Adaptive Perturb and Observe Algorithm for Photovoltaic Maximum Power Point Tracking

The optimization of energy generation in a photovoltaic (PV) system is necessary to let the PV cells operate at the maximum power point (MPP) corresponding to the maximum efficiency. Since the MPP varies, based on the irradiation and cell temperature, appropriate algorithms must be utilized to track the MPP. This is known as Maximum Power Point Tracking (MPPT). Different MPPT algorithms, each with its own specific performance, have been proposed in the literature. In this paper, a so-called Perturb and Observe (P&O) method is considered. This method is widely diffused because of its low-cost and ease of implementation. When atmospheric conditions are constant or change slowly, the P&O method oscillates close to MPP. However, when these change rapidly, this method fails to track MPP and gives rise to a waste of part of the available energy. An adaptive P&O method is proposed in this paper that has faster dynamics and improved stability compared to the traditional P&O. The MPPT algorithm was set up and validated by means of numerical simulations and experimental tests, confirming the effectiveness of the method.