Impact of gas price on electricity price forecasting via supervised learning and random walk

Abstract

The electricity is a regular commodity that is being sold and bought in a highly transparent and efficient market in Turkey. The market is operated by EXIST and an hourly energy price is formed for every hour in the day-ahead market. In Sept. 2018, EXIST also found a central natural gas market in Turkey which enables a ground for all shareholders in the natural gas industry. This study examines the impact of natural gas prices formed in the market on the electricity price. Different predictors are tested to lower the mean absolute percentage error. Addition of past natural gas price into the forecasting model reduces the error from 15.85% to 14.31% when the average of the last two weeks' natural gas price is used. This may indicate that the current natural gas price affects the electricity market two weeks later. The linear regression-based machine learning model doesn't include any random process; however, the proposed Fourier transform-based random walk forecasting method in this study does. The comparison of the forecasts is discussed on the effectiveness of the estimations on the Turkish DAM prices.