Uncertainty-Informed Renewable Energy Scheduling: A Scalable Bilevel Framework

作     者：Zhao, Dongwei Dvorkin, Vladimir Delikaraoglou, Stefanos Lamadrid, L. Alberto J. Botterud, Audun 

作者机构：MIT Energy Initiat & Lab Informat & Decis Syst Cambridge MA 02139 USA MIT Lab Informat & Decis Syst Cambridge MA 02139 USA Lehigh Univ Dept Econ Bethlehem PA 18015 USA Lehigh Univ Dept Ind & Syst Engn Bethlehem PA 18015 USA 

出 版 物：《IEEE TRANSACTIONS ON ENERGY MARKETS POLICY AND REGULATION》 (IEEE Trans. Energy. Mark. Policy. Regul.)

年 卷 期：2024年第2卷第1期

页      面：132-145页

核心收录：

基　　金：Advanced Research Projects Agency-Energy (ARPA-E)  U.S. Department of Energy [DE-AR0001277] 

主　　题：Costs Optimization Real-time systems Electricity supply industry Dams Uncertainty Generators Bilevel optimization electricity markets McCormick envelope renewable energy scalability uncertainty management unit commitment 

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.