考虑多元协同互动效应的主动配电网多目标规划方法研究

主动配电网规划时需充分计及风、光等间歇式分布式电源的不确定因素的影响,在常规负荷预测的基础上建立了接入主动配电网的风、光等间歇性分布式电源可信出力模型,并考虑负荷需求侧响应对负荷预测结果的影响,提出了考虑源-荷-储多元协同互动效应的配电网负荷预测模型。在负荷预测结果的基础上,建立了主动配电网双层多目标规划模型,上层规划为电网优化规划问题,以年网络综合费用最小为目标;下层规划模型是在上层规划所得到网架下以典型日系统运行经济性确定储能等可控资源的有功出力。通过优化求解得到主动管理模式下配电网网架规划方案及储能的选址定容方案,最终以上海某主动配电网为例验证所提规划方法的科学性和有效性。     

基于APDE算法的配电网分布式电源承载力评估

针对分布式电源接入配电网装机容量问题,提出一种基于自适应扰动差分进化算法（APDE）的配电网分布式电源最大承载能力评估方法。首先建立包含有载调压变压器及静止无功补偿器的配电网模型,并优化系统潮流与注入功率的关系表达式,通过考虑分布式电源及负荷的不确定性,建立基于机会约束规划下的源荷不确定性配电网分布式电源最大承载力评估模型;然后对差分进化算法进行改进,形成APDE算法以求解模型;最后基于IEEE-33节点配电系统对所建配电网模型进行分析,验证其满足电力系统分析需求,并进一步对所提配电网分布式电源承载力评估方法进行分析,通过与相关算法比较,证明了所建模型的可行性和改进方法的有效性。     

含高渗透率可再生能源的配电网可靠性分析

以高渗透率可再生能源接入配电网为背景,分析分布式电源的渗透率对所接入系统的供电模式以及可靠性分析的影响。在建立光伏、风电、储能以及含有家用电动汽车充电桩的负荷模型的基础上,提出以分布式电源为中心的区域供电模式、故障影响分析和功率匹配策略;并基于序贯蒙特卡洛随机模拟方法,设计配电网可靠性评估算法;最后采用所提出的算法对改进后的IEEE RBTS Bus2进行可靠性评估,通过算例分析给出区域供电模式下的可靠性指标,并对比不同可再生能源对可靠性指标的影响,为含高渗透率可再生能源的配电网的可靠性分析以及电源规划提供参考。     

考虑光伏储能和可控负荷的配电网检修计划优化

主动配电网（active distribution network, ADN）是传统配电网的一个发展方向,其特点是能够对接入配电网的分布式电源（distributed energy resources, DER）进行主动控制和主动管理,这会对配电网检修计划的制定产生一定的影响。以含有光伏-储能联合发电系统和可控负荷的配电网为例,研究分布式电源在配电网检修中所能起到的作用,建立了相应的二层优化模型。其中子模型为单设备检修优化模型,考虑天气情况对光伏发电出力的影响,通过对储能电池和可控负荷的优化设置来减小功率损失;主模型为全检修计划优化模型,考虑储能电池容量约束,优化目标为减少检修全过程中的经济损失。针对模型特点,采用混沌粒子群分层优化算法和改进的TSP搜索算法进行求解。IEEE33节点系统的仿真结果显示了模型的正确性和有效性,比较不同条件下的仿真结果可以说明分布式能源的接入有助于降低配电网检修造成的损失。     

一种计及无功补偿的分布式电源优化配置方法

可再生能源以分布式电源的形式接入配电网是消纳可再生能源的重要手段,为进一步提高可再生能源的利用率,本文在分布式电源优化配置过程中考虑无功补偿设备以及储能系统的配置,建立了分布式电源、储能系统、无功补偿设备建设成本最小,系统网络损耗最小,系统电压稳定指标最优的多目标优化模型,并提出基于概率分布策略的改进遗传算法用于优化模型的求解。最后,以IEEE-33节点配电网系统为例,表明本文提出的配置方法可以改善分布式电源的波动性对配电网的不利影响,在保证系统稳定的前提下,进一步提高可再生能源利用率。     

分布式能源接入后的电动汽车实时电价响应控制策略

随着电动汽车的规模化应用,为了缓解电网的压力,越来越多的分布式能源被接入。然而,电动汽车充电站的可再生能源供给一般小于电动汽车充电负荷,须与大电网联合运行。针对分布式能源与电网之间的协同增效利用,提出了微电网内的充电站储能系统与电网相互协调的策略。在建立电动汽车负荷模型的基础上,根据微网内可再生能源实时出力与负荷需求的求解不平衡率,使充电站储能系统和大电网根据不平衡率按一定比例协同运行。当电动汽车接入电网充电时,首次利用强化学习算法建立电价控制模型,实现两者的能源协调控制。以某地区的微网为例进行仿真分析,通过对比不同用户响应度的配电网负荷和充电站储能系统,验证该策略在微电网与大电网协同运行优化的有效性。该策略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,优化了电力负荷曲线,对解决如何有效地结合分布式能源和大电网对电动汽车进行充电等问题具有一定的实际意义和价值。     

基于储能环节的分布式新能源楼宇直流配电系统设计

随着直流技术的发展,直流配电网以其电能质量好、传输效率高、方便各类分布式电源接入等优点,成为区域性配电的新选择。文章提出了一种应用于楼宇、适于分布式电源接入的新型直流配电方案,建立了包含风电、光伏、燃料电池等新电源组成的直流配电网结构,在Dig SILENT软件中对分布式电源进行建模,通过仿真对比了并网状态下和非并网状态下储能系统的作用,并分别在系统正常工况下和发生故障时,分析储能系统在直流微电网中的重要影响,结果证明该方案有效可行。     

基于混沌自适应人工鱼群算法的含家庭储能配电网快速重构方法

针对分布式电源接入配电网具有波动性和随机性的特点,提出一种基于混沌自适应人工鱼群算法的含分布式电源配电网快速化重构方法。在风电、光伏和家用储能的数学模型和节点划分基础上,以电网网损、开关次数以及失电负荷成本最小为目标函数,建立基于多目标优化的含分布式电源配电网的优化重构模型。利用混沌自适应人工鱼群算法对模型进行求解,通过对鱼群的混沌初始化和自适应动态调整步长参数,提高了算法的全局搜索能力和收敛速度。根据电化学储能系统出力特性划分配电网网架重构的典型工作场景,通过含分布式电源的IEEE 33节点测试系统仿真实例验证了该文方法的有效性。仿真结果表明,与单独考虑电网网损成本相比,由该文方法得到的配电网优化重构成本降低了50%以上,优化重构时间均小于0.9 s,实现了含分布式电源配电网的快速自愈。     

分布式新能源发电对配电网电压影响研究

分布式发电能够最大限度地利用可再生能源,但无规划地引入分布式发电会对配电网的潮流分布、电压水平、短路容量等产生不良影响。文章建立了光伏和风力发电模型,在IEEE33节点配电网模型的基础上,分别从分布式电源接入容量和接入位置,分析单个分布式电源接入和多个分布式电源的接入对配电网电压分布的影响,为以后电网规划提供参考。     

基于配电网可靠性的分布式电源与充换电站协同规划

充换电站具有电源与负荷的双重性质,分布式电源与储能的联合装置可作为稳定的电网备用电源。当配电网中发生故障时,充换电站和分布式电源的选址定容将直接影响配电网运行的可靠性。该文以带时间函数负荷权重的全网电量中断损失费为目标函数,考虑配电网及交通网联合约束,建立分布式电源与充换电站的协同规划模型,同时采用矩阵方法对变量进行归一化处理,最后采用Matlab进行求解。在结合交通网的IEEE-RBTS Bus 6系统主馈线F4上进行仿真,仿真结果表明,协同规划分布式电源与充换电站能够提高配电网的可靠性指标,规划方案合理。     

基于指标关联的分布式电源并网规划策略

为解决新能源并网时的电源规划与风光消纳问题,考虑风光能源功率波动特性并计及储能单元提出一种计及风光协调出力的电网规划策略。综合考虑电压波动、新能源消纳及新能源发电效益建立多指标规划模型,采用引入指标关联策略的粒子群优化方法对模型进行求解,确定分布式电源及储能的位置和容量。进一步分析优化方案在电能质量方面的规划效果,统计对比电压累计概率密度对规划方案进行评价。以某电网45节点配电系统为例,采用所提分布式电源并网规划策略进行仿真,决策风光储并网方案,并验证所提策略的合理性和可行性。     

Probabilistic load flow using Monte Carlo techniques for distribution networks with photovoltaic generators

Connections of distributed generation (DG) systems to distribution networks are increasing in number, though they may often be associated with the need of costly grid reinforcements or new control issues to maintain optimal operation. Appropriate analysis tools are required to check distribution networks operating conditions in the evolving scenario. Load flow (LF) calculations are typically needed to assess the allowed DG penetration level for a given network in order to ensure, for example, that voltage and current limits are not exceeded.

The present paper deals with the solution of the LF problem in distribution networks with photovoltaic (PV) DG. Suitable models for prediction of the active power produced by PV DG units and the power absorbed by the loads are to be used to represent the uncertainty of solar energy availability and loads variation. The proposed models have been incorporated in a radial distribution probabilistic load flow (PLF) program that has been developed by using Monte Carlo techniques. The developed program allows probabilistic predictions of power flows at the various sections of distribution feeders and voltage profiles at all nodes of a network.

After presenting theoretical concepts and software implementation, a practical case is also discussed to show the application of the study in order to assess the maximum PV peak power that can be installed into a distribution network without violating voltage and current constraints. A comparison between Deterministic Load Flow (DLF) and PLF analyses is also performed.     

微网对配电系统可靠性的影响评估

为了更好地应用分布式电源（DG）,微网受到越来越多的关注,因此有必要对微网接入后配电系统的可靠性进行评估。本文应用光伏发电、风电、微型燃气轮机和储能等分布式电源构建微网,建立可靠性分析模型,并提出适用于含微网配电系统的新型可靠性指标。利用最小路法,按照不同方案对某辐射型配电系统进行可靠性评估,在评估中考虑了重要负荷的因素。结果表明,微网的接入可提高配电系统的可靠性,微网的接入位置、容量等也会对可靠性产生较大的影响。当考虑了重要负荷时,微网的效益更加显著。     

Stochastic scheduling of power system in the presence of electric vehicle and renewable sources considering security and economic indexes using an improved mutation particle swarm optimization (M-PSO) algorithm

Increased air pollution and global temperature as well as motor vehicle fuel consumption have depleted fossil fuel resources and increased environmental problems caused by the consumption of such fuels. In addition to methods such as combined heat and power (CHP) technology and distributed generation (DG) of energy at the consumption site, renewable energy sources and EVs are considered suitable methods for achieving this goal, which is prepared by the grid or battery electric energy. Generation uncertainty due to the lack of solar radiation and constant wind blow at different hours of the day is the only challenge for using renewable energies. Moreover, system reliability is a concept that refers to the safe and reliable operation of the system. In general, the wider and more important the system, the more attention that is paid to calculating its reliability in planning and decision making. This study aims to examine the problem of probabilistic power system planning by calculating the power system reliability, evaluating the effect of the presence of these vehicles on security and economic indicators and renewable energy sources, and modeling uncertainties using a Least Squares Generative Adversarial Network (LSGANs) method with generating various scenarios for solar irradiance and wind speed. Furthermore, the Kantorovich distance matrix (KDM) is used to reduce the number of generated scenarios. In the proposed model, the conditional value-at-risk (CVaR) method is implemented to assess and control the risk caused by uncertainties of the proposed problem. Using the power stored in the EV battery is evaluated to cover wind and solar energy source uncertainties.     

Grid integrated renewable DG systems: A review of power quality challenges and state-of-the-art mitigation techniques

Increased energy demands due to rapid industrialization, environmental concerns with fossil fuel–based generation, diminishing fossil energy resources, transmission network congestion, and technical performance deterioration are the motivations behind the integration of small renewable distributed generation (DG) units and turning the existing power systems into a restructured one. Optimizing the technical benefits offered by DG placement is a well-known challenge for distribution network operators (DNOs) for both fossil and renewable energy resource–based DGs, but renewable DG systems have several power quality (PQ) challenges associated additionally. Power quality is a very significant characteristic of renewable DG systems because today's loads are more sensitive to PQ disturbances and penetration of renewable energy as well as nonlinear loads is proliferating in distribution power networks. So the need for innovative power quality improvement (PQI) techniques becomes inevitable due to ongoing reformation in traditional distribution networks by the integration of renewable energy. This article presents a comprehensive analysis of power quality challenges with grid integration of renewable DG systems and current research status of associated mitigation techniques. Firstly, this paper puts emphasis on theoretically illustrating all the crucial power quality challenges associated with grid integration of renewable energy, and secondly, a thorough survey, of all PQI techniques introduced till date, is elaborated along with highlighting the opportunities for future research. Furthermore, all the crucial power quality issues, the impact of high penetration of renewable energy and mitigation techniques on power quality, are demonstrated also by simulating a grid integrated PV-based DG system in MATLAB/Simulink. This article is believed to be very beneficial for academics as well as industry professionals to understand existing PQ challenges, PQI techniques, and future research directions for renewable energy technologies.     

Analysis of access mode and control strategy of distributed energy storage system on user side

分布式储能系统在电力用户侧中的应用日益广泛,且应用场景多样化,对于电网来说是潜在的优良资源。然而其容量小、数量多、分布不均衡、单机接入成本高、系统操作及管理困难,给电网的规划运营带来了日益严峻的挑战和技术难题。本文就用户侧中的分布式储能典型应用模式及接入方式进行介绍,阐述各应用场景下分布式储能的应用模式和方案,并分析了典型应用场景下的分布式储能运行效果。通过对分布式储能系统技术形态和载体的分析,可为进一步研究分布式储能汇聚协调控制技术提供理论指导。     

Evaluation of intermittent-distributed-generation hosting capability of a distribution system with integrated energy-storage systems

The penetration rate of distributed generation is gradually increasing in the distribution system concerned. This is creating new problems and challenges in the planning and operation of the system. The intermittency and variability of power outputs from numerous distributed renewable generators could significantly jeopardize the secure operation of the distribution system. Therefore, it is necessary to assess the hosting capability for intermittent distributed generation by a distribution system considering operational constraints. This is the subject of this study. An assessment model considering the uncertainty of generation outputs from distributed generators is presented for this purpose. It involves different types of regulation or control functions using on-load tap-changers (OLTCs), reactive power compensation devices, energy storage systems, and the reactive power support of the distributed generators employed. A robust optimization model is then attained It is solved by Bertsimas robust counterpart through GUROBI solver. Finally, the feasibility and efficiency of the proposed method are demonstrated by a modified IEEE 33-bus distribution system. In addition, the effects of the aforementioned regulation or control functions on the enhancement of the hosting capability for intermittent distributed generation are examined.     

基于蚁群算法的多类型分布式电源优化配置

鉴于不同类型分布式电源接入配电网的位置及注入容量对系统潮流分布的影响,主要体现在能源的梯级利用率、电网规划成本、供电可靠性和电能质量等方面,在配电网规划建设期间建立各种分布式电源(DG)的出力模型,综合考虑需求侧的经济利益,建立以用户侧的投资运行成本和网络损耗费用最小为优化目标的函数,采用蚁群算法对函数进行求解得到优化的位置和容量。算例分析表明,该方法可以得到较为合理的方案,并可有效降低系统网损、节点电压偏差,提高需求侧的经济效益和电能质量。     

考虑源-荷发展不确定性的电网扩展规划模型

在城市电网的发展过程中,随着可再生能源及储能等可控负荷的大规模接入,系统内源-荷实时功率供需关系与未来容量发展的不确定性将会增加,导致可再生能源利用率降低,并给上级电网带来调峰压力。为解决这一问题,文章充分考虑源-荷发展不确定性对系统的影响,以总规划成本最小为目标,建立了基于多重不确定性的电网模糊扩展规划模型及其求解方法。通过仿真算例验证了所提模型可有效地提升电网规划的经济性。     

State of the art of the virtual utility: the smart distributed generation network

The world of energy has lately experienced a revolution, and new rules are being defined. The climate change produced by the greenhouse gases, the inefficiency of the energy system or the lack of power supply infrastructure in most of the poor countries, the liberalization of the energy market and the development of new technologies in the field of distributed generation (DG) are the key factors of this revolution. It seems clear that the solution at the moment is the DG. The advantage of DG is the energy generation close to the demand point. It means that DG can lower costs, reduce emissions, or expand the energy options of the consumers. DG may add redundancy that increases grid security even while powering emergency lighting or other critical systems and reduces power losses in the electricity distribution. After the development of the different DG and high efficiency technologies, such as co‐generation and tri‐generation, the next step in the DG world is the interconnection of different small distributed generation facilities which act together in a DG network as a large power plant controlled by a centralized energy management system (EMS). The main aim of the EMS is to reach the targets of low emissions and high efficiency. The EMS gives priority to renewable energy sources instead of the use of fossil fuels. This new concept of energy infrastructure is referred to as virtual utility (VU). The VU can be defined as a new model of energy infrastructure which consists of integrating different kind of distributed generation utilities in an energy (electricity and heat) generation network controlled by a central energy management system (EMS). The electricity production in the network is subordinated to the heat necessity of every user. The thermal energy is consumed on site; the electricity is generated and distributed in the entire network. The network is composed of one centralized control with the EMS and different clusters of distributed generation utilities and heat storage tanks. Each of these clusters is controlled by a local management station (LMS). Every LMS has information about the requirements (heat, cold and electricity) of the users connected to its cluster and the state of the utilities and water level of the storage tanks in its cluster. The EMS receives the information from the LMSs and sets the electricity input or output of every cluster in the network. With the information ordered by the EMS, the LMS set the run or stand‐by of the utilities of its cluster. The benefits of the VU are the optimization of the utilization yield of the whole network, the high reliability of the electricity production, the complete control of the network for achieving the main aim of the EMS, the high velocity for assuming quick changes in the demand of the system and high integration of renewable energy sources, plus the advantages of the DG. This paper indicates the state of the art of the VU concept, analyses the projects that are being developed in this field and considers the future of the VU concept. Copyright © 2004 John Wiley & Sons, Ltd.