电力系统保护与控制2025，Vol.53Issue(15)：71-82,12.DOI:10.19783/j.cnki.pspc.241005
基于二维水动力模型与数据融合的电力设施淹没风险动态评估及预警方法
Dynamic assessment and early warning method of power facility flood risk based on a 2D hydrodynamic model and data fusion
摘要
Abstract
To address the issue of power system failures and power outages caused by the flooding of power facilities during rainstorm,this paper proposes a dynamic assessment and early warning mechanism based on a two-dimensional(2D)hydrodynamic model and data fusion.First,by combining the Chicago rainfall model with a 2D hydrodynamic model,the depth of water accumulation at key power facility locations is accurately simulated,significantly improving prediction accuracy.Next,a comprehensive evaluation system is developed to quantify the risk of power facility failures due to flooding,taking into account factors such as water depth,equipment type,and potential failure modes.In addition,a short-term load forecasting model(VMD-LSTM)integrating variational mode decomposition(VMD)and long short-term memory(LSTM)is constructed to provide accurate forecasting of grid load changes during rainstorm as an critical input for risk assessment.Finally,a risk warning level scheme is designed to accurately identify the power grid nodes requiring warning,providing scientific decision-making support for operators.Through the analysis of specific regional power grid cases,the effectiveness and practicality of the propsoed method are demonstrated,providing solid technical support for disaster prevention and mitigation.关键词
暴雨淹没/电力设施/风险评估/负荷预测/二维水动力模型Key words
storm flooding/electric power facility/risk assessment/load forecasting/2D hydrodynamic model引用本文复制引用
于浩,张健,朱广杰,瞿舜克,肖克江,雷兴炜,陈亮..基于二维水动力模型与数据融合的电力设施淹没风险动态评估及预警方法[J].电力系统保护与控制,2025,53(15):71-82,12.基金项目
This work is supported by the General Program of National Natural Science Foundation of China(No.62173158 and No.62377023). 国家自然科学基金面上项目资助(62173158,62377023) （No.62173158 and No.62377023）
湖北省自然科学基金创新发展联合基金重点项目资助(2025AFD195) （2025AFD195）
中央高校基本科研业务费资助(CCNU25ai013) （CCNU25ai013）
数字教育湖北省重点实验室开放研究基金项目资助(F2024G01) （F2024G01）
国家电网有限公司科技项目资助(52243723000D) （52243723000D）
