基于加权Voronoi 图和GA-PSO的电动汽车充电站最优规划

考虑到电动汽车的普及,对充电站的需求越来越大,合理规划充电站是保证快速发展电动汽车的一项重要举措。根据某地区现有电动汽车的保有量,考察电动汽车的集中充电所需最大负荷,结合市场充电站的固定建设成本、运维成本、用户充电途中的耗时成本以及电池配送成本,综合考虑上述几种主要成本因素,以总成本最小为目标函数,建立充电站的规划模型。将交叉操作引入到PSO算法中,加强了PSO算法后期的寻优能力,通过采用加权Voronoi图和GA-PSO算法对模型进行计算。结果表明,在结合了多种成本并考虑用户需求的情况下,能够使得规划方法达到最优。     

考虑交通流量的电动汽车充电站优化规划方法

城市电动汽车保有量快速增长使充电站优化规划问题日益受到配电网规划领域的广泛关注。综合考虑城市交通流量空间分布特征与配电网络运行约束,提出了一种基于交通流量空间分布的公共充电站优化规划方法。首先建立城市交通流量分布单元模型,构建城市交通流量样本空间,用局部流量密度分析充电站服务范围内交通流量,用分布间距分析总体布局均衡性。然后以每个充电站周围具有较大交通流量密度、充电站站点分布均衡同时最优构建目标函数,结合城市交通流量分布和电动汽车保有量分析充电容量约束,基于充电容量分析电网运行潮流和电压偏移约束,采用聚类算法搜索发现局部流量密度和分布间距峰值,进行优化迭代,实现考虑交通流量的电动汽车充电站优化规划。最后以某规划区域为例,证明了该方法可为电动汽车充电站的优化规划提供依据。     

考虑安全效能成本的电动汽车充电站多目标规划方法

近年来,随着电动汽车的不断增多,其充电需求给配电网的规划和运行带来了一系列的问题。为解决这一问题,该文提出一种考虑安全效能成本的配电网充电站多目标规划方法。首先,构建考虑电压质量的配电网安全效能成本指标体系,然后在此基础上构建充电站规划模型,并采用向量序优化算法进行求解。最后通过基于25节点交通系统和IEEE33节点配电网系统的算例验证了该模型和算法的有效性和可行性。     

基于多源数据的电动汽车充电设施布局优化方法研究

针对电动汽车充电设施布局与电动汽车用户需求平衡性问题,提出了一种基于多源数据的电动汽车充电设施布局优化方法。首先,基于兴趣点位置、用户产生充电需求时的地点、需求偏好等多源数据构建电动汽车充电站双层布局优化模型。上层模型以社会总成本为目标函数对电动汽车充电站进行选址定容优化;下层模型以寻址距离、寻址时间、拥挤程度3个指标搭建用户最佳选择模型;然后,利用遗传算法对双层规划模型进行求解,获得电动汽车充电站布局优化方案。最后,通过实例验证了所提方法的可行性。     

面向用户需求的电动汽车充电站最优规划模型研究

考虑到用户出行的便捷和充电站运营商的利益,提出一种电动汽车充电站最优规划模型。该模型充分考虑电动汽车用户的出行需求和选择决策行为,同时还给出基于改进的免疫遗传算法的模型求解算法。以某市城区为例,利用MATLAB仿真,验证模型及算法的有效性。研究结果表明,由该模型求得的充电站建设方案能够有效地减少用户充电过程中的绕行距离,缩短耗费的时间,保证充电站的利用率及覆盖率;同时,还能提高充电站运营商的收益。     

计及分时电价及交通情况的电动汽车最优出行路径规划算法

随着电动汽车的普及,电动汽车的车主们对于出行路径规划的需求日益增加。一种计及分时电价及交通工况的电动汽车最优出行路径规划算法,通过出行路径上的充电站电价及道路交通情况,构建道路简化模型和最优路径规划模型,实现实时的电动汽车最优路径规划。该算法可实际应用于电动汽车的智能终端上,引导用户经济可靠地驾车出行。     

EV充电站选址定容及基于蚁群算法概念的建设规划方案研究

随着各类新能源汽车的不断普及,服务于大规模电动汽车(EV)的配套充电设施也同步进行建设。提出了基于实际环境条件及用户实际需求的充电桩选址定容方案,能够应用于电动汽车充电站建设的实际规划。提出基于蚁群算法概念的充电站时序建设规划算法,通过对计划建设的充电站进行重要程度评估,为决策人员提供充电站建设顺序的建议。通过仿真验证规划方案的可行性和有效性,提供充电站规划综合方案。     

基于两阶段优化模型的电动汽车充电站放电策略

随着电动汽车的普及,合理制定其充放电策略,实现主动配电网和充电站的双赢成为电动汽车负荷并网的研究重点,为此提出一种充电站充放电计划的两阶段优化模型.该模型综合考虑了主动配电网和充电站双方的利益,并计及了电动汽车实际负荷与预测负荷不符的情况.在日前优化阶段,以成本分析为基础,采用Nash谈判法求解配电网和充电站的多目标优...     

考虑用户价格需求响应的光-储充电站容量配置与定价方法研究

考虑基于价格的用户行为选择,提出一种计及用户价格型需求响应的光-储充电站容量配置与定价方法,分别以充电站运营商和电动汽车用户为上、下2层问题的主体,建立双层优化规划模型.利用线性化方法和KKT条件将问题转化为单层混合整数线性规划.最后,为了验证所提模型的有效性,通过算例分析得出规划运行方案,对比不同方案,结果表明通过制...     

基于分布鲁棒联合机会约束的光储充电站滚动优化调控模型

随着电动汽车的普及和清洁能源装机容量的日益增加,光储充电站展现出广阔的应用前景。针对电动汽车随机接入影响下光储充电站功率难以精准调控的问题,提出基于分布鲁棒联合机会约束（DRJCC）的光储充电站滚动优化调控模型。将基于混合整数规划（MIP）的精确DRJCC模型、基于CVaR-Slim凸松弛的DRJCC模型、基于Bonferroni不等式的DRJCC模型进行对比,通过算例分析验证了所提优化调控模型的有效性。算例分析表明,所提基于CVaR-Slim凸松弛的DRJCC模型能够同时满足更多电动汽车的充电需求。     

Dynamic planning and energy management strategy of integrated charging and hydrogen refueling at highway energy supply stations considering on-site green hydrogen production

The layout of electric vehicles charging stations and hydrogen refueling stations (HRSs) is more and more necessary with the development of electric vehicles (EVs) and progress in hydrogen energy storage technology. Due to the high costs of HRSs and the low demand for hydrogen, it is difficult for independent HRSs to make a profit. This study focuses on the dynamic planning of energy supply stations on highways in the medium and long term, considering the growth of EV charging demand and the change in the proportion of hydrogen fuel cell vehicles (HFCVs). Based on the perspective of renewable energy generators (REGs), this study seeks the dynamic optimal configuration and comprehensive benefits of adding HRS and battery to existing EVCS considering the travel rules of new energy vehicles (NEVs). The results show that (1) It is profitable for REGs to invest in HRSs; (2) The economy of investment in batteries by REGs depends on the source-load matching. It is feasible only when the output of renewable energy is difficult to meet the demand. (3) The business model of REGs producing hydrogen on-site and supplying both electricity and hydrogen is feasible.     

基于智能电网的电动汽车充放电分时电价及引导策略

为了以绿色、环保能源满足全球可持续发展的需求,可再生能源和电动汽车在全球范围内受到广泛推崇.在此情形下,高比例可再生能源发电和大规模电动汽车无序分散接入电网必将导致供求曲线的不稳定.为此,借助云存储技术和智能电网,提出了一种基于供求曲线的电动汽车充放电分时电价,并在制定充放电价格时考虑充电站的空闲率.以实现充电站和用户...     

Simultaneous planning of plug-in hybrid electric vehicle charging stations and wind power generation in distribution networks considering uncertainties

Recently, plug-in hybrid electric vehicles (PHEV) are becoming more attractive than internal combustion engine vehicles (ICEV). Hence, design and modeling of charging stations (CSs) has vital importance in distribution system level. In this paper, a new formulation for PHEV charging stations is presented with the strategic presence of wind power generation (WPG). This study considers constraints of the system losses, the regulatory voltage limits, and the charge/discharge schedule of PHEV based on the social behavior of drivers for appropriate placement of PHEV charging stations in electricity grid. The role of CSs and WPG units must be correctly assessed to optimize the investment and operation cost for the whole system. However, the wind generation owners (WGOs) have different objective functions which might be contrary to the objectives of distribution system manager (DSM). It is assumed that aggregating and management of charge/discharge program of PHEVs are smartly carried out by DSM. This paper presents a long-term bi-objective model for optimal planning of PHEV charging stations and WPG units in distribution systems which simultaneously optimize two objectives, namely the benefits of DSM and WGO. It also considers the uncertainty of load growth, electricity price and PHEV access to the charging station using Mont-Carlo simulation (MCS) method. Initial state of charge uncertainty is also modeled based on scenario approach in PHEV batteries and wind turbine power generation using weibull distribution. Non dominated sorting genetic algorithm (NSGA-II) is used to solve the optimization problem. The simulation has been conducted on the nine-bus system.     

Regulatory framework and business models for charging plug-in electric vehicles: Infrastructure,agents, and commercial relationships

Electric vehicles (EVs) present efficiency and environmental advantages over conventional transportation. It is expected that in the next decade this technology will progressively penetrate the market. The integration of plug-in electric vehicles in electric power systems poses new challenges in terms of regulation and business models. This paper proposes a conceptual regulatory framework for charging EVs. Two new electricity market agents, the EV charging manager and the EV aggregator, in charge of developing charging infrastructure and providing charging services are introduced. According to that, several charging modes such as EV home charging, public charging on streets, and dedicated charging stations are formulated. Involved market agents and their commercial relationships are analysed in detail. The paper elaborates the opportunities to formulate more sophisticated business models for vehicle-to-grid applications under which the storage capability of EV batteries is used for providing peak power or frequency regulation to support the power system operation. Finally penetration phase dependent policy and regulatory recommendations are given concerning time-of-use pricing, smart meter deployment, stable and simple regulation for reselling energy on private property, roll-out of public charging infrastructure as well as reviewing of grid codes and operational system procedures for interactions between network operators and vehicle aggregators.     

Design scheme for fast charging station for electric vehicles with distributed photovoltaic power generation

The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of “rationalization, modularization and intelligentization” of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.     

Electric,plug-in hybrid,hybrid, or conventional? Polish consumers’ preferences for electric vehicles

Poland aims at stimulating the market to reach a target of 50,000 plug-in and battery electric vehicles by 2020. However, as in other Eastern European countries, the market penetration stays very low. In Poland, there were only 475 battery electric vehicles and 514 plug-in electric vehicles registered in 2017. To identify effective support measures, this paper examines the preferences of Polish consumers for three types of electric vehicles: battery, hybrid, and plug-in hybrid vehicles. We use a discrete choice experiment to estimate the willingness to pay of a representative sample of consumers intending to buy a car in Poland. We find that electric vehicles are significantly less preferred than conventional cars, even under a public programme that would enable slow-mode charging in places where respondents usually park. We quantify the marginal willingness to pay for increasing the driving range, reductions in charging time, the availability of fast-mode charging stations, and the provision of policy incentives. The novelty of the paper lies in presenting a scenario with the slow-mode and availability of several levels of fast-mode charging stations and examination of the extent to which the heterogeneity of consumer preferences is driven by place of residence (urban, suburban, rural), intention to buy a new versus a used car, and the annual mileage. This is also the first discrete choice experiment on electric vehicles conducted in Eastern Europe. To stimulate the electric vehicle market, we recommend a pricing policy that affects the operating costs and other incentives along with an effective up-front price incentive scheme.     

智能电网框架下电动汽车充电设施建设研究

电动汽车是解决能源和环境问题的重要手段之一,电动汽车充电设施是发展电动汽车所必须的重要配套基础设施。随着智能电网建设的推进及电动汽车的推广,电动汽车作为分散储能单元,成为智能电网的重要组成部分,必须将其纳入到智能电网建设的统一规划中。分析了电动汽车充电设施建设状况,影响因素,探讨了充电设施建设原则,提出了充电设施建设方案,并进行了风险评估。     

Smart management of distinct plug‐in hybrid electric vehicle charging stations considering mobility pattern and site characteristics

Management of plug‐in hybrid electric vehicles (PHEVs) is an important alternative energy solution to accord the prevailing environmental depletion. However, adding PHEVs to the existing distribution network may stimulate issues such as increase in peak load, power loss, and voltage deviation. Addressing the aforementioned issues by incorporating distinct mobility patterns together will develop an attractive energy management. In this paper, suitable location of the charging station is presented for a novel 2‐area distribution system following distinct mobility patterns. A comprehensive study by considering the optimal, midst, and unfit site for placing the charging station is incorporated. For managing the charging sequence of PHEVs, a meta‐heuristic solving tool is developed. The main contribution of this programming model is its ability to schedule the vehicles simultaneously in both the areas. The efficiency of the proposed energy management framework is evaluated on the IEEE 33‐bus and IEEE 69‐bus distribution systems. The test system is subjected to different scenarios for demonstrating the superior performance of the proposed solving tool in satisfying the convenience of vehicle owner along with reducing the peak demand. The results show that charging at low electricity price period and discharging at high electricity price period enables the minimum operational cost.     

Optimal charging of electric drive vehicles in a market environment

With a potential to facilitate the integration of renewable energy into the electricity system, electric drive vehicles may offer a considerable flexibility by allowing for charging and discharging when desired. This paper takes the perspective of an aggregator that manages the electricity market participation of a vehicle fleet and presents a framework for optimizing charging and discharging of the electric drive vehicles, given the driving patterns of the fleet and the variations in market prices of electricity. When the aggregator is a price-taker the optimization can be stated in terms of linear programming whereas a quadratic programming formulation is required when he/she has market power. A Danish case study illustrates the construction of representative driving patterns through clustering of survey data from Western Denmark and the prediction of electricity price variations through regression on prices from the Nordic market. The results show that electric vehicles provide flexibility almost exclusively through charging. Moreover, the vehicles provide flexibility within the day but only limited flexibility from day to day when driving patterns are fixed.     

Optimal dispatch of hydrogen/electric vehicle charging station based on charging decision prediction

The hydrogen/electric vehicle charging station (HEVCS) is widely regarded as a highly attractive system for facilitating the popularity of hydrogen and electric vehicles in the future. However, conventional optimal dispatch of HEVCS could lead to poor performance due to the lack of adequate consideration of vehicle charging decision behaviours and neglection of the impacts of different information sources on it. This paper investigates a charging demand prediction method that considers multi-source information and proposes a multi-objective optimal dispatching strategy of HEVCS. First, an information interaction framework of integrated road network, vehicles and HEVCS is introduced. Road network model and HEVCS model are established based on the proposed framework. To improve the flexibility of dispatch, two charging modes are designed, which are intended to guide drivers to adjust their consumption behaviour by electricity price incentives. Furthermore, psychologically based hybrid utility-regret decision model and Weber-Fechner (W–F) stimulus model are developed to reasonably predict drivers' choice of charging stations and charging modes. The daily revenue of HEVCS and the total queuing time of drivers are the objective functions considered in this paper simultaneously. The above multi-objective optimization results that the proposed strategy can effectively improve the benefits of HEVCS and reduce energy waste. Additionally, this paper discusses the results of a sensitivity analysis conducted by varying incentive discount, which reveals the combined benefits of the HEVCS and the vehicles are effectively increased by setting reasonable incentive discounts.