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Bhatti Dhaval
The Maharaja Sayajirao University Baroda
Computer Science & IT Electrical & Electronics Engineering

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Short-term load forecasting with using multiple linear regression Bhatti Dhaval; Anuradha Deshpande
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.681 KB) | DOI: 10.11591/ijece.v10i4.pp3911-3917

Abstract

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.
Co-Authors Anuradha Deshpande