ARIMA Based Short Term Load Forecasting for Punjab Region
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 6)Publication Date: 2015-06-05
Authors : Sarabjit Singh; Rupinderjit Singh;
Page : 1819-1822
Keywords : Short Term Load Forecasting; ARIMA Auto Regression Integrated Moving Average; MAPE Mean Absolute Percentage Error;
Abstract
This paper deals with the STLF (Short Term Load Forecasting) using ARIMA (Auto Regression Integrated Moving Average) method to developed forecast of Northern INDIA, where historic results are used to determine the future load for next day or for next week. Our main focus is to minimize the (MAPE) Mean Absolute Percentage Error in the analysis and results. We purpose a three step method to load forecasting, consisting of pre-processing, forecasting and result analysis in post processing. This model is based on Time Series analysis methodology with the combination of explanatory variables by using the daily electrical load forecast. This method makes accuracy higher than other methods.
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