摘要
随着电动公交车使用的越来越多,公交充电站的电力负荷大增,其优化提上了议事日程。电动公交充电站电力负荷的优化是一个在出车班次、充电桩数量、变压器容量、充电时长和电价计费方式约束下的电费最少问题。针对上述问题,提出计及交通状况的电动公交的优化充电策略。首先考虑车辆排班计划生成可行的充电状态集以及该充电状态上可行的充电计划。然后充分考虑交通状况产生的影响与约束。最后在两部制电价计费基础上建立在交通状况影响下以充电站用电费用最低为目标的优化充电模型。基于真实运营数据,使用粒子群算法对模型进行仿真验证,结果表明所提模型相较于原有在充电成本、负荷峰值有着良好的改善,并且在交通状况升级情况下相较于常规应对方法在削减充电成本和减小负荷峰值也有着比较好的效果。
With the increasing use of electric buses,the power load at bus stations has increased significantly,and its optimization has been put on the agenda.The optimization of the electric power load of the electric bus station is a problem of minimizing the electricity cost under the constraints of the number of trips,the number of charging piles,the capacity of the transformer,the charging time and the electricity price and billing method.Aiming at this problem,an optimized charging strategy for electric buses that takes into account the traffic conditions is proposed.First,the vehicle scheduling plan was considered to generate a set of feasible charging states and a feasible charging plan on the state of charge.Then,the impact and constraints of the traffic conditions were fully considered.Finally,based on the two-part electricity price billing,an optimized charging model was established under the influence of the traffic condi-tions with the goal of the lowest electricity cost of the charging station.Based on real operating data,the particle swarm algorithm was used to simulate and verify the model.The results show that the proposed model has a good im-provement in charging costs and load peaks compared to the original,and compared with conventional response meth-ods under the escalation of traffic conditions.Cutting down the cost of charging and reducing the peak load also has a bettereffect.
作者
何鑫
孙国歧
魏晓宾
蔡旭
HE Xin;SUN Guo-qi;WEI Xiao-bin;CAI Xu(College of Information Science and Technology,Donghua University,Shanghai 201620,China;Shandong Deyou Electric Co.,Ltd.,Zibo Shandong 255088,China;College of Electronic Information and Electrical Engineering,Shanghai Jiaotong University,Shanghai 200240,China)
出处
《计算机仿真》
北大核心
2023年第6期138-146,共9页
Computer Simulation
基金
国家自然科学基金重点项目(51837007)
山东省重点研发计划(重大科技创新工程)(2019JZZY020804)。
关键词
电动公交
电动公交充电站
粒子群算法
交通指数
Electric bus
Electric bus charging station
Particle swarm optimization
Traffic performance index
