A novel price-maker ESS bidding model is proposed to maximize profits through energy arbitrage and the provision of ancillary services. SPQC is developed to capture the price probability distributions as functions of ESS bidding decisions.
These findings reinforce the practicality and adaptability of the proposed method for strategic ESS bidding in electricity markets with limit information and offer a solid foundation for future research on market-based ESS operations.
Singapore is actively promoting ESS deployment through its Accelerating Energy Storage for Singapore Programme, aiming to install 200 MWh of ESSs by 2025 . However, as a small-scale market, the National Electricity Market of Singapore (NEMS) is highly sensitive to supply-demand imbalances.
The proposed ESS bidding model aims to maximize the expectation profit by allocating the capacities bidding in energy, primary and contingency reserve, and regulation markets. The clearing prices of each market are considered as stochastic parameters in this paper. The daily optimal bidding model is formulated as follows.
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