蓄意攻击电力耦合网络风险概率预测算法研究
Research on Risk Probability Prediction Algorithm under Intentional Attacks on Power Coupling Networks
林虹 1周晟阳 2李平辉 3林俊吉 4王志宾4
作者信息
- 1. 福建华电可门发电有限公司,福建 福州 350500
- 2. 华电电力科学研究院有限公司,浙江 杭州 310000
- 3. 福建永福信息科技有限公司,福建 福州 350500
- 4. 深圳融安网络科技有限公司,广东 深圳 518000
- 折叠
摘要
为了准确预测电力耦合网络风险概率、提高电力耦合网络的稳定性,对蓄意攻击下的电力耦合网络风险概率预测算法进行了研究.在蓄意攻击状态下,将节点相关性矩阵引入Page Rank算法,分析电力耦合网络拓扑结构和实例潮流分布的重要程度,并进行归一化处理,以识别电力耦合网络关键节点.通过灰色模型预测电力耦合网络的风险指标,确定单项风险指标值.通过熵权法计算各项评价指标的动态权重,获取电力耦合网络的总体风险概率预测值.试验结果表明:电力耦合网络风险概率预测算法的电力耦合网络风险均衡度高达0.964;获取的电力耦合网络风险概率预测结果和真实风险概率更加接近;预测时间最低为0.0706 s,在0.2 ms以内即可完成收敛.该算法可以准确预测电力耦合网络风险概率,确保网络的稳定运行.
Abstract
To accurately predict the risk probability of power coupling networks and improve the stability of power coupling networks,the algorithm for predicting the risk probability of power coupling networks under intentional attack is investigated.Under the state of intentional attack,the node correlation matrix is introduced into the Page Rank algorithm to analyze the importance of the power coupling network topology and the distribution of instance currents,and normalization is performed to identify the key nodes of the power coupling network.The risk indicators of the power coupling network are predicted through the gray model and determine the value of individual risk indicators.The dynamic weight of each evaluation index is calculated through the entropy weight method to obtain the overall risk probability prediction value of the power coupling network.The experimental results show that:the power coupling network risk probability prediction algorithm has a high-power coupling network risk equalization degree of 0.964;the obtained power coupling network risk probability prediction results and the real risk probability are closer;the prediction time is as low as 0.0706 s,and the convergence can be accomplished in 0.2 ms or less.The algorithm can accurately predict the risk probability of power coupling network and ensure the stable operation of the network.
关键词
电力耦合网络/风险概率预测/蓄意攻击/Page/Rank算法/灰色模型/累加矩阵Key words
Power coupling network/Risk probability prediction/Intentional attack/Page Rank algorithm/Gray model/Cumulative matrix引用本文复制引用
出版年
2024
NETL
NSTL
万方数据