电器与能效管理技术 ›› 2026, Vol. 0 ›› Issue (7): 21-25.doi: 10.16628/j.cnki.2095-8188.2026.07.003

• 研究与分析 • 上一篇    下一篇

基于新型电力系统特征的负荷调控优化方法研究与应用

方佳韵1,2,3   

  1. 1 上海电器科学研究所(集团)有限公司, 上海 200063
    2 国家能源智能电网用户端重点实验室, 上海 200063
    3 上海市智能电网需求响应重点实验室, 上海 200063
  • 收稿日期:2026-05-18 出版日期:2026-07-30 发布日期:2026-08-12
  • 作者简介:方佳韵(1983—),女,高级工程师,从事智能电网软件开发及研究工作。

Research and Application of Load Regulation Optimization Method Based on Characteristics of the New-Type Power System

Fang Jiayun1,2,3   

  1. 1 Shanghai Electrical Apparatus Research Institute (Group) Co., Ltd., Shanghai 200063, China
    2 National Energy Smart Grid User Side Key Laboratory, Shanghai 200063, China
    3 Shanghai Key Laboratory of Smart Grid Demand Response, Shanghai 200063, China
  • Received:2026-05-18 Online:2026-07-30 Published:2026-08-12

摘要:

针对新型电力系统高渗透率可再生能源、高比例电力电子设备接入的“双高”特征,以及新能源发电波动性、间歇性与电动汽车规模化接入带来的调控难题,提出一种考虑新型电力系统特征的负荷调控优化方法。该方法通过反向传播(BP)神经网络实现日前新能源发电的精准预测,利用时间序列神经网络完成台区常规电力负荷预测,构建电动汽车充电需求计算模型估算台区电动汽车充电需求,最终结合新能源发电与常规负荷的时间维度特征,设计用户侧负荷调控优化策略,实现电动汽车充电计划与新能源发电峰值、常规负荷谷值的精准匹配,为新型电力系统的稳定运行与“双碳”目标的实现提供了技术支撑。

关键词: 新型电力系统, 负荷调控, 新能源消纳, 电动汽车, 神经网络预测, 峰谷差优化

Abstract:

Aiming at the “double-high” characteristics of new-type power systems with high penetration of renewable energy and high proportion of connected power electronic equipment,as well as the regulation difficulties caused by the volatility and intermittency of new energy generation and large-scale access of electric vehicles,a load regulation optimization method considering the characteristics of new-type power systems is proposed.Accurate day-ahead forecasting of new energy generation is realized via back propagation (BP) neural network,and forecasting of conventional station-area power loads is completed by time-series neural network.A calculation model for electric vehicle charging demand is constructed to estimate the charging demand of electric vehicles in the station area.Finally,combined with the temporal characteristics of new energy generation and conventional loads,an optimization strategy for user-side load regulation is designed.Accurate matching between electric vehicle charging schedules,the peak output of new energy generation and the valley value of conventional loads is achieved,and technical support is provided for the stable operation of new-type power systems and the realization of the “dual carbon” goals.

Key words: new-type power system, load regulation, new energy consumption, electric vehicles, neural network prediction, peak-valley difference optimization

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