Partially shaded photovoltaic (PV) modules have multiple peaks in the power-voltage (P-V) characteristic curve and conventional maximum power point tracking (MPPT) algorithm, such as perturbation and observation (P&O), which is unable to track the global maximum power point (GMPP) accurately due to its localized search space. Therefore, this paper proposes a differential evolution (DE) based optimization algorithm to provide the globalized search space to track the GMPP. The direction of mutation in the DE algorithm is modified to ensure that the mutation always converges to the best solution among all the particles in the generation. This helps to provide the rapid convergence of the algorithm. Simulation of the proposed PV system is carried out in PSIM and the results are compared to P&O algorithm. In the hardware implementation, a high step-up DC-DC converter is employed to verify the proposed algorithm experimentally on partial shading conditions, load variation, and solar intensity variation. The experimental results show that the proposed algorithm is able to converge to the GMPP within 1.2 seconds with higher efficiency than P&O.
All Science Journal Classification (ASJC) codes
- Atomic and Molecular Physics, and Optics
- Renewable Energy, Sustainability and the Environment
- Materials Science(all)