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

作　　者：林佳铭 董平平 LIN Jiaming;DONG Pingping

机构地区：[1]国网江苏省电力有限公司宿迁供电分公司,江苏宿迁223800

出　　处：《青海电力》2023年第1期21-26,共6页Qinghai Electric Power

摘　　要：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.

关 键 词：短期负荷预测 BP神经网络 电力负荷特性 

分 类 号：TM715[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]