Optimal scheduling of multi-energy hubs considering carbon trading and its benefit allocation

Abstract

ABSTRACT This study proposes a cooperative fuzzy optimal scheduling method for multi-energy hubs considering carbon trading. The traditional integrated energy system has difficulty integrating system economy and environment, as well as allocating benefits to multiple subjects. To address the problem, a multi-energy hub cooperative fuzzy optimization dispatching model, considering carbon trading, was developed to promote low carbon emissions and high renewable energy penetration. The model optimizes the dispatch of the integrated energy system while reducing CO2 emissions, also reducing the impact of renewable energy output uncertainty. Moreover, decision-makers can adjust the risk tolerance of the system according to their own risk appetite. To ensure a fair method of benefit distribution to achieve overall optimum through cooperation, this study introduced and examined three methods of secondary benefit distribution in cooperative games: Shapley value method, Kernel method, and Equal DP (Disruption Propensity) method. Finally, the model’s economic, environmental protection, and stability were verified by an example of cooperative optimal scheduling and collaborative residual benefit secondary allocation of three energy hubs. Moreover it was found that in the secondary allocation,the Equal DP method was more stable and acceptable to all subjects compared to the other two methods.