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Simulation study demonstrates a risk-constrained bidding model manages electricity price uncertainty for energy storage plants, suggesting improved financial robustness in day-ahead markets.
Electricity price forecasts are imperfect. Therefore, a merchant energy storage facility requires a bidding and offering strategy for purchasing and selling the electricity to manage the risk associated with price forecast errors. This paper proposes an information gap decision theory (IGDT)-based risk-constrained bidding/offering strategy for a merchant compressed air energy storage (CAES) plant that participates in the day-ahead energy markets considering price forecasting errors. Price uncertainty is modeled using IGDT. The IGDT-based self-scheduling formulation is then used to construct separate hourly bidding and offering curves. The theoretical approach to develop the proposed strategy is presented and validated using numerical simulations.
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Shafiee et al. (2016) studied this question.
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