摘要
输变电系统是电力输送的重要纽带,为了降低运维成本和提高识别效果,提出一种基于AI技术的输变电脆弱线路自动识别与控制应用方法。利用人工智能技术(AI)的决策树贪心算法(ID3)度量线路不同运行特征之间的信息量,得到线路特征,引入互信息特征选取(MIFS)优化决策树,利用调节系数和惩罚项平衡线路运行特征间的冗余度,并且引入加权度数,衡量节点权重并重点考虑所有连接线路的有功总量。在综合分析电纳介数和加权度数等指数前提下得到综合的脆弱线路自动识别指标,建立识别模型,最后改变输变电线路的潮流传输及负载变化实现控制。实验证明所提方法能够准确识别出脆弱线路位置,方法有效可行,其控制应用也有效降低了运维成本。
The power transmission and transformation system is an important link of power transmission.In order to reduce the cost of operation and maintenance and improve the recognition effect,an application method of automatic identification and control of transmission and transformation vulnerable lines was proposed based on artificial intelligence(AI)technology.Using the greedy decision tree algorithm(ID3)of AI to measure the amount of information between different operation characteristics of the line,it got the line characteristics,introduced mutual information feature selection(MIFS)to optimize the decision tree,balanced the redundancy between the line operation characteristics by using the adjustment coefficient and penalty term,and introduced the weighted degree,measured the node weight and focused on the total active power of all connecting lines.Based on the comprehensive analysis of the permittivity and weighted degree,the comprehensive automatic identification index of vulnerable lines was obtained,the identification model was established,and finally the power flow transmission and load change of transmission and transformation lines were changed to achieve control.The experiment shows that the proposed method can accurately identify the location of vulnerable lines,which is effective and feasible,and its control application also effectively reduces the operation and maintenance costs.
作者
吕征宇
LÜZhengyu(State Grid Shanghai Electric Power Design Co.,Ltd.,Shanghai 200002,China)
出处
《电气传动》
2024年第5期86-92,共7页
Electric Drive
基金
国家电网公司科技项目(521304170028)。
关键词
连锁故障
综合脆弱识别
AI技术
输变电线路
识别指标
控制应用
interlocking failure
comprehensive vulnerability identification
AI technology
power transmission and transformation lines
identification indicators
control application