ABSTRACT
Electricity is not only a product indispensable for us to continue our daily lives but also an important product used for the development of industry, trade, and nations. Since the energy resources used for electricity generation are limited, they must be used effectively. Limited resources are one of the important issues determining the energy policies of today’s countries. In many countries, supreme boards are formed to regulate the electricity markets, ensuring that the efficient and effective use of the electricity generated continues to be increased by regulatory studies. In this disordered market environment, electricity suppliers must optimize their generation capacities and bidding strategies. In the empirical study, we used financial optimization techniques, particularly mean-variance (MV) and mean-absolute deviation (MAD) optimization models. The MV and MAD optimization models have been adapted for geothermal power plants in the Turkish electricity market. A total of 12 optimizations have been made with six different objective functions—minimum risk portfolio, maximum utility (A = 3, A = 4, A = 5) portfolio, maximum Sharpe ratio portfolio, and maximum return portfolio—for each model. Then we analyzed all the optimization results. As a consequence, we compared the performances of the portfolios obtained for both models with the Sharpe ratio and we realized that the MAD optimal portfolios provided better results. It is expected that the results of the empirical study will provide significant contributions to both the literature and energy market decision makers in terms of establishing a decision support system.
