Collaborative Economic-Low-Carbon Dispatch Strategy for Low-Carbon Building Microgrid with V2G

Abstract In order to improve the economic and environmental benefits of intelligent buildings, this paper proposes a low-carbon building microgrid economic low-carbon collaborative optimization allocation strategy with V2G. Firstly, a smart building microgrid system model is constructed, including photovoltaic power, wind power, and electric vehicles (EVs); it comprehensively considers constraints such as power balance, indoor temperature comfort, and the total charging and discharging power of EV clusters, and takes minimizing the total energy cost over the operation cycle as the optimization goal. Secondly, the adaptive parameter control mechanism is introduced into the traditional quantum particle swarm optimization (QPSO) algorithm to form an improved AQPSO algorithm to improve the solution performance. Finally, two typical scenarios are set up for simulation. The results show that the AQPSO algorithm is superior to the comparison algorithm in terms of convergence speed and global optimization ability. The proposed scheduling strategy can effectively reduce the system operation cost, carbon emissions, and related carbon costs, and improve the level of clean energy consumption.