首页> 外文期刊>International Journal of Electrical and Computer Engineering >Short-term load forecasting with using multiple linear regression
【24h】

Short-term load forecasting with using multiple linear regression

机译:使用多元线性回归的短期负载预测

获取原文
           

摘要

In this paper short term load forecasting (STLF) is done with using multiple linear regression (MLR). A day ahead load forecasting is obtained in this paper. Regression coefficients were found out with the help of method of least square estimation. Load in electrical power system is dependent on temperature, due point and seasons and also load has correlation to the previous load consumption (Historical data). So the input variables are temperature, due point, load of prior day, hours, and load of prior week. To validate the model or check the accuracy of the model mean absolute percentage error is used and R squared is checked which is shown in result section. Using day ahead forecasted data weekly forecast is also obtained.
机译:在本文中,使用多个线性回归(MLR)完成短期负载预测(STLF)。本文获得了一天的载荷预测。借助于最小二乘估计的方法,发现了回归系数。电力系统的负载取决于温度,到期点和季节,并且负载与先前的负载消耗(历史数据)也具有相关性。因此,输入变量是前一周的温度,到期日,小时,小时和负载。为了验证模型或检查模型的准确性,使用模型绝对百分比误差,并检查R平方,在结果部分中显示。使用日期预测,还获得了预测数据预测。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号