基于分时充电电价的电动汽车消纳风电的机组调度优化模型

随着风电的大规模入网,其间隙性和随机性导致弃风现象严重,电动汽车的快速发展为风电消纳提供了新途径。文章以风电消纳最多、负荷方差最小和火电机组发电成本最低为目标函数,综合考虑电力系统的功率供需平衡、火电机组和风电出力等约束条件,建立了基于分时充电电价的电动汽车消纳风电的机组调度优化模型。根据电动汽车负荷对充电电价的响应,得出电动汽车的充电负荷,进而得到电力系统总负荷,以此为基础采用分步优化的方法对模型进行求解。首先以负荷方差最小和风电消纳最多为目标,通过多目标遗传算法NSGA-II对风电出力进行优化;然后以火电机组的发电成本最低为目标对火电机组的出力进行优化,达成风火机组的联动调度。算例结果表明,对电动汽车实行分时充电电价能够提升风电的消纳能力,平滑负荷曲线,降低火电机组的发电成本。     

配电网内电动汽车充电管理技术研究

电动汽车的普及,聚合商将在区域电动汽车充电管理中扮演重要角色。针对配电网内大量电动汽车接入电网充电的问题,提出了一种基于多代理技术的电动汽车充电分层管理策略,并详细阐述了各代理的具体设计和协作机制。其优化充电模型以聚合商的利益最大化为目标、考虑用户充电需求和配电网安全的约束条件,依次采用初次优化、考虑安全约束的再次优化以及越限之后的削减算法进行求解,并采用IEEE配电网33节点算例进行仿真和分析。研究结果表明,该充电控制策略可以较好地响应电网电价,提高电动汽车聚合商的收益,同时可以有效地解决配电网安全越限问题,平滑负荷曲线。     

基于V2G的配电网负荷优化策略研究

基于电动汽车与电网互动（V2G）系统,提出一种电动汽车参与配电网负荷优化调节的分析模型。设计了V2G参与负荷调节的控制系统框架,以配电网负荷曲线波动方差最小为目标,考虑电动汽车用户的充电需求、动力电池的充电约束和传输线的功率约束构建了优化分析模型,并采用遗传算法（GA）分析计算,获得负荷优化后的负荷曲线和电动汽车的充放电时间。实例仿真验证了该优化控制法的有效性。     

分布式电源电动汽车充电站储能系统电价分析

含分布式电源的电动汽车充电站的可再生能源供给常常小于电动汽车充电负荷,须要配电网辅助补充部分电能,不利于配电网的稳定运行。文章提出基于微电网内不平衡率的充电站储能系统的电能与电网电能联动策略。考虑配电网有峰、谷、平3种电价,故将充电站储能系统SOC分成3部分与之相对应,根据微网内可再生能源实时出力与负荷求出不平衡率U_R。当充电出现缺额时,由充电站储能系统和电网以不平衡率为比例协同补充充电缺额,实现了微电网内的能源协调控制。文章采用蒙特卡洛方法模拟电动汽车负荷,通过对比不同用户响应度的配电网等效负荷和充电站储能系统SOC,验证了该策略在微电网运行优化的有效性。该策略充分发挥了充电站储能系统和电网的联合运行优势,减小了电网负荷峰谷差,优化了电网负荷曲线。     

计及电动汽车入网的风火机组利益优化分析模型

以风电场利润最大、负荷方差最小和火电机组利润最大为目标函数,综合考虑电力系统的功率需求平衡、火电机组和风电场出力等约束条件,建立了基于风电消纳的计及电动汽车入网的风火机组利益优化分析模型。首先根据车主的行驶习惯通过蒙特卡罗模拟获得电动汽车的日充电功率,以此为基础通过多目标遗传算法NSGA-II对火电机组和风电出力进行优化。算例结果表明,对电动汽车进行有序充电能够提高风电的消纳水平,提高风火电机组的整体利润。     

分时电价下大用户直接消纳风电优化模型

风电出力与负荷需求的不协调性导致弃风现象时有发生,实行分时电价和引导大用户直接消纳风电可以优化弃风问题解决方案。文章建立了分时电价下大用户直接消纳风电时火电、风电、大用户3方的收益模型;建立了考虑火电、风电、大用户3方约束条件下的系统利益优化模型;以利益最大和弃风最小为目标,对提出的算例进行优化,表明大用户与分时电价双途径可以优化风电消纳,同时需要考虑合理的弃风,以使各方利益均衡。算例分析验证了所提出模型的有效性和适用性,表明该模型对风电与需求侧组合调度策略具有一定的参考价值和指导作用。     

源、网、荷三方利益最优的电动汽车充放电双层优化调度

电动汽车的无序充电会造成电网过负荷,影响电网的安全运行。文章基于分时电价机制和电动汽车的入网特性,考虑源、网、荷三方利益。在时间调度上,以负荷波动最小、用户花费最低为优化目标;在空间调度上,以负荷接入后发电厂燃料费用最低、配电网网损最小为优化目标。采用自适应变异率遗传算法及非线性规划寻优得到,电动汽车充放电时空双层调度计划,仿真验证了模型有效性。     

考虑分时电价和系统峰谷差动态约束的电动汽车有序充电策略

大规模电动汽车并网充电需要同时考虑聚合效应的经济效益和其对电力系统的影响。以电动汽车用户充电费用最优为目标,在考虑充电时间、并行充电汽车数量等传统约束的基础上,结合分时电价与实际负荷曲线,将充电行为对峰谷差和负荷波动的影响作为约束条件,提出了一种新的电动汽车充电行为有序充电策略。基于该策略,利用蒙特卡洛方法模拟了电动汽车用户行为,对比分析了分时电价环境下电动汽车无序充电和有序充电对电网负荷曲线的影响。仿真结果表明:考虑峰谷差和负荷波动约束,通过电动汽车实时响应分时电价,可避免大量电动汽车集中充电而产生新的负荷高峰,且在显著降低电动汽车充电费用的同时,可以实现平滑负荷波动并减少系统的峰谷差。     

考虑电动汽车碳配额及需求响应的电力系统调度研究

为深化电动汽车在降低交通系统碳排放、促进清洁能源高比例消纳的良好作用,该文构建了以电动汽车充电成本最小和电力系统发电成本最低为目标的优化调度模型。模型以电动汽车无序充电场景为基础,并进一步探究碳配额和需求响应协同作用对电动汽车用能成本和系统发电调度的影响。仿真算例结果表明,赋予电动汽车碳配额有利于加强用户的充电响应程度。协同调度在减少电动汽车充电成本、提升清洁能源消纳水平、平抑负荷波动等方面具有更显著的优化效果。     

基于用户需求的居民小区电动汽车充放电优化控制策略

文章提出了一种考虑用户需求和利益的居民小区电动汽车有序充放电策略。该策略基于分时电价机制,对现有负荷模型进行优化,并建立新的用户需求和利益模型;采用莫楞贝突变遗传算法求解每辆电动汽车的最优充放电时间;采用蒙特卡洛模拟法做出相应负荷曲线;以某个小区为例进行算例计算和分析验证。研究结果表明,该方法可防止变压器过载,其峰谷差率比无序充电降低了24.95%,用户平均充电成本降低了50%。     

小功率风力充电控制器

介绍了一种小功率风力充电控制器。相对于传统的基于Boost变换器的充电方式,该控制器有效地降低了损耗,能更加充分地利用风能;在风速较低时,通过Boost斩波器将整流输出电压升至一定值,再送至后级电路;当风速较高时,切断Boost电路,将整流输出电压直接送到后级给蓄电池充电。经过300 W风力充电系统的实验,验证了其设计的正确性。     

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.     

Reliability evaluation and analysis for NEV charging station considering the impact of charging experience

Battery electric vehicles (BEVs) and hydrogen fuel cell vehicles (HFCVs) will predominate in near future, and the new energy vehicle (NEV) charging station which provides charging services for aforementioned NEVs could grow rapidly. The reliability of the NEV charging station would be the primary concern for early construction and NEV users. This study investigates the reliability evaluation of NEV charging station considering the impact of charging experience and analyzes the influence of various factors by comparing the evaluation results. The explicit modelling of the station considering power generation system, coupling devices and hydrogen storage is presented and an optimal revenue model is established to coordinate the operation of the station. A reliability index system is established to evaluate the charging reliability of the NEV charging station and reflect the charging experience. In addition, an amount model estimating the number of vehicles accessed in the coming days is proposed to address the impact of driver charging experience on the reliability evaluation. The results show that it is necessary to consider the charging experience in reliability evaluation. The comparison and analysis of reliability evaluation results reveal that the charging reliability and profit of the charging station are influenced by the initial hydrogen in tank, the price of hydrogen/electricity and the sizes of electrolyzer, hydrogen tank and fuel cell. The reliability evaluation provides guidance for determining the parameters of these factors.     

Impact of charging efficiency variations on the effectiveness of variable-rate-based charging strategies for electric vehicles

The huge energy demand coming from the increasing diffusion of plug-in electric vehicles (PEVs) poses a significant challenge to electricity utilities and vehicle manufacturers in developing smart charging systems interacting in real time with distribution grids.These systems will have to implement smart charging strategies for PEV batteries on the basis of negotiation phases between the user and the electric utility regarding information about battery chemistries, tariffs, required energy and time available for completing the charging. Strategies which adapt the charging current to grid load conditions are very attractive. Indeed, they allow full exploitation of the grid capacity, with a consequent greater final state of charge and higher utility financial profits with respect to approaches based on a fixed charging rate.The paper demonstrates that the charging current should be chosen also taking into account the effect that different charging rates may have on the charging efficiency. To this aim, the performances of two smart variable-rate-based charging strategies, taken as examples, are compared by considering possible realistic relationships between the charging efficiency and the charging rate. The analysis gives useful guidelines for the development of smart charging strategies for PEVs as well as for next-generation battery charging and smart grid management systems.     

Energy-storage configuration for EV fast charging stations considering characteristics of charging load and wind-power fluctuation

Fast charging stations play an important role in the use of electric vehicles (EV) and significantly affect the distribution network owing to the fluctuation of their power. For exploiting the rapid adjustment feature of the energy-storage system (ESS), a configuration method of the ESS for EV fast charging stations is proposed in this paper, which considers the fluctuation of the wind power as well as the characteristics of the charging load. The configuration of the ESS can not only mitigate the effects of fast charging stations on the connected distribution network but also improve its economic efficiency. First, the scenario method is adopted to model the wind power in the distribution network, and according to the characteristics of the EV and the driving probability, the charging demand of each station is calculated. Then, considering factors such as the investment cost, maintenance cost, discharging benefit, and wind curtailment cost, the ESS configuration model of the distribution network is set up, which takes the optimal total costs of the ESS for EV fast charging stations within its lifecycle as an objective. Finally, General Algebraic Modelling System (GAMS) is used to linearize and solve the proposed model. A simulation on an improved IEEE-69 bus system verifies the feasibility and economic efficiency of the proposed model.     

Fast charging nickel-metal hydride traction batteries

This paper describes the fast charge ability, or “fast rechargeability”, of nominal 85 Ah Ni–MH modules under various fast charge conditions, including constant current (CC); typically 1-3C, and constant power (CP) regimes. Our tests revealed that there is no apparent difference between CC and CP fast charge regimes with respect to charge efficiency and time. Following the USABC Electric Vehicle Battery Test Procedures Manual (Revision 2, 1996), we demonstrated that we were able to return 40% state of charge (SOC) from 60% depth of discharge (DOD) to 20% DOD within 15 min. Most importantly, we found that the internal pressure of the cell is the most critical parameter in the control of the fast charge process and the safe operation of the modules.     

Electric vehicle charging infrastructure in Poland

This article describes the current state of development and future direction in the market for electric vehicles in Poland, with respect to the charging infrastructure. The authors have concentrated above all on the assumptions and results of ventures to-date in this field. There has also been conducted an analysis of the influence of electric vehicle development, in part concerning the charging infrastructure, on the Polish power system. In addition, this article outlines the potential for using electric vehicle charging terminals, in developing Semi Smart systems at the level of low-voltage distribution grids.     

Solar photovoltaic charging of lithium-ion batteries

Solar photovoltaic (PV) charging of batteries was tested by using high efficiency crystalline and amorphous silicon PV modules to recharge lithium-ion battery modules. This testing was performed as a proof of concept for solar PV charging of batteries for electrically powered vehicles. The iron phosphate type lithium-ion batteries were safely charged to their maximum capacity and the thermal hazards associated with overcharging were avoided by the self-regulating design of the solar charging system. The solar energy to battery charge conversion efficiency reached 14.5%, including a PV system efficiency of nearly 15%, and a battery charging efficiency of approximately 100%. This high system efficiency was achieved by directly charging the battery from the PV system with no intervening electronics, and matching the PV maximum power point voltage to the battery charging voltage at the desired maximum state of charge for the battery. It is envisioned that individual homeowners could charge electric and extended-range electric vehicles from residential, roof-mounted solar arrays, and thus power their daily commuting with clean, renewable solar energy.     

Economic valuation of green hydrogen charging compared to gray hydrogen charging: The case of South Korea

The South Korean government promotes hydrogen-powered vehicles to reduce greenhouse gas (GHG) emissions but these vehicles use gray hydrogen while charging, which causes GHG emissions. Therefore, converting this fuel into green hydrogen is necessary to help reduce GHG emissions, which will incur investment costs of approximately USD 20 billion over a decade. In this study, a contingent valuation method is applied in an analysis to examine the extent to which consumers are willing to pay for green hydrogen charging compared to gray hydrogen charging. The results indicate that the monthly mean of willingness to pay per driver is 51,674 KRW (USD 45.85), equivalent to 4302 KRW per kg (USD 3.82). Additionally, consumers accept a 28.5% increase in the monthly average fuel expenses when converting to green hydrogen. These findings can be used in the development of pricing and energy use plans to finance the expansion of green hydrogen infrastructure.