Enhancing the flexibility of decentralized energy resources through bi-level optimization in intra-day regional markets

This paper presents an innovative approach to an intra-day, intra-hourly Regional Flexibility Market (RFM) that enhances the utilization of Distributed Generation (DG) flexibility, including energy storage systems, electric vehicles, and photovoltaics. The market is managed by an Advanced Virtual Power Plant (AVPP), which acts as an intermediary and efficiently integrates DG flexibility into power system operations by coordinating transactions among DG aggregators. Beyond facilitating RFM trades, the AVPP also contributes to the Wholesale Flexibility Market (WFM) and helps mitigate short-term fluctuations within the Distribution Network (DN). To achieve an optimal market balance, a hierarchical market clearing mechanism is introduced, ensuring that DG flexibility is efficiently allocated while all participating entities gain economic benefits. The framework is modeled as a bilevel optimization problem with multiple lower-level decision processes, capturing the interactions between the AVPP and aggregators. While the AVPP at the upper level seeks to maximize its own profit, each lower-level problem represents an aggregator's strategic decision-making process. To enhance computational efficiency, the bilevel formulation is transformed into a single-level mixed-integer linear programming model and tested on a 119-bus DN. The results confirm that the framework effectively utilizes DG flexibility, increasing AVPP profit by 28% and reducing intra-hourly net-load deviations by 35%, thereby improving both economic efficiency and operational stability.