10 kV配电线路非节点无功优化算法

针对10kV配电线路无功分散补偿的不足之处,提出在10kV配电线路非节点处安装杆上无功补偿设备的优化算法,以进一步降低网损和提高用户电压。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(非节点)和最优补偿容量。算例计算验证了该算法的正确性。     

配电网高低压综合电压/无功优化方法

在10 kV线路上装设无功补偿装置可以有效地改善电压、提高运行经济性的前提下,提出了10 kV配电网高低压综合电压无功优化模型,该模型在传统的低压侧补偿、首端电压以及配变分接头调整控制的基础上融入了10 kV线路补偿控制,并提出了遗传算法应用于配电网电压无功优化时的初始群体产生两步法,介绍了采用该改进的遗传算法求解该综合优化模型的处理方法和主要步骤。采用门头沟一条实际的10 kV配电线路进行优化说明了将10 kV侧无功补偿纳入电压无功补偿模型进行综合考虑的必要性与可行性。     

配电网高低压综合电压/无功优化方法

在10 kV线路上装设无功补偿装置可以有效地改善电压、提高运行经济性的前提下,提出了10 kV配电网高低压综合电压无功优化模型,该模型在传统的低压侧补偿、首端电压以及配变分接头调整控制的基础上融入了10 kV线路补偿控制,并提出了遗传算法应用于配电网电压无功优化时的初始群体产生两步法,介绍了采用该改进的遗传算法求解该综合优化模型的处理方法和主要步骤.采用门头沟一条实际的10 kV配电线路进行优化说明了将10 kV侧无功补偿纳入电压无功补偿模型进行综合考虑的必要性与可行性.     

10kV及以下配电网无功动态补偿应用

针对河间市电力局10 kV线路应用传统无功补偿方式的局限性,从10 kV线路的无功补偿、10 kV配电变压器台区的无功补偿、用户无功补偿方面阐述了配电网无功动态补偿优化的实施方案.分析了10 kV及以下配电网无功动态补偿应用效果产生的经济效益,指出了无功动态补偿在农村配电网应用能够提高功率因数、平衡系统无功、降低线损.     

10kV配电线路无功优化的探讨

通过嘉善10kV配电用户负荷特性等实际情况分析,提出10kV配电线路应根据不同(分支)线路的功率因数特征进行无功补偿,确定补偿容量和补偿点选取方法以及补偿自动控制和保护的技术原则,对10kV配电线路并联电容补偿实施结果的经济效益进行了对比分析。     

10 kV配电线路无功补偿的选择

介绍了10 kV配电线路的现状和实施无功补偿的必要性,分析提出了10 kV配电线路无功补偿容量选取原则、安装地点选择计算方法,并结合电网发展的需要分析了自动控制的技术需求。采用本文介绍的办法,实地试装了两条线路,取得了理想的补偿效果。     

10kV配电线路无功补偿的选择

介绍了10 kV配电线路的现状和实施无功补偿的必要性,分析提出了10 kV配电线路无功补偿容量选取原则、安装地点选择计算方法,并结合电网发展的需要分析了自动控制的技术需求。采用本文介绍的办法,实地试装了两条线路,取得了理想的补偿效果。     

1OkV配电线路无功补偿的选择

介绍了10kV配电线路的现状和实施无功补偿的必要性，分析提出了10kV配电线路无功补偿容量选取原则、安装地点选择计算方法，并结合电网发展的需要分析了自动控制的技术需求。采用本文介绍的办法，实地试装了两条线路，取得了理想的补偿效果。     

10kV线路无功补偿技术在农网中的应用分析

无功补偿是节能降耗、改善电网电压质量、提高功率因数最方便、最经济有效的方法之一。随着农村用电负荷的迅速增长,部分供电半径大、负荷重的10 kV配电线路无法满足用户的需求,将线路无功补偿技术应用到10 kV农网线路中,是一种积极可行的手段。首先介绍了无功补偿的配置原则,然后介绍了10 kV线路无功补偿安装容量和安装位置的确定方法,最后介绍了10 kV线路无功补偿技术在德阳农网中的成功应用案例。     

10kV线路无功优化补偿系统

由于10kV线路中安装无功补偿装置补偿无功也存在不足,为进一步降低线损,提高用户电压质量,开发了10kV线路无功优化补偿系统。先运用非节点无功优化算法确定10kV线路无功补偿位置及补偿容量,在此基础上研制并安装了集无功自动补偿、电容器保护于一体的智能型户外无功补偿装置,经试运行分析,可有效提高电压质量水平,进而提高了运行的经济性。     

Bacterial foraging solution based fuzzy logic decision for optimal capacitor allocation in radial distribution system

This paper proposes a novel methodology for the optimal location and sizing of shunt capacitors in radial distribution systems. This method is based on a fuzzy decision making which using a new evolutionary method. The capacitor placement optimization problem includes: minimizing the cost of peak power, reducing energy loss and improving voltage profile. The installation node is selected by the fuzzy reasoning supported by the fuzzy set theory in a step by step procedure. Also an evolutionary algorithm known as bacteria foraging algorithm (BFA) is utilized in solving the objective multivariable optimization problem and the optimal node for capacitor placement is determined. The proposed approach is applied to 34-bus distribution system as a test study and the results are compared with previous method. The results show that this method provides more economic solution by reducing power losses, energy loss, total required capacitive compensation and show a good improvement in nodes voltage to be in the requested range. Comparison between the proposed method in this paper and similar methods in other research works shows the effectiveness of the proposed method for solving optimum capacitor planning problem.     

混合储能在配电网中的优化配置

单一蓄电池储能技术已应用于配电网中,作为备用容量和节省电能投资。鉴于单一蓄电池储能设备成本过高的问题,本文采用电池超级电容器混合储能(HESS)技术,建立以整个寿命周期内年均成本为最小的目标函数,以满足供电可靠性、调压、平抑大负荷功率冲击等为约束条件的容量优化配置模型。运用粒子群优化算法进行求解,与单一蓄电池储能作比较,验证了HESS混合储能在配电网中的经济性。     

New optimal placement of capacitors and dispersed generators using bacterial foraging oriented by particle swarm optimization algorithm in distribution systems

The shunt capacitor devices are utilized in distribution systems to possibly reduce reactive component of power losses. Besides, the dispersed generator (DG) units can be used to supply active power of loads and reduce active component of power losses. In this paper, by applying the multi-objective problem, optimal placements of these devices are determined based on bacterial foraging (BF) oriented by particle swarm optimization (PSO) algorithm (BF-PSO). The considered objective function includes the cost reduction of power losses and installation costs of shunt capacitor devices and DG units. Also, the problem solution at different load levels and the utilization of capacitor discrete values are performed for optimization. Finally, the proposed method is compared with genetic algorithm (GA), differential evolution (DE), and PSO methods. They are investigated on the IEEE 69-bus distribution system. The simulation results indicate the advantages of the proposed method for the optimization problem.     

基于改进蚁群算法的配电网电容器优化配置研究

提出一种改进蚁群算法求解辐射状配电网电容器优化配置问题,以系统的有功功率损耗费用和电容器的购买、安装和维护费用之和最小为目标函数,建立优化模型。以IEEE33节点系统为算例进行仿真分析,验证了算法的可行性和有效性。     

基于柔性互联技术的含高渗透率新能源配电网多目标优化运行

智能软开关（SOP）可控制潮流、提供无功补偿,进而改善配电网电压、降低网损。因此,针对可再生能源大规模接入配电网后电能质量下降问题,采用K-means算法构建风-光典型场景,同时建立了基于SOP、可投切电容器的含高渗透率分布式电源的主动配电网优化运行模型。该模型以电压偏差、系统网损最小以及系统运行成本最低为目标,综合考虑了能源利用率及系统运行稳定性。最后利用基于参考点的非支配排序方法的多目标优化算法（NSGA-III）进行求解,输出Pareto最优解集,并采用改进的IEEE 33节点系统对所建立模型的有效性进行了验证。     

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。     

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.     

基于二阶锥规划的交直流混合配电网优化调度

针对交直流混合配电网优化调度中控制变量多样化的趋势,以网损费用和弃光费用之和最小作为目标函数,综合考虑分布式电源、储能装置、电压源换流器、电容器组和静止无功补偿装置等控制变量集合,建立交直流混合主动配电网有功-无功多时段协同优化新模型,解决电压越限问题,实现功率快速补偿。针对变量维数增加引起的模型最优解精确性问题,采用二阶锥规划对非凸非线性问题松弛凸化,利用Cplex算法求得模型最优解。最后,通过拓展的49节点系统算例测试结果验证所提模型的有效性。     

Simultaneous placement of distributed generation and capacitors in distribution networks considering voltage stability index

With regard to widespread use of distributed generation in distribution network, its technical impacts in distribution network should be thoroughly analyzed. In this paper simultaneous placement of distributed generation (DG) and capacitor is considered in radial distribution network with different load levels. The objectives of the problem are reduction of active and reactive power loss, reduction of energy loss and improvement of voltage profile. Also effect of capacitor and DG on voltage stability improvement has been considered in the objective function. Memetic algorithm is used to find optimal solutions. This algorithm is combinatorial form of local search and genetic algorithm. The performance of the proposed method is assessed on a test distribution network.     

A genetic algorithm approach in optimal capacitor selection with harmonic distortion considerations

This paper reports the research findings of an innovative genetic algorithm approach for optimizing shunt capacitor sizes and their placement in radical distribution systems with the consideration of harmonic distortion limit due to the presence of nonlinear power electronic devices. The algorithm is based on a genetic algorithm solution technique to minimize cost under the additional constraints of maximum limit in harmonic distortion factor. A harmonic distortion calculation is embedded in the genetic algorithm solution routine to enhance the optimal capacitor allocation solution. Results of simulation show that the approach is effective for such a discrete value optimization problem.