Hierarchical Cooperative Dispatching Strategy of Multi-microgrid and Distribution Networks Based on Multi-agent Algorithm

CHEN Chiyao; MIAO Shihong; YAO Fuxing; WANG Tingtao; WANG Jiaxu; WEI Wenrong

doi:10.7500/AEPS20221115002

您当前的位置：

首页 >

文章列表页 >

Hierarchical Cooperative Dispatching Strategy of Multi-microgrid and Distribution Networks Based on Multi-agent Algorithm

Basic Research | 更新时间：2025-06-16

- Hierarchical Cooperative Dispatching Strategy of Multi-microgrid and Distribution Networks Based on Multi-agent Algorithm
- Automation of Electric Power Systems Vol. 47, Issue 10, Pages: 57-65(2023)
- 作者机构：
  
  1.华中科技大学电气与电子工程学院，湖北省武汉市 430074
  2.强电磁工程与新技术国家重点实验室，华中科技大学，湖北省武汉市 430074
  3.电力安全与高效湖北省重点实验室，华中科技大学，湖北省武汉市 430074
- 作者简介：
- 基金信息：
  
  the Science and Technology Project of State Grid Corporation of China(5419-202199551A-0-5-ZN)
- DOI：10.7500/AEPS20221115002
  CLC：
- Received：15 November 2022，
  
  Revised：2023-02-24，
  
  Published Online：23 April 2023，
  
  Published：25 May 2023
- 稿件说明：
移动端阅览
陈池瑶,苗世洪,姚福星等.基于多智能体算法的多微电网-配电网分层协同调度策略[J].电力系统自动化,2023,47(10):57-65.

CHEN Chiyao,MIAO Shihong,YAO Fuxing,et al.Hierarchical Cooperative Dispatching Strategy of Multi-microgrid and Distribution Networks Based on Multi-agent Algorithm[J].Automation of Electric Power Systems,2023,47(10):57-65.
陈池瑶,苗世洪,姚福星等.基于多智能体算法的多微电网-配电网分层协同调度策略[J].电力系统自动化,2023,47(10):57-65. DOI： 10.7500/AEPS20221115002.

CHEN Chiyao,MIAO Shihong,YAO Fuxing,et al.Hierarchical Cooperative Dispatching Strategy of Multi-microgrid and Distribution Networks Based on Multi-agent Algorithm[J].Automation of Electric Power Systems,2023,47(10):57-65. DOI： 10.7500/AEPS20221115002.

摘要

近年来，作为消纳可再生能源的有效方式之一，微电网在新型电力系统中扮演了愈来愈重要的角色，取得了显著的发展。但微电网的大量接入，改变了传统配电网的单级调度模式，使得调度过程中所面临的计算和通信任务日益繁重，而现行调度策略难以兼顾配电网运营商及微电网等多主体的利益诉求，也难以满足调度过程的计算高效性与通信私密性要求。对此，提出了一种基于多智能体算法的多微电网-配电网分层协同调度策略。首先，考虑配电网运营商与微电网在电力市场运行中的主从关系，构建了基于双层Stackelberg博弈的多微电网-配电网电力交易模型；然后，将多微电网-配电网协同调度表述为马尔可夫决策过程，采用基于数据驱动的多智能体深度策略性梯度算法求解Stackelberg均衡；最后，基于改进IEEE 33节点系统开展算例分析，验证了所提模型及算法的有效性。

Abstract

In recent years

as one of the effective ways to utilize renewable energy

microgrids play an increasingly important role in the new power system and achieve remarkable progress. However

the massive access of microgrids has changed the single-stage dispatching mode of the traditional distribution network

and brought rather onerous tasks to the calculation and communication in the dispatching process. The existing dispatching schemes fail to take into account the interests of distribution network operators and microgrids as well as other multiple entities

nor can it meet the requirements of computing efficiency and communication privacy in the dispatching process. In this regard

a hierarchical cooperative dispatching strategy of multi-microgrid and distribution networks based on a multi-agent algorithm is proposed. First

considering the leader-follower relationship between distribution network operators and microgrids in power market operation

a power transaction model of multi-microgrid and distribution networks based on two-layer Stackelberg game is constructed. Then

the power coordinated dispatching of multi-microgrid and distribution networks is expressed as a Markov decision process

and the Stackelberg equilibrium is solved by using data-driven multi-agent deep deterministic policy gradient algorithm. Finally

a numerical case based on the modified IEEE 33-bus system is analyzed to verify the effectiveness of the proposed model and algorithm.

关键词

Keywords

references

吴福保，刘晓峰，孙谊媊，等 . 基于冷热电联供的多园区博弈优化策略［J］. 电力系统自动化， 2018 ， 42 （ 13 ）： 68 - 75 .

WU Fubao ， LIU Xiaofeng ， SUN Yiqian ， et al . Game optimization strategy for multiple parks based on combined cooling heating and power ［J］. Automation of Electric Power Systems ， 2018 ， 42 （ 13 ）： 68 - 75 .

陈刚，杨毅，杨晓梅，等 . 基于分布式牛顿法的微电网群分布式优化调度方法［J］. 电力系统自动化， 2017 ， 41 （ 21 ）： 156 - 162 .

CHEN Gang ， YANG Yi ， YANG Xiaomei ， et al . Distributed optimization scheduling method for microgrid cluster based on distributed Newton method ［J］. Automation of Electric Power Systems ， 2017 ， 41 （ 21 ）： 156 - 162 .

MAZZOLA S ， ASTOLFI M ， MACCHI E . A detailed model for the optimal management of a multigood microgrid ［J］. Applied Energy ， 2015 ， 154 ： 862 - 873 .

RIFFONNEAU Y ， BACHA S ， BARRUEL F ， et al . Optimal power flow management for grid connected PV systems with batteries ［J］. IEEE Transactions on Sustainable Energy ， 2011 ， 2 （ 3 ）： 309 - 320 .

程义，李更丰 . 基于双层模仿学习的多园区综合能源系统分布式协同优化调度［J］. 电力系统自动化， 2022 ， 46 （ 24 ）： 16 - 25 .

CHENG Yi ， LI Gengfeng . Distributed collaborative optimal dispatch of multi-park integrated energy system based on bilayer imitation learning ［J］. Automation of Electric Power Systems ， 2022 ， 46 （ 24 ）： 16 - 25 .

吴定会，高聪，纪志成 . 混合粒子群算法在微电网经济优化运行的应用［J］. 控制理论与应用， 2018 ， 35 （ 4 ）： 457 - 467 .

WU Dinghui ， GAO Cong ， JI Zhicheng . Economic optimization operation of the microgrid using the hybrid particle swarm optimization algorithm ［J］. Control Theory & Applications ， 2018 ， 35 （ 4 ）： 457 - 467 .

孙庆凯，王小君，王怡，等 . 基于多智能体Nash-Q强化学习的综合能源市场交易优化决策［J］. 电力系统自动化， 2021 ， 45 （ 16 ）： 124 - 133 .

SUN Qingkai ， WANG Xiaojun ， WANG Yi ， et al . Optimal trading decision-making for integrated energy market based on multi-agent Nash-Q reinforcement learning ［J］. Automation of Electric Power Systems ， 2021 ， 45 （ 16 ）： 124 - 133 .

郝然，艾芊，朱宇超 . 基于多智能体一致性的能源互联网协同优化控制［J］. 电力系统自动化， 2017 ， 41 （ 15 ）： 10 - 17 .

HAO Ran ， AI Qian ， ZHU Yuchao . Cooperative optimal control of Energy Internet based on multi-agent consistency ［J］. Automation of Electric Power Systems ， 2017 ， 41 （ 15 ）： 10 - 17 .

ZHAO D D ， ZHANG C H ， CAO X Y ， et al . Differential privacy energy management for islanded microgrids with distributed consensus-based ADMM algorithm ［J/OL］. IEEE Transactions on Control Systems Technology ［ 2022-10-04 ］. https：//ieee xplore. ieee. org/ document/9910413 https://ieeexplore.ieee.org/document/9910413 .

LEE J ， GUO J ， CHOI J K ， et al . Distributed energy trading in microgrids： a game-theoretic model and its equilibrium analysis ［J］. IEEE Transactions on Industrial Electronics ， 2015 ， 62 （ 6 ）： 3524 - 3533 .

PAUDEL A ， CHAUDHARI K ， LONG C ， et al . Peer-to-peer energy trading in a prosumer-based community microgrid： a game-theoretic model ［J］. IEEE Transactions on Industrial Electronics ， 2019 ， 66 （ 8 ）： 6087 - 6097 .

LIN K ， WU J ， LIU D ， et al . Energy management optimization of micro energy grid based on hierarchical Stackelberg game theory ［J］. Power System Technology ， 2019 ， 43 （ 3 ）： 973981 .

李方圆 . 基于多智能体协同算法的智能电网分布式调度与优化［D］. 合肥：中国科学技术大学， 2019 .

LI Fangyuan . On distributed operation and optimization in smart grid： an MAS coordination algorithm-based approach ［D］. Hefei ： University of Science and Technology of China ， 2019 .

张帆，武东昊，陈玉萍，等 . 多智能体深度强化学习的分布式园区综合能源系统经济调度策略［J］. 电力系统及其自动化学报， 2022 ， 34 （ 12 ）： 18 - 26 .

ZHANG Fan ， WU Donghao ， CHEN Yuping ， et al . Economic scheduling strategy for integrated energy system in distributed parks based on multi-agent deep reinforcement learning ［J］. Proceedings of the CSU-EPSA ， 2022 ， 34 （ 12 ）： 18 - 26 .

巨云涛，陈希，李嘉伟，等 . 基于分布式深度强化学习的微网群有功无功协调优化调度［J/OL］. 电力系统自动化［ 2022-10-13 ］. https：//kns.cnki.net/kcms/detail/32.1180.TP.20221012.1702.004.html https://kns.cnki.net/kcms/detail/32.1180.TP.20221012.1702.004.html .

JU Yuntao ， CHEN Xi ， LI Jiawei ， et al . Active and reactive power coordinated optimal dispatch of networked microgrids based on distributed deep reinforcement learning ［J/OL］. Automation of Electric Power Systems ［ 2022-10-13 ］. https：//kns.cnki.net/kcms/detail/32.1180.TP.20221012.1702.004.html https://kns.cnki.net/kcms/detail/32.1180.TP.20221012.1702.004.html .

范培潇，柯松，杨军，等 . 基于改进多智能体深度确定性策略梯度的多微网负荷频率协同控制策略［J］. 电网技术， 2022 ， 46 （ 9 ）： 3504 - 3515 .

FAN Peixiao ， KE Song ， YANG Jun ， et al . Load frequency coordinated control strategy of multi-microgrid based on improved MA-DDPG ［J］. Power System Technology ， 2022 ， 46 （ 9 ）： 3504 - 3515 .

芮涛 . 基于博弈论的配电侧多微电网系统优化运行方法研究［D］. 合肥：安徽大学， 2019 .

RUI Tao . Research on optimal operation method of distribution side multi-micro grid system based on game theory ［D］. Hefei ： Anhui University ， 2019 .

RUI T ， LI G L ， WANG Q J ， et al . Hierarchical optimization method for energy scheduling of multiple microgrids ［J］. Applied Sciences ， 2019 ， 9 （ 4 ）： 624 .

孙伟卿，刘晓楠，向威，等 . 基于主从博弈的负荷聚合商日前市场最优定价策略［J］. 电力系统自动化， 2021 ， 45 （ 1 ）： 159 - 167 .

SUN Weiqing ， LIU Xiaonan ， XIANG Wei ， et al . Master-slave game based optimal pricing strategy for load aggregator in day-ahead electricity market ［J］. Automation of Electric Power Systems ， 2021 ， 45 （ 1 ）： 159 - 167 .

LIN K J ， WU J Y ， LIU D . Economic efficiency analysis of micro energy grid considering time-of-use gas pricing ［J］. IEEE Access ， 2019 ， 8 ： 3016 - 3028 .

ANOH K ， MAHARJAN S ， IKPEHAI A ， et al . Energy peer-to-peer trading in virtual microgrids in smart grids： a game-theoretic approach ［J］. IEEE Transactions on Smart Grid ， 2020 ， 11 （ 2 ）： 1264 - 1275 .

BARAN M E ， WU F F . Network reconfiguration in distribution systems for loss reduction and load balancing ［J］. IEEE Power Engineering Review ， 1989 ， 9 （ 4 ）： 101 - 102 .

赵鹏杰，吴俊勇，王燚，等 . 基于深度强化学习的微电网优化运行策略［J］. 电力自动化设备， 2022 ， 42 （ 11 ）： 9 - 16 .

ZHAO Pengjie ， WU Junyong ， WANG Yi ， et al . Optimal operation strategy of microgrid based on deep reinforcement learning ［J］. Electric Power Automation Equipment ， 2022 ， 42 （ 11 ）： 9 - 16 .

NI J M ， AI Q . Economic power transaction using coalitional game strategy in micro-grids ［J］. IET Generation ， Transmission & Distribution， 2016 ， 10 （ 1 ）： 10 - 18 .

GUO J R ， CHEN C Y ， LU Z P ， et al . Wind-solar power consumption strategy based on neural network prediction and demand-side response ［C］// 2020 Asia Energy and Electrical Engineering Symposium （AEEES）， May 29-31 ， 2020 ， Chengdu， China ： 805 - 809 .

BOLOUKAT M H S ， FOROUD A A . Multiperiod planning of distribution networks under competitive electricity market with penetration of several microgrids： Part Ⅰ modeling and solution methodology ［J］. IEEE Transactions on Industrial Informatics ， 2018 ， 14 （ 11 ）： 4884 - 4894 .

冯昌森，张瑜，文福拴，等 . 基于深度期望Q网络算法的微电网能量管理策略［J］. 电力系统自动化， 2022 ， 46 （ 3 ）： 14 - 22 .

FENG Changsen ， ZHANG Yu ， WEN Fushuan ， et al . Energy management strategy for microgrid based on deep expected Q network algorithm ［J］. Automation of Electric Power Systems ， 2022 ， 46 （ 3 ）： 14 - 22 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

No data

Related Author

ZHENG Ran

LIU Baozhu

HU Junjie

XIE Dongliang

LU Zimeng

LIAO Yuming

YANG Lei

LIU Wenlong

Related Institution

State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University)

State Grid Electric Power Research Institute (NARI Group Corporation)

College of Electrical Engineering, Zhejiang University

State Grid Shanghai Energy Interconnection Research Institute Co., Ltd.

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

⁰