Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 120, Issue -, Pages 388-396Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2016.04.082
Keywords
Stochastic self-scheduling; Renewable energy sources (RESs); Demand response program (DRP); Compressed air energy storage (CAES); Mixed-integer linear programming (MILP)
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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 (WI') and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of use (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 and minimize 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. (C) 2016 Elsevier Ltd. All rights reserved.
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