Multi-objective particle swarm optimization for optimal scheduling of household microgrids - Huang, Yu; He, Gengsheng; Pu, Zengxin; Zhang, Ying; Luo, Qing; Ding, Chao (Frontiers in Energy Research, 2024)
Aiming to address the issue of household loads and the concentrated power consumption of electric vehicles during low electricity price hours impacting the utility grid side, a multi-objective particle swarm algorithm-based optimal scheduling method for household microgrids is proposed. A household microgrid optimization model is developed to consider time-sharing tariffs and users' travel with electric vehicles. The model aims to optimize household daily electricity costs and grid-side energy supply variances. The mathematical model considers the actual input power and output power of each distributed energy source in the microgrid as the optimization variables. It also includes an analysis of capacity changes for the energy storage battery and the electric vehicle battery, which are combined with arithmetic simulation in the Pareto optimal solution set to select the optimal solution. Simulation results validate the efficacy of the proposed strategy in constraining fluctuations in energy input and output on the utility side, consequently reducing daily household electricity costs. This optimization approach not only enhances the overall quality of electricity consumption but also attests to its economic and practical viability.