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Game-theoretic modeling demonstrates reduced energy costs across community load aggregators with diverse storage, indicating effective spatiotemporal optimization via cooperative sharing.
With the advancement of energy storage technology, the user side equipped with heterogeneous storage has become the norm. Under this context, how to further improve energy utilization efficiency and reduce energy cost via heterogeneous energy sharing among diverse users of a community integrated energy system (CIES) has become an urgent problem to be solved. In this paper, an optimal energy use method for CIES was proposed based on hybrid game theory and investigated for the optimal energy strategy. In this method, different game models were adopted according the gaming characteristics between different participants. In addition, to achieve reasonable cooperation benefit allocation, an asymmetric bargaining model based on nonlinear energy mapping function was built to quantify each participant’s contribution. Based on the proposed method, the energy use strategies of different participants in CIES were analyzed by a case study. The results showed that the total costs for multiload aggregators (MLA) reduced 19.70%, of which purchased power and heat cost by MLA from CIES operators reduced 21.71% and 16.93%. Thus, the energy sharing among load aggregators (LA) with heterogeneous energy storage can effectively realize the spatiotemporal optimization of energy management among LA.
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Yan et al. (2026) studied this question.
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