电力系统自动化2024，Vol.48Issue(7)：94-102,9.DOI:10.7500/AEPS20230625007
基于时序注意力机制的电动汽车灵活性概率建模
Probabilistic Modeling of Electric Vehicle Flexibility Based on Temporal Attention Mechanism
摘要
Abstract
Electric vehicle(EV)is the flexible load that can provide flexibility to the power system.Most of the existing studies modeling the flexibility of EVs only consider the uncertainty of charging behavior and the impact of time-of-use tariffs.The deviation between the day-ahead tariff and real-time tariff is ignored,and the modeling of real-time tariff and charging load multi-timescale time-series characteristics is neglected.Aiming at this problem,this paper summarizes the manifestations and influencing factors of the flexibility of EVs,and proposes a probabilistic modeling method of the flexibility of EVs based on the temporal attention mechanism by considering the uncertainty of tariff-oriented response and the uncertainty of charging behavior.The different timescale weights are extracted by the time-series attention mechanism.A multi-timescale feature extraction network based on the temporal convolutional network is designed to learn the uncertainty of charging behavior and electricity price,and extract multi-timescale flexibility fluctuation features.The cases show that the proposed model can effectively learn charging behavior uncertainty and tariff-oriented response uncertainty,and its probabilistic modeling effect has higher reliability and accuracy.关键词
电力系统/灵活性/电动汽车/概率建模/多时间尺度/时序注意力机制/时序卷积网络Key words
power system/flexibility/electric vehicle/probabilistic modeling/multi-timescale/temporal attention mechanism/temporal convolutional network引用本文复制引用
王昊天,刘栋,秦继朔,史锐,但扬清,孙英云..基于时序注意力机制的电动汽车灵活性概率建模[J].电力系统自动化,2024,48(7):94-102,9.基金项目
国家电网公司总部科技项目(5100-202356026A-1-1-ZN). This work is supported by State Grid Corporation of China(No.5100-202356026A-1-1-ZN). （5100-202356026A-1-1-ZN）
