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Short-term Load Forecasting Using Method of Multiple Linear Regression | Chapter 6 | New Approaches in Engineering Research Vol. 14

We employ Multiple Linear Regression to forecast short-term load in this investigation. The goal of this research is to get a day-ahead load projection. The Least Squares estimation method was used to determine the regression coefficients. Forecasting load plays an important part in the efficient running of electricity utilities. Temperature, due point, and seasons, as well as previous load consumption (historical data), all influence load in an electrical power system [1]. The input variables are temperature, due point, prior day's load, hours, and prior week's load. To test or analyse the model's accuracy, the mean absolute percentage error is employed, and R squared is examined [2-5], as indicated in the results section. Using day-ahead forecasted data, a weekly projection can also be made.


Author (S) Details

Bhatti Dhaval
Department of Electrical Engineering, Faculty of Technology & Engineering, MSU OF BARODA, Vadodara, Gujarat, India.

Anuradha Deshpande
Department of Electrical Engineering, Faculty of Technology & Engineering, MSU OF BARODA, Vadodara, Gujarat, India.


View Book:-  https://stm.bookpi.org/NAER-V14/article/view/3525

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