Stochastic-based coordinated trading of combined cycle & wind unit

Trading of Combined Cycle Units (CCU) energy in short-term electricity markets is complicated since CCU operates with multiple configurations based on the number and the status of combustion turbines and steam turbines. However, CCU has distinct advantages like high efficiency, faster response, shorter installation time and environmental friendliness than the simple cycle (thermal unit). Therefore, combined cycle unit is suitable to coordinate with the wind energy due to wind bidding risks. Consequently, bidding wind energy during short-term has uncertainties like hourly available wind, energy prices, and imbalance penalties which could affect the electricity market as a high risks. In this thesis, the coordination between wind and combined cycle units is proposed for the day-ahead energy market bidding. For CCU, a component model is used. The problem is formulated as a mixed integer linear programming (MILP) problem that determines the optimal bidding curves for combined cycle and wind units. Also it determines the unit commitment of combined cycle.;Stochastic programming (SP) is used in order to account for uncertainties associated with wind power output, spot market energy price, and imbalance up/down price. The main objective is to determine the optimal trade-off bidding strategy that maximizes the total expected profits. This study takes into account the various constraints of combined cycle units such as minimum on/off time, ramping rates, minimum and maximum power outputs, and startup costs. A simulation study for a producer with combined cycle and wind units is carried out to demonstrate the benefits of coordination. The influence of risk control by using the conditional value at risk (CVaR) on the coordinated case is also considered.