CVaR-based stochastic wind-thermal generation coordination for Turkish electricity market

J. Mod. Power Syst. Clean Energy https://doi.org/10.1007/s40565-018-0492-3 CVaR-based stochastic wind-thermal generation coordination for Turkish electricity market Aycan AYDOĞDU1, Osman Bülent TÖR2, Ali Nezih GÜVEN1 Abstract Uncertainties in wind power forecast, day-ahead and imbalance prices for the next day possess a great deal of risk for the profit of generation companies participating in a day-ahead electricity market. Generation companies are exposed to imbalance penalties in the balancing market for unordered mismatches between associated day-ahead power schedule and real-time generation. Coordination of wind and thermal power plants alleviates the risks raised from wind uncertainties. This paper proposes a novel optimal coordination strategy by balancing wind power forecast deviations with thermal units in the Turkish dayahead electricity market. The main focus of this study is to provide an optimal trade-off between the expected profit and the risk under wind uncertainty through conditional value at risk (CVaR) methodology. Coordination problem is formulated as a two-stage mixed-integer stochastic programming problem, where scenario-based wind power approach is used to handle the stochasticity of the wind power. Dynamic programming approach is utilized to attain the commitment status of thermal units. Profitability CrossCheck date: 29 October 2018 Received: 21 May 2018 / Accepted: 29 October 2018 Ó The Author(s) 2018 & Osman Bülent TÖR Aycan AYDOĞDU Ali Nezih GÜVEN 1 Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara 06800, Turkey 2 The Bucharest University of Economic Studies, Bucharest, Romania of the coordination with different day-ahead bidding strategies and trade-off between expected profit and CVaR are examined with comparative scenario studies. Keywords Conditional value at risk (CVaR), Windthermal coordination, Electricity market, Wind power, Thermal power 1 Introduction Participation of wind-based power plant in electricity markets offers diverse privileges for utilities and end-use costumers. However, trading of wind power in electricity markets is a challenging issue. Most wind power producers prefer trading electricity with grant-in-aid fixed feed-in tariff or long-term agreements to guarantee their profits against price fluctuations in short-term electricity markets [1, 2]. Such risk-free long-term contracts usually have lower selling prices compared to those in short-term electricity markets. On the other hand, participation in dayahead (DA) electricity markets imposes a significant degree of risk for wind power producers. There are three main risk sources that the producers are faced with, namely, uncertainties in the forecasts of wind power, DA price, and balancing market price for the next day [3]. Contrary to the wind power generation, thermal generation is highly controllable and flexible. However, due to uncertainty and variability in market prices, thermal units are also subjected to risk of low profit or loss in DA markets [4]. Coordination facilitates thermal units to contribute to the revenue of a generation company by balancing wind generation deviations at periods of low thermal profitability. Wind generation, on the other hand, utilizes thermal units to avoid high imbalance penalties in 123 Aycan AYDOĞDU et al. balancing market with the coordination. Consequently, wind-thermal coordination has been found beneficial under wind and price uncertainties [5]. DA markets mandate participants to declare their generation schedules for the next day several hours before the start of the operational day. Time difference between the submission of bids and real-time operation ranges from 14 to 38 hours. For example, in Spanish DA market, bids are submitted a day before at 10:00 a.m. [5]. It is 11:30 a.m. for Turkish DA market case [6]. However, hourly wind power generation can be forecasted with a mean absolute error in the range of 15%-20% for a single plant from one day before; thus, deviations from DA schedule inevitably occur in actual generation [7]. Consequently, wind power producers are exposed to high imbalance penalties in balancing markets because of the uncertain wind forecasts. Likewise wind uncertainty, imbalance prices are also highly volatile and unpredictable. One of the reasons for this is that the amount of energy traded and the number of participants in balancing markets are relatively low compared to DA markets. Secondly, dual pricing mechanism, which Turkish balancing market has been practicing, makes imbalance prices even more difficult to estimate due to almost random nature of the direction of overall imbalances of the producers and the system. There are various studies in literature for hedging risks associated with wind uncertainty in DA markets. Authors in [1, 3, 8, 9] suggest bidding strategies for multiple shortterm markets for wind units alone. In addition to this, coordinating wind units with different generation types are widely suggested in recent studies. In [8, 10, 11], pumpedstorage and hydro-power units are proposed to complement the wind generation because of their capability to compensate imbalance power. There are other studies in [5, 12] that combine wind and thermal units to reduce imbalance penalties caused by wind deviations; however, they are not directly applicable to Turkish DA electricity market due to the different imbalance price mechanism. In addition to this, most of the previous research studied the wind-thermal coordination from an independent system operator (ISO) perspective [13, 14]. This paper contributes to the state-of-art with coordinating wind and thermal units by adapting conditional value at risk (CVaR) concept — a mathematical approach to optimize risk of profit — to control profit variation in DA markets from the view point of generation company. For this purpose, a stochastic programming procedure considering Turkish DA market mechanism is developed. Moreover, realistic scenario studies are carried out to test the profitability of coordination and the performance of the solution algorithm under different risk measures. Results show that it is more profitable to coordinate wind and 123 thermal units for DA and balancing markets than participation of wind and thermal units independently. The rest of the paper is organized as follows. Electricity market mechanism in Turkey is summarized in Section 2. Section 3 presents detailed description of the problem formulation. In Section 4, the algorithm developed to solve the coordination problem is introduced. In Section 5, numerical studies are carried out and comparisons are made to investigate the benefit of coordination and the effect of risk attitude of generation company on CVaR and expected profit. Finally, concluding remarks are given in Section 6. 2 Turkish electricity market In Turkish electricity market, participants can trade electricity via bilateral contra (...truncated)