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This article first presents an abstract model that includes information such as port distribution, pure electric ship parameters, and charging pile configuration. Based on this model, combined with probability and statistical analysis of electric ship navigation energy consumption and charging demand, the load of each port can be predicted in multiple scenarios and stages. Determine transmission lines, substations, photovoltaics, and wind turbines as optimization objects, establish an estimation model for investment costs, operating costs, power purchase costs, environmental penalty costs, and transmission loss costs, and define the optimization objective function. The GUROBI solver is called, combined with constraints such as power balance, grid topology, operation and construction, to solve the mixed integer nonlinear model, and obtain the optimal solution for the distribution network topology and distributed energy configuration scheme. In order to verify the feasibility of the planning algorithm, an optimal planning scheme for the distribution network is proposed based on the 21-node system. The scheme can meet the port load in each stage of peak and off-season, delay the investment in collaborative energy supply grid, and reduce the cost of system expansion planning.

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Collaborative Energy Supply Network Architecture Planning Method Taking into Account Pure Electric Ship Charging Load Forecasting

  • 会议论文

  • 发表日期：

    2025年

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  • Changpeng Sun,
  • Huaqi Ye,
  • Ning Gao,
  • Jingyi Lin,
  • Yi Lin

摘要

This article first presents an abstract model that includes information such as port distribution, pure electric ship parameters, and charging pile configuration. Based on this model, combined with probability and statistical analysis of electric ship navigation energy consumption and charging demand, the load of each port can be predicted in multiple scenarios and stages. Determine transmission lines, substations, photovoltaics, and wind turbines as optimization objects, establish an estimation model for investment costs, operating costs, power purchase costs, environmental penalty costs, and transmission loss costs, and define the optimization objective function. The GUROBI solver is called, combined with constraints such as power balance, grid topology, operation and construction, to solve the mixed integer nonlinear model, and obtain the optimal solution for the distribution network topology and distributed energy configuration scheme. In order to verify the feasibility of the planning algorithm, an optimal planning scheme for the distribution network is proposed based on the 21-node system. The scheme can meet the port load in each stage of peak and off-season, delay the investment in collaborative energy supply grid, and reduce the cost of system expansion planning.