Distributed Optimization of Joint Seaport-All-Electric-Ships System under Polymorphic Network

As a result of the trend towards auto intelligence and greening of vehicles and with the concept of polymorphic network being put forward, the power transmission mode between seaports and all-electric ships (AESs) is likely to be converted to peer-to-peer transmission. According to practical shore power systems and carbon trade mechanisms, an advanced peer-to-peer power dispatching model-joint seaport-AESs microgrid(MG) system has been proposed in the paper. The joint seaport-AES system model is proposed to minimize the total operational cost of power production and marketing, including distributed generation (DG) cost, electricity trading cost, and carbon emissions, and the boundary conditions are given as well. A parameter projection distributed optimization (PPDO) algorithm is utilized to solve the distributed optimization power operation planning of the proposed joint seaport-AES MG system under a polymorphic network and to guarantee the precision of power dispatching, which compensates for the insufficiency of the computing power. Finally, a case study of a five-node polymorphic joint seaport-AESs system is conducted. The feasibility of the parameter projection approach and the peer-to-peer power dispatching model are verified via the convergence of all the agents within the constraint sets.

Automated summary

This paper proposes an advanced joint seaport-AES microgrid system, aiming to minimize the total operational cost of power production and marketing, and utilizes a parameter projection distributed optimization algorithm to solve the power dispatching problem. The feasibility of this approach is verified through a case study.