| 引用本文: | 杨 悦,王 丹,胡 博,等.基于改进多智能体Q学习的多源最优联合调频控制策略研究[J].电力系统保护与控制,2022,50(7):135-144.[点击复制] |
| YANG Yue,WANG Dan,HU Bo,et al.Multi-source optimal joint frequency modulation control strategy based on improved multi-agent Q-learning[J].Power System Protection and Control,2022,50(7):135-144[点击复制] |
|
| 摘要: |
| 随着新能源渗透率的不断提高，只依靠传统火电机组无法满足新型电力系统的调频需求，所以多源联合调频成为缓解当前电网频率波动问题的主要措施。因此，提出了基于改进多智能体Q学习的多源最优联合调频方法。首先，分析各类型能源的调频特性并设计联合调频系统的控制策略。其次，将多智能体Q学习算法进行改进，选取预学习结果作为算法的初始矩阵并在贪婪策略基础上引入搜索因子，极大提高了算法的优化效果、缩短了运行时间。最后，利用算法的动态决策能力与PSCAD/EMTDC模型进行联合仿真并在两种负荷扰动条件下进行验证。结果表明该方法可以最大限度地减小系统频率波动，缩短调频所需时间，为一次调频提供了有利条件。 |
| 关键词: 多类型电源 联合调频 Q学习 频率动态分配 控制策略 |
| DOI：DOI: 10.19783/j.cnki.pspc.210923 |
| 投稿时间：2021-07-18修订日期：2021-10-25 |
| 基金项目:国家重点研发计划项目资助(2019YFB1505400) |
|
| Multi-source optimal joint frequency modulation control strategy based on improved multi-agent Q-learning |
| YANG Yue,WANG Dan,HU Bo,WANG He,LUO Huanhuan |
| (1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology,
Ministry of Education (Northeast Electric Power University), Jilin 132012, China;
2. State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China) |
| Abstract: |
| With the continuous increase of the penetration rate of new sources, it cannot meet the frequency modulation needs of new power systems relying only on a traditional thermal power unit. Therefore, multi-type unit joint frequency modulation has become the main measure to alleviate the current grid frequency fluctuation problem. This paper proposes a multi-source optimal combined frequency modulation strategy based on improved multi-agent Q learning. First, it analyzes the frequency modulation characteristics of various types of energy and designs a control strategy for the joint frequency modulation system. Secondly, the multi-agent Q learning algorithm is improved, the pre-learning result as the initial matrix of the algorithm is selected, and a search factor is introduced on the basis of the greedy strategy, which greatly improves the optimization effect and shortens the running time. Finally, the dynamic decision-making ability of the algorithm and the PSCAD/EMTDC model are used for joint simulation and verified under the two load disturbance conditions. The method in this paper can minimize the system frequency fluctuation and shorten the time required for frequency modulation, providing favorable conditions for primary frequency modulation.
This work is supported by the National Key Research and Development Program of China (No. 2019YFB1505400). |
| Key words: multi-type power combined frequency modulation Q learning dynamic frequency distribution control strategy |
