Risk management of a renewable-based compressed air energy storage system using downside risk constraints approach

The financial risks imposed from the uncertain parameters is a considerable issue in the optimization problem of renewable-based energy systems. Due to the various risks in renewable-based energy systems, a practical and simple risk measurement approach can be efficient in the risk-based strategy selection process. In this paper, the downside risk constraints (DRC) approach as a novel risk measurement approach is proposed to manage the imposed risks from the uncertain parameters over the stochastic problems. Therefore, various uncertainties, including solar irradiation, temperature, wind speed, electricity demand, and electricity market price uncertainties, are modeled using the DRC approach along with the stochastic programming. In addition, the compressed air energy storage (CAES) and demand response program (DRP) is implemented to manage the imposed risks. By using the proposed risk measurement method, the system operator can obtain a risk-strategy that is independent of scenarios. According to the obtained results, the expected cost of the stochastic problem is $ 6145.62, which by using the DRC approach, the system operator by paying the 3.4% ($ 6353.5) more cost can guarantee itself against the financial risks. The advantage of the proposed DRC approach is the conversion of the stochastic problem to a deterministic scenario-independent problem. •Stochastic based renewable and compressed air energy storage system is studied.•Use of a novel risk measurement tool called downside risk constraints (DRC).•Use of the demand response program and energy storage to control the uncertainties.•Risk-based scheduling of the dispatchable units using DRC approach.•Introducing a scenario-independent strategy for operators by DRC approach.