电力需求侧管理2024，Vol.26Issue(3)：9-14,6.DOI:10.3969/j.issn.1009-1831.2024.03.002
基于高斯过程回归的电动汽车集群灵活性的概率预测
Flexibility probabilistic prediction of electric vehicle fleet based on Gaussian process regression
摘要
Abstract
Electric vehicles(EVs)are important new adjustable load resources,and predicting their flexibility is an essential prerequisite for implementing optimized dispatch.A method to infer the fleet charging feasibility domain based on normal charging session data of EVs is proposed,forming a historical dataset on the flexibility of EV fleets.Subsequently,considering the high stochasticity of charging load,a probability prediction method for the flexibility of EV fleets based on Gaussian process regression is proposed.The obtained probability prediction results can be used to establish chance constraints for the optimization problem of EV fleet and convert them into deterministic constraints under specific confidence levels.Lastly,simulation verification is conducted using actual charging data.The results show that the proposed method can accurately predict the charging flexibility of EV fleets from both energy and power aspects.By adjusting the confi-dence level,it is possible to balance the economy and the implementability when optimizing the EV fleets.关键词
电动汽车/充电灵活性/累积电量包络线/高斯过程回归/机会约束Key words
electric vehicle/charging flexibility/cumulative energy envelope/Gaussian process regression/chance constraint分类
信息技术与安全科学引用本文复制引用
刘子腾,孙烨,张沛超,徐博强,赵建立..基于高斯过程回归的电动汽车集群灵活性的概率预测[J].电力需求侧管理,2024,26(3):9-14,6.基金项目
国网浙江省电力有限公司经济技术研究院科技项目(JY02202281) （JY02202281）
