数据与计算发展前沿 ›› 2025, Vol. 7 ›› Issue (5): 212-219.

CSTR: 32002.14.jfdc.CN10-1649/TP.2025.05.017

doi: 10.11871/jfdc.issn.2096-742X.2025.05.017

• 技术与应用 • 上一篇    

基于熵权-灰色层次分析的刀闸操作风险量化评估算法

阳晟1,*(),谢代钰1,刘津铭1,傅源1,陈章国2   

  1. 1.广西电网电力调度控制中心，广西 南宁 530000
    2.南京南瑞信息通信科技有限公司，江苏 南京 210003
  • 收稿日期:2024-11-06 出版日期:2025-10-20 发布日期:2025-10-23
  • 通讯作者: 阳晟
  • 作者简介:阳晟，硕士，高级工程师，主要研究方向：电力系统运行控制技术，电网调峰调频及辅助服务等。
    本文主要负责实验设计、数据处理、算法模型实现。
    YANG Sheng, with a master’s degree, is a senior engineer at the Electric Power Dispatching and Control Center Guangxi Power Grid Co., Ltd. His main research interests include power system operation and control, peak load and frequency regulation.
    In this paper,he is mainly responsible for experimental design, data processing, and algorithm model implementation.
    E-mail：kancai044530@163.com
  • 基金资助:
    中国南方电网有限责任公司科技项目“调控行为辅助防误及评价关键技术研究”(GXKJXM20222171)

Quantitative Evaluation Algorithm of Operational Risk of Knife Switch Based on Entropy Weight Grey Analytic Hierarchy Process

YANG Sheng1,*(),XIE Daiyu1,LIU Jinming1,FU Yuan1,CHEN Zhangguo2   

  1. 1. Power Dispatching Control Center, Guangxi Power Grid, Nanning, Guangxi 530000, China
    2. NARI Information & Communication Technology Co., Ltd., Nanjing, Jiangsu 210003, China
  • Received:2024-11-06 Online:2025-10-20 Published:2025-10-23
  • Contact: YANG Sheng

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摘要：

【目的】 针对电压越限严重度影响较大，使得刀闸操作风险量化准确性较低的问题，本文提出基于熵权-灰色层次分析的刀闸操作风险量化评估算法。【方法】 利用数据挖掘技术获取刀闸行为发生时的设备输出信号；定义刀闸操作风险状态，计算电压越限的严重程度；结合样本离散化函数，提取刀闸操作风险特征；引入状态转移矩阵分解刀闸操作风险特征项和风险趋势项，以掌握刀闸操作的风险趋势；利用熵权-灰色层次分析法计算各分解趋势项的组合权重，明确刀闸操作风险评估等级，由此实现对刀闸操作风险的量化评估。【结果】 实验结果表明：在不同电压越限概率条件下，所提方法的风险评估相对误差始终控制在0.4以下。【结论】 刀闸操作风险量化评估结果准确，可以较为准确地判断刀闸操作风险。

关键词: 熵权-灰色层次分析, 刀闸操作风险, 量化评估, 风险指标

Abstract:

[Purpose] In response to the problem that the severity of voltage exceeding the limit has a significant impact on the accuracy of quantifying the risk of knife switch operation, this paper proposes a knife switch operation risk quantification evaluation algorithm based on entropy weight grey analytic hierarchy process. [Methods] Use data mining techniques to obtain the device output signals when the knife switch behavior occurs. Define the risk status of knife switch operation and calculate the severity of voltage exceeding the limit. Extract the risk characteristics of knife switch operation by combining the sample discretization function. Introducing a state transition matrix to decompose the risk characteristics and trends of knife switch operations, in order to grasp the risk trends of knife switch operations. Using entropy weight grey analytic hierarchy process to calculate the combined weights of each decomposition trend item, clarify the risk assessment level of knife switch operation, and thus achieve quantitative evaluation of knife switch operation risk. [Results] The experimental results show that under different voltage limit probability conditions, the relative error of the risk assessment of the proposed method is always controlled below 0.4. [Conclusions] The quantitative assessment of the risk of knife switch operation is accurate and can accurately determine the risk of knife switch operation.

Key words: entropy weight grey analytic hierarchy process, operational risk of knife switch, quantitative evaluation, risk indicators