WSEAS Transactions on Power Systems
Print ISSN: 1790-5060, E-ISSN: 2224-350X
Volume 19, 2024
Time-Stratified Analysis of Electricity Consumption: A Regression and Neural Network Approach in the Context of Turkey
Authors: , , ,
Abstract: This study aims to apply seasonality and temporal effects in the analysis of electricity consumption in Turkey as a case mixed with regression and neural network methodologies. The study goal is to increase knowledge about the features and trending forces behind electricity usage which provide informed recommendations for smart energy planning and regulation. Comparing and contrasting the regression and neural network models makes it possible to carry out a thorough analysis of the merits and demerits of each model. Moreover, the examination of the limits of the models and their performance in forecasting electricity consumption patterns over the long term is done. The results of this study have a significant impact on power forecasting techniques, and they have meaningful effects on the policymakers, planners and utilities in Turkey. Understanding the story of the use of electricity around the world is very important for the development of sustainable energy policies, resource provision, and the maintenance of reliable and smart energy networks in the country.
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Keywords: Electricity Consumption, Time-Stratified Analysis, Regression Modeling, Neural Network Approach, Energy Forecasting, Turkey, Sustainable Energy Policies, Resource Optimization
Pages: 96-104
DOI: 10.37394/232016.2024.19.12