 700 meters, to achieve the required Carnot efficiencies. The studies indicated that Station 1 maintained a minimum depth as in previous seasons, while Station 2 and 3 required deeper installations to meet efficiency standards. The cooler temperatures during this season were attributed to the influence of east monsoon winds, which promoted upwelling and reduced the availability of warm surface water (Lahiri & Vissa, 2022 ). This seasonal variability showed the importance of understanding local oceanographic conditions in the planning and operation of OTEC systems. Table 1 , Seasonal data for OTEC potential parameters. Season Station Warm water temp. (°C) Cold water temp. (°C) Potential depth Carnot Efficiency (%) Gross power potential (MW) Net power potential (MW) West S-1 29.83 6.76 643.57 7.60 77.72 60.20 29.83 6.05 763.33 7.80 82.58 65.06 S-2 29.74 6.79 643.57 7.60 77.15 59.57 29.74 6.08 763.33 7.80 82.00 64.42 29.74 5.20 902.34 8.10 88.21 70.63 29.74 4.37 1062.44 8.40 94.28 76.70 29.74 3.68 1245.29 8.60 99.48 81.90 29.74 3.04 1452.25 8.80 104.42 86.85 29.74 2.58 1684.28 9.00 108.05 90.47 S-3 30.07 6.85 643.57 7.70 78.11 60.73 30.07 6.24 763.33 7.90 82.27 64.88 30.07 5.51 902.34 8.10 87.38 70.00 30.07 4.56 1062.44 8.40 94.28 76.89 30.07 3.77 1245.29 8.70 100.21 82.82 30.07 3.05 1452.25 8.90 105.77 88.38 30.07 2.63 1684.28 9.00 109.08 91.70 Transition 1 S-1 29.53 6.72 643.57 7.50 76.75 59.05 29.53 6.01 763.33 7.80 81.61 63.90 S-2 29.46 6.73 643.57 7.50 76.40 58.65 29.46 6.01 763.33 7.70 81.31 63.57 29.46 5.21 902.34 8.00 86.96 69.21 29.46 4.31 1062.44 8.30 93.53 75.79 29.46 3.72 1245.29 8.50 97.97 80.23 29.46 3.04 1452.25 8.70 103.22 85.47 29.46 2.61 1684.28 8.90 106.60 88.86 S-3 29.75 6.72 643.57 7.60 77.66 60.09 29.75 6.03 763.33 7.80 82.39 64.81 29.75 5.21 902.34 8.10 88.18 70.61 29.75 4.37 1062.44 8.40 94.32 76.75 29.75 3.65 1245.29 8.60 99.75 82.18 29.75 3.03 1452.25 8.80 104.54 86.97 29.75 2.60 1684.28 9.00 107.94 90.36 East S-1 28.93 5.90 643.57 7.60 79.86 61.79 28.93 5.71 763.33 7.70 81.19 63.12 S-2 28.20 5.67 763.33 7.50 78.41 59.88 28.20 4.91 902.34 7.70 83.79 65.25 28.20 4.22 1062.44 8.00 88.83 70.29 28.20 3.53 1245.29 8.20 94.02 75.48 28.20 2.91 1452.25 8.40 98.80 80.26 28.20 2.51 1684.28 8.50 101.95 83.41 S-3 27.74 5.04 902.34 7.50 80.92 62.08 27.74 4.21 1062.44 7.80 86.95 68.10 27.74 3.48 1245.29 8.10 92.42 73.58 27.74 2.91 1452.25 8.30 96.82 77.97 27.74 2.50 1684.28 8.40 100.04 81.20 Transition 2 S-1 27.32 5.83 763.33 7.20 73.64 54.50 S-2 26.73 4.45 1062.44 7.40 80.90 61.34 26.73 3.70 1245.29 7.70 86.44 66.88 26.73 3.04 1452.25 7.90 91.46 71.91 26.73 2.57 1684.28 8.10 95.13 75.57 S-3 26.02 4.47 1062.44 7.20 77.75 57.66 26.02 3.69 1245.29 7.50 83.48 63.39 26.02 3.01 1452.25 7.70 88.64 68.55 26.02 2.56 1684.28 7.80 92.14 72.05 Table 2, Gross and net power potential of OTEC Session Station Gross Power Potential (MW) Net Power Potential (MW) Average Max Min Average Max Min West S-1 80.15 82.58 77.72 62.63 65.06 60.20 S-2 93.37 108.05 77.15 75.79 90.47 59.57 S-3 93.87 109.08 78.11 76.49 91.70 60.73 Transition 1 S-1 79.18 81.61 76.75 61.48 63.90 59.05 S-2 92.28 106.60 76.40 74.54 88.86 58.65 S-3 93.54 107.94 77.66 75.97 90.36 60.09 East S-1 80.53 81.19 79.86 62.46 63.12 61.79 S-2 90.97 101.95 78.41 72.43 83.41 59.88 S-3 91.43 100.04 80.92 72.59 81.20 62.08 Transition 2 S-1 70.92 73.64 73.64 49.05 54.50 54.50 S-2 83.41 95.13 86.44 63.85 75.57 66.88 S-3 80.24 92.14 83.48 60.15 72.05 63.39 Transition 2 Season, which occurred from September to November, showed a further decline in SST with warm water intake temperatures dropping by 1–2°C compared to earlier seasons (Fig. 3 D). This reduction in temperature led to a more uniform distribution of cooler waters, which adversely affected the efficiency of OTEC systems. Station 1 became nonviable for OTEC operations as it failed to meet the necessary Carnot efficiency, even at maximum depths of 763 meters. Consequently, Station 2 and 3 required installations at depths exceeding 1,245 meters to achieve adequate efficiencies, with net power outputs of 66.88 and 63.39 MW, respectively. This shift in operational viability showed the critical role of seasonal temperature dynamics in determining the feasibility of OTEC projects (Alsebai et al., 2023 ). The observed seasonal variations in SST and the impact on OTEC potential were consistent with findings from other regions, where similar patterns had been documented. For instance, research by Soltani et al. ( 2021 ) showed the significance of local climatic conditions in influencing ocean thermal energy systems. The analysis indicated that understanding these dynamics was essential for optimizing energy production and ensuring the sustainability of OTEC technologies. Furthermore, the findings from Banda Sea contributed to the broader discourse on renewable energy sources, particularly in tropical regions where ocean thermal gradients could be effectively harnessed. The implications of these findings extended beyond energy production, informing policy and management strategies for marine resources. As shown Mathew et al. ( 2025 ), the incorporation of OTEC systems into coastal management frameworks could improve energy security while promoting sustainable practices in marine environments. The ability to generate clean energy from ocean thermal gradients presented an opportunity to mitigate the impacts of climate change and reduce reliance on fossil fuels. Therefore, the development of OTEC technologies in Banda Sea should be accompanied by comprehensive environmental assessments to ensure that marine ecosystems were protected. The analysis of OTEC potential in Banda Sea showed significant seasonal variability influenced by thermal gradients and oceanographic conditions. The findings signified the importance of continuous monitoring and adaptive management strategies to optimize OTEC systems. As the demand for renewable energy sources increased, the understanding acquired from this research could inform future research and development efforts in ocean thermal energy technologies. Continued teamwork among authors, policymakers, and industry stakeholders would be essential to harness the full potential of OTEC systems while ensuring environmental sustainability. Conclusion In conclusion, this research showed that ocean energy, particularly through OTEC, had significant potential to support the renewable energy transition in Indonesia, especially in Banda Sea region. Validation of Copernicus model temperature data against in-situ Argo observations signified high accuracy, with a MAPE of 2.814% and an R² of 0.9945, indicating the reliability of the model for ocean temperature analysis. Relating to this discussion, spatial and temporal analyses showed that OTEC potential was influenced by seasonal variations in SST and vertical temperature gradients, affecting Carnot efficiency as well as optimal installation depth. Among the three research stations analyzed, Station 2 was the most promising site for OTEC installation due to its favorable depth, relatively stable year-round temperature profile, and appropriate distance from the coastline. 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Handbook of energy & economic statistics of indonesia 2023 . Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to linear regression analysis . John Wiley & Sons. Nakib, T. H., Hasanuzzaman, M., Rahim, N. A., Habib, M. A., Adzman, N. N., & Amin, N. (2024). Global challenges of ocean thermal energy conversion and its prospects: a review. Journal of Ocean Engineering and Marine Energy, 1–35. https://doi.org/10.1007/s40722-024-00368-4 Nasir, M. N., & Bengi, K. S. (2024). The energy mix dilemma in Indonesia in achieving net zero emissions by 2060. ASEAN Natural Disaster Mitigation and Education Journal, 2 (1), 99–113. https://doi.org/10.61511/andmej.v2i1.2024.951 Nihous, G. C. (2021). Ocean Thermal Energy Conversion (OTEC). In Wind, Water and Fire: The Other Renewable Energy Resources (pp. 173–196). World Scientific. https://doi.org/10.1142/9789811225925_0006 Pattanaik, B., Sutha, S., Dinesh, D., & Jalihal, P. (2024). Data-driven model based adaptive feedback-feed forward control schemes for open cycle-OTEC process. Renewable Energy, 221 , 119765. https://doi.org/10.1016/j.renene.2023.119765 Pittman, S. J., Yates, K. L., Bouchet, P. J., Alvarez-Berastegui, D., Andréfouët, S., Bell, S. S., Berkström, C., Boström, C., Brown, C. J., & Connolly, R. M. (2021). Seascape ecology: identifying research priorities for an emerging ocean sustainability science. Marine Ecology Progress Series, 663 , 1–29. https://doi.org/10.3354/meps13661 Raihan, A. (2023). An overview of the energy segment of Indonesia: present situation, prospects, and forthcoming advancements in renewable energy technology. Journal of Technology Innovations and Energy, 2 (3), 37–63. https://doi.org/10.56556/jtie.v2i3.599 Resosudarmo, B. P., Rezki, J. F., & Effendi, Y. (2023). Prospects of energy transition in Indonesia. Bulletin of Indonesian Economic Studies, 59 (2), 149–177. https://doi.org/10.1080/00074918.2023.2238336 Roy, P., Pal, S. C., Chakrabortty, R., Chowdhuri, I., Saha, A., & Shit, M. (2023). Effects of climate change and sea-level rise on coastal habitat: Vulnerability assessment, adaptation strategies and policy recommendations. Journal of Environmental Management, 330 , 117187. https://doi.org/10.1016/j.jenvman.2022.117187 Sanchez-Arcilla, A., Staneva, J., Cavaleri, L., Badger, M., Bidlot, J., Sorensen, J. T., Hansen, L. B., Martin, A., Saulter, A., & Espino, M. (2021). CMEMS-based coastal analyses: conditioning, coupling and limits for applications. Frontiers in Marine Science, 8 , 604741. https://doi.org/10.3389/fmars.2021.604741 Schwing, F. B. (2023). Modern technologies and integrated observing systems are “instrumental” to fisheries oceanography: A brief history of ocean data collection. Fisheries Oceanography, 32 (1), 28–69. https://doi.org/10.1111/fog.12619 Soltani, M., Kashkooli, F. M., Souri, M., Rafiei, B., Jabarifar, M., Gharali, K., & Nathwani, J. S. (2021). Environmental, economic, and social impacts of geothermal energy systems. Renewable and Sustainable Energy Reviews, 140 , 110750. https://doi.org/10.1016/j.rser.2021.110750 Sotillo, M. G., Mourre, B., Mestres, M., Lorente, P., Aznar, R., García-León, M., Liste, M., Santana, A., Espino, M., & Álvarez, E. (2021). Evaluation of the operational CMEMS and coastal downstream ocean forecasting services during the storm Gloria (January 2020). Frontiers in Marine Science, 8 , 644525. https://doi.org/10.3389/fmars.2021.644525 Strielkowski, W., Civín, L., Tarkhanova, E., Tvaronavičienė, M., & Petrenko, Y. (2021). Renewable energy in the sustainable development of electrical power sector: A review. Energies, 14 (24), 8240. https://doi.org/10.3390/en14248240 Suprijo, T., Poerbo, P. R., Park, H., Kartadikaria, A. R., & Yosi, M. (2021). Potential Ocean Thermal Energy Conversion in Indonesian Waters Territory. Journal of Coastal Research, 114 (SI), 285–289. https://doi.org/10.2112/JCR-SI114-058.1 Tadjuddah, M. (2016). Observations of sea surface temperature on spatial and temporal using Aqua MODIS Satellite in West Banda Sea. Procedia Environmental Sciences, 33 , 568–573. https://doi.org/10.1016/j.proenv.2016.03.109 Tebaldi, C., Ranasinghe, R., Vousdoukas, M., Rasmussen, D. J., Vega-Westhoff, B., Kirezci, E., Kopp, R. E., Sriver, R., & Mentaschi, L. (2021). Extreme sea levels at different global warming levels. Nature Climate Change, 11 (9), 746–751. https://doi.org/10.1038/s41558-021-01127-1 Thomas, J. R., Martin, P., Etnier, J. L., & Silverman, S. J. (2023). Research methods in physical activity . Human kinetics. Tiwari, S., Bashir, S., Sarker, T., & Shahzad, U. (2024). Sustainable pathways for attaining net zero emissions in selected South Asian countries: role of green energy market and pricing. Humanities and Social Sciences Communications, 11 (1). https://doi.org/10.1057/s41599-023-02552-7 von Schuckmann, K., Le Traon, P.-Y., Smith, N., Pascual, A., Brasseur, P., Fennel, K., Djavidnia, S., Aaboe, S., Fanjul, E. A., & Autret, E. (2018). Copernicus marine service ocean state report. Journal of Operational Oceanography, 11 (sup1), S1–S142. https://doi.org/10.1080/1755876X.2018.1489208 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. 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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-6581259","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":452648700,"identity":"91ab3914-31b3-46f5-aef1-35e2cd2c5ff4","order_by":0,"name":"Muhammad Akbar Sunandi","email":"","orcid":"","institution":"Jenderal Soedirman University","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Akbar","lastName":"Sunandi","suffix":""},{"id":452648701,"identity":"ecc3bbaf-2612-4cf0-87df-56c0460896a3","order_by":1,"name":"Isnaini Prihatiningsih","email":"","orcid":"","institution":"Jenderal Soedirman University","correspondingAuthor":false,"prefix":"","firstName":"Isnaini","middleName":"","lastName":"Prihatiningsih","suffix":""},{"id":452648702,"identity":"af8afcf6-8ac0-4ceb-99d6-cf1b41279289","order_by":2,"name":"Amron Amron","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYNCCCgglASLYGBKI0XKGZC2MbUhaGAhp4Z929uHjwnmH8+Tbmw/eYKixY+BjJ6BF4na6sfHMbYeLDc4cS7ZgOJbMwMbzgICjbqexSfNuO5y4QSLHTIKB7QADmwQBW+TBWuYcTpw/I/+bBMM/IrQYgLU0HE5suJHDJsHYRoQWw9tpzMY8x9ITN5w5ZmyR2JfMQ9AvcrfTGB/z1Fgnzm9vfnjjwzc7Ofl2AragAqBiHlLUj4JRMApGwSjAAQCyND1XCKrSgAAAAABJRU5ErkJggg==","orcid":"","institution":"Jenderal Soedirman University","correspondingAuthor":true,"prefix":"","firstName":"Amron","middleName":"","lastName":"Amron","suffix":""}],"badges":[],"createdAt":"2025-05-03 01:08:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6581259/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6581259/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82562004,"identity":"ba09d88d-3a21-4bac-9085-6ff8abc29d18","added_by":"auto","created_at":"2025-05-13 01:41:38","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":224122,"visible":true,"origin":"","legend":"\u003cp\u003eResearch stations\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6581259/v1/d1d71794d38c45b408065eb8.jpeg"},{"id":82562715,"identity":"3ac523a4-83a7-4047-a75d-d30e56a9dcfa","added_by":"auto","created_at":"2025-05-13 01:49:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43541,"visible":true,"origin":"","legend":"\u003cp\u003eMarine Copernicus model Vs Argo Plot\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6581259/v1/c87d738fb81537585790ef30.png"},{"id":82562001,"identity":"1bf642b8-c184-4ff5-aaee-dc6b6b806aa9","added_by":"auto","created_at":"2025-05-13 01:41:38","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":577783,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of minimum depth for OTEC potential in various seasons. (A) east; (B) transition 1; (C) west; and (D) transition 2.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6581259/v1/b3b4db8a27f35a8d3aee60fa.jpeg"},{"id":82562009,"identity":"a8726027-8d94-4c67-9067-0df8d49f3299","added_by":"auto","created_at":"2025-05-13 01:41:39","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":432629,"visible":true,"origin":"","legend":"\u003cp\u003ePotential depth for OTEC installation\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6581259/v1/1cbddf9e9fd6319f3c9ae0f8.jpeg"},{"id":90563754,"identity":"742b1df8-abeb-4169-b6c1-f179af34dd2a","added_by":"auto","created_at":"2025-09-04 06:47:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2162674,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6581259/v1/e95c3ca6-da98-4bfb-bfb8-28b5dd7b2347.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating Renewable Energy from the Sea: A Study of OTEC Feasibility in the Banda Sea, Indonesia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe increasing global demand for electricity is driven by rapid technological advancements and infrastructure development, impacting all sectors, including households, industries, as well as government operations. As electricity becomes a fundamental necessity for daily life, its importance continues to grow (Jaiswal et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Maka \u0026amp; Alabid, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Strielkowski et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Currently, many nations heavily rely on fossil fuels as the primary energy source, which significantly contributes to rising carbon dioxide (CO2) emissions. This reliance on fossil fuels is a major factor in climate change, inspiring urgent calls for a transition to renewable energy sources. Various countries including Indonesia have started making changes to reduce greenhouse gas emissions and achieve net-zero targets. This marks a significant shift in energy policies and practices of the countries (Kusuma et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nasir \u0026amp; Bengi, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Resosudarmo et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tiwari et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe detrimental environmental impacts associated with fossil fuel use, particularly greenhouse gas emissions, have raised alarms about global warming. Increased temperatures and rising sea levels pose severe threats to ecosystems and human settlements worldwide (Griggs \u0026amp; Reguero, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Isiaka et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Roy et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tebaldi et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In response, governments globally are making commitments to reduce carbon emissions and promote cleaner energy alternatives. This is evident in the national energy policies of Indonesia, which set ambitious targets for renewable energy usage, aiming for 23% by 2025 and 31% by 2050, respectively (Kanugrahan et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Raihan, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The targets reflect the commitment of the country to a sustainable energy future, while also addressing the pressing issue of climate change.\u003c/p\u003e \u003cp\u003eDespite these commitments, Indonesia faces significant challenges in transitioning to renewable energy. High costs associated with renewable technologies and the slow pace of development have hindered progress, with only 11.31% of total energy consumption coming from renewable sources as of 2020 (MEMR-RI, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The continued dependence on fossil fuels, particularly coal, which accounts for over 40% of the national electricity supply, shows the urgency of accelerating renewable energy initiatives (MEMR-RI, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Addressing the challenges is crucial for the country to meet its energy needs sustainably while also reducing carbon footprint.\u003c/p\u003e \u003cp\u003eA promising avenue for renewable energy development in Indonesia lies in its vast marine resources. The country has significant potential to harness ocean energy, particularly through Ocean Thermal Energy Conversion (OTEC) with the second-longest coastline in the world. Research indicates that thermal ocean potential of Indonesia is estimated at approximately 2.5 x 10\u0026sup2;\u0026sup3; joules, with the capacity to generate around 0.1\u0026ndash;451.7 GW of power (Langer et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Suprijo et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This potential positions OTEC as a viable option for improving the renewable energy mix in the country and supports international efforts to transition to cleaner energy sources.\u003c/p\u003e \u003cp\u003eBanda Sea has surfaced as a particularly promising site for renewable energy development due to its favorable characteristics, including depths exceeding 2,000 meters and stable sea surface temperatures (SST) ranging from 26\u0026ndash;30\u0026deg;C throughout the year (Gordon \u0026amp; Susanto, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Iskandar, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Tadjuddah, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The combination of warm surface waters and cooler deep ocean temperatures creates ideal conditions for OTEC, allowing efficient energy conversion. Therefore, further investigation into the thermal dynamics of Banda Sea is essential for optimizing the development and implementation of renewable energy technologies in this region.\u003c/p\u003e \u003cp\u003eAccurate temperature measurements are critical for the successful application of OTEC and other renewable energy technologies. These measurements can be obtained through various methods, including direct sampling and modeling procedures. The use of oceanographic models, such as those provided by the Copernicus Marine Environment Monitoring Service (CMEMS), offers a practical solution for monitoring sea temperatures across extensive areas (Sanchez-Arcilla et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sotillo et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; von Schuckmann et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The accuracy of these models is influenced by numerous factors such as the algorithms used and the data quality, signifying the need for strong as well as up-to-date modeling to support renewable energy transition effectively in Indonesia. Moreover, the country can improve its understanding of marine resources and increase the feasibility of renewable energy projects by leveraging these advanced modeling methods, contributing to a sustainable energy future.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eThe research employs a combination of hardware and software tools for comprehensive data analysis. The primary equipment included a personal computer with an Intel Core i7 processor, which was essential for processing image data and conducting in-depth analyses of the results. Additionally, major software used in this research included Anaconda for Python programming, ArcGIS for advanced data visualization, Ocean Data View (ODV) for extracting and visualizing temperature data, and Microsoft Excel for tabulation and further data analysis. The data for the analysis comprised Marine Copernicus model data with a horizontal resolution of 9 km, aimed at analyzing temperature concentration in Banda Sea, alongside Argo Float data from 2023, which served as a critical reference for validating temperature concentration measurements.\u003c/p\u003e \u003cp\u003eThe method applied during the research was fundamentally observational, engaging in systematic observation and recording of phenomena using specialized instruments to gather scientific facts (Dehalwar \u0026amp; Sharma, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schwing, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This research leveraged secondary data sourced from Marine Copernicus website and in-situ measurements obtained from Argo Floats accessible via Coriolis website. The analysis process proceeded through stages of data collection, processing, and analysis, with a concentrated focus on Banda Sea region, particularly around stations known for high population density in Maluku. This method supported modern oceanographic research that showed the importance of incorporating diverse data sources to improve the accuracy of environmental assessments (Schwing, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe fieldwork was scheduled between October and December 2024, taking place at Oceanography and Marine Technology Laboratory at Jenderal Soedirman University. The research area comprised Banda Sea, with specific coordinates ranging from 2\u0026deg;S to 4\u0026deg;S and 125\u0026deg;E to 131\u0026deg;E (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During the process, three research stations were strategically identified based on geographic significance, particularly in regions such as Seram Bagian Barat, Ambon, and Maluku Tengah, which were characterized by high population density as well as ecological diversity. This selection process reflected current trends in marine research that prioritized locations with significant human impact and ecological importance (Pittman et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMarine Copernicus model data was initially downloaded in .nc format and subsequently converted to .txt format using ODV software for data processing. Initial preprocessing in Microsoft Excel was conducted to remove erroneous measurement values and to combine the data with reference values obtained from Argo. Relating to the analysis, the processed data was then exported for visualization at each coordinate of the research station using ODV software. The handling of Argo Float temperature data followed a similar method, ensuring that it followed the temperature data derived from Copernicus model, thereby facilitating a comprehensive analysis that supported best Data analysis incorporated both statistical and descriptive methods during the research. The validation of model data was thoroughly analyzed by comparing it with in-situ data from Argo Floats, specifically focusing on temperature data for the year 2023. Methods such as Mean Absolute Percentage Error (MAPE) and simple linear regression were used to assess model accuracy. In the context of the research, MAPE served as a critical measure of forecasting accuracy by calculating the average absolute error relative to actual observed values, with lower MAPE values indicating superior model performance (Chicco et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, simple linear regression was used to elucidate the relationships between independent and dependent variables, offering an understanding of how fluctuations in one variable influenced another (Montgomery et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe identification of OTEC potential was conducted seasonally, examining data from various periods throughout 2023. The net power potential was calculated by assessing the warm water intake at a depth of 15 meters, alongside the cold-water intake at depths that complied with Carnot efficiency standards. Moreover, the Carnot efficiency was calculated to optimize energy conversion, based on specific temperature differentials and operational parameters (Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The research identified potential OTEC installation sites by considering underwater topography, specifically targeting locations with depths greater than 700 meters and proximity to shorelines in 30 km, ensuring compliance with the efficiency criteria necessary for effective OTEC operations. This methodological framework supported contemporary research that showed the importance of incorporating thermodynamic principles with oceanographic data to assess renewable energy potential effectively (Fan et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eValidity of Coppernicus model\u003c/h2\u003e \u003cp\u003eThe validation of Marine Copernicus model data against Argo data represented a significant advancement in the understanding and application of oceanographic models. The use of MAPE as a metric for assessing prediction accuracy provided a strong framework for evaluating model performance. Following the discussion, the model indicated a high level of accuracy with a MAPE value of 2.814%, as it was less than the 10% threshold by Chicco et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This low error margin showed that Marine Copernicus model could be confidently used in decision-making processes, particularly in marine resource management and climate change research, where precise temperature data was critical (Drenkard et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe application of simple linear regression analysis to quantify the relationship between model data and in-situ measurements improved the credibility of the findings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The regression equation \u0026#119910;=0.9941\u0026#119909;\u0026minus;0.2144 indicated a nearly one-to-one relationship between the model and observed temperatures, reinforcing the reliability of the model. Relating to the discussion, a coefficient of determination (R\u0026sup2;) of 0.9945 signified an exceptional fit, with 99.45% of the variability in model temperature data explained by Argo temperature data. This strong correlation was crucial for validating the predictive capabilities of the model, which was essential for applications in fields such as oceanographic research and climate modeling (Haghbin et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe implications of these findings extended beyond validation, showing the potential of Marine Copernicus model as a crucial tool for assessing oceanic conditions. Accurate temperature data was essential for understanding marine ecosystems, influencing biological productivity, and managing fisheries sustainably. As explained by Brodie et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), reliable models could aid in predicting shifts in marine species distribution in response to changing ocean temperatures, thereby informing conservation strategies and policy decisions. The ability to accurately model temperature dynamics played an essential role in addressing the challenges posed by climate change in marine environments.\u003c/p\u003e \u003cp\u003eHigh accuracy of Marine Copernicus model supports its incorporation into broader oceanographic frameworks, where the method complemented other data sources. The findings showed that combining satellite-based models with in-situ measurements from platforms such as Argo improved the understanding of complex ocean dynamics. This incorporated method was increasingly recognized as necessary for effective ocean monitoring and management (Gacutan et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Research could acquire a more comprehensive view of oceanic conditions and the fluctuations over time by leveraging both remote sensing and in-situ data.\u003c/p\u003e \u003cp\u003eThe results from this research could inform future research directions in oceanography. The reliability shown reliability of Marine Copernicus model inspired further exploration into its applications, such as in climate change impact assessments and the development of renewable energy resources such as OTEC. Research by Mart\u0026iacute;nez et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) described that understanding thermal gradients in ocean water was essential for optimizing OTEC systems, and Marine Copernicus model could provide valuable data for such initiatives. This opened avenues for interdisciplinary research that combined oceanography, renewable energy, and environmental science.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe validation of Marine Copernicus model against Argo data confirmed its accuracy and showed the significance as a tool for scientific inquiry as well as practical applications. The strong correlation between modeled and observed temperatures indicated that this model could effectively inform decision-making in marine and environmental management. As the challenges posed by climate change continued to change, the reliance on strong models such as Marine Copernicus became crucial for developing effective strategies to mitigate impacts on marine ecosystems and ensure sustainable resource use.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSpatial and temporal distribution of OTEC potential\u003c/h3\u003e\n\u003cp\u003eThe potential for OTEC in Banda Sea was significantly influenced by seasonal variations in SST and corresponding thermal gradients at various depths (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During the west season, the warm water intake at a depth of 15 meters showed temperatures ranging from 29\u0026ndash;30\u0026deg;C, which was conducive for OTEC installations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The minimum installation depth of 643 meters across all research stations indicated that the thermal gradient was sufficient to achieve Carnot efficiencies between 7.60\u0026ndash;7.70%. These efficiencies were critical for the economic viability of OTEC systems, directly correlating with the energy output that could be harnessed from the temperature differential between warm surface and cold deep water (Khan et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Langer et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The results supported previous research that showed the importance of thermal gradients in optimizing OTEC systems (Aresti et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe stability of SST led to a consistent distribution of potential depths for OTEC installations in Transition 1 Season, which spanned from March to May (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The warm water intake temperatures remained relatively high, ranging from 29.40-29.75\u0026deg;C, allowing the same minimum installation depth of 643 meters. The Carnot efficiencies achieved during this season were comparable to those in the west season, indicating that the thermal conditions remained favorable for energy conversion. However, the slight decline in SST during this period showed that continuous monitoring was essential to adapt to changing thermal conditions, as even minor fluctuations could impact the efficiency of OTEC systems (Nakib et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This signified the need for adaptive management strategies in the deployment of OTEC technologies.\u003c/p\u003e \u003cp\u003eThe East Season, which occurred from June to August, presented a different scenario where the potential for OTEC installations was significantly affected by cooler SST, ranging from 27.74\u0026ndash;28.93\u0026deg;C (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). This necessitated deeper installations which exceeded 700 meters, to achieve the required Carnot efficiencies. The studies indicated that Station 1 maintained a minimum depth as in previous seasons, while Station 2 and 3 required deeper installations to meet efficiency standards. The cooler temperatures during this season were attributed to the influence of east monsoon winds, which promoted upwelling and reduced the availability of warm surface water (Lahiri \u0026amp; Vissa, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This seasonal variability showed the importance of understanding local oceanographic conditions in the planning and operation of OTEC systems.\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\u003e, Seasonal data for OTEC potential parameters.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeason\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWarm water temp. (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCold water temp. (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePotential depth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCarnot Efficiency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGross power potential (MW)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNet power potential (MW)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e82.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59.57\u003c/p\u003e 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align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e902.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e70.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.37\u003c/p\u003e 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colname=\"c8\"\u003e \u003cp\u003e86.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e108.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e90.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e78.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e82.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e64.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e902.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e87.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e70.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e94.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e76.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e100.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e82.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e105.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e88.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e109.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e91.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransition 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e81.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e63.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e81.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e63.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e902.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e69.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e93.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e75.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e97.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e80.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e103.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e85.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e106.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e88.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e82.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e64.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e902.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e70.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e94.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e76.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e99.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e82.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e104.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e86.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e107.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e90.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e643.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e79.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e61.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e81.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e63.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e78.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e902.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e83.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e70.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e94.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e75.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e80.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e101.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e83.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e902.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e80.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e62.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e68.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e92.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e73.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e77.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e100.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e81.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransition 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e763.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e73.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e54.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e80.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e61.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e66.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e91.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e71.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e75.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1062.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e57.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e83.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e63.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1452.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e68.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1684.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e92.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e72.05\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\u003eTable 2, Gross and net power potential of OTEC\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSession\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eStation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 208px;\"\u003e\n \u003cp\u003eGross Power Potential (MW)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 217px;\"\u003e\n \u003cp\u003eNet Power Potential (MW)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e80.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e82.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e77.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e62.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e65.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e60.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e93.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e108.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e77.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e75.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e90.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e59.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e93.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e109.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e78.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e76.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e91.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e60.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eTransition 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e79.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e81.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e76.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e61.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e63.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e59.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e92.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e106.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e76.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e74.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e88.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e58.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e93.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e107.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e77.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e75.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e90.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e60.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eEast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e80.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e81.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e79.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e62.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e63.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e61.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e90.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e101.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e78.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e72.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e83.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e59.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e91.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e100.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e80.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e72.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e81.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e62.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eTransition 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e70.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e73.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e73.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e49.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e54.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e54.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e83.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e95.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e86.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e63.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e75.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e66.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003eS-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e80.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e92.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e83.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e60.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e72.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e63.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cbr\u003e\u003cp\u003eTransition 2 Season, which occurred from September to November, showed a further decline in SST with warm water intake temperatures dropping by 1\u0026ndash;2\u0026deg;C compared to earlier seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). This reduction in temperature led to a more uniform distribution of cooler waters, which adversely affected the efficiency of OTEC systems. Station 1 became nonviable for OTEC operations as it failed to meet the necessary Carnot efficiency, even at maximum depths of 763 meters. Consequently, Station 2 and 3 required installations at depths exceeding 1,245 meters to achieve adequate efficiencies, with net power outputs of 66.88 and 63.39 MW, respectively. This shift in operational viability showed the critical role of seasonal temperature dynamics in determining the feasibility of OTEC projects (Alsebai et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe observed seasonal variations in SST and the impact on OTEC potential were consistent with findings from other regions, where similar patterns had been documented. For instance, research by Soltani et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) showed the significance of local climatic conditions in influencing ocean thermal energy systems. The analysis indicated that understanding these dynamics was essential for optimizing energy production and ensuring the sustainability of OTEC technologies. Furthermore, the findings from Banda Sea contributed to the broader discourse on renewable energy sources, particularly in tropical regions where ocean thermal gradients could be effectively harnessed.\u003c/p\u003e \u003cp\u003eThe implications of these findings extended beyond energy production, informing policy and management strategies for marine resources. As shown Mathew et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), the incorporation of OTEC systems into coastal management frameworks could improve energy security while promoting sustainable practices in marine environments. The ability to generate clean energy from ocean thermal gradients presented an opportunity to mitigate the impacts of climate change and reduce reliance on fossil fuels. Therefore, the development of OTEC technologies in Banda Sea should be accompanied by comprehensive environmental assessments to ensure that marine ecosystems were protected.\u003c/p\u003e \u003cp\u003eThe analysis of OTEC potential in Banda Sea showed significant seasonal variability influenced by thermal gradients and oceanographic conditions. The findings signified the importance of continuous monitoring and adaptive management strategies to optimize OTEC systems. As the demand for renewable energy sources increased, the understanding acquired from this research could inform future research and development efforts in ocean thermal energy technologies. Continued teamwork among authors, policymakers, and industry stakeholders would be essential to harness the full potential of OTEC systems while ensuring environmental sustainability.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this research showed that ocean energy, particularly through OTEC, had significant potential to support the renewable energy transition in Indonesia, especially in Banda Sea region. Validation of Copernicus model temperature data against in-situ Argo observations signified high accuracy, with a MAPE of 2.814% and an R\u0026sup2; of 0.9945, indicating the reliability of the model for ocean temperature analysis. Relating to this discussion, spatial and temporal analyses showed that OTEC potential was influenced by seasonal variations in SST and vertical temperature gradients, affecting Carnot efficiency as well as optimal installation depth. Among the three research stations analyzed, Station 2 was the most promising site for OTEC installation due to its favorable depth, relatively stable year-round temperature profile, and appropriate distance from the coastline. Developing OTEC at Station 2 could be a strategic step toward reducing dependence on fossil fuels and supporting national clean energy targets with a net power potential reaching up to 75.79 MW.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors listed have significantly contributed to the development and the writing of this article. A.A.: conceived and designed the experiments, performed the experiments, analyzed and interpreted the data, contributed reagents, materials, analysis tools or data, and wrote the paper; M.A.S.: conceived and designed the experiments, performed the experiments, analyzed and interpreted the data, and wrote the paper; I.P.: conceived and designed the experiments, analyzed and interpreted the data, and wrote the paper\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlsebai, F., Kang, H.-S., Yaakob, O., \u0026amp; Yazid, M. (2023). Review of resources from the perspective of wave, tidal, and ocean thermal energy conversion. 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Journal of Operational Oceanography, \u003cem\u003e11\u003c/em\u003e(sup1), S1\u0026ndash;S142. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/1755876X.2018.1489208\u003c/span\u003e\u003cspan address=\"10.1080/1755876X.2018.1489208\" 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":"[email protected]","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":"Ocean Thermal Energy Conversion, Banda Sea, Renewable Energy, Oceanographic Modeling, Temperature Gradient","lastPublishedDoi":"10.21203/rs.3.rs-6581259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6581259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe growing global demand for electricity, which is driven by rapid technological and infrastructure developments, has intensified the need to transition from fossil fuels to renewable energy sources. Indonesia holds significant potential for Ocean Thermal Energy Conversion (OTEC) with its abundant marine resources, particularly in Banda Sea. Therefore, this research aimed to explore the seasonal and spatial distribution of OTEC potential using temperature data from Marine Copernicus model, validated with Argo Float measurements. The validation produced a Mean Absolute Percentage Error (MAPE) of 2.814% and an R\u0026sup2; value of 0.9945, indicating high model accuracy. Moreover, seasonal variations showed that Carnot efficiency values between 7.60\u0026ndash;7.70% were achievable at depths of 643\u0026ndash;1,245 meters, depending on sea surface temperature (SST) fluctuations. Station 2, which was located 9 km from the coast, indicated the most consistent and optimal conditions for year-round OTEC operation with net power output ranging 63.85\u0026ndash;75.79 MW. This research showed the viability of OTEC in Banda Sea and indicated the importance of continuous monitoring and accurate modeling to support renewable energy transition in Indonesia.\u003c/p\u003e","manuscriptTitle":"Evaluating Renewable Energy from the Sea: A Study of OTEC Feasibility in the Banda Sea, Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 01:41:34","doi":"10.21203/rs.3.rs-6581259/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"c170f9fd-1391-46b4-a6f1-e8489b1cd188","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-04T06:39:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 01:41:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6581259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6581259","identity":"rs-6581259","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}