Short term electricity price forecasting in Turkish electricity market

Özgüner, Erdem
With the aim for higher economical efficiency, considerable and radical changes have occurred in the worldwide electricity sector since the beginning of 1980s. By that time, the electricity sector has been controlled by the state-owned vertically integrated monopolies which manage and control all generation, transmission, distribution and retail activities and the consumers buy electricity with a price set by these monopolies in that system. After the liberalization and restructuring of the electricity power sector, separation and privatization of these activities have been widely seen. The main purpose is to ensure competition in the market where suppliers and consumers compete with each other to sell or buy electricity from the market and the consumers buy the electricity with a price which is based on competition and determined according to sell and purchase bids given by producers and customers rather than a price set by the government. Due to increasing competition in the electricity market, accurate electricity price forecasts have become a very vital need for all market participants. Accurate forecast of electricity price can help suppliers to derive their bidding strategy and optimally design their bilateral agreements in order to maximize their profits and hedge against risks. Consumers need accurate price forecasts for deriving their electricity usage and bidding strategy for minimizing their utilization costs. This thesis presents the determination of system day ahead price (SGOF) at the day ahead market and system marginal price (SMF) at the balancing power market in detail and develops artificial neural network models together with multiple linear regression models to forecast these electricity prices in Turkish electricity market. Also the methods used for price forecasting in the literature are discussed and the comparisons between these methods are presented. A series of historical data from Turkish electricity market is used to understand the characteristics of the market and the necessary input factors which influence the electricity price is determined for creating ANN models for price forecasting in this market. Since the factors influencing SGOF and SMF are different, different ANN models are developed for forecasting these prices. For SGOF forecasting, historical price and load values are enough for accurate forecasting, however, for SMF forecasting the net instruction volume occurred due to real time system imbalances is needed in order to increase the forecasting accuracy.


Price based unit commitment with reserve considerations
Okuşluğ, Ali; Güven, Ali Nezih; Tör, Osman Bülent; Department of Electrical and Electronics Engineering (2013)
In electricity markets of modern electric power systems, many generation companies, as major market participants, aim to maximize their profits by supplying the electrical load in a competitive manner. This thesis is devoted to investigate the price based unit commitment problem which is used to optimize generation schedules of these companies in deregulated electricity markets. The solution algorithm developed is based on Dynamic Programming and Lagrange Relaxation methods and solves the optimization probl...
Renewable energy planning in Turkey with a focus on hydropower
Gök, Emre; Kentel Erdoğan, Elçin; Department of Civil Engineering (2013)
As a country highly dependent on foreign fossil fuel sources, Turkey experiences many problems due to its increasing energy consumption in parallel with increasing population and rapid economic growth. Foreign fossil fuel dependency adversely affects sustainable development of the country by hindering its economic development. Because of this, renewable energy sources of the country should be evaluated and developed as soon as possible. Prioritization of the development of renewable energy sources to increa...
Demand, supply and partial equilibrium analysis of electricity energy pricing for Turkish market
Özdemir, Asena; Kestel, Sevtap Ayşe; Department of Actuarial Sciences (2013)
Electricity energy is a fundamental commodity for all sectors of the economy. For this reason, estimating the factors and their impacts on electricity consumption and production are important to maintain sustainability in electricity energy market. The aim of the study is to determine the association between main macroeconomic and sectorial indicators with electricity consumption and production. For estimating electricity demand, annual electricity consumption, Gross Domestic Product (GDP), electricity tran...
Mathematical modeling and solution approaches for balancing Turkish electricity day ahead market
Yörükoğlu, Sinan; Avşar, Zeynep Müge; Kat, Bora; Department of Industrial Engineering (2015)
In the Turkish Electricity Market, electricity trade is carried out largely through Bilateral Agreements and the emerging short term imbalances are settled in the Balancing Power Market, particularly the Day Ahead Market. In the Day Ahead Market, the participants submit their bids for each hour of the next day in the form of price-quantity pairs and the Market Operator evaluates those bids using an optimization tool. After the evaluation of the bids, a Market Clearing Price at every hour of the next day and...
On the parametric and nonparametric prediction methods for electricity load forecasting
Erişen, Esra; İyigün, Cem; Department of Industrial Engineering (2013)
Accurate electricity load forecasting is of great importance in deregulated electricity markets. Market participants can reap significant financial benefits by improving their electricity load forecasts. Electricity load exhibits a complex time series structure with nonlinear relationships between the variables. Hence, new models with higher capabilities to capture such nonlinear relationships need to be developed and tested. In this thesis, we present a parametric and a nonparametric method for short-term ...
Citation Formats
E. Özgüner, “Short term electricity price forecasting in Turkish electricity market,” M.S. - Master of Science, Middle East Technical University, 2012.