This article studies an energy transaction management of multienergy prosumers (MEPs) in integrated energy community (IEC). A novel MEPs coalitional game model with transferable utility is proposed to coordinate the electricity-heat transactions and enhance the local energy consumption among MEPs in IEC. The superadditivity of the proposed coalitional game is rigorously proven to ensure coalition incentives. A superadditivity-directed coalition formation algorithm is developed to achieve a stable and efficient coalition partition with significantly reduced computational burden. Furthermore, the nonemptiness of the core for the proposed coalitional game is rigorously proven, and a Shapley value-based payoff allocation mechanism is designed and proven to align with the core, ensuring both fairness and stability in the proposed coalitional game. Simulation results show that the proposed model and method achieve the highest payoff across all cases, ensure the fair and stable payoff allocation, achieve reductions of 99.2% in iterations and 98.98% in solving time, and confirm their feasibility for large-scale applications.
Coalitional Game-Based Energy Transaction Management of Multienergy Prosumers in Integrated Energy Community
Siano P.
2026
Abstract
This article studies an energy transaction management of multienergy prosumers (MEPs) in integrated energy community (IEC). A novel MEPs coalitional game model with transferable utility is proposed to coordinate the electricity-heat transactions and enhance the local energy consumption among MEPs in IEC. The superadditivity of the proposed coalitional game is rigorously proven to ensure coalition incentives. A superadditivity-directed coalition formation algorithm is developed to achieve a stable and efficient coalition partition with significantly reduced computational burden. Furthermore, the nonemptiness of the core for the proposed coalitional game is rigorously proven, and a Shapley value-based payoff allocation mechanism is designed and proven to align with the core, ensuring both fairness and stability in the proposed coalitional game. Simulation results show that the proposed model and method achieve the highest payoff across all cases, ensure the fair and stable payoff allocation, achieve reductions of 99.2% in iterations and 98.98% in solving time, and confirm their feasibility for large-scale applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


