多模态数据融合配电终端淹没风险快速预测方法  

A rapid prediction method for flooding risk of distribution terminals based on multimodal data fusion

作　　者：王乐 王珂 覃桂锋 张玉波 WANG Le;WANG Ke;QIN Guifeng;ZHANG Yubo(Electric Power Research Institute,Guangxi Power Gird Co.,Ltd.,Nanning 530023,China;Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment,Nanning 530023,China;Nanning Power Supply Bureau,Guangxi Power Gird Co.,Ltd.,Nanning 530029,China)

机构地区：[1]广西电网有限责任公司电力科学研究院,南宁广西530023 [2]广西电力装备智能控制与运维重点实验室,南宁广西530023 [3]广西电网有限责任公司南宁供电局,南宁广西530029

出　　处：《电力科学与技术学报》2024年第6期92-100,共9页Journal of Electric Power Science And Technology

基　　金：广西电网有限责任公司科技项目(GXKJXM20220107)。

摘　　要：受气候变化与城市布局影响,城市内涝日趋严重,威胁配电系统可靠供电。探索城市洪涝灾害预测模型,实现配电设备风险预测,可以降低洪涝灾害带来的影响。然而,现有基于水动力模型的方法计算复杂度过高,难以保证大范围淹没模拟预报的时效性,基于数据驱动模型方法的训练数据不足,难以满足快速精准城市内涝预警需求。为解决以上问题,提出基于多模态数据融合的降雨内涝快速预测模型。该方法通过水动力模型生成训练数据以解决训练数据量不足的问题,将高程地图等图像数据与降雨序列时序数据进行融合以提高预测精度,并以桂林市作为研究对象,验证所提方法的有效性。实验结果表明,所提方法在保持较高精度的同时,有较低的计算复杂度,可为配电终端风险评估提供参考。Due to climate change and urban layout,urban waterlogging disasters are becoming increasingly severe,posing a serious threat to the stable power supply of the distribution system.In order to minimize the impact of flood disasters,it is urgent to explore urban flood disaster prediction models to achieve distribution equipment risk prediction.However,the existing hydrodynamic model-based method has high computational complexity and is difficult to guarantee the timeliness of large-scale flooding simulation forecast.The data-driven model-based method has insufficient training data,which is insufficient to meet the requirements of fast and accurate urban waterlogging warnings.To this end,a rapid waterlogging prediction model based on multimodal data fusion is proposes.This method generates training data through a hydrodynamic model to solve the problem of insufficient training data and integrates image data such as elevation maps with rainfall sequence time series data to improve prediction accuracy.Furthermore,Guilin City is used as the research object to verify the effectiveness of the proposed method.The experimental results show that the proposed method maintains high accuracy while reducing computational complexity.This method can provide a reference for risk assessment of distribution terminals.

关 键 词：多源数据融合 深度学习 内涝预测 配电终端风险评估 

分 类 号：TM863[电气工程—高电压与绝缘技术]