考虑分时电价和多车型的电动公交行车计划优化

Optimization of Electric Bus Scheduling Considering Time-of-use Electricity Pricing Policy and Multiple Vehicle Types

为最小化电动公交系统的总运营成本,本文提出一种考虑分时电价和多车型的电动公交行车与充电计划的一体化优化模型。该模型同时考虑车次链构建、充电时间窗及充电桩数量等实际运营约束。通过设计自适应大邻域搜索算法(Adaptive Large Neighborhood Search, ALNS)求解车次链,该算法针对多车型下的车次与车型匹配和车次链可行性等问题特性多元化设计可行解的破坏与修复算子。对于ALNS迭代中生成的可行车次链组合,构建分时电价下的充电计划优化子问题,并将其转化到特定的网络图中,设计基于最小费用流的算法求解充电时长,优化决策充电开始时间。选取北京市的3条公交线路验证模型和算法,结果显示,相比于现状,车队规模从30辆减少至24辆,电费成本和运营总成本分别降低了25.84%和20.63%。通过对比实验,探讨不同修复指标权重和车型组合对优化结果的影响。

This paper proposes an optimization model for electric bus scheduling and charging scheduling with the consideration of time-of-use electricity pricing policy and multiple vehicle types,aiming to minimize the total operation cost of electric bus system.The practical operational constraints of bus schedule chain formulation,charging time window,and limited number of chargers are considered in the model.An adaptive large neighborhood search(ALNS)algorithm is proposed to solve the bus schedule optimization problem.This algorithm incorporates diverse destruction and repair operators tailored to the characteristics of the problem,such as the trip-to-vehicle allocation and the feasibility of the bus schedule chain under multiple vehicle types.For the feasible bus schedule chain combinations generated by ALNS,the charging schedule optimization subproblem under time-of-use electricity price is constructed and mapped into a dedicated network.An algorithm based on the minimum-cost-flow is designed to solve for the charging duration,which leads to an optimal decision on charging start time.The model and algorithm are validated using three bus routes in Beijing.The results show that compared with the current situation,the fleet size is reduced from 30 to 24 vehicles,resulting in a decrease in electricity cost and total operation cost by 25.84%and 20.63%,respectively.Comparative experiments are conducted to explore the impact of different weights of repair indicators and combinations of vehicle types on the optimization results.