Performance enhancement of maximum power point tracking of wind energy system using horse herd optimization for direct current grid-wind-photovoltaic-battery storage hybrid structure: Design and comparative analysis

Green energy being the viable solution to endless power generation necessitates the construction of future direct current (DC) grids incorporating renewable energy sources (RESs), and various source and load uncertainties. Because of the irregular nature, unmatched load, and generation patterns and the need to impose minimal stress on the grid, a storage solution becomes necessary with maximum power extraction from the RESs. Here, an effort has been made to design a futuristic DC grid integrating RESs considering load and source uncertainities occuring during operation, with maximum power point tracking (MPPT) of the wind energy system (WES) achieved and implemented using a novel horse herd optimization algorithm (HHOA). The MPPT of the photovoltaic (PV) system is also implemented using the same optimization technique. Analysis includes operation of an interconnected wind-PV-battery storage-DC grid for rapid fluctuations in output of RESs and connected loads. In-depth performance analysis is presented to showcase the enhanced performance of the HHOA MPPT for WES. Quantitative and qualitative simulation results indicate the superior performance of the HHOA MPPT for WES under all operating conditions, with the percentage of maximum power extracted being 98.67%, average time to reach MPP being 0.025 s and ripple in the steady-state power being 0.27%. Parameter sensitivity analysis and computational complexity analysis of HHOA are included where results demonstrate superior performance of HHOA compared to other notable optimization techniques. Perturb and Observe MPPT method for WES is also implemented on the same WES, and its performance is contrasted with the HHOA MPPT controller's performance to showcase the efficacy of the designed system.