Özet:

For each unit of electricity supplied in electricity markets, one of the operation processes and operated through EPİAŞ in Turkey, a market-clearing price is formed according to the supply and demand balance. The market-clearing price is formed hourly and reported to the participants on transparent platforms. The aim of this study is to analyse the market-clearing price in Turkish Electricity Markets and to compare the performances of statistical prediction analysis methods frequently used in the literature. In this study, multiple regression method and artificial neural networks models were applied by using R statistical package program; with the Eviews package program the analysis and estimation of the past market price was performed using the ARIMA method. Analyses were applied to 2928 data of market clearing prices realized in March, April, May and June 2020. In the multiple regression and artificial neural network models, factors, thought to directly affect the market price, are considered as independent variables. In the ARIMA method, analyses were carried out by taking the past values of the data as a reference. The results of the analysis methods used in the study show that the best performance was obtained through artificial neural networks, multiple regression method and ARIMA method, respectively.