In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air
energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind
turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-ofuse (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive
period to the cheap one in order to flatten the load curve andminimize the operation cost, consequently. The
proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering
technical and physical constraints. The proposed model is formulated as mixed integer linear programming
(MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package.
Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker
to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind
speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP
and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained,
which indicate the validity of the proposed stochastic program.