2022 18th International Conference on the European Energy Market (EEM) 2022
DOI: 10.1109/eem54602.2022.9921172
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Short-Term Load Forecast in Power Systems: A Comparison of Different Practical Algorithms

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“…The impact of all these factors should be studied to improve the accuracy of the load forecasting model. Over the years, several studies have investigated the characteristics and factors affecting energy consumption in order to develop electricity demand forecasting models [3][4][5][6][7][8][9][10][11][12][13]. Reference [3] used an econometric model with a loglinear demand function to study the monthly electricity consumption of private customers during the summer months from 1972 to 1975.…”
Section: Introductionmentioning
confidence: 99%
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“…The impact of all these factors should be studied to improve the accuracy of the load forecasting model. Over the years, several studies have investigated the characteristics and factors affecting energy consumption in order to develop electricity demand forecasting models [3][4][5][6][7][8][9][10][11][12][13]. Reference [3] used an econometric model with a loglinear demand function to study the monthly electricity consumption of private customers during the summer months from 1972 to 1975.…”
Section: Introductionmentioning
confidence: 99%
“…Although this reference is old, it is still applicable to traditional modeling tasks. In [4] a detailed comparison of numerous practical algorithms (sinusoidal regression, polynomial regression, ANNs and machine learning) for short-term demand forecasting was provided. the electric load was displayed in terms of two variables: temperature and calendar days.…”
Section: Introductionmentioning
confidence: 99%