智能电网框架下电动汽车智能充电系统设计研究

近年来,电动汽车和插电式电动汽车（Plug-in electric vehicles, PEVs）的销量稳步增长,充电桩数量急剧增加,这一现象可能会给电网和当地配电电路和变压器造成负担,而且可能会导致电力公司的成本增加。文中介绍了智能电网系统的设计和实现逻辑,使电动汽车、PEV与电网之间能够实现动态交互。这种智能和动态的交互能够减轻电网负荷,从而最大限度地减少成本,避免负载过大造成的损害。本文以开发算法为重点,提出了完整的系统设计,该系统充电速度快、效率高,可以成功地用于减轻电网的负担。     

A nonlinear control method for price-based demand response program in smart grid

This paper proposes a price-based demand response program by the nonlinear control method. The demand response program is formulated as a nonlinear power management system with price feedback. We give the conditions of the price parameters for both the global asymptotic stability of the system and the social welfare optimality of the equilibrium point. Furthermore, the system is shown to be input-to-state (ISS) stable when there are additive disturbances on the power measurements and the price, and the discrete-time implementation of the power management system is given. Simulation results demonstrate the balance between supply and demand and the stability of the system with and without disturbances.     

电动汽车入网一次调频控制策略研究

针对电动汽车维持电池能量和补给能量2种行为,分别提出了电动汽车入网一次调频控制策略,即维持电池能量调频控制和电池计划充电调频控制。用椭圆函数构建电视荷电状态与充/放电下垂之间的函数关系,实现维持电池能量和频率下垂控制。根据用户充电需求和电池荷电状态,实时修正计划充电功率,满足用户充电需求。最后,在2区域互联电网模型上进行仿真实验,仿真结果验证了所提出控制策略的有效性。     

Quantifying economic benefits of second life batteries of gridable vehicles in the smart grid

Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEV) with vehicle-to-grid capability, referred to as “gridable vehicles” (GVs), have become a useful choice for storage devices in the smart grid environment. The success of a smart grid system with GVs heavily depends on the market penetration of GVs and their participation rate in the vehicle-to-grid (V2G) program. Battery lifetime and revenue earning potential are influential factors for GV owners considering whether to participate in the V2G program. Second use of GV batteries, after their automotive life, can generate some revenue for the owners to recover a part of their battery purchase cost. However, this is dependent on the remaining capacity of the battery and the capacity degradation rate both in the automotive and second life. In this paper, capacity degradation and the remaining energy of a GV battery at different operating cycles have been quantified in both their automotive and second lives. Cost of battery energy both in automotive and second life have also been modelled that informs the owners of the revenue potentials, especially from the second life use. Finally, an economic load dispatch model with the inclusion of second life revenue has been developed to establish that using GV batteries in this way would earn extra revenue thus contributing to the initial buying price and encouraging more GV participation in the smart grid. Simulation results show that the proposed model can contribute up to 19.56% of the initial battery purchase cost, while still ensuring economic load dispatch.     

Demand-side management in smart grid operation considering electric vehicles load shifting and vehicle-to-grid support

Demand fluctuation in electric power systems is undesirable from many points of view; this has sparked an interest in demand-side strategies that try to establish mechanisms that allow for a flatter demand curve. Particularly interesting is load shifting, a strategy that considers the shifting of certain amounts of energy demand from some time periods to other time periods with lower expected demand, typically in response to price signals.In this paper, an optimization-based model is proposed to perform load shifting in the context of smart grids. In our model, we define agents that are responsible for load, generation and storage management; in particular, some of them are electric vehicle aggregators. An important feature of the proposed approach is the inclusion of electric vehicles with vehicle-to-grid capabilities; with this possibility, electric vehicles can provide certain services to the power grid, including load shifting and congestion management. Results are reported for a test system based on the IEEE 37-bus distribution grid; the effectiveness of the approach and the effect of the hourly energy prices on flattening the load curve are shown.     

New development in relay protection for smart grid

This series of papers report on relay protection strategies that satisfy the demands of a strong smart grid. These strategies include ultra-high-speed transient-based fault discrimination, new co-ordination principles of main and back-up protection to suit the diversification of the power network, optimal co-ordination between relay protection and auto-reclosure to enhance robustness of the power network. There are also new development in protection early warning and tripping functions of protection based on wide area information. In this paper the principles, algorithms and techniques of single-ended, transient-based and ultra-high-speed protection for EHV transmission lines, buses, DC transmission lines and faulty line selection for non-solid earthed networks are presented. Tests show that the methods presented can determine fault characteristics with ultrahigh-speed (5 ms) and that the new principles of fault discrimination can satisfy the demand of EHV systems within a smart grid.     

Improved-ELM method for detecting false data attack in smart grid

Power grid is a complex system which closely links the power generation and power consumer through transmission and distribution networks. With the development of smart grid, smart grid is more open to external communication systems, it also has exposed some problems in the network attacks. A new false data injection attack (called the unobservable attack) that can bypass the traditional BDD and inject random errors into state estimation. We propose an improved extreme learning machine (ELM) for attack detection. The artificial bee colony (ABC) incorporates the thought of differential evolution algorithm (DE) to optimize ELM for improving detection precision. In this paper, Autoencoder is used to reduce the dimensionality of the measurement data, which makes the low-dimensional data information basically and fully represent high-dimensional data. We verify the performance of the proposed method on IEEE bus systems, and prove that the proposed method can effectively detect such unobservable attack.     

一种新型的基于风速预测的风力发电系统

为了使风力发电系统的有功出力波动维持在规定的范围内,同时保证系统的蓄电池储能水平基本保持不变,使系统能有效地应对输入功率突然增加及输出功率急剧下降的紧急情况,在风速预测的基础上提出一种新型的风力发电系统蓄电池充放电控制策略。当预测的风力发电系统输入功率的波动超过规定的功率变化范围时,通过对蓄电池的充放电控制以减弱网侧功率的波动,并且使蓄电池的充放电能量在一个周期内基本平衡,从而保证系统预留一定容量的储能装置以接收大功率输入或补充严重不足的并网功率,有效地减少了风能损失、提高了系统的效率。仿真结果验证了所提控制策略的有效性和可靠性。     

Real-time voltage control algorithm with switched capacitors in smart distribution system in presence of renewable generations

One of the most important responsibilities of Distribution System Operator (DSO) is to maintain the customer voltage within specified ranges. Capacitor banks have long been used to provide voltage support and to correct displacement power factor on distribution network. This paper presents a new approach for real time voltage control of distribution networks that has improvements over the conventional voltage control models. This approach will be active in emergency conditions where, in real time, the voltages in some nodes leave their permissible ranges. In the proposed model, it is assumed that renewable distributed generations are integrated in the distribution system, and the communication infrastructure of smart grid has already been implemented. Also, all the capacitors are fitted with Remote Terminal Unit (RTU) and are completely accessible and controllable. Unlike previous voltage control methods, the proposed approach does not need the load and renewable generation forecast data to regulate voltage. Moreover, the calculation time of the proposed approach is considerably reduced. The proposed voltage control algorithm is applied on two different models, and each presented model has a substantial improvement over previous models. DSO can choose one of them based on a trade-off between cost and power quality index. To verify the effectiveness and robustness of the proposed control scheme, the developed voltage control scheme is tested on a typical distribution network. The simulation results show that the proposed real time voltage control has the capability to maintain distribution voltage in specified ranges.     

智能充电运行管理系统在电动汽车充电站的应用

阐述建设电动汽车充电设施监控系统的必要性,从充电监控功能、配电监控功能、计量计费功能、安防监控功能等方面介绍江苏扬州吴州路充电站所采用的智能充电运行管理系统以及该系统的组网方式,论证监控系统在充电设施建设中的重要地位。     

智能电网下的新型能源管理系统设计方案

在介绍智能电网的定义、内涵、关键特征的基础上,提出了一种智能电网下的新型能源管理系统的设计方案,具体分析了该能源管理系统的组成及其各部分的功能特点.作为智能电网技术在用电系统的一个典型应用,新型能源管理系统为更好地管理、节约、监控能源使用提出了一种解决方案,将在未来得到广泛应用.     

Integration of PV and EVs in unbalanced residential LV networks and implications for the smart grid and advanced metering infrastructure deployment

Voltage unbalance is a relevant problem that causes a less efficient operation of the system due to higher energy losses and lower hosting capacity. Unbalance has often been neglected by distribution system operators due to the lack of monitoring data in the low voltage (LV) grid. However, the massive deployment of smart metering in recent years in many countries provides very valuable information to detect unbalance. Moreover, in the current context of increasing presence of single-phase distributed energy resources connected to LV networks, such as electric vehicles (EVs) and photovoltaic (PV) generation, unbalance is bound to increase.This article investigates the technical impact of future integration of EV and PV in LV unbalanced networks. This paper has assessed the daily energy losses and voltage problems as load unbalance gradually increases, based on load flow analysis on an hourly basis, considering residential demand and homogeneously distributed EV and PV. The analysis has been carried out for several rural and semi-rural LV networks and various scenarios of demand level and penetration degree of EV and PV. The three-phase load flow analysis is computed using the forward-backward sweep algorithm.Furthermore, this work discusses the implications for the deployment of supervision and monitoring solutions based on advanced metering infrastructure (AMI). Their implementation should be prioritized in more loaded and longer networks where high integration of distributed energy resources is expected so that unbalance can be detected and corrective actions can be applied.     

A novel Volt-VAR Optimization engine for smart distribution networks utilizing Vehicle to Grid dispatch

In recent years, Smart Grid technologies such as Advanced Metering, Pervasive Control, Automation and Distribution Management have created numerous control and optimization opportunities and challenges for smart distribution networks. Availability of Co-Gen loads and/or Electric Vehicles (EVs) enable these technologies to inject reactive power into the grid by changing their inverter’s operating mode without considerable impact on their active power operation. This feature has created considerable opportunity for distribution network planners to explore if EVs could be used in the distribution network as reliable VAR suppliers. It may be possible for network operators to employ some EVs as VAR suppliers for future distribution grids. This paper proposes an innovative Smart Grid-based Volt-VAR Optimization (VVO) engine, capable of minimizing system power loss cost as well as the operating cost of switched Capacitor Banks, while optimizing the system voltage using an improved Genetic Algorithm (GA) with two levels of mutation and two levels of crossover. The paper studies the impact of EVs with different charging and penetration levels on VVO in different operating scenarios. Furthermore, the paper demonstrates how a typical VVO engine could benefit from V2G’s reactive power support. In order to assess V2G impacts on VVO and test the applicability of the proposed VVO, revised IEEE-123 Node Test Feeder in presence of various load types is used as case study.     

考虑电网调频需求时的直流负载电压下垂控制方法

电解电镀、冶金化工、电动汽车等行业的直流型用电负载在电网中的占比越来越大,对电网频率稳定性的影响也因此更加明显了。以响应电网调频需求为目标,提出了在保证电网电能质量的前提下,通过电力电子接口电路实现对直流负载电压的下垂控制,使可调型直流负载能够对电网频率异常事件进行响应。此外,为了确保直流负载的正常用电,并且避免对直流负荷进行频繁切换控制,还进一步提出了分区间调频控制模式,从而满足了需求侧响应、电网友好等电网需求。提出的控制方法结构简单,容易实现,可降低直流负载接入对电网的影响,提升电网对大规模直流负载接入的适应性。最后通过Simulink仿真验证了此方案的可行性、有效性。     

电动汽车大功率充电设备的多段恒流充电方法

目前大多数电动汽车充电设备输出功率有限,所采用的充电方法较为简单,造成电动汽车的充电过程存在时间长、能耗高、温升大等问题.为了解决这些问题,设计了一种大功率充电设备,基于最优充电曲线,提出了一种电动汽车的多段恒流充电方法,并将此充电方法应用于大功率充电设备中.首先,设计了大功率充电设备的电气结构图;其次,根据动力电池的...     

考虑用户充电计划的电动汽车辅助调频控制策略

电动汽车(electric vehicle,EV)可作为储能装置参与电网调频,但车网互动(vehicle-to-grid,V2G)过程的低惯性、低阻尼会影响电网稳定性,且目前的EV辅助调频策略无法保证按时完成用户的充电计划。因此,文中将虚拟同步机技术应用于EV的充放电控制中,使充电机具有与同步发电机类似的惯性、阻尼特性。然后,基于T-S模糊控制器,提出一种考虑用户充电计划的EV辅助调频控制算法,EV的充/放电功率由其充电状态和电网频率共同决定。仿真结果表明,所提控制策略能够在不同的充电计划、EV荷电状态和电网频率条件下,智能调节电网与EV之间的功率流动。在满足用户充电需求的同时,该策略能有效提高电网的频率稳定性,规避电池过充、过放风险。     

Multi-agent systems for reactive power control in smart grids

Power system monitoring is the most fundamental prerequisite for making reasonable decisions in a control center. In recent years, with the advent of smart grids, monitoring and control of reactive power in power systems has entered a new era. This issue have highlighted the need for effective methods of decentralized optimal reactive power control (DORPC), especially based on the new available frameworks which have emerged along with the smart grids. This paper presents a novel approach to the DORPC problem based on a Holonic architecture. The Holonic architecture has some unique features by which the objective of the DORPC problem could be optimized through a timely proposed strategy. In order to demonstrate the features of the proposed approach, it is compared with two other methods considering a set of indices. Accordingly, the proposed approach has great potential to reduce the active power losses and to fully exploit the available reactive power resources. It requires a limited set of data while improves the fault tolerance of the network.     

Voltage collapse detection using Ant Colony Optimization for smart grid applications

Load demand levels in power networks are continuing to increase especially considering the penetration of Plug-in Hybrid Electric Vehicles, and as a result bus voltages are requiring more support from generators elsewhere in the network in order to maintain the voltage within specified limits. If the network is unable to support the increasing demand, bus voltage will begin to degrade until the point of voltage collapse which can lead to catastrophic network failure. Previous studies have shown that evolutionary computing techniques are effective methodologies for locating voltage collapse points. Ant Colony Optimization techniques allow for the optimization of many independent parameters simultaneously, the loading parameter for each bus is considered in this work. In this study, Ant Colony Optimization is applied to detect voltage collapse conditions in power networks, to obtain faster computing time with the future goal of providing online detection and prediction for use in smart grids. Two case studies are considered in this study to assess the performance of the proposed detection algorithm; the first case study includes 9-bus system while the other case study involves IEEE 118-bus system. Results obtained from both cases and conclusions drawn are also presented.     

Typification of load curves for DSM in Brazil for a smart grid environment

The deployment of a smart grid environment is a worldwide trend and generates of a large volume of data. The load curve for each consumer in real time is an example of this. The challenge is the transformation of these data into useful information that may help to improve efficiency in the management, planning and operation of the power grid. The implementation of demand side management (DSM) requires an analysis of the data generated in a smart grid environment to determine which policies are most appropriate for each type of consumer. Because of the large number of customers, the application of these policies involves the selection of patterns for the load curve.This study discusses the use of DSM in a smart grid environment in Brazil and presents the simulation for creating load curve patterns using the k-means technique from the consumer data of a concessionaire for the Brazilian electric system. The result obtained in this research is the creation of the load curve patterns for selecting the policies of DSM.     

基于Agent的智能电网集成优化控制策略

智能电网集成优化控制技术是实现各环节协调运行的关键,智能代理技术为解决这一问题提供了良好的方法。在介绍国内外智能代理研究现状和发展趋势的基础上,介绍了基于Agent的智能电网集成优化控制技术总体架构,基于Agent的动态分解与协调技术,并以微电网为例,对微电网中基于Agent的即插即用技术进行了分析,提出了相关的解决方案,并对基于Agent智能电网集成优化技术做了展望,指出智能代理和多代理系统通过快速进行信息处理,将使智能电网的集成优化实时控制提高到一个新的水平。