基于DAOP算法的配电网电容器优化投切

配电网电容器补偿使负荷无功功率具有就地平衡的特点,符合离散上升优化算法(Discrete Ascent Optimal Programming,DAOP)的应用条件.提出了1种基于DAOP算法的电容器优化投切算法,该方法以划分的子树为优化单位,应用DAOP算法得到电容器投切组数的浮点值,并进行归整.算法继承了DAOP算法计算效率高、易考虑各种约束条件且不存在收敛问题的优点,以子树为单位分别归整,避免了统一归整计算量大且易陷入局部最优解的缺点.不同规模的配电网络分析计算结果验证了算法的准确性和实用性.     

配电网重构及电容器投切综合优化方法

提出了以网损最小为目标的配电网重构及电容器投切综合优化方法。采用有效减小生成树数量法进行网络重构,确定网损小于参考网络损耗的辐射状网络;利用改进电容器投切作用范围法进行电容器投切,避免了交替迭代算法只对网损最小生成树进行电容器投切的问题。电容器投切后,根据支路交换法的网损估算公式判别电容器有投切网络是否需要重构,提高了计算效率。IEEE 69节点算例验证了方法的有效性。     

含分布式电源的配电网综合优化重构

分布式电源(DG)的接入对配电网重构带来诸多影响,使含DG的配电网重构难以用传统模型来描述。为了充分发挥DG对配电网的有利作用,将DG视为可调度设备,建立了以网络开关组合、DG注入功率、DG位置为控制变量的配电网综合优化重构模型,采用量子进化算法(QEA),以网损最小为目标函数,对模型进行求解,降低了配电网的有功损耗。采用IEEE33节点测试系统进行仿真计算,结果表明了该方法是正确、有效的。     

考虑负荷与分布式电源变化的配电网动态重构

配电网动态重构是实现配电网架优化运行的重要手段,随着电网中分布式电源(Distributed Generator,DG)的大量接入,实际配电网中负荷需求和DG的出力在不断变换,以往静态重构无法满足配电网实际运行要求.本文建立了以网络损耗、电压偏移和弃电率为优化目标的配电网重构模型,针对动态重构时段划分问题,综合考虑负荷...     

考虑分布式电源出力调整的多目标配电网重构

配电网重构可以提高配电网运行的经济性和安全性,而分布式电源(Distributed Generator,DG)加入配电网直接影响潮流分布,对配电网重构将产生较大影响。考虑到DG对配电网重构的影响,以开关状态、DG出力为优化变量,建立了以网络损耗、负荷均衡化率最小为目标函数的多目标优化模型。将生成树、蚁群算法和遗传算法相结合,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。该方法利用基于生成树原理的蚁群算法对配电网结构进行优化,保证蚂蚁路径满足网络拓扑约束,有效提高了可行解的数量;采用Pareto最优遗传算法对分布式电源出力进行优化,可获得满足多目标需求的若干优化方案。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。     

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。     

计及分布式电源的配电网重构研究

分布式电源因其独有的环保性和经济性,在电力系统中拥有广阔的发展前景,但同时对配电网络的运行控制等方面产生了重大影响。研究了计及分布式电源的配电网络重构,采用了一种适合于含分布式电源的配电网络重构的改进二进制粒子群优化算法,并建立了计及分布式电源的配电网络辐射状运行判定依据。最后对IEEE33节点测试系统进行仿真,表明本文所用的方法是合理有效的。     

计及分布式电源动态行为的配电网重构优化策略

解决分布式电源高渗透率地区电压越限的根本方法是实施合理的配电网规划。现有方法存在着人工智能算法初始域搜索半径过大以及动态时段划分与拓扑寻优分离的问题。引入半不变量法计算随机潮流来处理分布式电源动态行为带来的不确定性,并采用改进的NSGA-II算法实现配电网重构,提出了一种计及分布式电源动态行为的配电网重构概率约束优化策略和求解方法。特别提出了在网架寻优的基础上再在时间层面上依据优压参数再次整合优化来构建配电系统动态重构数学模型,最后采用嵌套基因回路搜索策略改进NSGA-Ⅱ算法并求解上述优化模型,以解决传统配电网规划中对强相关性随机变量考虑较少的不足。IEEE-33节点配电系统算例验证了所提方法的有效性。     

含分布式电源的配电网优化运行研究

针对分布式能源大规模接入配电网带来的配电网规划和电能质量等问题,进行配电网优化运行研究。从分布式电源给配电网带来的影响出发,对配电网重构技术、分布式电源位置和容量优化及滤波器选型和位置优化三个角度进行了综述,同时分析总结配电网优化运行的建模方式和约束条件,并围绕多目标非线性且多约束的组合优化问题求解算法进行了梳理归纳,对配电网优化运行做总结与展望。     

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。     

考虑网络结构优化的含风电配电网多目标重构

为了提高配电网的供电可靠性,从网络自然连通性角度,引入网络抗毁性指标作为配电网重构的一个新目标函数。同时考虑风电出力的随机性与间歇性,根据风速区间及风速概率密度函数构建多个风电出力随机变量,以及对应概率。在此基础上,以开关状态为优化变量、风电出力为随机变量以及在置信水平下的网络损耗最小为另一个目标函数建立了基于机会约束规划的含风电的配电网多目标重构模型。应用改进蚁群算法,结合生成树策略保证蚂蚁路径满足网络辐射状网络拓扑约束,求解所建配网重构模型,并利用Pareto寻优得到最优解集。IEEE33节点和PGE69节点系统算例仿真结果验证了该模型和算法的有效性。     

Extended flow algorithm for online reconfiguration of large‐scale distribution system with interconnected distributed generators

The interconnection of distributed generators (DGs) in a power system increases the difficulty of managing the system. The minimization of the voltage deviation by network reconfiguration is an important requirement for dealing with the issue. We had previously developed a reconfiguration technique, named the intelligent flow algorithm (IFA), for determining the optimum or suboptimum network configuration within a short computation time. In the present paper, we propose an extension of IFA, named the extended flow algorithm (EFA), for more effective determination of the optimal network configuration of a distribution system containing massive installations of DGs. EFA is a two‐stage method in which the configuration that produces uniform power supply, referred to as the balanced configuration, is first generated, and then used to seek the optimal configuration using an improved branch exchange approach. Accordingly, EFA is more simplified to improve its computation speed on large‐scale systems. The algorithm was tested by case studies of different test distribution systems in the MATLAB environment, and was confirmed to have high performance to cope with DG installations and large‐scale systems. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A smart distribution system reconfiguration algorithm with optimal active power scheduling considering various types of distributed generators

This paper presents an efficient way of solving the distribution system reconfiguration (DSR) problem in electrical power systems with consideration of different types of distributed generators (DGs). The objective of a DSR is to minimize the system power loss while satisfying the system constraints and keeping the topology of the system radial. In this paper, a new DSR algorithm based on a modified particle swarm optimization (PSO) is proposed to incorporate DGs with the constant voltage control mode. The proposed method is very efficient because it avoids an extra iteration loop for computing the reactive power at PV buses in order to keep the voltage at a specified magnitude. Furthermore, if the reactive power requirement is not met in between the extreme limits, the proposed algorithm strictly searches for the best possible tie switch combination to simultaneously reduce the power loss and ensure that the DGs operate in PV mode within acceptable reactive power limit. The proposed algorithm also integrates hourly DSR with optimal DG active power scheduling considering the DG type, generation limit constraints, and the allowable DG penetration level. The validity and the effectiveness of the proposed method has been tested using standard IEEE 33‐bus and 69‐bus distribution networks with various case studies. Test results show that the proposed method is robust and delivers a minimal average power loss compared with different methods, and it efficiently models DGs in DSR, demonstrating that the presence of DGs can further reduce the system loss. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Optimal switching sequence path for distribution network reconfiguration considering different types of distributed generation

Minimizing power losses in a distribution system is commonly realized through optimal network reconfiguration. In the past, network reconfiguration research was focused on planning, where the final configuration with the lowest power losses was the main goal. However, power losses during switching operations from the initial state to the final state of the configuration were not considered. This paper presents the optimal switching sequence path to minimize power losses during the network switching operation. Apart from this contribution, the simultaneous optimal network reconfiguration for variable load network and distributed generation (DG) output is also proposed. The proposed methodology involves the (i) optimal network reconfiguration with variable load and DG output simultaneously, and (ii) the optimal sequence of switching operations required to convert the network from the original configuration to the optimal configuration obtained from (i). The selected optimization technique in this work is the firefly algorithm. To assess the capabilities of the proposed method, simulations using MATLAB are carried out on IEEE 33‐bus radial distribution networks. The results demonstrate the effectiveness of the proposed strategy to determine the sequence path of switching operations, as well as the optimal network configuration and optimal output of DG units. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A dynamic method for feeder reconfiguration and capacitor switching in smart distribution systems

In distribution systems, feeder reconfiguration (FR) can lead to loss reduction, reliability improvement and some other economic savings. These advantages can be intensified by proper control and switching of Capacitor Banks (CBs). In this paper, using Ant Colony Optimization (ACO) technique, a novel method is proposed for simultaneous dynamic scheduling of FR and CB switching in the presence of DG units having uncertain and variant generations over time. This method is applicable to both smart and classic distribution systems. While for the latter, state estimation method should be used to estimate the loads at different buses by employing a limited number of measurements. The objective of this method is to minimize the total operational cost of the grid, including the cost of power purchase from the sub-transmission substation, cost of customer interruption penalties, Transformers Loss of Life (TLoL) expenses, and the switching costs (CBs and disconnecting switches). To perform this study, the planning period is divided into several intervals for each of them the network topology and CBs reactive power are determined to satisfy the objective function. Additionally, due to the curse of dimensionality, a Case Reduction Technique (CRT) is proposed in order to decrease the computational burden of the proposed method. Finally, the efficiency of the proposed method is verified through its application on the IEEE 118-bus distribution test system, and evaluating its economic and operational characteristics.     

分布式电源并网动态无功优化调度的研究

根据分布式电源并网的控制特性,将分布式电源设计为电压控制型和无功补偿型,考虑其与地区电网的电压无功控制手段相结合,参与地区电网动态无功优化调度。建立以降低地区电网网损、抑制电压波动为综合目标的地区电网模糊动态无功优化调度模型。在该模型中,通过构造模糊评价函数,将目标函数转化为对优化结果的满意度,并利用自适应权重法将综合目标进行归一化处理。最后采用改进遗传算法有效求解含分布式电源的地区电网动态无功优化调度策略。算例表明,提出的模型和方法是合理的,具有一定参考价值。     

基于二进制量子粒子群算法的含分布式电源配电网重构

配电网重构是一个复杂的非线性组合优化问题。为了克服基本优化算法易陷入局部最优解的问题,提出了一种改进的二进制量子粒子群算法(BQPSO),对含分布式电源(DG)的配电网重构模型进行求解。通过引入遗传算法的交叉操作和变异操作来避免早熟来提高算法的全局搜索能力,改进了算法的性能。并且选择了适当的不可行解处理方式来提高了算法的计算效率。最后通过对IEEE33节点配电系统进行仿真,验证所提算法在求解重构问题时得到的解更好,收敛速度和全局寻优能力都有提升。     

一种考虑DG出力优化分配的配电网重构方法

分布式电源接入(DG)电网将变为常态,提出了一种考虑DG出力优化分配的以降低系统网损为优化目标的重构算法。首先基于DG的发电成本,采用复制动态算法(Replicator Dynamics, RD)离散化求解,经过进化博弈之后获得DG出力的优化分配。然后,分三个优化过程实现配电网的优化重构求解。初始优化利用最小生成树算法寻找一个较优的初始解,二次优化基于改进的启发式规则对候选开关进行评价得到最优开关及二次优化解。经过第三个优化过程的修正,一般可以得到最优重构方案。算法不依赖网络的初始拓扑;改进的启发式规则可以减少待评价候选开关的数量,提高算法的计算效率;而通过修正可克服环路对进化规则的影响,得到(近似)最优解。两个典型算例结果检验了算法的有效性和可行性。     

主动配电网优化技术研究现状及展望

分布式电源(distributed generation,DG)和电动汽车的大量接入、智能家居的普及、需求侧响应的全面实施等显著增强了配电系统规划与运行的复杂性,同时,未来的配电网对规划与运行的优化策略提出了更高的要求。作为未来配电网的一种发展模式,主动配电网(active distribution network,ADN)开始受到人们的关注。介绍了ADN的概念和内涵,从规划和运行2个方面总结了ADN优化技术的国内外研究现状和关注重点,并从"源-网-荷"互动的综合优化、多周期优化及其协调配合、分层分布式优化策略等3个角度对其未来的发展趋势进行分析和梳理。     

Determination method for loss‐minimum configuration considering reconnection of distributed generators

In the field of electrical power system, various approaches, such as utilization of renewable energy, loss reduction, and so on, have been taken to reduce CO₂ emission. So as to work toward this goal, the total number of distributed generators (DGs) using renewable energy connected into 6.6‐kV distribution systems has been increasing rapidly. The DGs can reduce distribution loss by appropriate allocation. However, when a fault occurs such as distribution line fault and bank fault, DGs connecting outage sections are disconnected simultaneously. Since the simultaneous disconnection of DGs influences restoration configuration and normal configuration after the restoration, it is necessary to determine the system configuration in the normal state considering simultaneous disconnection of DGs. In this paper, the authors propose a computation method to determine the loss minimum configuration in the normal state considering reconnection of DGs after simultaneous disconnection by fault occurrence. The feature of determined loss minimum configuration is satisfying with operational constraints even if all DGs are disconnected from the system. Numerical simulations are carried out for a real‐scale distribution system model with 252 sectionalizing switches (configuration candidates are 2²⁵²) and 120 DGs (total output is 38.46 MW which is 23% of total load) in order to examine the validity of the proposed algorithm. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(4): 7–14, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21142