基于数据驱动和负荷准线的储能与 多类用户需求响应优化策略

董伦; 黄媛; 许潇; 王镜峣; 孙增杰

doi:10.19725/j.cnki.1007-2322.2024.0023

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基于数据驱动和负荷准线的储能与多类用户需求响应优化策略

储能 | 更新时间：2026-06-02

- 基于数据驱动和负荷准线的储能与多类用户需求响应优化策略
- Energy Storage and Multi-user Demand Response Optimization Strategy Based on Data-driven and Customer Directrix Load
- 现代电力 2026年43卷第3期页码：540-549
- 作者机构：
  
  1. 四川大学电气工程学院,四川省,成都市,610065
  2. 国网河北省电力有限公司,河北省,石家庄市,050021
- 作者简介：
  
  董伦(1999)，男，硕士研究生，研究方向为电网优化调度、需求响应，E-mail：dl199944@163.com
  黄媛(1974)，女，博士，副教授，通信作者，研究方向为配电网的规划与运行、电力系统稳定与控制，E-mail：yuanhuang@scu.edu.cn
  许潇(1996)，男，博士，副研究员，研究方向为人因交互电力系统相关理论与方法、电力交通社会复杂系统建模分析、新能源电力系统优化，E-mail：xxiao@scu.edu.cn
  王镜峣(1998)，女，硕士研究生，研究方向为配电网扩展规划，E-mail：455147314@qq.com
  孙增杰(1972)，男，学士，高级工程师，研究方向为电网调度自动化与科技管理，E-mail：807797749@qq.com
- 基金信息：
  
  国家自然科学基金项目(52207128)。
- DOI：10.19725/j.cnki.1007-2322.2024.0023
  中图分类号： 3
- 纸质出版：2026
- 稿件说明：
移动端阅览
董伦, 黄媛, 许潇, 等. 基于数据驱动和负荷准线的储能与多类用户需求响应优化策略[J]. 现代电力, 2026,43(3):540-549.

DONG Lun, HUANG Yuan, XU Xiao, et al. Energy Storage and Multi-user Demand Response Optimization Strategy Based on Data-driven and Customer Directrix Load[J]. 2026, 43(3): 540-549.
董伦, 黄媛, 许潇, 等. 基于数据驱动和负荷准线的储能与多类用户需求响应优化策略[J]. 现代电力, 2026,43(3):540-549. DOI： 10.19725/j.cnki.1007-2322.2024.0023.

DONG Lun, HUANG Yuan, XU Xiao, et al. Energy Storage and Multi-user Demand Response Optimization Strategy Based on Data-driven and Customer Directrix Load[J]. 2026, 43(3): 540-549. DOI： 10.19725/j.cnki.1007-2322.2024.0023.

摘要

新型电力系统中高渗透率的新能源机组不断削弱发电侧的调节能力，而需求侧的可调资源拥有巨大的调节潜力。需求侧的负荷种类繁多且用电特性复杂，利用数据驱动的方法能有效解决需求侧的精细化建模和调度管理难度较大等问题。为此，提出一种基于数据驱动和负荷准线的储能与多类用户需求响应优化策略。首先，评估需求侧各类可调资源参与需求响应的调节潜力。其次，考虑负荷分类后的响应特性，电网公司对参与需求响应的不同用户给予差异化奖励。再次，将需求响应优化模型转化为马尔科夫决策过程，以在全时段内贴近准线为目标，对负荷曲线进行整形，从而实现电网总运行成本最小化。最后，算例分析表明，负荷准线型需求响应不仅显著降低了该园区电网的总运行成本，而且充分就地消纳了新能源。相比各类负荷分别响应准线，将园区微网内可调的工业、商业和居民负荷与储能组成聚合负荷后，响应准线的效果更佳。

Abstract

In the context of a new power system

the high penetration of new energy units continuously weakens the regulation capacity on the generation side. Meanwhile

the adjustable resources on the demand side possess substantial potential for adjustment. There is a wide variety of load types on the demand side

each exhibiting complex electrical characteristics. Employing a data-driven approach can effectively address the challenges of precise modeling and scheduling management on the demand side. Therefore

an energy storage and multi-user demand response optimization strategy is proposed based on data-driven and customer directrix load. Firstly

an assessment is conducted on the adjustment potential of various adjustable resources on the demand side participating in demand response. Secondly

considering the response characteristics of the classified loads

the grid company provides differentiated rewards to different users participating in demand response. Thirdly

the demand response optimization model is transformed into a Markov decision process

shaping the load curve throughout the entire time period to closely align with the target directrix

thereby minimizing the overall operational cost of the grid. Finally

the case analysis shows that the customer directrix load demand response not only significantly decreases the overall operational cost of the park's grid but also effectively accommodates new energy locally. Compared to different types of loads responding to the directrix separately

the effect of aggregating adjustable industrial

commercial

and residential loads with energy storage in a park microgrid within a region yields superior results in responding the directrix.

关键词

Keywords

references

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