MULTIPLE LINEAR REGRESSION APPROACH FOR SHORT-TERM FORECASTING OF ELECTRIC ENERGY CONSUMPTION IN TOGO
- ResearchLaboratory in Engineering Sciences (Larsi), Regional Center of Excellence for the Control of Electricity (CERME), Department of Electrical Engineering of the National Superior School of Engineers (ENSI), University of Lome (UL), BP 1515, Lome, Togo.
Abstract
A Linear Multiple Regression approach is used to model the energy consumption of electricity in Togo. This model is developed from the load data recorded at the electric power source stations in Togo during the period from 2016 to 2017. This model predicts four input parameters (Day of the week, the type of day (working day). or not), Hours in the day and Load data of the same time of the previous day) is used to predict the electrical energy consumption data for the period of 2018 with a MAPE of 4.4964% and a correlation coefficient R2 equal to 95.5889%.
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How to Cite This Article
Comlanvi Adjamagbo, Akim Adekunle Salami, Yao Bokovi, Djamil Gado and Ayite Senah Akoda Ajavon (2020); MULTIPLE LINEAR REGRESSION APPROACH FOR SHORT-TERM FORECASTING OF ELECTRIC ENERGY CONSUMPTION IN TOGO, Int. J. of Adv. Res., 8 (10), 22-28, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/11818
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