基于深度自适应动态规划的多源调频博弈协调策略研究

宋述停; 唐震; 王伟; 白雪婷; 李焓宁; 赵泽宇

doi:10.19725/j.cnki.1007-2322.2023.0348

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基于深度自适应动态规划的多源调频博弈协调策略研究

新能源电力系统 | 更新时间：2025-10-22

- 基于深度自适应动态规划的多源调频博弈协调策略研究
- Multi-source Frequency Modulation Strategies Based on Stackelberg Game and Deep Adaptive Dynamic Programming
- 现代电力 2025年42卷第5期页码：947-955
- 作者机构：
  
  1. 国网山西省电力公司,山西省,太原市,030021
  2. 国网山西省电力科学研究院,山西省,太原市,030001
  3. 中国电力科学研究院有限公司, 北京市海淀区,100192
- 作者简介：
  
  [ "宋述停(1967)，男，硕士，高级工程师，研究方向为电力科技管理及相关技术，E-mail: 15333666585@189.cn" ]
  [ "唐震(1966)，男，硕士，正高级工程师，研究方向为继电保护、电力电子化电力系统风险防控相关技术，E-mail: tangzhen@sx.sgcc.com.cn" ]
  [ "王伟(1989)，男，高级工程师，研究方向为高压与大型设备故障诊断、在线识别相关技术，E-mail: 604186127@qq.com" ]
  [ "白雪婷(1997)，女，硕士，助理工程师，研究方向为配电自动化及相关技术，E-mail: baixt9707@163.com" ]
  [ "李焓宁(1998)，男，硕士，通信作者，研究方向为大规模储能运行控制技术，E-mail: xtlihanning@163.com" ]
  [ "赵泽宇(1998)，男，博士研究生，研究方向为新能源发电、自动发电控制相关技术，E-mail: zeyu981116@163.com" ]
- 基金信息：
  
  国网山西省电力公司科技项目(52053022000G)。
- DOI：10.19725/j.cnki.1007-2322.2023.0348
  中图分类号： 5
- 纸质出版：2025
- 稿件说明：
移动端阅览
宋述停, 唐震, 王伟, 等. 基于深度自适应动态规划的多源调频博弈协调策略研究[J]. 现代电力, 2025,42(5):947-955.

SONG Shuting, TANG Zhen, WANG Wei, et al. Multi-source Frequency Modulation Strategies Based on Stackelberg Game and Deep Adaptive Dynamic Programming[J]. 2025, 42(5): 947-955.
宋述停, 唐震, 王伟, 等. 基于深度自适应动态规划的多源调频博弈协调策略研究[J]. 现代电力, 2025,42(5):947-955. DOI： 10.19725/j.cnki.1007-2322.2023.0348.

SONG Shuting, TANG Zhen, WANG Wei, et al. Multi-source Frequency Modulation Strategies Based on Stackelberg Game and Deep Adaptive Dynamic Programming[J]. 2025, 42(5): 947-955. DOI： 10.19725/j.cnki.1007-2322.2023.0348.

摘要

为了解决新能源高渗透率下电网频率波动较大的问题，提出一种用于智能发电控制的博弈深度自适应动态规划(Stackelberg deep adaptive dynamic programming，SDADP)的多源调频协调策略。首先，采用自适应动态规划模型的3个深度神经网络结构，学习电网历史数据特征，顺序进行预测、评价、执行动作，预测总调频功率指令，以减小多源系统的区域控制误差。然后，基于主从博弈，合理调度风光水火储调频源的功率，提高调频收益。最后，通过仿真验证所提多源调频博弈策略的协调优化结果。结果表明，所提SDADP多源调频博弈协调策略可降低多源系统频率偏差，并提高调频整体经济收益。

Abstract

To address the issue of large frequency fluctuation in high penetration grid

a multi-source frequency regulation strategy of Stackelberg deep adaptive dynamic programming (SDADP) is proposed for smart generation control. Firstly

three deep neural network structures of the adaptive dynamic programming model are employed to acquire the characteristics from the historical data of the power grid and sequentially perform the prediction

evaluation

and execution actions for predicting the total frequency regulation power command

so as to minimize regional control error in a multi-source system. Based on the Stackelberg game

the power from wind

solar

hydropower

fire

and storage sources is subsequently reasonably scheduled to enhance the frequency regulation gain. Finally

the coordination optimization results of the proposed multi-source frequency regulation game strategy are verified through simulation analysis. The proposed SDADP multisource frequency regulation game strategy can mitigate the frequency deviation in the multisource system and improve the overall economic gain of frequency regulation.

关键词

Keywords

references

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