Environmentally-Benign Energy Solutions, Ibrahim Dincer,C. Ozgur Colpan,Mehmet Akif Ezan, Editör, Springer, London/Berlin , Ontario, ss.155-175, 2020
Electricity markets is evolving into a complex competitive business environment with an increasing role of the private sector in production, consumption and retailing of electricity. Even transmission and distribution activities have private share in many countries. Technology is also rapidly adding new concepts such as smart grids, batteries, and prosumers (participants that are both on the production and consumption side). Nevertheless, the demand and supply of electricity need to be kept in constant balance in real time to provide a stable supply of electricity. This requirement generates several OR related complicated problems to maintain balance and determine the price of this commodity.
This study first gives a brief history on the liberalization of Electricity Markets, specifically concentrates on the Turkish Markets. Other European Markets also had similar historical developments. Secondly, we provide the market participants and their roles as well as briefly introduce the problems they need to solve. Then, the paper discusses the market types such as Day-Ahead Market, Intraday Market and Balancing Power Market. Furthermore, we explain the auction mechanism to determine prices in these markets.
The market participants have different objective functions to achieve. Policy makers such as Ministry of Energy, regulatory or exchange authorities are responsible for the supply security and transparency of price determination. Transmission and distribution system operators are focuses on the quality of the electricity providing services. Producers and consumers need to understand their electricity production and consumption behaviors as well as their relation to market prices to manage their risks.
Finally, we give an illustration for predicting the electricity prices of next days using a forecasting methodology called ARIMA. We use a real data set from Turkish market and provide a step by step procedure for calculating the prices using an open source statistical software R.