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Photovoltaic solar array: Modeling and output power optimization

Photovoltaic energy is a natural form of energy and can replace conventional fuels. The photovoltaic performance depends mainly on the incident solar irradiation, temperature, photovoltaic generator material composition. This article proposes a method of photovoltaic arrays modeling. With data provided by the manufacturer, the method finds the electric equations (current versus voltage, power versus voltage) for photovoltaic array at standard conditions. Model also takes account of temperature and insolation variations to determine novel characteristics for specific conditions. This article also discusses the use of DC–DC converter realized as a means of maximum power point tracker (MPPT). The control card obtains informations from the PV array through microcontroller's ports. Combined methods: jump to maximum power point (MPP) and power's comparison method are used as an algorithm to track the maximum power point of the PV array. Analysis experimental results were carried in order to verify the proposed method. Another purpose of this article is to model the optimal power using the methodology of experimental design. An optimization of power delivered by photovoltaic generator takes into account the insolation and temperature factors. In general, in the methods in literature, only solar irradiation variations or load variations are considered. But, the results do not reflect the conditions that occur in the real conditions. The design of experiment (DoE) technique and the response surface methodology (RSM), are employed to analyze the results of tests obtained during different climatic conditions. Results are given and analyzed in this article. Results are used to fit and adjust response surfaces to experimental data. The obtained results made it possible to propose a mathematical model and, consequently to study interactions between temperature and insolation. The DOE simulation model can be implemented in future works. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1529–1536, 2016