Global Maximum Power Point Tracking of Photovoltaic Module Arrays Based on Improved Artificial Bee Colony Algorithm

In this paper, an improved artificial bee colony (I-ABC) algorithm for the maximum power point tracking (MPPT) of a photovoltaic module array (PVMA) is presented. Even though the P-V output characteristic curve with multi-peak was generated due to any damages or shading discovered on the PVMA, the I-ABC algorithm could get rid of stuck on tracking the local maximum power point (LMPP), but quickly and stably track the global maximum power point (GMPP), thereby improving the power generation efficiency. This proposed I-ABC algorithm could search for the higher power point of a PVMA by a small bee colony, determine the next tracking direction through the perturb and observe (P&O) method, and keep tracking until the GMPP is obtained. This method could prevent tracking the GMPP for too long due to applying a small bee colony. First, in this study, the photovoltaic modules produced by Sunworld Co., Ltd. were used and were configured as a PVMA with four series and three parallel connections under different numbers of shaded modules and different shading ratios, so that corresponding P-V output characteristic curves with multi-peak values were generated. Then, the GMPP was tracked by the proposed MPPT method. The simulation and experimental results showed that the proposed method performed better both in dynamic response and steady-state performance than the traditional artificial bee colony (ABC) algorithm. According to the experimental results, it showed that the tracking accuracy for the GMPP based on the proposed MPPT with 100 iterations under 5 different shading ratios was about 100%; on the other hand, that of the traditional ABC algorithm was 70%, and that of the P&O method was lower at about 30%.