摘要
电力系统的短期负荷预测精度对智能电网安全运行有着重要影响,其中预测精度和训练步数至关重要,目前当地气象因素逐渐成为负荷预测中的关注点。以某市短期电力负荷为研究对象,建立了考虑日特征相关因素的支持向量回归机短期电力负荷预测模型,随后对某市考虑气象及日期类型的电力负荷做出预测。研究表明:利用考虑实时气象因素的SVR预测模型对短期电力负荷进行预测精度较高;考虑气象及日期类型的预测误差比不考虑气象及日期的预测误差小;嵌入维数和时间延迟对负荷预测模型精度具有重要影响。
The short-term load forecasting accuracy of the power system directly affects the stable and safe operation of smart grid,in which the prediction accuracy and the number of training steps are essential.At present,local meteorological factors gradually become the focus of load forecasting.This paper takes a city load as an example to study the short-term load forecasting,and establishes the SVR short-term prediction model considering the relevant factors of daily characteristics,and then,makes a prediction on the power load of a city considering the meteorological factors and date type.The results show that the SVR forecasting model considering real-time meteorological factors has higher forecasting accuracy for short-term power load.The forecasting error considering meteorological and date type is smaller than that without considering meteorological and date.The embedded dimension and time delay have greater impact on the accuracy of the forecasting model.
作者
杨捷
罗成臣
张思路
范美位
李珗
Yang Jie;Luo Chengchen;Zhang Silu;Fan Meiwei;Li Xian(Kunming Power Supply Bureau,Yunnan Power Grid Co.,Ltd.,Kunming 650031,China;Yunnan Yundian Tongfang Technology Co.,Ltd.,Kunming 650031,China)
出处
《电测与仪表》
北大核心
2020年第16期96-100,共5页
Electrical Measurement & Instrumentation
基金
国家自然科学基金资助项目(51177047)
云南电网公司科技项目(YNKJQQ00000275)。
关键词
相空间重构
支持向量机
负荷预测
气象因素
phase space reconstruction
support vector machine
load forecasting
meteorological factors
