Comparative evaluation of maximum power point algorithms in photovoltaic systems for renewable energy utilization

Anotace: The irregular generation patterns of renewable energy systems lead to undesirable fluctuations in power grids. Integrating energy storage facilities into renewable energy systems is proposed as a solution to this issue. In this study, a photovoltaic energy system with energy storage is designed, and the effects of deterministic and stochastic optimisation-based algorithms on maximum power point tracking are analysed to ensure high-efficiency operation. In the designed system, maximum power point tracking of the photovoltaic system is achieved using the conventional Perturb and Observe, Incremental Conductance, Fuzzy Logic-Based Perturb and Observe, and Particle Swarm Optimization. The algorithms are extensively compared based on performance metrics such as rise time, settling time, and overshoot rate. The Fuzzy Logic-Based Perturb and Observe algorithm exhibits the best performance, with a rise time of 14.28 milliseconds and a settling time of 51.6 milliseconds, achieving the highest efficiency with a battery state of charge level of 69.97%. Detailed simulation analyses conducted in the Matlab/Simulink environment reveal that the fuzzy logicbased method provides faster and more stable results than other methods. Furthermore, a 24-hour real solar irradiance dataset is utilised to test the model under realistic environmental conditions, allowing for a more reliable evaluation of the performance of our storageintegrated photovoltaic.