A robust optimization method for bidding strategy by considering the compressed air energy storage

Power market tariff is a main problem in electricity yields that is challenged by yield markers. For tackling this challenge, optimization of offering/bidding methods is so crucial. Present work suggested a novel method called synthetic stochastic-robust approach for maximization of anticipated revenue of compressed air energy system (CAES), in which, uncertain parameters such as market tariff and max potential of cavern are taken into account. In this proposed method, modeling of market tariff uncertainty is done by means of a collection of cases through stochastic optimization whereas uncertainty of max potential of cavern is modeled by robust method. As well, this paper suggested a new method for achieving offering and bidding profiles that have robustness versus uncertain parameters including: market price and cavern max capacity. Achieved results confirm, entire benefit in absence of cavern uncertainty. In the other words, having robustness versus uncertainty of cavern max potential decreases entire revenue.