The optimal scheduling of multi-energy hub systems plays an important role in the safety, stability, and economic operation of the system. However, due to the strong uncertainty of renewable energy access, serious coupling, and the interaction among energy hubs of multi-energy hub systems, it is difficult for the traditional optimal scheduling method to solve these problems. Therefore, game theory was used to solve the optimal scheduling problem of multi-energy hub systems. According to the internal connection mode and energy conversion relationship of energy hubs, along with the competitive and cooperative relationship between multi-energy hubs, the game theoretic optimal scheduling model of the multi-energy hub system was established. Then, two cases and 50 groups of wind speed series were used to test the robustness of the proposed method. Simulation results show that the total power injection is −16,805.8, 104.1847, and −865.561 and the natural gas injection is 46,046.81, 27,727.65, and 63,039.54 in spring/autumn, summer, and winter, respectively, which is consistent with the characteristics of the four seasons. Furthermore, the optimal scheduling method using game theory has a strong robustness in multi-energy hub systems.
Multi-energy carriers system (MECS), in which diverse energy carriers and different energy systems interact together, has drawn the interest of many researchers in recent years. However, the optimal economic operational model of the MECS is a nonlinear, multi-variable, and multi-period problem, of which it is difficult to find the solution because several different energy flows are integrated in the system. To this end, three interest bodies in the MECS were investigated, which included the energy provider, the energy facilitator, and the energy consumer, and a hierarchical optimal economic operation strategy was then presented. A hybrid optimization strategy combining the swarm intelligence algorithm and interior point method was developed taking advantage of the merits of each method. Case studies were conducted to verify the effectiveness of the proposed hierarchical optimal economic operation strategy, whereby demonstrating that the proposed strategy can achieve rational energy allocation and decrease the energy cost in the MECS compared with traditional energy systems.
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