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。     

考虑DG及负荷时序性的多目标配电网重构与DG调控综合优化规划

为解决分布式电源（distributed generation,DG）出力及负荷的时变性给实际配电网调度所造成的不利影响,使配电网的优化规划方案更加切实可行,提出了一种基于配电网重构和DG选址定容结合的多目标粒子群动态优化模型,该模型以配电网有功损耗、电压偏差及经济成本为优化目标,考虑负荷及DG出力的时变性,对配电网络重构和DG调度进行综合优化求解。通过基于随机森林模型（random forest,RF）及长短期记忆神经网络(long short-term memory,LSTM)模型的混合预测模型对配电网负荷及DG出力进行预测。采用经帕累托最优理论改进的粒子群算法得到配电网重构及DG调控的帕累托最优解集并利用模糊隶属度函数法来确定帕累托最优解集中的最佳配电网调度方案。基于IEEE 33标准测试系统设计多个算例进行仿真分析,结果表明,所提考虑负荷及DG出力时序性的配电网重构和DG调度联合优化模型可显著改善配电网络运行的经济性和稳定性。     

基于路径描述模型的城市电网负载均衡方法

负载均衡是降低城市电网运行风险、提高系统运行质量的有效手段,但现有负载均衡研究方法无法兼顾多层转供可能性和方法最优解的获取。对此,提出一种基于路径描述模型的城市电网负载均衡方法,以路径通断状态为变量,将问题转化为混合整数线性规划问题,将负载率控制纳入约束条件,同时以开关操作次数最少为目标函数,求解结果为综合考虑均衡性和可靠性的优化网络拓扑。经算例验证,该方法可有效降低系统主变压器的平均负载率以及负载率差异波动性,降低系统损耗,提升系统可靠性。     

基于网架结构相似性和适应性的主动配电网动态重构

为了提升主动配电网对可再生能源的消纳能力、优化分布式电源(DG)入网环境,提出了一种基于网架结构相似性和适应性的配电网动态重构策略。首先,以各单位时段内DG出力最大为目标进行静态重构。然后,从网络拓扑结构量的角度提出了开关状态相似度和改进节点介数相似度两个指标,根据网架结构相似度确定合并时段。随后,从运行状态量的角度定义了网架结构适应性,再依据该指标来客观指导合并时段内最优网架的选择。针对含DG的配电网静态重构问题,提出了一种基于趋化步长自适应调整的改进型细菌觅食算法(IBFA)进行求解。最后,采用PG&E 69节点系统验证了所提重构策略及算法的正确性与有效性。     

考虑负荷控制的有源配电网故障恢复策略

主动配电网的建设使得负荷控制成为电力系统日常调度手段之一。根据有源配电网的负荷灵活控制特性,提出了考虑负荷控制参与的有源配电网故障恢复策略。基于目前配电网仍存在大量手动开关的现状,故障发生时,由于开关操作时间较长,不利于迅速形成孤岛恢复失电负荷。首先利用自适应选择数学模型的负荷控制策略,快速切负荷形成孤岛,充分发挥DG的出力,保障重要负荷的不间断供电;然后对整个有源配电网重构优化,以网络损耗小、开关操作次数少为目标建立优化模型,采用环路编码策略,利用NSGA2算法进行求解。算例表明,所提出的策略能有效解决有源配电网故障恢复问题。     

基于负荷受电路径电气剖分信息的配电网重构算法

大规模配网重构问题的非线性组合优化特点对计算方法的效率造成了极大困难。该文应用交流支路电气剖分方法,由负荷受电剖分路径电气距离指标构造一种新的物理寻优方法。该方法在合环操作形成的闭环中根据电气距离为负荷分配供电路径,从而确定应断开的支路,使损耗降到最低。同时,根据定义的单位功耗以及物理规则确定需计算电气距离的负荷节点以减少运算量,并通过优化待处理分段开关的顺序以保证能寻找到更优良的解。由于算法属于物理寻优方式,避免了不收敛或者难收敛的情况。IEEE69系统分析表明,算法具有快速求得优良解的特性,能够应用到大型配电网络重构问题。     

Optimal Installation of Different DG Types in Radial Distribution System Considering Load Growth

In power distribution network, the gradual increase in system load is a natural process, and it results in increased real and reactive power losses and reduced voltage profile. In this paper, optimal single and multiple installations of different types of distributed generation (DG) units are used to handle annual growth in system load, while satisfying system operational constraints. For load growth study, a predetermined growth in system annual load is considered. Minimization of system total real power loss is taken as the main objective, and optimal location and sizing of different DG types are determined using a hybrid configuration of weight-improved particle swarm optimization (WIPSO) with gravitational search algorithm (GSA) called hybrid WIPSO-GSA algorithm. The effect of load growth is studied using standard 33-bus radial distribution system, and the results illustrate significant reduction in system real and reactive power losses, enhancement in system voltage profile, and improvement in load carrying capacity of distribution feeder sections. Moreover, the economic benefits of DG on system annual load growth are also established. Also, the effectiveness of the proposed algorithm is demonstrated by comparing the results with other evolutionary optimization techniques.     

Comments on “A new heuristic approach for optimal reconfiguration in distribution systems” in 81 (2011) 282-289

This short communication is a discussion of the paper entitled “A new heuristic approach for optimal reconfiguration in distribution systems” introduced a new approach for optimal reconfiguration of radial distribution systems. Besides, a load flow algorithm based on graph theory was presented in order to give precise branch currents, node voltages and system power losses. In the abstract and in the conclusion section of the above mentioned study, the author stated that the results show that the performance of the proposed method is better than that of several methods available in other published articles, and that the proposed technique represents an improved, more efficient method which can easily solve the distribution network reconfiguration problem compared with those other methods. However, this conclusion can not be deduced from the results given by the author because with the optimal radial configuration given for the test system used, the power losses obtained are higher than those obtained by some of the other methods. So, the proposed final solution is worse.     

Optimal network reconfiguration for congestion management by deterministic and genetic algorithms

In this paper, the problem of finding the optimal topological configuration of a power transmission system is considered with the aim of providing system operators with a tool suited for congestion management. Network reconfiguration looks particularly appealing since it allows transmission system operators to alleviate overloads by means of switching operations that may avoid costly generation or load curtailments. The techniques of corrective switching proposed in the 1980s are profitably employed to formulate the problem of network reconfiguration for the purpose of congestion management. The solution of the resulting large-scale mixed-integer programming problem is carried out both by a deterministic branch-and-bound algorithm included in the CPLEX optimization package and by a genetic algorithm. Tests were performed on a 33-bus CIGRE test system and on an actual 432-bus network of Italian origin.     

考虑场景联合概率的主动配电网运行重构策略

分布式能源的大规模接入与电动汽车的普及使主动配电网的潮流波动更加剧烈。并且随着智能电网中技术的发展,配电网动态重构的频率将会进一步提升。以减少网络损耗、优化网络潮流为目的,提出一种主动配电网运行重构策略。对配电网重构模型与各元素建模分析,考虑时空分布的EV负荷与计及出力波动的风电、光伏电源;采用多场景模拟技术针对EV负荷与DG出力预测的不确定性进行若干离散联合概率场景的分解;为了使原始非凸非线性问题能够求解,采用二阶锥松弛技术对其进行优化,将问题转化为混合整数二阶锥规划(MISOCP)问题。算例结果证实了所提模型的有效性、鲁棒性与准确性。     

Optimal DG Allocation in Radial Distribution Systems with High Penetration of Non-linear Loads

This paper addresses the optimal distributed generation sizing and siting for voltage profile improvement, power losses, and total harmonic distortion (THD) reduction in a distribution network with high penetration of non-linear loads. The proposed planning methodology takes into consideration the load profile, the frequency spectrum of non-linear loads, and the technical constraints such as voltage limits at different buses (slack and load buses) of the system, feeder capacity, THD limits, and maximum penetration limit of DG units. The optimization process is based on the Genetic Algorithm (GA) method with three scenarios of objective function: system power losses, THD, and multi-objective function-based power losses and THD. This method is executed on the IEEE 31-bus system under sinusoidal and non-sinusoidal (harmonics) operating conditions including load variations within the 24-hr period. The simulation results using Matlab environment show the robustness of this method in optimal sizing and siting of DG, efficiency for improvement of voltage profile, reduction of power losses, and THD. A comparison with particle swarm optimization (PSO) method shows that the proposed method is better than PSO in reducing the power losses and THD in all suggested scenarios.     

考虑动态交通网络的综合能源配电网灾后紧急响应策略

为减少电力系统因突发自然灾害事件导致配电网大面积停电损失,提出一种考虑动态交通网络的综合能源配电网灾后紧急响应策略。首先,通过调整燃气轮机出力和基于分布式电源个数的多微网划分方法的网络重构对配电网负荷进行恢复,最大化快速恢复配电网中负荷;其次,根据网络重构后配电网结构和负荷恢复情况,采用移动应急电源基于动态交通网络模型的最短路径算法进行选择移动路径,进一步恢复负荷供电;最后,采用改造后的IEEE33节点配电网系统进行仿真分析,基于多种灾害场景验证所提方法的正确性和有效性。     

Impacts of load models and power factor control on optimal sizing of photovoltaic distributed generators in a distribution system

This paper studies the impact of optimal sizing of photovoltaic distributed generators (PV‐DGs) on a distribution system using different static load models (i.e., constant power, constant current, and constant impedance) and various power factor (PF) operations. A probabilistic approach with Monte Carlo simulation is proposed to obtain the optimal size of PV‐DG. Monte Carlo simulation is applied to predict the solar radiation, ambient temperatures, and load demands. The objective is to minimize average system real power losses, with the power quality constraints not exceeding the limits, i.e. voltage and total harmonic voltage distortion (THDv) at the point of common coupling (PCC). A modified Newton method and a classical harmonic flow method are employed to calculate the power flow and THDv values, respectively. An actual 51‐bus, medium‐voltage distribution system in Thailand is employed as a test case. Results demonstrate that the proposed method performs well to provide the optimal size of PV‐DG based on technical constraints. Further, the results show that the three static load models do not affect the optimal PV‐DG size but the model has a different impact for various PF operations. PV‐DGs may improve the voltage regulation and decrease the losses in distribution systems practically, but the THDv values could increase. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Optimal Allocation and Operating Point of DG Units in Radial Distribution Network Considering Load Pattern

Distributed generation (DG) is a new approach for solving some problems of older power networks. Due to the increasing power demand in recent power systems, the importance of power loss reduction and maintaining system voltages within an acceptable range has given rise to the wide use of DG units in power systems. On the other hand, unplanned and non-optimal application such as installation and operation of DG units might cause other technical problems. In addition, it is important to consider the load pattern in the network, and the best decision for DG unit's operation must be chosen accordingly. In this paper, a method is introduced in order to make the optimal placement and find an optimal operating point for the DG units, which means the power output of DG units, considering the load pattern of the network. This load pattern has an average load of 24 hr a day, four seasons a year. In the proposed method, optimization has two goals: first, is optimizing the DG unit's placement based on improvement of the voltage profile, and the second is operating DG units with optimum power factor, minimizing power loss, and improving voltage profile, with regard to the load pattern. In order to solve this problem, the gravitational search algorithm and genetic algorithm are used. The proposed method is applied on the IEEE 33-bus test system, and the result shows the effectiveness of the proposed method. In order to solve the optimization problem, MATLAB software is used.     

含分布式电源优化调度的配电网络重构

配电网络重构是配电网优化的重要措施,分布式电源（DG）接入配电网将改变网络潮流分布,直接影响网络重构结果,而网络重构引起的DG相对位置变化也将引起DG最优输出功率的变化,进行单个优化不能达到整体最优的效果。针对这一问题提出了一种含分布式电源优化调度的配电网络重构方法。采用改进最小生成树算法和改进粒子群算法将网络重构和DG的优化调度相结合进行交叉迭代。首先,进行DG的优化调度;其次,进行网络重构。只要网络结构发生变化,就需要重新进行DG优化调度,直到重构和DG优化调度均无操作时算法收敛,停止计算。实际算例表明,该方法能有效降低配电网的网络损耗、改善电压质量,可以达到配电网总体最优。     

考虑负荷变化的配电网动态分时段重构

针对负荷是动态随时间变化而我国负荷峰谷差大,提出了一种配电网动态分时段重构方法以满足实际要求。该方法将整个时区分成若干个连续的时间间隔,以网损最小为目标函数,分别进行各时间间隔静态重构,得到最优网损曲线以获得各时间间隔开关操作引起的网损下降量,再据此客观指导时段长度的划分,并通过分析不同时段数与网损下降量的关系,确定最优时段数,得出整个时区内比较理想的重构时段长度和数目,从而得到比较理想的可行解。最后通过IEEE经典算例的验证,结果表明所提方法的有效性。     

Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method

A great number of methods have been proposed for distributed generation (DG) placement in distribution networks to minimize the power loss of Medium Voltage (MV) lines. However, very few researches have been done for network configuration in parallel with the DG siting and sizing for the maximum system loss reduction. In this paper, a heuristic method based on “uniform voltage distribution based constructive reconfiguration algorithm” (UVDA) is proposed for the simultaneous reconfiguration and DG siting and sizing. The results obtained from the application of the proposed method on two well-known distribution networks and a real network clearly verify the robustness of the contributed technique. The simulation results demonstrate that the proposed approach is able to find the best solution of the problem found so far. Also, the presented method is applicable to real large-scale distribution systems to find the optimal solution in a very short period of time.     

Optimal reconfiguration of distribution systems with representation of uncertainties through interval analysis

The present work presents an approach for optimal reconfiguration of electrical distribution systems (EDS) to minimize energy losses considering uncertainties in the load demand and in the wind based distributed generation (DG). The optimization algorithm applied to solve the reconfiguration problem is based on the bio-inspired metaheuristic Artificial Immune Systems (AIS). An interval power flow model is used to obtain an interval energy loss from the representation of the uncertainties. The interval loss is used to guide the AIS algorithm through the search space. Network and operational constraints as the radiality and connectivity of the network as well as different load levels are considered. Well-known test systems are used to assess the impact of the uncertainties representation in the reconfiguration problem.     

基于模糊多目标协调优化的配电网络重构研究

配电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。建立以网损最小、馈线负载均衡指标最小、开关操作次数最少多个目标协调优化的配电网络重构的数学模型。引入模糊隶属度函数对各目标进行模糊化处理,根据模糊集理论的最大最小法则,将多目标优化问题转化为单目标非线性规划问题。应用禁忌算法对该配电网络重构模型进行优化求解。对某个69节点配电网络系统,比较分析了四种不同的优化方案,仿真结果验证了所提出模型和求解方法的正确有效。     

分布式电源的配电网重构和电容器优化投切

综合考虑最优潮流、配电网重构和电容器优化投切,建立了计及分布式电源的配电网经济运行模型。鉴于模型的复杂性,采用结合最优潮流和改进蚁群算法的混合优化方法进行求解。该方法将最优潮流嵌入改进蚁群算法中,利用最优潮流求解考虑网络安全约束的分布式电源优化调度问题,利用改进蚁群算法优化配电网结构和电容器档位。为了提高蚁群算法的优化效率,建立含有局部搜索蚂蚁的混合蚁群,平衡蚁群算法的全局和局部搜索能力。通过对16节点和33节点的测试系统仿真,表明提出的模型和算法正确有效。