Adaptive Robust Self-Scheduling for a Wind Producer With Compressed Air Energy Storage

Due to uncertain nature of wind energy, the profit of a wind producer (WP) is at a notable risk. To overcome the risk associated with the uncertain wind power productions, energy storage systems have attracted an increasing attention. However, due to electricity price forecast errors, storage systems might not be able to efficiently participate in an electricity market as they both purchase and sell energy. Therefore, although the combination of WPs and storage systems can be economically promising, they require a proper offering and bidding strategy, which effectively characterizes the uncertainty associated with both wind power production and price forecast errors. To do so, this paper proposes an adaptive robust self-scheduling model for a WP paired with a compressed air energy storage system to participate in the day-ahead energy market. The proposed model addresses the uncertainties regarding the wind power productions and price forecast errors. Furthermore, the flexibility and the robustness of the proposed method can he controlled using a parameter denominating the budget of uncertainty. Simulation results illustrate the effectiveness of the proposed method.