Novel hybrid improved bat algorithm and fuzzy system based MPPT for photovoltaic under variable atmospheric conditions

Nowadays, photovoltaic (PV) systems are supplying electrical power networks in developed countries due to their economic, technical and environmental profits. However, to achieve the mentioned advantages, PV systems must produce power at their maximum possible power. Maximum power point tracking (MPPT) controllers are used to extract the maximum power in PV systems. Nevertheless, the performance of conventional MPPT con-trollers is not acceptable in variable climate circumstances. To manage this challenge, a fuzzy logic controller (FLC) with the improved bat algorithm (IBA) is used to reach efficiently MPP. The IBA algorithm is employed to fine-tune member functions (MFs) of FLC. Using this method, the stochastic behavior of irradiances and tem-peratures can be addressed. Simulation results in different case studies are done to confirm the edge of the suggested technique over conventional techniques. In addition, a battery storage system is utilized to meet the demand over some hours of the day that the PV system cannot supply the load alone. The results of case studies show that the IBA-FLC has advantages such as generating maximum power and low convergence time in changing atmospheric conditions over conventional MPPT methods.

Automated summary

This study proposes a method combining improved bat algorithm with fuzzy logic controller to achieve effective maximum power point tracking in photovoltaic systems. Results show that the method performs better in various climate conditions compared to traditional MPPT methods.