Optimization of Microgrid Scheduling with Electric Vehicles Based on Improved Hiking Optimization Algorithm

With the prevalence of electric vehicles and the progress of microgrid (MG) technology, MG scheduling optimization with electric vehicles(EVs) has become a research hotspot. Therefore, this study proposes an innovative MG scheduling optimization method with electric vehicles based on the improved hiking algorithm. Firstly, Latin hypercubic sampling is used to establish the disordered electric vehicle charging model. Then, the structure and operation characteristics of the MG system containing electric vehicles are analyzed to clarify the scheduling objectives and constraints. Secondly, the hiking intelligent optimization algorithm is improved to form the improved hiking optimization optimization algorithm. Finally, the MG scheduling model is solved by the improved hiking algorithm. Simulation results demonstrate the superior performance of the proposed method, with IHOA reducing total MG operating costs by up to 300 RMB/day compared to conventional HOA, PSO, POA, and GWO algorithms. This work advances MG scheduling techniques by providing an effective solution to the challenges posed by stochastic EV loads while maintaining system stability and economic performance.