含电动汽车和智能软开关的配电网动态重构

提出含分布式能源、智能软开关(SOP)和电动汽车(EV)有序接入的配电网重构策略。基于上班族的出行习惯模拟EV的无序充电模型,并构建配电网重构下的SOP模型;对于接入的EV无序充电负荷,采用拉格朗日松弛分散式优化算法和虚拟电价进行EV的有序调度;以最小化网损费用,SOP运行费用,弃风、弃光费用与开关动作费用之和为目标函数,通过大M法和二阶锥松弛将配电网重构模型转化为混合整数二阶锥规划模型,采用CPLEX求解器进行求解。IEEE 33节点标准系统的仿真结果表明,在配电网动态重构中采用SOP代替传统开关能够提升配电网运行的经济性,同时采用所提有序调度方法优化EV充电可以改善配电网电压质量。     

配电网重构的自适应和声搜索算法

采用和声搜索算法（ＨＳＡ）搜索最优方案进行配电网重构时,会受初始参数值的影响。为此,提出自适应和声搜索算法（ＡＨＳＡ）。在和声搜索算法中加入局部搜索进行改进,增强了算法的寻优性能。建立以降低网络的有功和无功功率损耗为目标的配电网重构的数学模型,采用基于节点分层的前推回代法对网络结构进行潮流计算和分析。对IEEE69节点配电网进行仿真,与和声搜索算法,遗传算法（ＧＡ）的结果进行对比分析,表明该算法的迭代次数少,有较好的收敛效果。在配电网重构的算例应用中,证明了自适应和声搜索算法是可行的。     

基于双层动态时段划分的配电网重构

动态网络重构能有效降低配电网的网络损耗以及分布式电源的弃风弃光量,为此提出了基于双层动态时段划分的配电网重构方法。上层优化中以网损成本与弃风弃光惩罚费用之和最小为优化目标,决策变量为主动管理元素的出力;下层优化中则以网损最小为目标函数来确定各时段开关状态量。为了减小模型的规模与复杂度,提出了将割集法作为辐射状约束的表示方法。同时,将该模型转化为混合整数二阶锥规划模型,并结合和声搜索算法对其进行求解。通过改进IEEE 33节点系统进行仿真,验证了所提方法的实用性和有效性。     

馈线自动化中环网开关状态组合优化算法

针对配电网中馈线上的开关繁多,网络重构困难的情况,采用遗传算法进行配电网馈线上开状状态的优化组合,在满足用户供电可靠性的前提下,使网损最小,支路不出现过负荷,网络结构最优等,以实现配电网重构,通过算例,说明该方法是行之有效的。     

LOSS REDUCTION IN DISTRIBUTION NETWORKS USING NEW NETWORK RECONFIGURATION ALGORITHM

ABSTRACT

Network reconfiguration is an operation task, and consists in the determination of the switching operations such to reach the minimum loss conditions of the distribution networks. In this paper, a general formulation of the network reconfiguration for loss minimization is given for the optimization of distribution loss reduction and a solution approach is presented. The solution employs a search over different radial configurations, created by considering branch exchange type switches. The solution algorithm for loss minimization has been developed based on the two stage solution methodology. The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. For this purpose a simple-to-use formula, called loop loss reduction formula, has been developed. To find a branch exchange, which results in the maximum loss reduction in the loop, the second stage applies a proposed technique called distance-center technique. Therefore, the solution algorithm of the proposed method can identify the most effective branch exchange operations for loss reduction, with a minimum computational efforts. The solution algorithm of the proposed method has been tested, with very promising results, on a 69-bus radial distribution system. Test results prove that, via proposed network reconfiguration for loss minimization, real power loss is reduced significantly, and that the voltage profile of the network is considerably improved. As compared to the established methods the proposed method eliminates the need to run numerous load flows.     

兼顾供电可靠性和经济性的多目标网络重构

提出了基于隐含并行寻优思想的兼顾供电可靠性提高和网损降低的配电系统多目标网络重构算法。该算法采用了大规模配电系统三相潮流计算和可靠性评估方法,实现了配电系统可靠性与经济性水平的综合最优化。该算法具有不依赖于网络开关的初始状态,也不受初始联络开关的操作次序的影响,可以高效地求解系统的有效解,实现多目标综合优化的特点。算例结果表明,该算法是灵活和高效的。     

基于渔夫捕鱼优化算法的配电网络重构

针对正常运行条件下配电网络重构问题,提出一种基于模拟渔夫捕鱼寻优算法(SFOA)的配电网络重构算法。以有功网络损耗最小为目标函数,建立配电网络重构的数学模型,并采用易于编码实现、寻优能力较强的渔夫捕鱼算法对重构模型进行求解。根据配电网络的特点,应用一种基于网孔开关的编码策略,在不背离算法本身搜索方法前提下,简化移动搜索和收缩搜索,以实现对解空间的全局搜寻。最后利用Visual C++对IEEE-33节点算例进行重构,结果表明,提出的方法是有效可行的。     

以配电网运行效益最优为目标的网络重构

目前配电网重构模型大多以网损最低为目标函数,并没有考虑配电网的可靠性和停电事故带来的经济损失。针对这个现状,提出以配电网运行效益最优为目标的网络重构。首先介绍了配电网经济性与可靠性指标及其计算方法,并通过平均电价折算倍数法定量的计算停电损失费用。然后,以配电网运行损失费用最低为目标函数构建重构模型。最后在网络等效化简的基础上通过混合粒子群算法,求得配电网的运行效益最优时的开关状态。     

Joint Optimization for Power Loss Reduction in Distribution Systems

In distribution systems, network reconfiguration and capacitor control, generally, are used to reduce real power losses and to improve voltage profiles. Since both capacitor control and network reconfiguration belong to the complicated combinatorial optimization problems, it is hard to combine them efficiently for better optimization results. In this paper, a joint optimization algorithm of combining network reconfiguration and capacitor control is proposed for loss reduction in distribution systems. To achieve high performance and high efficiency of the proposed algorithm, an improved adaptive genetic algorithm (IAGA) is developed to optimize capacitor switching, and a simplified branch exchange algorithm is developed to find the optimal network structure for each genetic instance at each iteration of capacitor optimization algorithm. The solution algorithm has been implemented into a software package and tested on a 119-bus distribution system with very promising results.     

计及分布式电源接入的配电网重构

分布式电源的接入使得配电网重构需要考虑更多的安全因素。基于配电网支路潮流模型,建立以重构周期内网络有功损最低,以满足分布式电源接入下网络运行安全为约束的配电网重构。为有效求解该重构数学模型,利用凸松弛方法将原问题中二次项进行松弛,使之形成混合整数二阶锥规划形式,从而可利用YALMIP商业软件进行高效求解。最后,通过改进的IEEE 33节点测试系统进行仿真分析,并与现有基于粒子群算法及启发式算法的配电网重构方法进行对比,结果表明基于凸优化技术的重构结果不仅能够有效避免算法陷于局部最优,而且稳定性好、计算效率高。     

计及过程安全性的配电网重构开关顺序优化

配电网重构过程应采用合理、可靠的开关操作顺序以避免对配电网的稳定运行产生冲击。采用改进的二进制粒子群算法求取配电网重构解集,对迭代过程中的无效粒子进行随机性的坐标修正,提升搜索效率;提出配电网重构实施过程合环、解环应满足的安全性约束,并应用戴维南等效模型计算合环冲击电流;提出用于求解计及过程安全性的配电网重构开关顺序的递归算法,搜索过程遵循贪心策略;针对递归过程中的无效中间解,以二进制编码方式记录,避免重复计算。IEEE 33节点系统、PGE 69节点系统算例结果验证了所提方法的有效性。     

基于引力搜索算法的含分布式电源配电网重构

分布式电源接入配电网将直接改变潮流分布,而网络重构通过改变开关的开合状态以提高供电的可靠性和经济性。以降低网损和缺供电量为目标,以可调度DG的有功输出和开关状态为优化变量,建立多目标协调优化的配电网络重构的数学模型。将引力搜索算法、Pareto最优解理论和模糊决策理论相结合,提出了求解上述模型的多目标混合优化方法,以实现配电网结构和DG出力的协同优化。通过对IEEE33节点测试系统的仿真结果,表明所提出方法能够实现DG出力和网络重构的综合优化和多目标优化,并且在全局寻优能力和收敛速度上表现出色。     

含微电网的配电网可靠性最优化

提出了一种含微电网的配电网可靠性最优化模型和算法。目的是在引入微电网后,在不增加投资的条件下,通过改变网络结构来达到可靠性提高的最大化,为规划运行人员提供决策参考。模型以系统平均停电频率指标、系统平均停电持续时间指标、系统平均供电不可用率指标以及系统平均供电量不足指标的加权组合的最小化为目标函数,以系统安全稳定极限以及微电网运行特点为约束条件。设计了基于可靠性的启发式的开关交换算法对模型进行求解。改进了传统的牛顿法,使之适用于含微电网的配电网的重构特点。算例分析表明所建模型在优化网络结构,改善负荷分布以及提高网络整体可靠性等方面具有积极作用。     

采用时段动态划分和分层优化策略的配电网重构

为更好地处理配电网动态重构中重构时刻、开关操作费用、降损效果之间的平衡问题,提出了采用时段动态划分和分层优化策略的配电网重构方法。首先利用功率矩法进行重构时段动态划分,该划分方法可控制最大重构次数;然后利用免疫算法进行分层优化,第1层优化用以网损最小为目标,采用传统静态重构优化方法确定各时段内不考虑开关动作次数限制及操作费用的开关动作方案,并将该开关动作方案作为第2层优化的搜索空间,且第2层优化中加入了开关动作次数限制及操作费用约束,根据方案运行费用最低原则确定最优重构方案。算例结果验证了该方法的有效性。     

An improved distribution network reconfiguration method based on minimum spanning tree algorithm and heuristic rules

This paper presents an improved distribution network reconfiguration method with the goal to minimize active power loss. The proposed method combines the minimum spanning tree (MST) algorithm and improved heuristic rules. It consists of three procedures. The first procedure calculates the branch (edge) weights with bus (vertex) voltages, and then carries out preliminary optimization with MST algorithm to get a local optimal solution. The second procedure gets alternative optimal solution based on the improved heuristic rules. Then during the third procedure, the optimal solution can generally be obtained through correcting the results. The algorithm does not rely on the initial network topology. The local optimal solution, solved by MST algorithm, provides a favorable initial condition for the subsequent optimization procedures. Further with the improved heuristic rules, the amount of the candidate switches can be significantly reduced. Two typical test systems, 33-bus system and 69-bus system, and a real 210-bus MV utility distribution system verified the feasibility and effectiveness of the proposed method. The method has higher efficiency and can be used to the large distribution systems.     

混沌遗传混合算法在配电网重构中的应用

指出网络重构是配电系统运行和控制的手段,也是配电管理系统的重要内容。考虑配电网运行特点,建立了以有功网损最小为目标的配电网重构数学模型,并计及潮流、电压、容量及辐射状运行等约束条件。针对该模型的特点,采用一种新型混沌遗传混合算法对配电网进行重构计算,该算法既具有遗传算法的全局性和并行性,又具有混沌搜索的遍历性和快速性。将该算法用于IEEE33节点系统重构计算,并与重构前、单一遗传算法重构结果进行比较,证明了所提出混沌遗传混合算法的有效性和快速性。     

Optimal reconfiguration of electrical distribution network using the refined genetic algorithm

This paper proposes an improved method to study distribution network reconfiguration (DNRC) based on a refined genetic algorithm (GA). The DNRC model, in which the objective is to minimize the system power loss, is set up. In order to get the precise branch current and system power loss, a radiation distribution network load flow (RDNLF) method is presented in the study. The refined genetic algorithm is also set up, in which some improvements are made on chromosome coding, fitness function and mutation pattern. As a result, premature convergence is avoided. The proposed approach is tested on 16-bus and 33-bus distribution networks. Study results are given in the paper.     

Oppositional krill herd algorithm for optimal location of capacitor with reconfiguration in radial distribution system

The delivery of power from sources to the consumer points is always accompanied of power losses. Basically, active losses in distribution systems can be reduced by optimal reconfigurations of the network. Optimal capacitor allocation problem in reconfigured distribution network is a challenge of researchers for several decades. This paper presents a computationally efficient methodology namely, krill herd (KH) algorithm to find optimal location of capacitor and optimal reconfiguration in order to minimize real power loss of radial distribution systems. Moreover, the opposition based learning (OBL) concept is integrated with KH algorithm for improving the convergence speed and simulation results. In order to show the usefulness and supremacy, the conventional KH and proposed oppositional KH (OKH) algorithms are tested on 33-bus and 69-bus radial distribution networks. The simulation results of the proposed methods are compared with fuzzy multi-objective approach and non dominated sorting genetic algorithm (NSGA). The solution results show that OKH technique could generate better quality solutions and better convergence characteristics than those obtained by conventional KH algorithm and other existing optimization techniques available in the literature. Results also show the robustness of the proposed methodology to solve reconfigured distribution network (RDN) problems.     

Effect of network reconfiguration on power quality of distribution system

Effect of network reconfiguration on power quality issues of distribution system has been investigated. The problem of network reconfiguration is reformulated with an objective to improve the power quality of the distribution system. Along with the traditional objective of loss minimization, power quality related objectives such as minimization of harmonic distortion of the voltage waveform, minimization of voltage unbalances at the nodes and maximization of sag voltages are identified as the objectives of reconfiguration. Branch exchange technique has been used to establish each of the objectives. The problem has also been formulated as a multi-objective optimization problem. The multiple objectives are, however, incorporated into a single objective using weighting multipliers and branch exchange technique has been judicially applied to take care of all the objectives. It is found that network reconfiguration can be used as an effective tool to improve the power quality of distribution system. Besides, the distributed energy sources also have great impacts on distribution network, as their size and locations are found to have great importance on the power loss, voltage sag, voltage harmonic distortion and unbalance. The effectiveness of the network reconfiguration on power quality issues have been studied on 25-bus network and IEEE 33-bus network with and without presence of distributed generation and VAr sources.     

配电网重构的逐级开关状态互换法

配电网重构是一个多目标、多约束、离散的非线性组合优化问题。根据配电网的特点,结合开关交换原理和网络构建算法,提出了开关状态互换的概念,并对其实现优化的原理进行了详细分析,表明可以收敛到最优解。利用启发信息简化寻优途径,在求解过程中运用禁忌思想,避免不必要的重复计算,大大加快收敛速度。将配电网供电恢复和优化重构统一考虑,并考虑了电容器的投切,为运行人员提供满足系统电压、容量和拓扑约束的配电网运行结构和开关操作列表,构建了配电网的优化运行方式。算例表明该算法是有效的。