부산대학교 도서관

Port shore power technology can effectively reduce emissions from auxiliary engines and improve local and regional air quality, while also using renewable energy for energy supply. The process of power demand side management has been promoted, but there are still some problems, such as the insufficient response of power users, the enthusiasm of power grid enterprises has not been improved. The role of power service institutions can not be brought into play. In this paper, a dual-objective travel planning scheme for charging scheduling of electric vehicles under port transportation traffic flow is constructed, which aims at the optimization of energy consumption and travel cost of charging scheduling of electric vehicles. Then, the process of adaptive dynamic search ant colony optimization algorithm to deal with the optimization problem under different time-varying speeds and time slices of traffic flow is described. The effectiveness and stability of the improved ant colony optimization algorithm proposed in this paper are proved by the comparative test results and effect analysis.