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基于斜回归树及其集成算法的静态电压稳定规则提取
作者:
作者单位:

1.电力系统及大型发电设备安全控制和仿真国家重点实验室,清华大学,北京市 100084;2.清华大学电机工程与应用电子技术系,北京市 100084;3.国网青海省电力有限公司,青海省西宁市 810008

摘要:

可再生能源渗透率的增加给电力系统安全稳定运行带来持续性的挑战,传统方法分析系统稳定性、控制电网稳定运行变得愈加困难。针对这一难题,提出了内嵌安全稳定约束的电力系统优化运行框架以及用于电力系统安全稳定规则提取的斜回归树及其集成算法。该算法首先优化斜划分系数以训练单棵斜回归树,然后利用boosting思想集成斜回归树,并通过正则化方法保证树的稀疏度,增强算法的可解释性。相比神经网络等黑箱模型,文中提出的方法能够提取显式安全稳定规则,为内嵌安全稳定约束的电力系统优化运行奠定了基础。最后,以静态电压稳定问题为例验证算法的有效性,算例验证结果表明所提算法具有良好的可解释性、较强的表示能力和较高的集成效率。

关键词:

基金项目:

国家重点研发计划资助项目(2017YFB0902200);国家电网公司科技项目(5228001700CW)。

通信作者:

作者简介:

贾宏阳(1999—),男,主要研究方向:数据驱动的电力系统优化运行、高比例可再生能源电力系统稳定分析。E-mail:jhy21@mails.tsinghua.edu.cn
侯庆春(1993—),男,博士研究生,主要研究方向:数据驱动的电力系统优化及分析、高比例可再生能源电力系统安全稳定优化运行及规划。E-mail:hqc16@tsinghua.org.cn
刘羽霄(1993—),男,博士研究生,主要研究方向:数据驱动的电力系统建模与优化、电力系统连锁故障等。E-mail:liuyuxiao16@mails.tsinghua.edu.cn
张宁(1985—),男,通信作者,博士,副教授,主要研究方向:可再生能源、电力系统规划与运行、多能源系统等。E-mail:ningzhang@tsinghua.edu.cn


Extracting of Static Voltage Stability Rule Based on Oblique Regression Tree and Its Ensemble Algorithm
Author:
Affiliation:

1.State Key Laboratory of Power System and Generation Equipment, Tsinghua University, Beijing 100084, China;2.Department of Electrical Engineering, Tsinghua University, Beijing 100084, China;3.State Grid Qinghai Electric Power Co., Ltd., Xining 810008, China

Abstract:

The increase of the penetration of renewable energy brings continuous challenges to the safe and stable operation of the power system. It becomes more and more difficult to analyze the system stability and control the stable operation of the power system by traditional methods. To solve this problem, a power system optimal operation framework with embedded security and stability constraints and an oblique regression tree and its ensemble algorithm for extracting power system security and stability rules are proposed. The algorithm first optimizes the oblique split coefficient to train a single oblique regression tree, then uses the boosting idea to integrate the oblique regression tree, and uses the regularization method to ensure the sparsity of the tree and enhance the interpretability of the algorithm. Compared with the black box model such as neural network, the proposed method can extract explicit security and stability rules, which lays a foundation for the optimal operation of the power system with embedded security and stability constraints. Finally, the static voltage stability problem is taken as an example to verify the effectiveness of the algorithm. The results show that the algorithm has good interpretability, strong representation ability and high ensemble efficiency.

Keywords:

Foundation:
This work is supported by National Key R&D Program of China (No. 2017YFB0902200) and State Grid Corporation of China (No. 5228001700CW).
引用本文
[1]贾宏阳,侯庆春,刘羽霄,等.基于斜回归树及其集成算法的静态电压稳定规则提取[J].电力系统自动化,2022,46(1):51-59. DOI:10.7500/AEPS20210109003.
JIA Hongyang, HOU Qingchun, LIU Yuxiao, et al. Extracting of Static Voltage Stability Rule Based on Oblique Regression Tree and Its Ensemble Algorithm[J]. Automation of Electric Power Systems, 2022, 46(1):51-59. DOI:10.7500/AEPS20210109003.
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  • 收稿日期:2021-01-09
  • 最后修改日期:2021-06-23
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  • 在线发布日期: 2022-01-05
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