This paper proposes a two-stage stochastic bi-level framework for joint energy and reserve scheduling of grid-connected Multi-Microgrids (MMGs) to achieve a win-win outcome in the presence of renewable resources and demand response programs (DRPs). In this framework, interconnected Microgrids (MGs) collaborate to facilitate bilateral energy exchange, leveraging economic advantages through peer-to-peer (P2P) energy and reserve trading platforms. Also, an MMG operator (MMGO) facilitates the interaction between MGs and plays a pivotal role in supplying loads, ensuring safety, and providing reserve as well as trading energy with the main grid, covering both day-ahead and real-time markets. To this end, a bi-level problem is formulated in which, at the upper level of the problem, the MMGO reschedules the MGs based on the P2P energy trading by considering the targets of each MG, while, at the lower level, each MG tries to optimize the local energy and reserve scheduling. In this model, flexible resources of MGs can provide upward/downward reserves to the grid through reserve trading, where the MMGO is responsible for reserve procurement. Numerical results show that the simultaneous energy trading and reserve services between MGs can help them achieve economic benefits. Moreover, DRPs can assist MGs in sharing more energy and reserve when the P2P trading floor is considered.

A decision-making framework for multi-microgrids scheduling considering joint P2P energy and reserve trading floor

Siano P.
2025

Abstract

This paper proposes a two-stage stochastic bi-level framework for joint energy and reserve scheduling of grid-connected Multi-Microgrids (MMGs) to achieve a win-win outcome in the presence of renewable resources and demand response programs (DRPs). In this framework, interconnected Microgrids (MGs) collaborate to facilitate bilateral energy exchange, leveraging economic advantages through peer-to-peer (P2P) energy and reserve trading platforms. Also, an MMG operator (MMGO) facilitates the interaction between MGs and plays a pivotal role in supplying loads, ensuring safety, and providing reserve as well as trading energy with the main grid, covering both day-ahead and real-time markets. To this end, a bi-level problem is formulated in which, at the upper level of the problem, the MMGO reschedules the MGs based on the P2P energy trading by considering the targets of each MG, while, at the lower level, each MG tries to optimize the local energy and reserve scheduling. In this model, flexible resources of MGs can provide upward/downward reserves to the grid through reserve trading, where the MMGO is responsible for reserve procurement. Numerical results show that the simultaneous energy trading and reserve services between MGs can help them achieve economic benefits. Moreover, DRPs can assist MGs in sharing more energy and reserve when the P2P trading floor is considered.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4916619
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