面向港口关键起重设备调峰的协调优化运行方法OACSCD

Intelligent and green development is an inevitable trend for future port development.After electrification upgrades,key port equipment is supplied by the port microgrid,and a safe and stable power supply is the foundation for efficient port transportation operations.Focusing on critical large-scale port cranes in automated container termi-nals,this study investigates a coordinated operational scheduling strategy for peak shaving and valley filling in port microgrids.A unified load-calculation model for ship-to-shore cranes(STS)and rail-mounted gantry cranes(RMG)is established.By dividing the stages of the equipment's dual-cycle operating process,a multi-stage,full-time-hori-zon load profile under standard working conditions is developed.Building on the load modeling and considering the charge-discharge capability of centralized port energy storage,an exact optimization model is proposed for the coor-dinated operation between the operating cycles of crane clusters and the energy storage system.Logical variables are introduced to characterize the operating stage and power level of each machine,and constraints and an objective function are formulated to account for aggregated power impacts from equipment clusters.Solving the optimization model yields the optimal start times for multiple machines,thereby smoothing load fluctuations of port equipment clusters and improving energy utilization efficiency.Simulation analyses are conducted for equipment operation and energy storage capacity configuration,verifying that the multi-equipment coordinated scheduling method can effec-tively reduce the peak-valley difference,achieving more than a 20%reduction in peak power in the considered sce-narios.Comparative analyses between exact optimization and heuristic optimization validate the optimality and scal-ability of the exact approach.In addition,the feasible region of start times under stochastic equipment operation is provided,identifying safe start-time combinations under non-ideal conditions.An extension of the proposed optimi-zation model to non-standard operating conditions is also presented,demonstrating strong engineering practicality.