Solar energy as the most important source of renewable energy is an important alternative to fossil and non-renewable energies. This energy source, in addition to many benefits, is also very sensitive to environmental changes. Atmospheric changes can be expressed as a main factor in reducing the performance of Solar Cells. In this study, by using particle swarm optimization algorithm, the amount of solar energy dissipation in solar panels affected by atmospheric changes (the most important factor), including radiation, precipitation and wind, has been investigated. For this purpose, a comparative method with the base state has been used and the amount of difference between the two results in the solar cells is measured. In this regard, created solar cells in Maragheh city are considered as the basis for analysis. Based on the results of measurements and simulation by particle swarm optimization algorithm, the maximum atmospheric effect is related to the variations curve of the precipitation and then the variations curve of the radiation (shadow). Also, wind changes have had the least impact on reducing the performance of solar panels in the area. تفاصيل المقالة

Fossil fuels as known as non-renewal sources which are mostly affect environment very adverse were extraction operations are costly which that the new-energy sources application is widely considered. The solar panels are the most effective devices for receive and control solar energy which focused on this study. The most important issue in solar cells is the problem of energy dissipation during day-night cycles. For this purpose, the particle swarm optimization (PSO) and perturb & observe (P&O) algorithms are utilized for evaluate the energy dissipation amounts were implemented in MATLAB. As basic of the analysis, Maragheh city's solar cells site is conducted to assessments. According to the results, the P&O method as well as PSO is suited for single-element solar radiation and for radiation/time response at tracking of maximum power point tracking (MPPT) were related to the day-night cycles. تفاصيل المقالة