This paper proposes a distributed energy management strategy, based on dual decomposition mixed integer linear programming for port integrated energy systems (PIESs), to improve the utilization of renewable energy, and to foster green ports. Firstly, due to the distributed characteristics presented by various heterogeneous devices, a polymorphic network-based PIES was established, instead of the traditional single IP protocol, incorporating electricity replacement and energy conversion devices. Secondly, taking into account the coupling of various energy flows, an energy management model was constructed, to ensure reliable operation for the PIES. Thirdly, an energy management strategy based on distributed dual decomposition mixed integer linear programming for the PIES was proposed, which took into account the distributed characteristic of the PIES. Finally, the effectiveness of the proposed strategy was demonstrated, by simulation cases in different scenarios for the PIES. The obtained energy management results were similar to the centralized algorithm.

To enhance the efficiency of a port microgrid, this paper proposes an energy management method and a topology construction mechanism considering the convergence rate and information transmission distances, respectively. Firstly, a distributed fixed-time energy management method is proposed to solve an energy management problem in a known time and guarantee the efficiency of the port microgrid. Secondly, to address the challenge of heterogeneous devices with multiple communication protocols, information exchange between different devices is facilitated through a polymorphic network. To obtain a connected communication topology that can ensure the implementation of the distributed energy management method, a connected networking mechanism is proposed. This mechanism minimizes the total communication distance to reduce the effect of the information transmission distance on communication effectiveness. Finally, the effectiveness of both algorithms is demonstrated by simulation, and the advantages of the distributed fixed-time energy management method on the convergence rate are reflected through a comparison with other methods.