A two‐stage energy management strategy for household microgrids considering the influence of electric vehicle travel characteristics and daylight hours

Abstract

We propose a two‐stage energy management strategy for household microgrids to improve their operational efficiency and economic benefits by making full use of the time‐of‐use electricity price and considering the impact of temporal and spatial uncertainty of electric vehicles (EVs) and different sunshine hours on household photovoltaic (PV). The strategy combines the time‐sharing tariff period and the travel time of EVs to make full use of the dual attributes of EVs as both load and generation units. Particle swarm algorithm is used to optimize the household PV output, EV and storage system charging/discharging strategies, and the energy interaction between the microgrid and the main network. This algorithm guides the household microgrid to achieve the optimal economic operation while cutting the peaks and filling the valleys of the main network to realize the efficient allocation of power resources. Finally, three typical scenarios are used for optimization, and the results show that the proposed energy management strategy can provide savings of 1,413.02, 1,026.94 and 929.19 yuan per day under the three scenarios analyzed, respectively, which verifies the effectiveness and rationality of the model. A sensitivity analysis is also conducted.