电工技术学报  2021, Vol. 36 Issue (9): 1914-1925    DOI: 10.19595/j.cnki.1000-6753.tces.200119
电力系统及综合能源 |
基于多智能体深度确定策略梯度算法的有功-无功协调调度模型
赵冬梅1, 陶然1, 马泰屹1, 夏轩2, 王浩翔1
1.华北电力大学电气与电子工程学院 北京 102206;
2.国网绍兴供电公司 绍兴 312000
Active and Reactive Power Coordinated Dispatching Based on Multi-Agent Deep Deterministic Policy Gradient Algorithm
Zhao Dongmei1, Tao Ran1, Ma Taiyi1, Xia Xuan2, Wang Haoxiang1
1. School of Electrical and Electronic Engineering North China Electric Power University Beijing 102206 China;
2. State Grid Shaoxing Power Supply Company Shaoxing 312000 China
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摘要 实现有功-无功协调调度是促成“未来一体化大电网调控系统”建设中的关键一环。为解决调度中存在反复调节、难以协调冲突等问题,采用多智能体技术,智能组织多种有功调控资源和无功调控资源,建立电网有功-无功协调调度模型;为解决电力系统环境在多智能体探索过程中出现的不稳定问题,采用多智能体深度确定策略梯度算法,设计适用于有功-无功协调调度模型的电力系统多智能体环境,构造智能体状态、动作和奖励函数。通过算例仿真和对比分析,验证所提模型及算法的有效性。
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赵冬梅
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马泰屹
夏轩
王浩翔
关键词 多智能体多智能体深度确定策略梯度算法策略迭代灵活调控资源有功-无功协调    
Abstract:Achieving active and reactive power coordination dispatching is a key link in promoting construction of "future integrated large scale power grid control system". In order to solve the problems of repeated regulation and difficult to coordinate conflicts in dispatching, multi-agent technology is adopted to intelligently organize various active and reactive power control resources, and establish a power grid active and reactive power coordination dispatching model. In order to solve the instability of the power system environment in the process of multi-agent exploration, adopt multi-agent deep deterministic policy gradient algorithm, and design a multi-agent environment which is suitable for active and reactive power coordination dispatching model, and constructs the agent's state, action and reward function. The effectiveness of the proposed model and algorithm is verified by case study and comparative analysis.
Key wordsMulti-agent    multi-agent deep deterministic policy gradient (MADDPG)    policy gradient    flexible dispatched resources    active and reactive power coordination   
收稿日期: 2020-02-07     
PACS: TM734  
基金资助:国家重点研发计划(2017YFB0902600)和国家电网公司科技项目(SGJS0000DKJS1700840)资助
通讯作者: 陶 然 男,1995年生,硕士研究生,研究方向为电力系统分析与控制、新能源发电与智能电网。E-mail:ta0ran@163.com   
作者简介: 赵冬梅 女,1965年生,博士,教授,研究方向为电力系统分析与控制、新能源发电与智能电网。E-mail:zhao-dm@ncepu.edu.cn
引用本文:   
赵冬梅, 陶然, 马泰屹, 夏轩, 王浩翔. 基于多智能体深度确定策略梯度算法的有功-无功协调调度模型[J]. 电工技术学报, 2021, 36(9): 1914-1925. Zhao Dongmei, Tao Ran, Ma Taiyi, Xia Xuan, Wang Haoxiang. Active and Reactive Power Coordinated Dispatching Based on Multi-Agent Deep Deterministic Policy Gradient Algorithm. Transactions of China Electrotechnical Society, 2021, 36(9): 1914-1925.
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