Optimal Stochastic Operation of a Power System Incorporated with Compressed Air Energy Storage and Wind Turbine

This paper proposes the two-stage stochastic operation model for optimal scheduling of the power system integrated with the conventional power plants as the backup systems, renewable energy resources (RERs) for clean energy production, and compressed air energy storage (CAES) systems to facilitate the presence of the RERs. In the DA market (first stage problem), the system is targeted to minimize the operational cost of the conventional units while the second stage problem is focused to model the system considering the variations of the RERs in the RT balancing market. In this study, the coordinated operation of both the reserve and energy markets are carried out to provide a reliable condition for energy supply to the consumers in the presence of the uncontrollable energy generation units. The solar radiation and wind speed are considered as the uncertain parameters, which the Monte Carlo simulation (MCS) and fast forward selection (FFS) techniques are exerted for scenario generation and reduction. In this study, the effective role of the CAES system is investigated by analyzing the three cases. The modified IEEE 24-bus test system is considered for evaluating the extracted results during a day. The results indicate the presence of the CAES units is necessary for optimal operation of the power grid with a high share of RERs not only for minimizing energy costs but also for more clean energy production in the electricity network.