浙江电力2025，Vol.44Issue(6)：82-90,9.DOI:10.19585/j.zjdl.202506008
基于AQPSO算法的智能楼宇微电网优化调度
Optimal scheduling of smart building microgrids based on AQPSO
摘要
Abstract
To enhance the economic efficiency and low-carbon performance of smart building operations,this paper proposes an optimal economic scheduling strategy for smart building microgrids based on the adaptive quantum par-ticle swarm optimization(AQPSO).Firstly,a smart building microgrid model incorporating photovoltaic,wind power,and electric vehicle(EV)is established,considering constraints such as power balance,thermal comfort,and the total charging/discharging power of EV clusters,with the objective of minimizing energy costs over the build-ing's operational cycle.Secondly,the improved quantum particle swarm optimization(QPSO)is improved through adaptive parameter control,and the AQPSO is employed to solve the model.Finally,four scenarios are set up for case analysis.The results demonstrate that the AQPSO outperforms traditional methods in terms of convergence speed and optimization capability.The proposed model and optimal scheduling strategy effectively reduce building operating costs,carbon emissions,and carbon emission costs,while improving the utilization rate of clean energy.关键词
智能楼宇微电网/车一网互动/自适应量子粒子群优化/优化调度Key words
smart building microgrid/V2G/AQPSO/optimal scheduling引用本文复制引用
叶傲霜,李逸超,胥栋,杜佳玮,张宇华,汪健辉..基于AQPSO算法的智能楼宇微电网优化调度[J].浙江电力,2025,44(6):82-90,9.基金项目
上海市科委科技创新计划项目(22010501400) （22010501400）
