基于人工智能技术的电网基建安全状态自动估计研究  

Research on Automatic Estimation of Power Grid Infrastructure Security State Based on Artificial Intelligence Technology

作　　者：王孔耀 安希胜 陶修冬 文雅弘 蓝长盛 WANG Kong-yao;AN Xi-sheng;TAO Xiu-dong;WEN Ya-hong;LAN Chang-sheng(Laibin Power Supply Bureau of Guangxi Power Grid Co.,Ltd.,Laibin 530000 China)

机构地区：[1]广西电网有限责任公司来宾供电局,广西来宾530000

出　　处：《自动化技术与应用》2025年第3期164-167,175,共5页Techniques of Automation and Applications

基　　金：广西电网有限责任公司科技项目(XKYS2019KJ0014)。

摘　　要：为实时监控和全面管理电网基建现场的安全状况,提出基于人工智能技术的电网基建安全状态自动估计方法。首先通过分类识别影响电网基建安全状态的风险因素,对风险因素中的主要风险因素进行定级,获取风险等级数据集,然后将该数据集输入贝叶斯网络,完成各主要风险因素评估及高风险因素控制,并根据因素变化完成主要风险因素再评估,实现电网基建安全状态自动估计,实验结果表明:选取的各主要风险因素覆盖度高,代表性极佳;不同样本数量的电网基建安全状态估计效果良好,可以显著提升电网基建安全水平。In order to monitor and manage the security status of power grid infrastructure in real time,an automatic estimation method of power grid infrastructure security status based on artificial intelligence technology is proposed.Firstly,it identifies the risk factors affecting the safety state of power grid infrastructure by classification,ranks the main risk factors in the risk factors,obtains the risk level data set,then inputs the data set into Bayesian network to complete the evaluation of main risk factors and the control of high-risk factors,and completes the re evaluation of main risk factors according to the change of factors.Finally,the experimental results show that the selected main risk factors have high coverage and excellent representativeness.The estimation results of power grid infrastructure security state with different sample numbers are good,which can significantly improve the security level of power grid infrastructure.

关 键 词：人工智能技术 电网基建 安全状态 自动估计 贝叶斯网络 风险因素 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]