Photovoltaic MPPT Control Based on Improved KMTOA in Complex Environment

Under the complicated environment, the maximum power point tracking (MPPT) ofPV system is carried out by traditional algorithm, which is very easy to be failed due to tracking to local extremum maximum power point. Therefore, the M control of local shadow based on intelligent algorithm is becoming more and more popular. However, the conventional intelligent algorithm also has the disadvantage of falling into a local maximum and introducing a large tracking oscillation to the MPPT control system. To solve these problems, this paper proposes an MPPT control strategy based on niche kinetic-molecular theory optimization algorithm (NKMTOA), which combines the ability of niche to jump out of local extremum and the simplicity and efficiency of KTMOA algorithm. The simulation results show that the proposed algorithm can track more accurately and faster, with smaller oscillation at the maximum power point and higher energy conversion rate, which can track the maximum power point in complex environment in real time