Forecasting Electricity Demand for Turkey: Modeling Periodic Variations and Demand Segregation
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Date
2017
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Publisher
Elsevier
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Abstract
In deregulated electricity markets the independent system operator (ISO) oversees the power system and manages the supply and demand balancing process. In a typical day the ISO announces the electricity demand forecast for the next day and gives participants an option to prepare offers to meet the demand. In order to have a reliable power system and successful market operation it is crucial to estimate the electricity demand accurately. In this paper we develop an hourly demand forecasting method on annual weekly and daily horizons using a linear model that takes into account the harmonics of these variations and the modulation of diurnal periodic variations by seasonal variations. The electricity demand exhibits cyclic behavior with different seasonal characteristics. Our model is based solely on sinusoidal variations and predicts hourly variations without using any climatic or econometric information. The method is applied to the Turkish power market on data for the period 2012-2014 and predicts the demand over daily and weekly horizons within a 3% error margin in the Mean Absolute Percentage Error (MAPE) norm. We also discuss the week day/weekend/holiday consumption profiles to infer the proportion of industrial and domestic electricity consumption. (C) 2017 Elsevier Ltd. All rights reserved.
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Keywords
Time series analysis, Fourier series, Electricity demand for Turkey, Demand segregation, Load forecast
Turkish CoHE Thesis Center URL
Fields of Science
Citation
68
WoS Q
Q1
Scopus Q
Q1
Source
Volume
193
Issue
Start Page
287
End Page
296