某地区电力负荷特性影响因素分析及短期负荷预测方法研究

Analysis of Influencing Factors of Fower Load Characteristics in a Region and Study on Short-term Load Forecasting Method

以华东电网某地级市电力负荷特性为例,分析影响该地区电力负荷变化的因素,并利用BP神经网络法,考虑天气、温度、节假日、新冠疫情等因素搭建负荷预测模型,采用一阶Sugeno模糊模型的推理算法,研究利用过去某一时刻负荷数据,预测未来相同时刻的负荷数据,更快更精准地进行电力负荷预测。

Taking the power load characteristics of a prefecture-level city in East China Power Grid as an example,this paper analyzes the factors affecting the change of power load in this region,and uses BP neural network method to build a load prediction model considering weather,temperature,holidays,COVID-19 and other factors.The reasoning algorithm of first-order Sugeno fuzzy model is adopted to study the load data at a certain time in the past.Forecast the load data at the same time in the future,so as to predict the power load faster and more accurately.