气象灾害条件下电网应急物资预测方法

为提高电网应急物资调配响应速度和电网抢修效率,提出一种案例推理与深度学习相结合的电网气象灾害条件下的应急物资预测方法.以气象信息、电网设备数据和地理环境数据为输入信息,利用案例推理方法确定预测模型输入、输出结构,并根据不同输入信息的特点进行处理和量化,利用深度置信网络完成案例适配,综合事故规模信息建立动态电网应急物资预...

Prediction method of power grid emergency supplies under meteorological disasters

In order to improve the efficiency of grid emergency repairs, a method for predicting emergency supplies under the conditions of power grid meteorological disasters combining case-based reasoning, deep belief network and deep learning was proposed. Based on meteorological data, power grid maintenance data and geographic environment data, this method was used case-based reasoning to determine the appropriate input and output structure of the prediction model, and different methods was used to process and quantify according to the characteristics of disagreeing input factors. Deep belief networks were used to complete case adaptation, and integrate accident scale information was used to establish a dynamic power grid emergency supplies prediction model. The analysis results showed that the emergency material prediction method proposed in this paper could comprehensively analyze various characteristic factors, and combined the scale of the accident to establish the relationship between the emergency material demand of the power grid, and accurately predicted the material demand for the emergency response of the power grid under the weather disaster. and provided a scientific reference for emergency decision-making of power grids.