Computational intelligence techniques for maximum power point tracking in PV systems: A review

Maximum power point (MPP) tracking (MPPT) is an important technique for maximizing the power extraction from photovoltaic (PV) systems under varying climatic conditions. In an array of PV modules it is possible to observe multiple peaks in the power versus voltage (P-V) curve due to the current versus voltage (I-V) PV cell mismatch caused by differences in the received irradiance, such as occurs during partial shading. In these circumstances, the ability of the MPPT devices to track the global MPP of the PV array directly influences the system efficiency. In the literature, various MPPT techniques have been proposed. Among them, computational intelligence (CI) algorithm based MPPT methods have demonstrated the ability to find the global MPP. This paper presents a detailed and specific review of CI- based MPPT techniques. Each method type is classified into one of several subcategories according to its application strategy. The various ways of applying CI into MPPTs are analyzed in detail. The advantages and disadvantages of each method are discussed and compared. The purpose of this study is to provide a compendium on CI-based MPPT techniques for users to understand and select an appropriate method based on application requirements and system constraints.