Multi-Objective Approach for Reconfiguration of Distribution Systems with Distributed Generations

This paper presents a fuzzy multi-objective based heuristic algorithm for network reconfiguration of distribution systems considering distributed generations (DGs). The objectives of reduction of real power loss, branch current carrying capacity limit, maximum and minimum voltage constraints, and feeder load balancing are considered for performance enhancement of the distribution system. Since these objectives are non-commensurable and difficult to solve simultaneously using conventional approaches, they are converted into fuzzy domain and a fuzzy multi-objective function is formulated. A sensitivity analysis based on voltage profile improvement and real power loss reduction is used for obtaining optimal locations of DGs and genetic algorithm is used for optimal sizing of DGs. The proposed reconfiguration algorithm is implemented in two stages, initially in the first stage without incorporating DGs and in the second stage incorporating DGs for obtaining an optimal distribution system network reconfiguration. The advantage of the proposed method is demonstrated through a seventy node four feeders and a sixteen node three feeders distribution systems.     

基于数据挖掘的配电网故障风险预警

为了提高配电网风险预警的准确性,提出了基于数据挖掘的配电网故障关联因素分析与风险预警的方法。通过数据清洗、数据变换、数据集成和离群样本剔除,归纳配电网四大类共28个故障特征;采用改进的Relief-Wrapper算法进行故障关联因素分析,剔除了6个冗余特征,形成了由22个故障特征组成的最优故障特征子集;提出了兼顾故障发生频率和失电负荷比例的配电网故障风险指标和风险等级划分方法,采用基于径向基函数的支持向量机(SVM)方法和最优故障特征子集进行风险预警。对某市120条馈线配电网进行了风险预警算例分析,结果验证了所提方法的有效性。     

基于柔性多状态开关的主动配电网负荷在线紧急转供策略

配电网故障后,传统基于联络线的负荷转供方法存在停电转供、容易引起非故障线路过负荷等诸多问题。近年来出现的一种配电灵活交流输电(DFACTS)设备——智能软开关为上述问题的解决提供了契机。依托其对多条相连线路功率的柔性调节能力,提出了一种兼顾故障馈线残余负荷以及非故障馈线安全运行约束的负荷快速在线转供策略。首先建立了线路末端功率和各节点电压的关系,设置满足配电网正常运行状态的约束条件;在此基础上,以最大负荷转供量为上层目标函数,以电压偏差最小为下层目标函数,在约束范围内进行求解,获取最优潮流分配方法。最后针对上述最优潮流可能影响非故障馈线的安全运行的特殊场景,提出了在保证正常线路安全运行前提下最大程度保全待转供负荷的紧急切负荷策略和实现方案。依托大江东工程实际拓扑结构,搭建了基于PSCAD-MATLAB的联合仿真平台。结果表明,所提出的方案能够实现负荷的不断电在线转供。     

Determination of loss‐minimum configuration with mathematical optimality in a three‐sectionalized three connected distribution feeder network

In a distribution system, in order to enhance the reliability of power supply, the distribution feeder is divided into several sections by installing sectionalizing switches, and then each of the sectionalized sections is connected to a different feeder. For example, one feeder is divided into three sections by two sectionalizing switches, and then each of the divided sections is connected to the other feeder through sectionalizing switch. Since a distribution system with many feeders has many sectionalizing switches, the system configuration is determined by states (opened or closed) of sectionalizing switches. Usually, a power utility tries to obtain distribution loss‐minimum configuration among large numbers of configuration candidates. However, it is very difficult to determine the loss‐minimum configuration such that the mathematical optimality is guaranteed, because it is well known that determination of a distribution system's configuration is to decide whether each sectionalizing switch is opened or closed by solving a combinatorial optimization problem. In this paper, the authors propose a determination method of loss‐minimum configuration by which the mathematical optimality is guaranteed for a three‐sectionalized three‐connected distribution feeder network. A problem to determine the loss‐minimum configuration is formulated as a combinatorial optimization problems with four operational constraints ( feeder capacity, voltage limit, radial structure, and three‐sectionalization). In the proposed method, after picking up all partial configurations satisfied with radial structure constraint by using enumeration method, optimal combination of partial configurations is determined under the other operational constraints by using conventional optimization method. Numerical simulations are carried out for a distribution network model with 140 sectionalizing switches in order to examine the validity of the proposed algorithm in comparison with one of conventional meta‐heuristics (tabu search). © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 167(1): 56– 65, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20530     

树状配电线路并联电容器无功优化规划

为解决含分支树状配电线路无功补偿问题,提出了在树状配电线路安装多台固定容量电容器的无功优化规划方法。该方法以净节约金额最大为目标函数,采用等效负荷法将树状配电线路转化为多个梳状配电线路,分别对各个等效线路进行优化规划,将目标函数值最大者对应的方案确定为最优规划方案。实例分析和规划结果验证了该方法的正确性和可行性。     

A new algorithm for power distribution system planning

In this paper, an attempt has been made to develop a new algorithm for distribution system planning. The proposed algorithm does not require prior knowledge of candidate substation location and can automatically select location of a substation, the optimal feeder configuration and the optimal sizes of branch conductors while satisfying constraints such as current capacity, voltage drop and heuristic rules. Several algorithms are proposed for distribution systems planning. A generalized algorithm is developed for obtaining the optimal feeder path and the optimal location of substation on minimum loss criterion. Heuristic rules are incorporated in the above algorithm. Another algorithm is for branch conductor optimizations. Modified load flow method is also presented in the paper, which can handle composite load models. The load flow algorithm is used for solving radial distribution networks (RDN) and branch conductor optimization algorithm. The load flow algorithm and branch conductor optimization techniques are used as subroutine in the generalized distribution systems planning algorithm. Through numerical example the validity of proposed method is verified.     

Optimal Reconfiguration in Radial Distribution System Using Gravitational Search Algorithm

This article presents an innovative technique for solving network reconfiguration problems with an objective of minimizing network I²R losses for an explicit set of loads. Amid many performance standards considered for optimal network reconfiguration, voltage constraint is an important one. This problem calls for determining the best combination of feeders to be opened in the radial distribution system so it provides optimal performance in the preferred settings. In solving this problem, the gravitational search algorithm is used to reconfigure the radial distribution system; this algorithm practices an optimal pattern for sustaining the radial nature of the network at every stage of the solution, and it further allows proficient exploration of the solution space. The anticipated scheme minimizes the objective function, which has been given in the problem formulation to reduce I²R losses in addition to balancing loads in the feeders. The solution technique involves determination of the best switching combinations and calculation of power loss and voltage profile. The practicality of the anticipated technique is validated in two distribution networks, where attained results are compared by means of available literature. Correspondingly, it is seen from the results that network losses are reduced when voltage stability is enriched through network reconfiguration.     

AN ALGORITHM FOR RELOCATION OF DISTRIBUTION TRANSFORMERS

ABSTRACT

Relocation of distribution transformers is a widely used strategy for reducing the energy losses in radial distribution systems. Existing algorithms for optimal feed point location are either based on ‘ Rule of Thumb ’ or brute force search methods. In this paper two algorithms are presented. The first algorithm is meant for finding the location corresponding to minimum peak power loss in the system, and the other algorithm is intended to locate the feed point corresponding to minimum voltage regulation in the system. The optimal location is found using these two algorithms. The proposed algorithm is extremely simple and involves very little computation. The practicality of the proposed approach has been demonstrated by using them for determining the optimal feed points for real life distribution networks.     

配电网模式化接线优化规划

为了指导配电网模式化接线设计,提出了一系列优化规划方法。指出对于"手拉手"环状网,在2条馈线的最下游子分区间的最短路建设联络线的方案最优。以联络线的建设费用最小为目标函数,将各供电分区作为偶图的2列,采用最小权匹配算法得到"手拉手"环状网的最优配对结果。在此基础上,采用遗传算法和最小权匹配算法相结合的方法,通过交叉和变异操作改变偶图2列的节点,实现了多分段、多联络接线模式优化规划。对一个10条线路的实例进行了规划,结果表明所提出的方法是可行的,并且具有较高的效率。     

基于N-1准则的中压配电线转供能力实用测算分析

为了确定配电网中压馈线之间的负荷转供情况,结合线路的最大负荷电流、允许载流量和多种约束条件,提出了基于“N-1”准则的负荷转供实用测算和分析方法。在了解馈线联络情况的基础上,确定由单馈线或多馈线承担负荷转供的可能性;在满足多种约束条件下,计算、分析并获得馈线首端故障后的转供负荷容量和多种转供方案。通过对变电站各回馈线转供数据进行汇总,可以得出变电站不同故障情况下的负荷损失率。经过实际配电网转供的工程应用,验证了测算分析方法的实用性和有效性。     

分时域10kV配电网极限线损计算分析

配电网线损为电力系统经济运行的重要指标之一,体现着配电网的规划设计和运营水平。本文完善10kV配电网极限线损概念,利用均方根电流法基于配电网入口端负荷约束等式和负载端最大负荷约束条件建立配电网极限线损数学模型,利用遗传算法求解目标函数,分析极限线损最大最小值变化区间及趋势,比较最小线损率情况下的各负荷节点最优功率值,从能耗的角度分析配电网规划的合理性及改进方向。研究表明,10kV配电网极限线损的最大最小值计算结果处于合理区间,该拓扑结构下的配电网线损处于该区间内,对供电公司下达综合线损率指标提供了有力的理论支撑。     

基于馈线偶的配电网快速减小网损重构方法

作为配电网自动化高级应用模块,网络重构应满足快速性的要求而达到在线应用的目的。而许多配电网重构方法因追求全局最优或多次潮流计算而不能满足该要求。文中提出一种基于馈线偶的快速减小网损重构方法。该方法利用馈线偶内网损估算公式推导馈线偶内最佳转移负荷来寻找最优分段开关,可以避免多次潮流计算,完成馈线偶内重构。以馈线偶内重构为基础,并按照全网所有馈线偶的联络开关两侧压差的大小顺序进行全网网络重构。全网重构时对所有馈线进行"优化标定",可以起到避免重构死循环和结束全网重构的作用。最后采用13节点和185节点配电网进行了编程计算,结果表明了该方法的快速性和有效性,可以满足配电网重构在线应用的要求。     

Reliability and costs optimization for distribution networksexpansion using an evolutionary algorithm

This paper presents a multiobjective optimization methodology, using an evolutionary algorithm, for finding out the best distribution network reliability while simultaneously minimizing the system expansion costs. A nonlinear mixed integer optimization model, achieving the optimal sizing and location of future feeders (reserve feeders and operation feeders) and substations, has been used. The proposed methodology has been tested intensively for distribution systems with dimensions that are significantly larger than the ones frequently found in the papers about this issue. Furthermore, this methodology is general since it is suitable for the multiobjective optimization of n objectives simultaneously. The algorithm can determine the set of optimal nondominated solutions, allowing the planner to obtain the optimal locations and sizes of the reserve feeders that achieve the best system reliability with the lowest expansion costs. The model and the algorithm have been applied intensively to real life power systems showing its potential of applicability to large distribution networks in practice     

基于改进拉格朗日松弛算法的电力通信网络负载均衡优化策略研究

针对传统电力通信网络路由策略存在的负载分布不均和丢包率较高等问题,基于软件定义网络,提出了一种基于改进拉格朗日松弛算法的电力通信网络QoS路由策略。以链路时延、可用带宽和丢包率为约束建立路由模型,并采用改进的拉格朗日松弛算法进行路径选择。通过仿真与传统路由方法进行对比,验证了该方法的可行性。结果表明,与传统路由策略相比,该方法能够规划出符合QoS要求的路径,负载分布更加均衡,有效降低了业务丢包率,丢包率由45%降低到0.1%,具有一定的实用价值。     

计及分布式电源的变电站个数及馈线条数概率规划

随着分布式电源渗透率的提高,分布式电源对配电网规划方法和结果的影响研究更具现实意义。采用概率规划方法,建立了涉及分布式电源的变电站个数及馈线条数优化简化模型,模型目标为变电站和中压线路的相关总费用最小,并考虑了线路的容量约束;提出了中压主干线与分支线长度的近似计算模型,并考虑了负荷变化、分布式电源随机性和线路负荷转供率对停电时间和停电费用的影响。基于模型求解获得的变电站优化个数、馈线优化条数和最小总费用,定义了相应的三大类置信变量。算例表明了概率规划对于变电站个数和馈线条数选择的意义以及分布式电源的替代作用。     

基于量子粒子群算法多目标优化的配电网动态重构

为保证配电网动态重构后系统安全稳定的运行,提出了以网损和节点电压稳定性为目标函数的量子粒子群算法的配电网动态重构。针对配电网动态重构过程中时段划分问题,提出以负荷曲线的单调性和幅值变化大小为依据初步划分时间段落。采用整数型量子粒子群算法进行动态重构,重构过程中以相邻时段的网损变化值的关系获取最佳重构段落,然后综合考虑配电网网损最小和节点电压值最大且波动最小为目标寻找最佳重构结构。以IEEE33配电系统为例验证了所提方法的有效性和实用性。     

计及全年风光资源的分布式电源选址方法

针对分布式电源优化选址问题,现有方法一般都简化处理全年风光资源和负荷数据,且算例规模较小,不能完全满足实际应用要求。提出了计及全年风光资源和负荷数据的大规模多馈线配电网分布式电源选址方法。首先,建立计及全年风光资源的大规模多馈线配电网分布式电源优化选址模型,然后基于遗传算法给出优化模型的求解策略,最后采用实际大规模多馈线配电网算例进行验证。结果表明,由于考虑到风机位置会受到全年负荷及风能资源时序特性的影响,因此风机位置优化后的网损更低;采用大规模多馈线整体优化的方案后,采用该方法计算的网损结果也明显优于单馈线范围内的优化结果。     

实现最大供电能力的配电网馈线与主变压器容量匹配

提出了一种新的配电网规划中馈线与变电站主变压器容量的匹配方法。首先,定义了达到最大供电能力下的馈线平均负载率和主变压器平均负载率两个指标,再分析其随馈线容量与主变压器容量比值的变化规律,发现两个指标无法同时达到最大。然后,根据馈线与变电站的建设成本差异,确定馈线与主变压器容量的最优配比,在该配比下单位供电能力的电网建设总投资最小。最后,分析得到多个算例的不同情况的馈线与主变压器容量的最优配比,该值随着馈线相对变电站造价比值的增加而减小;并随着馈线联络均衡度的增加而增加。在现有城网造价水平下建议配比取1.0~1.6,明显低于传统配电网以及规划经验值约1.5~2.0的区间。     

一种新的水火电力系统优化潮流模型

提出了一种新的水火电力系统的优化潮流模型,该模型以最小化燃料费用和污染排放量为目标。模型中的约束条件考虑了网损和系统稳定性2个方面,其中网损用发电量和发电量转移分配系数表示,系统的暂态稳定性和静态电压稳定性分别用动态安全域和静态电压稳定域的方式表示。该文还就目标函数中考虑燃料费用和污染排放比例关系进行了研究。优化模型的雅克比矩阵由网损和各节点发电量之间的灵敏度因子以及动态安全域和静态电压安全域的系数构成。该模型的求解使用牛顿-拉夫逊迭代法实现,并采用一种新的初值设定方法以提高计算的收敛特性。通过2个标准系统算例验证了该模型的有效性。     

考虑降损和平抑峰谷的配电网储能电池Pareto优化模型

为发挥储能电池在配电网运行中降损及平抑峰谷的作用,建立了一种考虑降损和平抑峰谷的配电网储能电池Pareto多目标优化模型。该模型以配电系统中有功损耗最小和1天中各时段负荷方差最小为目标函数,以储能电池的充放电功率为控制变量,以罚函数的形式处理电池容量约束和静态安全约束。依据日负荷曲线获取储能电池最佳充放电时段,结合前推回代潮流计算方法和带精英策略的快速非支配排序遗传算法（non-dominated sorting genetic algorithm II,NSGA-II）对多目标模型进行求解。基于最大满意度,在Pareto解集中分别分析了网损最小、削峰填谷效果最优和网损与削峰填谷折中最优3种优化方案,以获取不同的储能电池运行优化方案。最后,以IEEE33配电网系统为例,验证了所提方法的实用性和有效性,并分析了不同决策策略下运行方案的优劣,为配电网经济运行提供决策参考。