An improved sensorless maximum power point tracker technique for a photovoltaic pump system operating under partial shading conditions

Abstract PV irrigation systems are primarily used in rural areas and regions far from power transmission lines. Photovoltaic (PV) systems are expected to operate with high performance under both uniform irradiation and partial shading conditions (PSC). Maximum Power Point Tracking (MPPT) algorithms have been developed to achieve maximum efficiency of PV systems under varying atmospheric conditions. In conventional algorithms, at least two of the PV system's current, voltage, and at least two environmental variables are measured. In this study, a PV pump system using a Brushless Direct Current (BLDC) motor and Zeta converter is simulated in the MATLAB/Simulink environment. Four different partial shading conditions, each drawing maximum power in different voltage regions, are created. A new MPPT algorithm that does not rely on PV system information, current, or voltage is proposed. Speed and current information are required and measured for the control of the BLDC motor. The proposed MPPT algorithm uses the speed and current information of the BLDC motor and consists of two stages. The proposed algorithm is compared with conventional sensorless, Cuckoo Search Algorithm (CSA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO) based MPPT methods. Using the proposed algorithm, an average power of 472.61W and an average efficiency of 99.61% were achieved in four different PSC cases. The closest efficiency to the proposed algorithm was achieved with the traditional sensorless algorithm, which was 98.86%.