Integrated energy management and operations planning in oil-electric hybrid container terminals considering multi-energy supply

Abstract

With the rapid increase in container terminal throughput and operations, terminals face the challenge of dealing with high energy consumption and emissions while achieving higher operational efficiency. As container terminal equipment undergoes electrification upgrades and renovations, the variety of operational equipment types and complexity of operational conditions have grown. Considering the intricate energy demands of terminal operations and the diversified nature of terminal energy supply, striking a balance between terminal operational efficiency and energy management is essential for green port development. In this study, we investigate the integrated energy management and operations planning problem in oil-electric hybrid container terminals during the electrification transformation process. The problem involves decisions on ship berthing, equipment allocation, and multi-energy supply scheme. To solve the problem, we formulate a mixed-integer linear programming (MILP) model with the objective of minimizing the total operation costs. Based on the framework of adaptive large neighborhood search (ALNS), a tailored ALNS + Gurobi heuristic (AGH) algorithm is developed. The AGH algorithm proposes destroy-and-repair operators and heuristics adapted to the problem characteristics, and invokes Gurobi to solve the energy management model to obtain the energy supply scheme. Computational experiments validate the superior performance of the proposed algorithm, and sensitivity analysis provides some managerial implications to assist terminal operators in making operational decisions.