Time-Stratified Analysis of Electricity Consumption: A Regression and Neural Network Approach in the Context of Turkey
Author:
Yi̇ği̇t Si̇mge1, Turgay Safi̇ye1, Cebeci̇ Çi̇ğdem2, Kara Esma Sedef3
Affiliation:
1. Department of Industrial Engineering, Sakarya University, 54187, Esentepe Campus Serdivan-Sakarya, TURKEY 2. Department of Electrical Machinery and Material Supply, Energy Branch Directorate, Sakarya Municipality, Saski General Directorate, Sakarya, TURKEY 3. Rüstempaşa Mahallesi, İpekyolu Caddesi, No.120, 54600, Sapanca-Sakarya, TURKEY
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.
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
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