Author
Poyrazoğlu, Göktürk
Publication Date
2019
Publication Place
-
IEEE
Subject
Electricity price forecasting, Natural gas price, Price formation, Multiple linear regression, Interaction regression, Lagged price
Type
Document
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
978-1-7281-1257-2
Record ID
f3f2a786-e144-4880-96ad-8b5833b64f63
Library Location
Electrical & Electronics Engineering
Date
2019
Sample Text
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.
DOI
10.1109/EEM.2019.8916448
