Multi-agent Cooperative Optical Storage Operation Strategy Based on Demand Response

刘文霞; 吕笑影; 万海洋; 成锐

doi:10.19725/j.cnki.1007-2322.2023.0425

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

Multi-agent Cooperative Optical Storage Operation Strategy Based on Demand Response

更新时间：2026-02-02

- Multi-agent Cooperative Optical Storage Operation Strategy Based on Demand Response
- Vol. 43, Issue 1, Pages: 193-200(2026)
- 作者机构：
  
  华北电力大学电气与电子工程学院, 北京市昌平区,102206
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0425
  CLC： 1
- Published：2026
- 稿件说明：
移动端阅览
刘文霞, 吕笑影, 万海洋, et al. Multi-agent Cooperative Optical Storage Operation Strategy Based on Demand Response[J]. 2026, 43(1): 193-200.
DOI：

刘文霞, 吕笑影, 万海洋, et al. Multi-agent Cooperative Optical Storage Operation Strategy Based on Demand Response[J]. 2026, 43(1): 193-200. DOI： 10.19725/j.cnki.1007-2322.2023.0425.

摘要

随着配电网市场化改革的推进，光储聚合商逐渐成为市场参与主体。在此背景下，为确保配电网运行的经济性和安全性，防范高渗透率下分时电价引发的激励转移等问题，提出一种考虑需求响应的多主体协同光储运行策略。首先，在分时电价基础上引入引导电价，构建影子价格理论及相应模型，该理论和模型能够更准确地反映电力市场的实际情况，提高光储运行策略的适应性。通过引导电价的引入，可以更好地引导光储聚合商参与市场。其次，以各主体经济性最优为目标，建立配电网和光储聚合商运行的双层优化模型，通过该模型，可以有效平衡配电网的运行需求和光储聚合商的经济目标，实现多主体的协同运行。最后，通过算例验证所提出模型的有效性。

Abstract

With the advancement of market-oriented reform in distribution networks

optical storage aggregators have gradually become the main market participant. In this context

to ensure the economy and security of distribution grid operation and mitigate issues such as incentive shifting triggered by time-of-use prices under high penetration rates

a multi-body synergistic optical storage operation strategy is proposed with demand response taken into account. Firstly

a shadow price theory and corresponding model are developed by introducing a bootstrap price on the basis of time-of-use prices. This theory and model have the ability of more accurately reflecting the actual situation of the power market and improving the adaptability of the optical storage operation strategy. The introduction of the bootstrap price enables better market participation for the optical storage aggregator. On this basis

a two-layer optimization model for the distribution network operation and the optical storage aggregator is established with the objective of the optimal economy of each subject. Using this model

the balance between both the operation demand of the distribution network and the economic objectives of the optical storage aggregator can be effectively achieved to realize the synergistic operation of multiple subjects. Finally

the effectiveness of the proposed model is verified through arithmetic examples.

关键词

Keywords

references

MURTY V V S N, KUMAR A. Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems[J]. Protection and Control of Modern Power Systems, 2020, 5(1): 1−20.

LI Xiangjun, WANG Lijun, YAN Ning, et al . Economic dispatch of distribution network with distributed energy storage and PV power stations[C ] //2020 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD). Tianjin, China: Tiangong University, 2020: 1-2.

ZHANG Shuhua, WANG Jinsong, LIU Haibo, Prediction of energy photovoltaic power generation based on artificial intelligence algorithm[J]. Neural Computation, 2020, 33(1): 821-835.

CHEN Wei, AI Xin, WU Tao, et al . A review of research on the impact of photovoltaic grid-connected power generation systems on the power grid[J ] . Electric Power Automation Equipment, 2013, 33(2): 26−32(in Chinese).

陈炜, 艾欣, 吴涛, 等. 光伏并网发电系统对电网的影响研究综述[J]. 电力自动化设备, 2013, 33(2): 26−32.

ZHANG Jun, ZHANG Wei, CAO Lingjie, et al . Analysis of the development of energy storage market and the key development direction in China[J ] . Power Energy, 2020, 41(6): 739−743.

WANG Jinsong, CHEN Xuhui, ZHANG Fan, et al . Building load forecasting using deep neural network with efficient feature fusion[J ] . Journal of Modern Power Systems and Clean Energy, 2021, 9(1): 160−169.

SHI Jinkai, BAO Yan, CHEN Zhen, et al . A robust optimal allocation method for charging station energy storage taking into account charging load uncertainty[J ] . Automation of Electric Power System, 2021, 45(20): 49−58(in Chinese).

石锦凯, 鲍谚, 陈振, 等. 计及充电负荷不确定性的充电站储能鲁棒优化配置方法[J]. 电力系统自动化, 2021, 45(20): 49−58.

GE Shaoyun, SUN Rui, LIU Hong, et al . Multi-stage planning of photovoltaic storage charging and switching station with embedded operation optimization and power battery stepwise utilization[J ] . Electric Power Automation Equipment, 2022, 42(10): 149−156(in Chinese).

葛少云, 孙睿, 刘洪, 等. 内嵌运行优化与动力电池梯次利用的光储充换电站多阶段规划[J]. 电力自动化设备, 2022, 42(10): 149−156.

ZUO Guanlin, GUO Hongxia, LIN Wenzhi, et al . Optimal configuration of microgrid considering low-carbon hydrogen production[J ] . Electric Power Automatio n Equipment, 2023, 43(2): 9−18(in Chinese).

左冠林, 郭红霞, 林文智, 等. 考虑低碳制氢的微电网优化配置[J]. 电力自动化设备, 2023, 43(2): 9−18.

CHEN Yuanbo, ZHENG Kedi, GU Yuxuan, et al . Distributed optimal scheduling of distribution grid-side photovoltaic storage system considering electrochemical model[J ] . Automation of Electric Power System, 2024, 48(2): 37−47(in Chinese).

陈远博, 郑可迪, 顾宇轩, 等. 考虑电化学模型的配电网侧光储系统的分布式优化调度[J]. 电力系统自动化, 2024, 48(2): 37−47.

WANG Zhe, LIN Hua, MA Yajun, et al . Analysis and control strategy of modular multilevel converter with integrated battery energy storages system based on voltage source mode[C ] //2018 20th European Conference on Power Electronics and Applications (EPE'18 ECCE Europe).Rīga, Latvia, 2018: 1-9.

LI Xiangjun, WANG Shangxing. Energy management and operational control methods for grid battery energy storage systems[J]. CSEE Journal of Power and Energy Systems, 2021, 7(5): 1026−1040.

CHEN Wei, CHEN Longkang, WEI Zhanhong, et al . Multi-scenario cooperative optimization strategy for distributed optical storage based on net capacity and second-order cone planning[J ] . Electric Power Automation Equipment, 2024, 44(6): 26−34(in Chinese).

陈伟, 陈龙康, 魏占宏, 等. 基于净能力及二阶锥规划的分布式光储多场景协同优化策略[J]. 电力自动化设备, 2024, 44(6): 26−34.

XU Chengying, YANG Jun, DOU Zhenlan, et al . Research on intraday rolling scheduling technology of distribution grid and microgrid-level integrated energy system based on data-driven robust optimization[J ] . Journal of Wuhan University (Engineering Edition), 2025, 58(8): 1206−1216(in Chinese).

徐澄莹, 杨军, 窦真兰, 等. 基于数据驱动鲁棒优化的配电网与微网级综合能源系统日内滚动调度技术研究[J]. 武汉大学学报(工学版), 2025, 58(8): 1206−1216.

HUANG Kun, FU Ming, ZHAI Jiaxiang, et al . Distributed coordinated optimization of economic operation of multiple microgrids based on improved linearized ADMM[J ] . Electric Power, 2025, 58(02): 193−202(in Chinese).

黄堃, 付明, 翟家祥, 等. 基于改进线性化ADMM的多微网经济运行分布式协调优化[J]. 中国电力, 2025, 58(02): 193−202.

ZHAO Huiru, WANG Xuejie, LI Bingkang, et al . Distributed robust optimal scheduling of multi-community optical storage systems considering energy sharing[J ] . Automation of Electric Power System, 2022, 46(09): 21−31(in Chinese).

赵会茹, 王学杰, 李兵抗, 等. 考虑能量共享的多社区光储系统分布鲁棒优化调度[J]. 电力系统自动化, 2022, 46(09): 21−31.

ZHANG Hong, YAN He, SHEN Xin, et al . Distributed optimal scheduling of distribution network producers and consumers for energy community energy management[J ] . Proceedings of the CSEE, 2022, 42(12): 4449−4459(in Chinese).

张虹, 闫贺, 申鑫, 等. 面向能源社区能量管理的配网产消者分布式优化调度[J]. 中国电机工程学报, 2022, 42(12): 4449−4459.

MORET F, PINSON P. Energy collectives: A community and fairness based approach to future electricity markets[J]. IEEE Transactions on Power Systems, 2019, 34(5): 3994−4004.

NIU Gaoyuan, MENG Fanti, LIU Miaomiao, et al . Research on control strategy of optical storage charging and discharging machine based on time-sharing tariff[J ] . Electrotechnics Electric, 2022(12): 25−31(in Chinese).

牛高远, 孟凡提, 刘苗苗, 等. 基于分时电价的光储充放一体机控制策略研究[J]. 电工电气, 2022(12): 25−31.

CHENG Fei, GUO Chunlin, GAO Zeyang, et al . Scheduling strategy of electric heavy truck exchange station participating in grid peak shaving regulation[J ] . Automation of Electric Power System, 2024, 48(9): 1 20−128(in Chinese).

程飞, 郭春林, 高泽阳, 等. 参与电网削峰调节的电动重卡换电站调度策略[J]. 电力系统自动化, 2024, 48(9): 120−128.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Two-layer Low-carbon Optimized Dispatching for Integrated Energy Systems Considering Carbon Liability Allocation and Demand Response

Optimal Dispatching of Integrated Energy Systems Considering Demand Response and Carbon Price Uncertainty

A Scheduling Model of Virtual Power Plant Considering Source-load Uncertainty

Integrated Energy System Dispatch Optimization Considering Generalized Integrated Demand Response

Coordination Optimization of Distribution Network Considering Hydro-photovoltaic-load Uncertainty

Related Author

Yan SHI

Wenjie LI

Fengjiu YANG

Xiulin ZHOU

Chunming LIU

Hang YANG

Tao ZHANG

Huajun RAN

Related Institution

Power Supply Service Supervision and Support Center of State Grid Inner Mongolia East Electric Power Co., Ltd., Tongliao 028000, Inner Mongolia Autonomous Region

School of Electrical and Electronic Engineering, North China Electric Power University,Changping District

College of Electrical Engineering and New Energy, China Three Gorges University

Hubei Provincial Engineering Research Center of Intelligent Energy Technology, China Three Gorges University

Xianning Power Supply Company, State Grid Hubei Electric Power Co., Ltd.

AI问答

⁰