To fully coordinate multiple community integrated energy systems (IES) for achieving complementary energy sharing and promoting low-carbon economic operation
this paper proposes a cooperative game-based collaborative optimization strategy for community-level IES that accounts for the correlation characteristics of wind and solar power generation. The strategy aims to construct a multi-IES collaborative framework using cooperative game theory
achieving resource sharing among participants and minimizing total operational costs. Firstly
to address the inherent uncertainties and spatiotemporal correlations of wind and solar resources
the Gaussian kernel Copula theory is employed to generate joint probability scenarios of wind-solar power output correlations
providing an accurate data foundation for subsequent optimization. Secondly
within the cooperative game framework
a two-stage interactive trading strategy encompassing “cost minimization” and “transaction bargaining” is meticulously designed. The alternating direction method of multipliers (ADMM) is adopted for distributed solution
optimizing energy trading quantities and prices separately to ensure the feasibility and effectiveness of the strategy. Simulation results demonstrate that the proposed model is effective
significantly reducing the operational costs of each IES
enhancing system synergy and mutual support capabilities
and promoting regional energy systems toward economical
robust
and low-carbon operation through a diversified electricity-heat-carbon trading mechanism.
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