Optimization of Solar Panel Orientation for Maximum Energy Efficiency

• Published in: 2023 4th International Conference on Smart Electronics and Communication (ICOSEC) pp. 159 - 162
• Main Authors: Selvi, S., Mohanraj, M., Duraipandy, P., Kaliappan, Seeniappan, Natrayan, L., Vinayagam, Nadanakumar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 20.09.2023
• Subjects: ANOVA analysis; Climate change; Climate change mitigation; Energy efficiency; Geographical locations; Machine learning algorithms; Optimization methodology; Predictive models; Production; Regression analysis; Shading factors; Solar angles; Solar panel orientation; Sustainable energy solutions; Weather forecasting
• DOI: 10.1109/ICOSEC58147.2023.10276287

This report details the findings of a research that was conducted with the purpose of establishing where exactly solar panels should be positioned in order to make the most of their potential to convert sunlight into usable electrical power. The angle at which solar panels are positioned relative to the sun is one of the most important determinants of the amount of energy they produce; hence, maximizing this characteristic has the potential to considerably boost energy efficiency. For the purpose of the research, statistics were gathered on the amount of energy produced by solar panels positioned in a variety of various angles. An exercise in regression analysis was carried out in order to determine the primary elements that determine the degree to which sun angles and shading factors have an effect on energy efficiency. The results of the regression analysis were put to use in the process of developing a strategy for improving the orientation of solar panels. Following that, an analysis of variance was carried out in order to assess how well the planned approach had been implemented. Alterations in the orientation of solar panels were found to have the greatest effect on the amount of energy produced when both the angle of sunlight's incidence and the degree of shadowing were taken into consideration. The findings of our research might have important implications for the development of environmentally friendly energy alternatives and for the reduction of the negative effects of climate change. In addition to this, they are important considerations in the design and installation of systems that use solar panels. Because it may assist in the optimization of panel orientation to achieve maximum energy output, the suggested methodology can serve as a useful tool for stakeholders who are involved in the development and implementation of solar panel systems. This is because the proposed methodology can help achieve maximum energy output. In next research initiatives, it may be worthwhile to investigate the possibility of using more sophisticated modelling approaches, like as machine learning algorithms, in order to improve the accuracy of solar panel orientation forecasts for various geographical areas and meteorological situations.