标题： 考虑不确定性的可再生能源调度：一种可扩展的双层框架 显示英文标题

标题： Uncertainty-Informed Renewable Energy Scheduling: A Scalable Bilevel Framework

摘要： 这项工作提出了一种考虑不确定性的投标调整框架，用于将可变可再生能源（VRES）整合到电力市场中。 该框架采用双层模型来计算最优的VRES日前投标。 其目标是在日前和实时阶段最小化预期系统成本，并近似随机市场设计的成本效率。 然而，对于大规模系统来说，求解双层优化问题在计算上具有挑战性。 为克服这一挑战，我们引入了一种基于强对偶性和McCormick包络的新技术，该技术将问题松弛为线性规划，从而实现大规模应用。 所提出的双层框架应用于1576节点的NYISO系统，并与一种短视策略进行对比，其中VRES投标是概率功率预测的均值。 结果表明，在高VRES渗透水平（例如，40%）下，我们的框架可以通过在日前市场中高效优化VRES数量显著降低系统成本和市场价格波动。 此外，我们发现当输电容量增加时，所提出的双层模型仍将降低系统成本，而短视策略可能由于在日前市场过度调度VRES以及实时中缺乏灵活的传统发电机组而导致更高的成本。 显示英文摘要

摘要： This work proposes an uncertainty-informed bid adjustment framework for integrating variable renewable energy sources (VRES) into electricity markets. This framework adopts a bilevel model to compute the optimal VRES day-ahead bids. It aims to minimize the expected system cost across day-ahead and real-time stages and approximate the cost efficiency of the stochastic market design. However, solving the bilevel optimization problem is computationally challenging for large-scale systems. To overcome this challenge, we introduce a novel technique based on strong duality and McCormick envelopes, which relaxes the problem to a linear program, enabling large-scale applications. The proposed bilevel framework is applied to the 1576-bus NYISO system and benchmarked against a myopic strategy, where the VRES bid is the mean value of the probabilistic power forecast. Results demonstrate that, under high VRES penetration levels (e.g., 40%), our framework can significantly reduce system costs and market-price volatility, by optimizing VRES quantities efficiently in the day-ahead market. Furthermore, we find that when transmission capacity increases, the proposed bilevel model will still reduce the system cost, whereas the myopic strategy may incur a much higher cost due to over-scheduling of VRES in the day-ahead market and the lack of flexible conventional generators in real time.