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文章摘要
电动汽车充电路径不确定优化调度
Optimal scheduling of electric vehicles for charging route under uncertainty
Received:May 10, 2018  Revised:May 10, 2018
DOI:
中文关键词: 电动汽车  充电路径  优化调度  不确定
英文关键词: Electric  vehicle (EV), charging  route, optimal  scheduling, uncertainty
基金项目:江苏省产学研合作计划项目(BY2016026-01);江苏省高校自然科学研究面上项目(16KJB480006)
Author NameAffiliationE-mail
Zhou Tianpei* Xuzhou College of Industrial and Technology zhoutianpei_001@163.com 
Sun Wei China University of Mining and Technology sw3883204@163.com 
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中文摘要:
      电动汽车充电路径优化调度中的很多参数变量都具有不确定性,传统的优化调度方法适用性较差。针对上述问题,将不确定优化应用其中,建立了基于随机期望值的不确定优化调度模型。鉴于传统的粒子群优化算法容易陷于局部优化和收敛速度较慢,将模拟退火算法引入并组成混合智能算法进行模型求解。对比实验证明该混合智能算法能够有效减少电动汽车车主到充电站所用的行驶距离、在充电站的等待时间和充电时间。
英文摘要:
      The traditional optimal scheduling method has poor applicability in optimal scheduling of electric vehicles (EVs) for charging route because many parameter variables are uncertain. In view of the problem, uncertain optimization is applied to optimal scheduling of the EVs for charging route. Optimal scheduling model for charging route of the EVs based on random expected value is built. For the disadvantage that the particle swarm optimization algorithm is easy to fall into local optimization and the convergence speed is slow, the simulated annealing algorithm is introduced into the hybrid intelligent algorithm to solve the model. The comparison experiments show that the hybrid intelligent algorithm can effectively reduce the driving distance which the owners reach the charging station, waiting time and charging time at the charging station.
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