面向数字孪生的电-气综合能源系统静态安全性风险评估  

Static Security Risk Assessment Static Security Risk Assessment of Electric-Gas Integrated Energy Systems for Digital Twins

作　　者：刘一江 陈厚合[1] LIU Yijiang;CHEN Houhe(School of Electrical Engineering,Northeast Power University,Jilin Jilin 132012)

机构地区：[1]东北电力大学电气工程学院,吉林吉林132012

出　　处：《东北电力大学学报》2024年第4期56-64,共9页Journal of Northeast Electric Power University

基　　金：国家自然科学基金(52077028)

摘　　要：能源转型环境下,电-气综合能源系统(Electric-Gas Integrated Energy System, EGIES)得到了快速发展,但复杂性的增加也使得电-气综合能源系统的安全稳定运行受到挑战。为了更好地评估其存在的运行风险,文中提出了一种使用数字孪生技术的电-气综合能源系统风险评估方法。通过使用数字孪生相关技术进行监测和仿真,可以有效地评估电-气综合能源系统的安全性风险。文中首先通过计算求得系统正常运行时系统的原始数据电压、潮流和气压等运行状态;然后,根据计算出的综合能源系统风险指标数据建立数据库,再将算得的风险指标数据值利用CNN模型进行训练,将CNN模型训练获得的数据值作为新的输入特征值在XGBoost模型中训练;最终根据两个模型结合成的CNN-XGBoost技术得到预测的安全风险评估指标。算例结果表明,所提方法能有效提高电-气系统的风险评估预测精度与效率。In the energy transition environment,the electric-gas integrated energy system has developed rapidly.However,the increase of complexity also challenges the safe and stable operation of the electric-gas integrated energy system.In order to better evaluate the operational risk between the two,this paper presents a risk assessment method that can reflect the risk of the electric-gas integrated energy system by using digital twin technology.By monitoring and simulating the operating state of the digital twin model,the operational risk of the electric-gas integrated energy system can be evaluated effectively.This method has the advantages of high precision and reliability,and has a wide prospect in practical application.In this paper,the original data of the system during normal operation are calculated by ox method to obtain the operating state of the system voltage,pressure and power flow.Then,the integrated energy system risk index is calculated to generate a database,and finally the calculated index data is evaluated and predicted using CNN-XGBoost technology.The example results show that the method used can improve the accuracy and efficiency of safety risk assessment and prediction of electric-gas system well.

关 键 词：数字孪生 综合能源 风险评估 预测精度 

分 类 号：TM744[电气工程—电力系统及自动化]