基于改进粒子群算法的配网电容器优化配置

随着国民经济发展,配电网规模不断扩大。依照经验配置电容器的局限性日益显著,具体表现为电容器容量配置的不足或过剩,部分电容器需要时由于局部电压的限制而不能投入。将模拟退火粒子群算法用于解决配电网电容器优化配置问题,建立了相应的数学模型,目标函数为配电网有功网损费用、电容器的购置及安装总费用最小,该算法将电容器的安装位置及安装容量离散化,采用基于适应度值的动态阈值来控制实施局部搜索的粒子数目,来改善算法摆脱局部极值点的能力,提高算法的收敛速度和精度。对一个33节点配电网的电容器优化配置结果表明了模拟退火粒子群算法的合理性和优越性。     

基于SA-PSO的配电网电容器优化配置

应用模拟退火粒子群优化算法(simulated annealing particle swarm optimization,SA-PSO)求解配电网电容器优化配置问题,在同时考虑系统有功损耗费用和补偿电容器购买、安装和维护费用的基础上,建立了相应的数学模型.为了改善算法摆脱局部极值点的能力,提高算法的收敛速度和精度,采用基于适应度值的动态阈值来控制实施局部搜索的粒子数目.将其应用到一个IEEE 33节点配电网的电容器优化配置中,结果表明,模拟退火粒子群优化算法具有合理性和可行性.     

基于Tabu搜索算法的配电网电容器优化配置

应用Tabu搜索算法来解决配电网电容器优化配置问题，建立了相应的数学模型，目标函数为系统有功损耗费用和补偿电容器费用之和最小。文中在传统Tabu搜索法的基础上，利用灵敏度分析和嵌套Tabu搜索等方法对配电网电容器的安装位置和容量进行了优化配置。利用灵敏度分析可以产生较优的初始解，并在Tabu搜索中定义更好的邻域试验解，这样可以更快速地搜索到邻域内的最优解；嵌套Tabu搜索法对电容器安装位置和容量分别进行优化配置，保证可以搜索到整个可行域，从而能更有效地搜索全局最优解。用测试算例验证了文中算法的有效性和可行性。     

10kV配电网电容器的优化配置规划决策

配电网电容器优化配置规划决策系统从降损节能、改善电能质量的角度,侧重依据电网实际运行状态,利用智能分组算法,保证在各种运行条件下都能对电网无功补偿、电压调节提供最优的补偿容量组合;并针对当前的无功补偿投资预算,给出经济效益最佳的配置方案组合。配电网电容器优化配置规划决策系统科学、合理地解决了配电网电容器的补偿容量、补偿地点和补偿分组问题,算例及分析表明了该分组算法应用于配电网电容器优化配置的有效性和实用性。     

SOA结合模拟退火算法优化电容器配置研究

为了应对近年来不断增加的电力系统负荷,对配电网的电容器进行配置优化是十分必要和重要的,提出了一种SOA结合模拟退火算法运用到IEEE 33节点配电系统,并对电容器进行优化配置,建立相应的电容器优化配置模型。仿真结果表明,SOA结合模拟退火算法对于此类问题的求解具有一定的可行性及有效性,为电容器的优化配置以及缓解电力负荷提供了理论基础。     

基于改进遗传算法的电容器优化配置

提出一种改进的遗传算法,应用到配电网的固定电容器与可投切电容器最优容量的配置与安装位置的选择中。在算法中将电容器的安装位置与安装容量视为离散变量,将电容器购买费用,安装费用,维护费用与系统有功损耗支出的总和最小作为目标函数。并针对简单遗传算法的一些不足之处(如搜索效率不高和过早收敛),将遗传操作过程中的编码、选择、交叉、变异和中止条件进行了改进。然后将其应用在一个27节点的配电网络中,取得了良好的效果。     

一种适合于解决辐射状配电网电容器最优配置问题的遗传算法

提出了一种可解决辐射状配电网电容器最优配置问题的遗传算法.将电容器看作离散变量,对给定的目标函数求最佳的电容器安装位置和容量;设计了针对该问题有效的遗传因子,并对一个实际的配电网进行了计算,得到了较好的结果.对遗传算法用于辐射状配电网的电容器最佳配置问题进行了探讨.     

配电网无功优化规划软件包的研制与应用

分析了包头地区配电网进行无功优化规划的必要性,建立了综合考虑网损、电压偏差及电容器投资费用为最少的配电网无功优化规划数学模型．给出了适合于配电网的潮流计算方法和无功优化规划算法。在此基础上,采用Visual Basic6．0编程语言研制开发了配电网无功优化规划软件包,应用该软件确定配电网并联补偿电容器的最佳安装地点和容量。通过以包头地区配电网为实例进行的计算,证明了软件的实用性。     

基于改进GA的两种思路求解电容器优化配置

将一种改进的遗传算法应用到配电网电容器的优化配置问题中。该算法将电容器的安装位置与安装容量视为离散变量,将电容器购买费用、安装费用、维护费用与系统有功损耗支出的总和最小作为目标函数,提出了两种实现思路。思路一:先在最大负荷下定出电容器的安装位置和各节点最大安装台数,然后在此基础上计算其他负荷下电容器的投切情况与固定电容器的数目,再定出总收益。思路二:先在最小负荷下计算出固定电容器的数目,然后在此基础上计算其他负荷下所需安装的可投切电容器数目再定出总收益。针对简单遗传算法的一些不足之处(如搜索效率不高和过早收敛),将遗传操作过程中的编码、选择、交叉、变异和终止条件进行了改进。最后将其应用到一个27节点的配电网络中,结果表明这两种思路都是合理可行的。     

计及无功经济价值的配电网电容器优化配置

提出了一种计及无功经济价值的配电网电容器优化配置方法.分析了并联电容器接入系统后,对系统网损、容量释放产生的经济价值和其本身具备的能量经济价值,并从经济学角度确定了电容器优化配置的一般原则.根据电路网络基本原理的简化分析,推导出单位无功与系统网损的定量关系,进而得出单位无功降损的线性化表达,并将非线性的无功选址优化问题转化成含整型变量的线性问题.新的优化模型中定量地考虑了无功的安装成本和经济价值.仿真结果表明,相对于其他方法,该方法确定的无功安装位置和容量更经济,效果更加明显.     

An efficient optimal capacitor allocation in DG embedded distribution networks with islanding operation capability of micro-grid using a new genetic based algorithm

Capacitor banks are commonly used in electric distribution networks as a kind of reactive power sources. These sources are located in distribution networks for power factor correction, loss reduction, and voltage profile improvement. For these purposes optimal capacitor placement is needed to determine capacitors types, sizes and locations. Distribution system with Distributed Generation (DG) can have micro-grid that it will operate in both grid-connected and islanded modes of operation. The aim of this paper is to provide a method for optimal capacitor (fixed and switchable) placement in such a distribution network. The effect of different operation modes of DGs on the network is also investigated. The proposed method can guarantee the benefits of capacitor installation at different load levels. It is based on genetic algorithm (GA) with new coding and operators. Switching table of the allocated capacitors can be found through the proposed structure of the chromosome. Some case studies developed to illustrate the efficiency of the proposed method.     

配电网电容器优化投切的改进模型及算法

配电网电容器优化投切的目的是在实时运行阶段有效降低电网的有功损耗,同时避免电容器过多投切造成损毁。文章研究了考虑投切次数限制的配电网电容器优化投切问题,针对现有静态模型的局限性和动态模型的复杂性,提出了目标函数中计及投切代价的优化模型,将全局动态优化问题解耦为分段静态优化问题,在有效控制电容器投切次数的基础上大大缩减了解空间的规模。针对此模型,采用改进粒子群优化算法进行求解。算例分析表明文中的模型和方法在实用性、可行性和计算速度等方面均有良好表现。     

Allocation of capacitor banks in distribution systems through a modified monkey search optimization technique

This work presents a methodology for the allocation of fixed capacitor banks in electrical power distribution systems by applying a bio-inspired optimization technique. The goal is to optimize the distribution network operation over a planning horizon by minimizing the system losses with minimum cost of investment in capacitors. For this aim to be achieved, this work proposes improvements to the Monkey Search optimization technique to achieve a better representation of the capacitor allocation problem and to increase the computational efficiency. Distribution systems that are widespread in the literature are used to evaluate the proposed methodology.     

Maximum savings approach for location and sizing of capacitors in distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in radial distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. To calculate the energy savings and the deferral investment cost exactly, a load flow for radial distribution network is executed before and after the compensation. The proposed method has also been applied for compensating to an actual radial distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 s after 22,298 iterations demonstrates the ability of the proposed methodology for efficiently handling compensation problems.     

A hybrid optimization approach for distribution capacitor allocation considering varying load conditions

This work presents a new algorithm based on a combination of fuzzy (FUZ), Forward Update (FWD), and Genetic Algorithm (GA) approaches for capacitor allocation in distribution feeders. The problem formulation considers three distinct objectives related to total cost of energy loss and total cost of capacitors including the purchase and installation costs and one term related to total cost of produced power under peak load condition. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed methodology of this article uses an iterative optimization technique based on Forward Update approach which is embedded in a Genetic Algorithm framework. The fuzzy reasoning supported by the fuzzy set theory is used for sitting of capacitors and the GA is employed for finding the optimum shape of membership functions. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder along with a 34-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.     

Improved Harmony Algorithm and Power Loss Index for optimal locations and sizing of capacitors in radial distribution systems

In this paper, an Improved Harmony Algorithm (IHA) is proposed for optimal allocations and sizing of capacitors in various distribution systems. Initially, Power Loss Index (PLI) is introduced to get the highest candidate buses for installing capacitors. Then, the proposed IHA is employed to decide the most optimal locations of capacitors and their sizing from the elected buses by PLI. The objective function is designed to reduce the total cost and losses and consequently, to increase the net saving per year. The proposed algorithm is tested on three different radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight its benefits. Moreover, the results are introduced to verify the effectiveness of the suggested algorithm under different loading conditions.     

10kV架空线路无功优化算法的研究

针对10kV配电线路无功分散补偿的不足之处,为了进一步降低网损和提高用户电压,提出了在10kV配电线路安装杆上无功补偿设备的优化算法。该算法以年运行费用最小为目标函数,运用遗传算法求出最佳的补偿地点和最优补偿容量。IEEE33节点算例计算验证了该算法的正确性。