A multi-objective optimization problem for allocating parking lots in a distribution network

This paper presents a multi-objective approach to determine optimal site and size of parking lots, which provide vehicle to grid (V2G) power in distribution system as new type of distributed generations (DGs). In this approach, the reliability of distribution system and power losses along with investment cost are considered in optimization problem. This optimization problem is solved using genetic algorithm (GA) method. Simulation study is carried out on a nine bus test system. The results of simulations show that the economic issue of parking lots installation depends on many factors such as availability of electric vehicles (EVs) as well as the electricity price. Also, it is shown that by taking enough incentive for EVs owners, optimal sitting and sizing of parking lots has economical benefit for distribution system companies. Also, optimal allocation of parking lots can improve the distribution system voltage profile.     

The impact of vehicle-to-grid on the distribution grid

Plug-in hybrid electric vehicles (PHEVs) can be connected to the power grid. The power flow of this connection can be bidirectional, so vehicles can charge and discharge. This vehicle-to-grid option can aid to improve grid efficiency and reliability. A simulation covering an entire day is essential to obtain an accurate assessment of the impact of PHEVs. It is important to know when, statistically, vehicles are available for charging or discharging. In this work is shown that uncoordinated charging of PHEVs in distribution grid can lead to local grid problems. Therefore, coordinated charging and discharging is investigated and a voltage constraint is implemented. These vehicles can support the grid in terms of voltage control and congestion management. In that way, the distribution grid can handle more PHEVs without reinforcements. Distributed generation units are more common nowadays in the distribution grid with some of these generation units based on intermittent renewable resources. This paper shows that there could be a good combination with PHEVs as they can provide storage to take care of the excess of produced energy and use it for driving or release it into the grid at a later time. In that way, consumption and generation are more efficiently matched.     

Economic evaluation of charging/discharging control of electric vehicles as system flexibility considering control participation rate

In Japan, installed capacity of variable renewable generation (VRG) is rapidly increasing. Through the efforts to make VRG into one of main power resource, vehicle-to-grid (V2G) is considered as an effective source of flexibility, which is concerned to lack under large amount of VRG. In this study, we analyze the cost reduction effect of using V2G as system flexibility through calculation of day-ahead unit commitment (UC) in Kyushu area. To consider uncertainty of day-ahead UC, we calculate UC simulation with operation reserve requirement considering day-ahead forecast error of photovoltaic generation, followed by economic dispatch simulation using actual photovoltaic generation. V2G as LFC reduces operation cost especially when demand is low, even with 180 000 electric vehicles (EVs). Cost reduction per EV is about 20-80 JPY/day with 180 000 EVs, which saturates if more EV participates in the control. V2G as operation reserve reduces discharge from EV for about 0.5-1.5 kWh/day/EV, which results in reducing degradation of EV battery.     

Economic analysis of unit commitment with distributed energy resources

Classic unit commitment (UC) is an important and exciting task of distributing generated power among the committed units subject to several constraints over a scheduled time horizon to obtain the minimum generation cost. Large integration of distributed energy resources (DERs) in modern power system makes generation planning more complex. This paper presents the individual and collective impact of three distributed energy resources (DERs), namely, wind power generator as a renewable energy source, plug-in electric vehicles (PEVs) and emergency demand response program (EDRP) on unit commitment. In this paper, an inconsistent nature of wind speed and wind power is characterized by the Weibull probability distribution function considering overestimation and underestimation cost model of the stochastic wind power. The extensive economic analysis of UC with DERs is carried out to attain the least total cost of the entire system. To obtain the optimum solution, Teaching–learning based optimization (TLBO) algorithm is employed to solve the unit commitment problem considering IEEE standard 10 unit test system in this study. It is found that the combined effect of wind power generator, plug-in electric vehicles and emergency demand response program on UC significantly lessen the total cost of the system.     

A solution to the ramp rate and prohibited operating zone constrained unit commitment by GHS-JGT evolutionary algorithm

Unit commitment (UC) problem on a large scale with the ramp rate and prohibited zone constraints is a very complicated nonlinear optimization problem with huge number of constraints. This paper presents a new hybrid approach of ’Gaussian Harmony Search’ (GHS) and ’Jumping Gene Transposition’ (JGT) algorithm (GHS-JGT) for UC problem. In this proposed hybrid GHS-JGT for UC problem, scheduling variables are handled in binary form and other constants directly through optimum conditions in decimal form. The efficiency of this method is tested on ten units, forty units and hundred units test system. Simulation results obtained by GHS-JGT algorithm for each case show a better generation cost in less time interval, in comparison to the other existing results.     

考虑分布式光伏和电动汽车接入的配电网空间负荷预测方法

针对大规模分布式光伏和电动汽车接入配电网对空间负荷预测影响的问题,提出一种考虑远景年屋顶分布式光伏饱和安装、大规模电动汽车参与V2G的城市配电网空间负荷预测方法。区分不同小区,依据相应的容积率和可利用率系数计算屋顶光伏饱和安装面积,结合历史辐射值数据计算光伏出力。基于改进型停车生成率模型预测停车需求,结合日行驶里程、停车特性和充放电策略,建立电动汽车V2G负荷预测模型,利用蒙特卡罗仿真得出V2G负荷时空分布情况。采用改进型负荷密度指标法,实现对考虑时序的配电网传统日负荷的预测。以某规划区为例,预测结果表明:屋顶分布式光伏和电动汽车V2G对配电网空间负荷预测结果影响较大,且对不同小区负荷影响的程度不同。     

含可入网电动汽车（V2G）和分布式电源的配电网优化规划

考虑配电网中可入网电动汽车（V2G）、负荷和分布式电源（DG）输出功率的波动性,进行配电网优化规划。以协调配电公司和分布式电源投资商（包括V2G）两者的利益为出发点,引入V2G和DG的发电环境效益作为协调因子;以配电公司和投资商总费用最小为目标函数,采用计及V2G和DG的配电网随机潮流计算结果进行约束条件的检验,建立了基于机会约束规划模型的含V2G和DG的配电网随机规划数学模型。应用基于混合编码的改进自适应遗传算法对模型进行了求解。算例结果表明,通过优化模型所建的配电网网架,能更好地接纳V2G的前提下取得最优经济性,并且协调配电公司与V2G和DG投资商之间利益。     

基于DILAUX的地下车库LED照明设计

目前由于汽车的广泛普及,对城市的地下车库照明提出了更多的要求,但随着新一代照明光源LED照明技术进一步的发展与完善,使得地下车库照明有了更节能、更环保、更经济的可能。往DILAUX中建模57×33．3m^2的中型地下车库,并利用DILAUX计算软件对地下车库的LED照明进行模拟、计算、优化,不断的凋整灯具位置以及灯具间隔来到达最佳的照明效果,通过实景分析来探讨LED在地下车库照明领域应用的可行性及其应用前景,并为地下车库照明提供一种设计上的借鉴。     

计及电动汽车无功支撑能力的分布式电源与智能停车场联合规划方法

随着大量分布式电源(DG)及电动汽车(EV)接入配电网,为保证电网的高效、清洁、经济和安全运行,必须对二者进行合理的规划。为此,提出一种计及EV无功支撑能力的DG及智能停车场(IPL)联合规划方法。首先,基于有源配电网的基本物理结构,对EV动力电池的无功可调范围进行了推导。进一步考虑风电等间歇性DG出力、常规用电以及EV充电负荷时空分布的不确定性,通过构建发电—负荷场景以综合计及上述不确定性因素的影响。在此基础上,分别以系统投资和运行成本最小作为目标函数,构建了综合考虑DG和IPL选址定容的两阶段优化模型。根据模型特点,采用经典的遗传算法实现问题求解。以33节点配网系统为例,对所提模型的有效性进行验证。仿真结果表明,在配电网投资规划中充分考虑规模化入网EV的无功支撑能力,能够有效改善系统的电能质量,促进可再生能源高效利用,从而带来更好的经济效益。     

Robust controller design of microturbine and electrolyzer for frequency stabilization in a microgrid system with plug-in hybrid electric vehicles

This paper proposes a new robust controller design of microturbine (MT) and electrolyzer (ES) in a control and monitoring system (CMS) for frequency stabilization in a microgrid system with plug-in hybrid electric vehicles (PHEVs). In the studied microgrid, the MT is normally used to provide the main power to the loads while the ES absorbs the power from the system to produce the hydrogen as the fuel input for the power generation of the fuel cell. On the other hand, the large numbers of PHEVs are utilized in the consumer side. The concurrent charging powers of PHEVs cause a problem of severe frequency fluctuation in the microgrid. To solve this problem, the frequency stabilization of CMS is performed by controlling the power output of MT and ES. The controller structure of MT and ES is a proportional integral with a single input. To enhance the tracking performance and the robustness against system uncertainties of the designed MT and ES controllers, the control parameters are optimized by shuffled frog leaping algorithm based on specified-structure mixed H₂/H_∞ control technique. Simulation results not only show the frequency stabilization effect against the random charging power of PHEVs but also the high robustness of the proposed robust MT and ES controllers against the system parameters variation.     

Coordinated Electric Vehicle Charging for Commercial Parking Lot with Renewable Energy Sources

Electric vehicles (EVs) are increasing in popularity because of their low operating cost and environmental friendly operation. The anticipated rise in EV usage, along with the increased use of renewable energy sources and smart storage devices for EV charging, presents opportunities as well as challenges. Time-varying electricity pricing and day-ahead power commitment add another dimension to this problem. In this research, we develop coordinated EV charging strategies for renewable energy powered charging stations in parking lots. This work maximizes the profits for parking lot operators by taking advantage of time-varying electricity pricing while satisfying system constraints. We propose a linear programming-based strategy for EV charging, and we specifically derive a centralized linear program that minimizes the charging cost for parking lot operator while satisfying customers’ demand in available time.     

一种机组优化组合问题的遗传算法

火力发电厂的发电机组优化组合问题具有高维数、非凸、离散、非线性、多约束的特点,增加了求解的复杂性。讨论了机组优化启停的遗传算法,通过可行性检查使初始解群中的所有个体都是可行解,也使求解过程中建立了一种从不可行解域到可行解域的映射关系,这样可以大大减少无效的遗传搜索过程。实例计算表明,该方法收敛性好,适应性强,计算速度快,能够使计算的结果更加有效地接近全局最优解。     

基于SCUC的可入网混合电动汽车优化调度方法

在可入网混合电动汽车(PHEV)有望规模化应用的背景下,以传统的计及安全约束的机组最优组合(SCUC)问题为基础,发展了能够容纳PHEV的电力系统优化调度数学模型。所发展的模型以保证系统安全运行为前提,兼顾了PHEV车主的经济效益与发电的碳排放成本。利用PHEV作为可移动电量储存单元的特性,将模型解耦为机组最优组合与计及交流潮流约束的充/放电计划优化2个子模型。应用混合整数规划方法和牛顿—拉夫逊潮流算法迭代求解优化问题,可以同时获取日前机组调度计划和各时段的PHEV最优接纳容量及充/放电计划等结果。最后,以6节点和IEEE 118节点2个系统为例,验证了所构建模型的正确性和有效性。     

基于低谷填入法的插电式混合动力汽车集中充电策略

近年来,插电式混合动力汽车(plug-in hybrid electric vehicle,PHEV)逐渐走进人们的生活。车辆—电网模式(vehicle-to-grid,V2G)实现了交通系统与电能系统的连接。研究发现,大量PHEV的自主充电可能会加大原有负荷曲线的峰值,拉大峰谷差,不利于电网的经济运行。在此基础上,以分时电价为背景提出集中充电策略,根据该策略提出一种基于低谷填入思想的PHEV集中充电算法。以某市2020年预测数据为例进行仿真,结果表明所提策略对负荷的削峰填谷有显著效果。     

充电式电动汽车停车场的V2G模型及接入配电网方案优化研究

从配电网潮流分析的角度出发,建立了基于电价引导原则的车网互联(V2G)功率模型。针对充电式电动汽车停车场负荷接入配电网的馈线和接入点选择问题,以减小馈线网损和日内电压波动为目标,建立了考虑V2G行为的接入规划模型。结合实例分析了负荷类型和光伏渗透率对规划方案的影响,算例结果表明电动汽车的V2G行为对配电网运行效益有显著影响,且不恰当接入方案下V2G行为可能会给配电网带来明显的负面影响。     

On the application of wavelet transform for symmetrical components computations in the presence of stationary and non-stationary power quality disturbances

Symmetrical components method allows systematic analysis of unbalanced three-phase systems. This method represents the backbone for many applications in an electric power system (EPS) such as fault analysis, power system protection, power and energy measurements. Moreover, with the increased penetration of plug-in hybrid electric vehicles (PHEVs), studying and evaluating the distribution system unbalance considering power quality disturbance pronounced by fleet of these vehicles, becomes a necessity. In time-invariant polluted environment, the measurements of the symmetrical components for the fundamental and harmonic components could be performed using Fourier basics. However Fourier-based techniques are unsuitable in the presence of any time-variant power quality disturbance which is typically the case when considering PHEVs and other nonlinear industrial process such as computer numerical control (CNC) machines. In this paper, time-frequency expressions for the symmetrical components are developed using different wavelet transforms: Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT) and Stationary Wavelet Transform (SWT). The paper also includes a comparative study of the results obtained when applying the developed approach using different wavelet basis functions, such as Daubechies, Coiflets and Symlets into three case studies (two synthetic and one real) including unbalanced three-phase system under different operating conditions while considering different kind of disturbances. The results are analyzed and conclusions are presented. The outcomes of this study lay the ground for further studies in unbalanced distribution system with high penetration of PHEVs, two-way protection devices for smart grid and power quality evaluation.     

基于GPS数据的电动出租车充电桩选址定容

随着电动出租车规模化的增长,关于电动出租车集群充电桩的选址定容问题日益凸显。该类车辆的轨迹分布在城区,并且该类车辆对公共充电桩的依赖远高于私家电动汽车。为了能够满足这类车辆充电的需求,提出了一种基于全球卫星定位系统(GPS)考虑电动出租车运行轨迹、车辆进入停车场时序性和停车场现有负荷水平的电动出租车充电桩规划方法。采用k-means算法分析得到电动出租车的常驻点并将其作为精选地址的相关依据;计及相邻预选址之间的干扰,以最小花费成本为目标函数对充电桩预选址进行精选;考虑车辆进入停车场的时序性和停车场现有负荷水平计算充电桩的可安装数目。仿真结果表明,针对电动出租车这类特殊集群有常驻点,通过计算最小成本可进行进一步优化,避免出现2个预选址距离太近的情况;在精选地址下对车辆进场时序性和负荷进行分析,可为城区规划修建充电桩提供有力的理论支撑。     

基于B2G模式下电动汽车参与电网互动运行策略

V2G（vehicle to grid）是目前电动汽车参与电网互动的主要模式,但也存在很多问题,影响电动汽车进一步发展。相较之下,B2G（battery to grid）模式解决了V2G模式下模型庞大繁复,难以控制的问题。提出了一种基于B2G模式下的电动汽车参与电网互动策略,以申报用电调整计划的方式,根据电站实时运行状态,以电站运行经济效益最大化为目标,求解最优用电调整计划,从而达到互动效果。通过银川某电站的示范运行,证明该策略具有可操作性,可以带来良好的经济效益。     

基于改进离散粒子群算法的电力系统机组组合问题

提出一种新的离散粒子群算法。结合改进的自学习策略优化粒子群算法适用于求解电力系统中的机组组合（unit commitment,UC）问题。算法将UC问题分解为具有整型变量和连续变量的2个优化子问题,采用离散粒子群优化和原对偶内点法相结合的双层嵌套方法对外层机组启、停状态变量和内层机组功率经济分配子问题进行交替迭代优化求...     

一种计及光伏发电功率不确定性的实时调度方法

大规模光伏发电注入电力系统,其功率的不确定性给实时调度带来了挑战,进而对光伏发电功率和负荷预测的精度提出了更高的要求。针对此问题,文章提出一种计及光伏发电功率不确定性的实时调度方法。首先,基于实时调度的有效稳态安全区域法和线性潮流模型,提出一种计及电压幅值的实时调度模型;其次,通过鲁棒优化等方式将原问题转化为确定性的线性规划问题求解;然后,根据所提方法,分析光伏发电功率和负荷预测精度对于电力系统实时调度安全性和经济性的影响;最后,通过改进IEEE 9节点系统和IEEE 118节点系统进行算例分析,说明所提方法的有效性和高效性。