Optimal bidding strategy for a GENCO in day-ahead energy and spinning reserve markets with considerations for coordinated wind-pumped storage-thermal system and CO2 emission

In competitive electricity markets, generation company (GENCO) is responsible for maximizing its profits according to other participants bidding behaviors and power systems operating conditions. With a diversified portfolio consisting of renewable and non-renewable generation plants, a GENCO coordinates wind and pumped storage units with thermal units to achieve higher profit and lower CO2 emission. The goal of this study is to solve the optimal bidding strategy problem for a GENCO with coordinated wind-pumped storage-thermal system for maximizing economic profit with participation in day-ahead energy and spinning reserve markets with considerations for CO2 emission and wind power uncertainty. The heuristic optimization algorithm used in this study is successfully applied to two case studies. In the first case used for validation, it is determined that the heuristic optimization algorithm improves profits of a GENCO by 4.15-47.95% and 20.84-31.30% in single-sided and double-sided auctions, respectively. For the second case study, the coordination of wind and pumped storage with thermal units results in profit improvements by 0.52-1.00%, as compared with uncoordinated operation. It is concluded that three factors, namely, wind farm maximum power, pumped storage maximum power, and CO2 emission price have considerable effects on optimal bidding strategy of coordinated wind-pumped storage-thermal system.