Microgrids incorporate distributed energy resources (DERs) and flexible loads, which can provide energy and reserve services for the main grid. However, due to uncertain renewable generations such as solar power, microgrids might under-deliver reserve services and breach day-ahead contracts in real-time. If multiple microgrids breach their reserve contracts simultaneously, this could lead to a severe grid contingency. This paper designs a distributionally robust joint chance-constrained (DRJCC) game-theoretical framework considering uncertain real-time reserve provisions and the value of lost load (VoLL). Leveraging historical error samples, the reserve bidding strategy of each microgrid is formulated into a two-stage Wasserstein-metrics distribution robust optimization (DRO) model. A JCC is employed to regulate the under-delivered reserve capacity of all microgrids in a non-cooperative game. Considering the unknown correlation among players, a novel Bayesian optimization method approximates the optimal individual violation rates of microgrids and market equilibrium. The proposed game framework with the optimal rates is simulated with up to 14 players in a 30-bus network. Case studies are conducted using the California power market data. The proposed Bayesian method can effectively regulate the joint violation rate of the under-delivered reserve and secure the profit of microgrids in the reserve market.

翻译：微网集成了分布式能源资源（DERs）和柔性负荷，能够为主电网提供能量和备用服务。然而，由于太阳能等可再生能源发电的不确定性，微网可能在实时市场中无法足额交付备用服务，从而违反日前合同。若多个微网同时违反备用合同，可能导致严重的电网紧急事故。本文设计了一种考虑实时备用供给不确定性与失负荷价值（VoLL）的分布式鲁棒联合机会约束（DRJCC）博弈理论框架。利用历史误差样本，将每个微网的备用投标策略建模为两阶段Wasserstein度量分布式鲁棒优化（DRO）模型。在非合作博弈中，采用联合机会约束（JCC）来规范所有微网的备用容量不足交付问题。考虑参与者间未知的相关性，提出一种新颖的贝叶斯优化方法，近似求解微网的最优个体违规率及市场均衡。在30节点网络中模拟了多达14个参与者的博弈框架，并利用加州电力市场数据进行案例研究。结果表明，所提贝叶斯方法能有效调控备用不足交付的联合违规率，并保障微网在备用市场中的利润。