基于路网的电动汽车快速充电站布局决策研究

大力发展和推广纯电动汽车已成为全世界众多国家的共同选择。但电动汽车有限的续航能力及公共快速充电设施的缺乏,制约着人们的使用和长途出行。本研究针对我国公共快速充电网络建设亟待完善的问题,基于我国主干高速公路网络,对服务途中充电需求的快速充电站科学分布问题建立分布决策模型。研究表明,对续航能力低于200公里的电动汽车,应用最优策略分布的快速充电站数量从50座增加到250座时,可将途中充电需求覆盖率从50%左右提高到90%以上,而对续航能力超过250公里的电动汽车,150座按最优策略分布的快速充电站即能覆盖至少96.49%的途中充电需求。通过对不同续航能力和不同充电站数量约束下共30种情形的分析,本研究不仅能为多情形下充电站分布问题提供最优选址和数量组合决策方案,也为我国充电基础设施的完善及电动汽车产业可持续发展提供有力的理论支持和政策建议。     

“双积分”政策下汽车制造商生产和电池回收投资策略研究

在一个由新能源汽车制造商、传统能源汽车制造商和消费者三大主要参与者构成的市场中,建立考虑电池回收利用投资和异质消费者效用的Stackelberg博弈模型.求解了企业平均燃料消耗量积分不足、积分平衡和积分富裕三种情形下制造商的最优定价、产量,分析了政府的最优积分政策.研究表明:电池回收率和积分价格是影响新能源汽车和传统能源汽车最优价格与产量的两个关键因素;两个制造商的收益都随着电池回收率的增大而减小,但新能源汽车制造商的收益对电池回收率更敏感;动力电池回收利用生产者责任延伸制对新能源汽车产业发展的作用是双向的,一方面降低了新能源汽车单车收益,另一方面却增大了新能源汽车的需求.     

政府补贴与新能源汽车产业发展——基于系统动力学的演化博弈分析

新能源汽车被视为缓解能源消耗及环境问题的重点项目,成为了战略性新兴产业的一个重点发展目标。为探究在政府补贴策略下的政府、汽车企业以及消费者间的博弈关系,基于系统动力学基础运用演化博弈方法研究了政府补贴与新能源汽车产业发展的关系。从长远来看,政府补贴会削弱企业的核心竞争力,政府对汽车企业的适当惩罚会促进新能源汽车的产业发展。政府应通过建立机动补贴机制并适时增加补贴多样性,完善惩罚机制,加大对新能源汽车产业体系的建设及配套基础设施的投入,以促进新能源汽车产业的持续发展。     

基于遗传算法的快慢充充电站综合布局优化研究

随着能源和环境问题的日益加剧,电动汽车产业逐渐兴起.作为其运营所必须的基础配套服务设施,充电站的布局优化对于处在发展初期的电动汽车大规模推广应用具有重要意义.兼顾建设运营方和电动汽车用户方综合利益,以目标区域内建设快速充电站和慢速充电站综合费用最小化为目标,以满足电动汽车用户最大充电需求,保证用户充电便利性为约束条件,综合考虑地理位置、充电需求等因素建立了多等级电动汽车充电设施选址模型,并利用遗传算法求解模型.最后,算例表明所提出的方法和模型对目标区域电动汽车充电站的优化布局具有一定可行性和合理性.     

考虑交通流量和总成本的电动汽车充电站规划研究

针对目标区域充电桩规划需求问题,在对区域充电需求分析和充电站数量估算的基础上,利用以同心圆的圆周和圆心为站址的充电站选址方法,构建以俘获的车流量与充电站所有成本之比最大的数学规划模型.在此基础上,根据南昌市某区电动汽车数量,确定所需要的充电站数量为4~9个,并规划出六种方案,然后对每一种方案的规划目标值进行计算和比较,得出第三种方案即建设6个充电站为最优方案.研究结果有利于完善城市的交通网络,提升城市电动汽车的运营能力.     

新能源移动充电车路径优化问题研究

在绿色城市背景下,新能源汽车的数量快速增长,现有公共充电设施的不完善使得移动充电服务应运而生。投入运营成本较高而利润低成为阻碍移动充电业务运营的瓶颈之一,如何通过科学合理的调度提高平台利润成为重要问题。本文研究了移动充电车队的调度和路径优化问题,以平台最大收益为目标,综合考虑顾客软时间窗、移动电池容量以及充电车续航里程等约束,建立数学规划模型;设计了一种最大最小蚁群算法,并通过数值实验验证了模型的合理性和算法的有效性,为移动充电企业运营提供决策参考。     

拥塞情形下的电动汽车充电设施选址优化

由于充电汽车充电时间较长,充电设施具有明显的拥塞情形.在假设充电设施容量限制的基础上,研究了在车流量和充电时间随机的情形下,如何对充电设施布局使得充电车满足充电服务的平均数量最大化.在基本截流选址模型的基础上,建立了0-1非线性整数规划,通过选址决策使得截得的平均车流量最大化,并结合贪婪算法和dogleg路径信赖域方法来求解该问题,通过算例表明了算法的有效性.     

电动汽车质保服务与充电设施建设水平对销量影响的有效性研究

通过构建电动汽车和燃油汽车的微分博弈模型，分析电动汽车质保服务与充电设施建设水平对电动汽车销量的影响。研究结果表明：存在质保服务临界点，只有超过临界点情况下，电动汽车厂商才能有效利用增加质保服务投入策略或延长质保期策略促进电动汽车市场销量，并且增加质保服务投入和延长质保期对促进电动汽车市场销量才具有交互正效应；电动汽车厂商无法在较低质保投入水平下通过降低电动汽车故障率实现提高质保服务投入策略有效性，但在质保期内故障次数大于1情况下，可以在较低质保投入水平下通过降低电动汽车故障率实现延长质保期策略有效性；在充电设施建设水平较低时期，电动汽车厂商合作参与充电设施建设比利用质保服务策略能更有效促进电动汽车销量，当充电设施达到一定水平后，再有效利用质保服务策略提高市场销量。     

电动汽车充电设施优化网络布局研究

电动汽车在解决环境污染和能源短缺上扮演着越来越重要的角色为了解决充电站选址定容问题,建立基于Voronoi图方法的充电站选址模型和基于排队论方法的充电桩定容模型,以满足规划区域内的所有充电需求;在此基础上,建立社会总成本最小的优化模型,得到人车桩网最优布局最后实例分析验证规划方法的可行性与合理性,结果表明:充电站为7座时,社会总成本最小,达到923.2万元;充电站位置靠近重心,布局合理,各充电站需配置充电桩数量依次为:14、18、10、19、13、13、13台研究结果有利于完善城市交通系统,为电动汽车管理和充电设施建设提供理论依据.     

电动公交枢纽直流快速充电模式及充电设施最优配置

发展电动公交能减少燃油消耗和城市污染物排放,对改善城市环境具有十分重要的意义.提出一种能显著减少电动公交运营成本的直流快速充电方式及相应的充电设施的建设模式.对公交枢纽直流快速充电模式下电动公交充电服务排队模型、高峰和平峰期充电设施最优配置模型进行了研究,并通过算例验证了这些模型的有效性.研究成果对我国电动公交的充电设施建设具有借鉴意义.     

Optimizing garbage collection vehicle routing problem with alternative fuel-powered vehicles

Abstract

This paper considers the garbage collection problem in which vehicles with multiple compartments are used to collect the garbage. The vehicles are considered to be Alternative Fuel-powered Vehicles (AFVs). Compared with the traditional fossil fuel powered vehicles, the AFVs have limited fuel tank capacity. In addition, AFVs are allowed to refuel only at the depot. We provide a mathematical formulation and develop two solution approaches to solve the problem. The first approach is based on the saving algorithm, while the second is based on the ant colony system (ACS) metaheuristic. New problem instances have been generated to evaluate the performance of the proposed algorithms.     

成渝地区双城经济圈核心城市的博弈分析与对策研究——以交通物流基础设施建设为例

推进成渝地区双城经济圈建设已经上升为国家发展战略.以交通物流基础设施建设为例,从个体理性和团体理性两个方面,对竞争状态、合作状态和混合状态三种情况分别构建博弈关系模型并求解,得出结论:在成渝地区双城经济圈建设交通物流基础设施的过程中,核心城市的个体利益大于团体利益,表现为个体理性与团体理性之间的冲突,即两者存在非合作博弈关系.最后针对核心城市存在的非合作博弈关系,提出促进成渝地区双城经济圈核心城市协同发展的对策建议.     

Minimizing grid capacity in preemptive electric vehicle charging orchestration: Complexity,exact and heuristic approaches

Unlike refueling an internal combustion engine vehicle, charging electric vehicles is time-consuming and results in higher energy consumption. Hence, charging stations will face several challenges in providing high-quality charging services when the adoption of electric vehicles increases. These charging infrastructures must satisfy charging demands without overloading the power grid. In this work, we investigate the problem of scheduling the charging of electric vehicles to reduce the maximum peak power while satisfying all charging demands. We consider a charging station where the installed chargers deliver a preemptive constant charging power. These chargers can either be identical or non-identical. For both cases, we address two optimization problems. First, we study the problem of finding the minimum number of chargers needed to plug a set of electric vehicles giving different arrival and departure times and required energies. We prove that this problem belongs to the complexity class P, and we provide polynomial-time algorithms. Then, we study the problem of minimizing the power grid capacity. For identical chargers, we prove that the problem is polynomial, whereas it is NP-hard in the case of non-identical chargers. We formulate these problems as a mixed-integer linear programming model for both cases. To obtain near-optimal solutions for the NP-hard problem, we propose a heuristic and an iterated local search metaheuristic. Through computational results, we demonstrate the effectiveness of the proposed approaches in terms of reducing the grid capacity.     

基于BP神经网络的行业间中小企业信用评估模型及应用

首先构建了行业间中小企业信用评估指标体系,然后利用安徽省不同行业的800家中小企业调查数据,将其分为训练样本集和测试样本集,对BP神经网络的构造进行讨论,确定BP神经网络的算法,建立起基于BP神经网络的行业间信用评估模型,并代入2003年度全国农业和工业的部分分行业数据进行实证,并对仿真结果做出分析,指出造成农、工行业信用较大差距的原因,并提出加强农业行业信用建设的建议.     

Optimizing the initial setting of complex adaptive systems–optimizing the layout of initial AFVs stations for maximizing the diffusion of AFVs

There are occasions when people want to optimize the initial setting of a CAS (complex adaptive system) so that it evolves in a desired direction. A CAS evolves by heterogeneous actors interacting with each other. It is difficult to describe the evolution process with an objective function. Researchers usually attempt to optimize an intervening objective function, which is supposed to help a CAS evolve in a desired direction. This article puts forward an approach to optimize the initial setting of a CAS directly (instead of through an intervening objective function) by nesting agent‐based simulations in a genetic algorithm. In the approach, an initial setting of a CAS is treated as a genome, and its fitness is defined by the closeness between the simulation result and the desired evolution. We test the applicability of the proposed approach on the problem of optimizing the layout of initial AFV (alternative fuel vehicle) refueling stations to maximize the diffusion of AFVs. Computation experiments show that the initial setting generated with the approach could better induce the desired evolving result than optimizing an intervening objective function. The idea of the approach can also be applied to other decision making associated with a complex adaptive process. © 2015 Wiley Periodicals, Inc. Complexity 21: 275–290, 2016     

VALUING A TIMBER HARVEST CONTRACT AS A HIGH‐DIMENSIONAL AMERICAN CALL OPTION VIA LEAST‐SQUARES MONTE CARLO SIMULATION

Abstract Industrial timberland ownership in the United States has shifted substantially in the last 20 years. Having sold their fee‐owned timberlands, forest products companies relied heavily on the open market for raw timber. To reduce their exposure to market risks, however, forest products companies have been using a number of supply chain instruments, such as timber harvest contracts. As these vehicles become increasingly important to the forest industry, it is necessary and important to determine their economic values. In this study, we treated a 3‐year timber harvest contract on a 30‐year‐old loblolly pine plantation as a high‐dimensional American call option and calculated its value by the least‐squares Monte Carlo simulation technique. The estimated values of such a contract ranged from $1,693/ac to $1,984/ac under two timber price assumptions. With reasonable starting timber prices and strike price in the simulation, random timber prices led to higher contract values. Results from this study can help private landowners, timber brokers, and forest products companies better manage their business risks.     

An arc cover–path-cover formulation and strategic analysis of alternative-fuel station locations

In this study, we present a new formulation of the generalized flow-refueling location model that takes vehicle range and trips between origin–destination pairs into account. The new formulation, based on covering the arcs that comprise each path, is more computationally efficient than previous formulations or heuristics. Next, we use the new formulation to provide managerial insights for some key concerns of the industry, such as: whether infrastructure deployment should focus on locating clusters of facilities serving independent regions or connecting these regions by network of facilities; what is the impact of uncertainty in the origin–destination demand forecast; whether station locations will remain optimal as higher-range vehicles are introduced; and whether infrastructure developers should be willing to pay more for stations at higher-cost intersections. Experiments with real and random data sets are encouraging for the industry, as optimal locations tend to be robust under various conditions.