Multi-target automobile charging method and device based on particle swarm optimization, and medium
Multi-target automobile charging method and device based on particle swarm optimization, and medium
- New search for: JIAO HAO
- New search for: CHEN JINMING
- New search for: ZHAO XINDONG
- New search for: LIU WEI
- New search for: GUO YAJUAN
- New search for: CHEN YE
- New search for: ZHUANG LING
- New search for: CAI DONGYANG
- New search for: CHE WEI
- New search for: JIAO HAO
- New search for: CHEN JINMING
- New search for: ZHAO XINDONG
- New search for: LIU WEI
- New search for: GUO YAJUAN
- New search for: CHEN YE
- New search for: ZHUANG LING
- New search for: CAI DONGYANG
- New search for: CHE WEI
The invention relates to the technical field of electric vehicle ordered charging methods, in particular to a particle swarm optimization-based multi-target vehicle charging method and device and a medium, and the method comprises the following steps of: establishing a typical curve of an electric vehicle load by adopting a Monte Carlo method; establishing an electric vehicle charging scheduling multi-target model; determining the weights of the plurality of optimization targets by using an improved entropy method; and an optimal charging control strategy of the electric vehicle under multi-objective optimization is searched through a particle swarm algorithm. According to the method, targets can be increased or decreased according to needs, the weight can be modified according to objective indexes, finally, the optimal charging control strategy of the electric vehicle under multi-target optimization is found through the particle swarm optimization, power grid peak-valley difference aggravation caused by concentrated charging of the electric vehicle at night can be effectively reduced, the charging cost of a user can be effectively reduced, and the user experience is improved. And the grid-connected photovoltaic power generation amount is considered in a target, so that the photovoltaic consumption can be greatly improved, and the power grid load fluctuation caused by photovoltaic output is reduced.
本发明涉及电动汽车有序充电方法技术领域，尤其涉及一种基于粒子群算法的多目标汽车充电方法、设备及介质，包括如下步骤：采用蒙特卡洛方法建立电动汽车负荷的典型曲线；建立电动汽车充电调度多目标模型；利用改进熵值法确定多个优化目标的权重；通过粒子群算法寻得多目标优化下电动汽车最优充电控制策略。本发明中，可以根据需要增加或者减少目标并根据客观指标修改权重，最终通过粒子群算法寻得多目标优化下电动汽车最优充电控制策略，能够有效降低电动汽车夜晚集中充电造成的电网峰谷差加剧，不仅能够有效降低用户充电成本，还能提高电网的安全可靠性，在目标中考虑并网光伏发电量，能够大幅提高光伏的消纳，减少光伏出力造成的电网负荷波动。
Document information
Multi-target automobile charging method and device based on particle swarm optimization, and medium
一种基于粒子群算法的多目标汽车充电方法、设备及介质
2022-12-02
Patent
Electronic Resource
Chinese
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