信息受限电力市场中价格型储能系统的战略投标策略

Abstract Utility-scale energy storage systems (ESSs) are increasingly participating in the electricity market and may influence market prices as price-makers. However, many electricity markets only disclose limited market information, e.g., the National Electricity Market of Singapore (NEMS) which does not release network parameters and rival bidding data, making it challenging for ESSs to make optimal bidding decisions. This paper uses NEMS as a case study to propose a generic strategic bidding strategy for price-maker ESSs with limited information, which only requires the publicly available demand data and its market clearing price. Through statistical analysis of historical data , the clearing price is modeled using Stochastic Price Quota Curves (SPQCs), which capture price probability distributions as a function of ESS bidding decisions. Integrating SPQCs into the bidding model results in a stochastic nonlinear problem with decision-dependent uncertainties. To address this, the problem is reformulated into a deterministic equivalent using SPQC expectations, and a specific trust-region-based iterative solution algorithm is proposed. A case study with real NEMS data validates the effectiveness of the method.