Using AI-Based Approaches to Sustainably Develop Energy Production in a Solar Power Plant

In a photovoltaic (PV) system, shading conditions caused by weather and ambient factors can significantly affect the electricity production. For more than a decade, applications of artificial intelligence (AI) techniques have been used to improve energy production efficiency in the solar energy sector. In this paper, we present how using AI-based can increase energy production for solar power plants experiencing shading conditions. It is shown that the application of these techniques paves the road towards sustainable development for the solar power sector. Employing maximum power point tracking (MPPT) control systems, running metaheuristic and computer-based algorithms, help PV arrays to cope with shading conditions effectively. Using a case study, we compare energy productions of the solar power plant in two scenarios: I) PVs without a control system, and II) PV arrays equipped with MPPT boards. System Advisory Model (SAM) is used to calculate monthly powers generated by the PV system. Our results prove our hypothesis that the PV system using MPPT systems provides a greater monthly energy production than without MPPTs.