Maximum power point tracking of a standalone photovoltaic system using electromagnetic field optimization algorithm

There are non-stop efforts being put into enhancing the performance of the available maximum power point tracking methods and proposing new tracking methods. In this paper, a novel maximum power point tracking method based on a physics-inspired metaheuristic algorithm called Electromagnetic Field Optimization algorithm is proposed. The methodology of applying the Electromagnetic Field Optimization method on the maximum power point tracking problem is explained. The proposed method is applied to control the duty cycle of a DC–DC converter in a standalone photovoltaic system. The performance of the proposed method is evaluated against the Cuckoo Search Algorithm method, the Particle Swarm Optimization method, the Perturb and Observe method, and the Incremental Conductance method. A simulation test using MATLAB/Simulink software was conducted for varied sun irradiance levels under fixed temperature and load conditions. An experimental test was also conducted under fixed load and fixed weather conditions. The proposed method achieved tracking efficiencies of 100% and 80.14% in the simulation and experimental tests, accordingly. The superiority of the proposed method over the other applied metaheuristic-based methods is highlighted as the proposed method achieved short tracking times, no steady-state oscillations, and no duty cycle oscillations in both tests. The easiness of tuning the proposed method’s parameters is also an advantage of it.