峰值电量约束下的场桥能耗最小化问题研究

随着化石能源的大量使用带来的环境污染问题日益严峻,关注能源使用效率的集装箱港口绿色化运营研究成为近年来的热点之一.本文以集装箱堆场中需要执行预倒箱作业的场桥为研究对象,考虑场桥不同运行状态下的单位时间电量需求不同以及峰值电量实时约束,建立了以总能耗最小化为目标的多场桥调度问题的混合整数规划数学模型.继而,将关键变量利用非连续贝和连续贝两种不同的方式进行编码,将次级变量利用启发式规则进行解码,并设计了相对应的遗传算法交叉与变异方法.数值实验表明,连续贝编码方法表现更为优异;通过与Cplex在小规模算例中的比较,与粒子群算法及人工蜂群算法在大规模算例中的比较,验证了所设计遗传算法的有效性.同时,通过与传统策略的对比,表明本模型可以同时实现能耗总需求与峰值需求两方面的优化,从而可以为港口管理人员在不影响既定日常运营工作的前提下降低能源成本提供科学有效的指导.

Minimizing the total energy consumption of yard crane under the peak demand constraint

With the increasing concern of environment pollution caused by the massive usage of fossil fuels,the energy-efficient operation of green container terminals is becoming one of the hottest topics in recent years.This paper investigates the yard cranes with the pre-marshalling tasks,in which the power demand of crane is different when the crane runs in different mode.Considering the peak power constraint,a mixed integer programming model is established to minimize the total energy consumption of all cranes with non-crossing and safety clearance requirements in the storage yard.Two kinds of coding methods are designed based on the idea of discrete bay and continuous bay,then the chromosome is decoded using heuristic rules.And,the crossover and mutation methods are designed for the genetic algorithm(GA)correspondingly.Numerical results show that the method of continuous bay is better than the discrete bay.Then,the effectiveness of designed GA is validated by the results obtained by the comparison between GA and Cplex,particle swarm optimization,artificial bee colony algorithm.In addition,compared with the traditional policy,our model performs well in both of total energy consumption and peak demand.The research findings can guide the port managers to reduce the energy cost effectively without interfering the processing of daily tasks.