A Petri net based protection monitoring system for distribution networks with distributed generation

Connection of distributed generation (DG) essentially changes distribution network operation and creates a range of well-documented effects varying voltage levels and short circuit currents. Among others, DG can alter protection system operations in distribution networks, leading to failure of reclosing, disconnection of healthy feeder or prevention of protection operation. This paper proposes a procedure, based on Petri nets and supported by a centralized monitoring architecture for monitoring failures of the protection systems in radial distribution networks. Some case studies applied to a real Italian distribution network proved the effectiveness of the proposed procedure that can therefore represent an effective solution to improve distribution systems reliability in presence of DG.     

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.     

A novel neural network and backtracking based protection coordination scheme for distribution system with distributed generation

With the increased installation of renewable energy based distributed generations (DGs) in distribution systems, it brings about a change in the fault current level of the system and causes many problems in the current protection system. Hence, effective protection schemes are required to ensure safe and selective protection relay coordination in the power distribution system with DG units. In this paper, a novel adaptive protection scheme is proposed by integrating fault location with protection relay coordination strategies. An automated fault location method is developed using a two stage radial basis function neural network (RBFNN) in which the first RBFNN determines the fault distance from each source while the second RBFNN identifies the exact faulty line. After identifying the exact faulty line, then protection relay coordination is implemented. A new protection coordination strategy using the backtracking algorithm is proposed in which it considers the main protection algorithm to coordinate the operating states of relays so as to isolate the faulty line. Then a backup protection algorithm is considered to complete the protection coordination scheme for isolating the malfunction relays of the main protection system. Several case studies have been used to validate the accuracy of the proposed adaptive protection schemes. The results illustrate that the adaptive protection scheme is able to accurately identify faulty line and coordinate the relays in a power distribution system with DG units. The developed adaptive protection scheme is useful for assisting power engineers in performing service restoration quickly so as to decrease the total down time during faults.     

应用边界保护原理提高分布式发电系统并网协调性的方法

为解决分布式发电系统与配电网保护的协调性问题,提出了一种新的分布式发电(distributed generation,DG)并网控制方法。由于在DG系统并网点上游和下游线路故障时,DG系统对电网保护的影响是不同的,因此提出在带有DG 系统的配电线路上装设阻波器构成线路边界的思想,采用行波边界保护模式,对DG系统并网点上游和下游故障进行选择性保护,进而保证配电线路故障后DG系统能够快速准确地解列,确保系统的安全运行,并最大限度地提高DG的利用效率。仿真结果和理论分析表明,新保护方法可提高DG与配电网的协调性,并可有效提高DG的利用效率。     

含分布式电源的配电网广域保护容错算法

随着分布式电源的引入,传统的配电网保护系统难以满足运行方式灵活多变的多DG配电系统的要求.为此,基于最大故障特征信息量准则提出了一种适用于含DG配电网的保护算法.该算法以广域保护原理为基础,以通信为支撑,仅利用电流量进行故障搜索方向的判别,适用于无PT通道的中低压配电网.算法分故障区域定位和故障区段定位两步完成.故障区...     

A novel probabilistic neural network‐based algorithm for classifying internal fault in transformer windings

The major function of protective devices in a power system is to detect the occurrence of faults and to isolate the faulty sections from the rest of the system. Much progress has been made in the development algorithms for detecting faults in power transformers, which depend on transients‐based techniques. This paper presents an algorithm based on a combination of discrete wavelet transforms and probabilistic neural networks (PNNs) for classifying internal faults in a two‐winding three‐phase transformer. Fault conditions of the transformer are simulated using alternative transients program/electromagnetic transients program (ATP/EMTP) in order to obtain current signals. The mother wavelet Daubechies4 is employed to decompose the high‐frequency components from these signals. All three phases of the differential current signals are used in the fault detection decision algorithm. The variations of first‐scale high‐frequency component that detects fault are used as an input for the training pattern. The training process for the neural network and fault diagnosis decision is implemented using toolboxes on MATLAB/Simulink. Various cases and fault types based on the Thailand electricity transmission and distribution systems are studied to verify the validity of the algorithm. Backpropagation neural network is also compared with the PNN in this paper. It is found that the proposed method gives satisfactory accuracy with less training time, and will be particularly useful in the development of a modern differential relay for a transformer protection scheme. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于改进灰狼算法的DG接入配电网反时限过电流保护定值优化

反时限过电流保护在含分布式电源的配电网中应用广泛,但其定值整定大多依赖工程经验,限制了实际的工程应用。为此,提出一种基于改进灰狼算法(GWO)的DG接入配电网反时限过电流保护定值优化方法,在保护动作特性方程和对保护灵敏性、速度性、选择性要求的基础上建立优化模型。为克服灰狼算法容易早熟、收敛精度低等缺陷,在保留可调参数少这一优势的前提下,引入了佳点集初始化、收敛因子指数衰减、变异和启发式参数确定这4种策略对灰狼算法做了改进。仿真算例验证了所提模型在两相和三相故障下的可行性与优越性,并探讨了时间级差对整定的影响、将来算法优化和工程应用的方向,为大规模DG接入配电网的保护定值优化问题提供了研究思路。     

储能设备接入配电网的新运行方式及其可靠性计算

随着越来越多的储能设备接入配电网,储能设备对配电网可靠性的影响引起人们的广泛关注。通过分析储能设备接入配电网后对配电网常用的两种保护系统的影响,提出了一种针对大量接入储能设备的、以断路器和隔离开关为保护系统的配电网的新的运行方式。当故障发生时,可以缩小故障影响范围和故障时间,从而提高配电网可靠性。文末采用混合法计算两种运行方式下IEEE-RBTS BUS 6系统不同位置负荷的可靠性参数,通过仿真运行数据可知,在储能设备接入配电网后,可以明显提升网络末端负荷的可靠性。     

Dynamic fault location method for distribution networks with distributed generation

This paper presents a new analytical time-based fault location algorithm for radial distribution networks with synchronous generators used for distributed generation (DG). The algorithm uses the voltage and current samples recorded at the main feeder head along with the scheduled injected active and reactive powers by the network synchronous generators to estimate the fault location. A full order synchronous machine model has been used to consider dynamic behaviour of the DG plants during fault transients. The algorithm, therefore, uses time domain analysis and is dynamic in the sense that it uses the updated synchronous machines and network data at each time step. The algorithm is implemented in two sequential steps. In the initialisation step, by using the measured pre-fault voltage at the main feeder head and scheduled power injections by the DG plants, a pre-fault load flow calculation is performed to evaluate different parameters of the synchronous generators, initial values of the network node voltages, line section currents, loads and capacitive charging currents. In the second step, the numerical fault location algorithm is performed by moving the data window from the pre-fault to a post-fault cycle. The accuracy of the proposed algorithm has been validated by several simulated fault studies carried out on a 205-node 20 kV practical radial distribution feeder. The results have shown remarkable accuracy in fault location when considering only the current and voltage measurements at the main feeder head have been used.     

An efficient algorithm for assessing reliability indexes of general distribution systems

This paper presents a practical reliability assessment algorithm for distribution systems of general network configurations. This algorithm is an extension of the analytical simulation approach for radial distribution systems. In the proposed algorithm, the meshed network is first converted to a radial network. All network elements are divided mainly into three classes according to the possibility for them to obtain power supplies from different directions. Accordingly, three different methods are employed to obtain two types of reliability topology zones for the elements. The algorithm is efficient for large-scale radial/meshed distribution systems, and can accommodate the effects of fault isolation and load restoration. The validity and effectiveness of the proposed algorithm is demonstrated by applying a computer program developed based on the proposed algorithm to a number of test systems and hundreds of real distribution networks.     

An approach for simultaneous distribution,sub-transmission,and transmission networks expansion planning

Sub-transmission network, as an intermediate grid between the distribution and transmission systems, receives the electric energy from the transmission network at extra high voltage levels, and delivers it to the distribution network at medium or low voltage levels. The adequate design and operation of sub-transmission system will lead to an efficient design of transmission network from the technical and economic viewpoints on one hand and the adequacy of power delivery to the distribution loads on the other hand. Therefore, the design optimality of these three networks is highly dependent on each other. However, as the simultaneous design of distribution, sub-transmission, and transmission systems is highly complicated, very few researches have tried to model and solve such a difficult problem. In this paper, a new approach has been developed for simultaneous distribution, sub-transmission, and transmission networks expansion planning. The proposed approach has been formulated as an optimization problem where an efficient and improved genetic algorithm (GA) is employed to solve such a complex problem. The utilized GA has been equipped with different modifying operators in order to make sure of its appropriate performance in obtaining useful and optimal solutions for the coordinated planning problem. The conducted approach has been implemented on a real network of Zanjan Regional Electrical Company (ZREC), and the results are compared with those of conventional method, i.e. separate expansion planning of these networks. The simulation results demonstrate the effectiveness of the conducted approach.     

基于模型识别的有源配电网单相接地故障定位方法

分布式电源(distributed generation, DG)大量接入使配电网继电保护面临严峻挑战。单相接地故障发生概率大,但故障信息十分微弱,特别是在DG多样化故障输出特性的影响下,有源配电网单相故障定位的准确性常难以保证。为此,提出了一种基于模型识别的有源配电网单相接地故障定位方法。分析了配电网单相接地故障下DG的输出特性,建立了在不同故障位置下有源配电网的正序增广网络,构建了故障位置关于馈线出口以及DG输出电流的函数,建立了配电网单相接地故障位置模型,利用不同故障位置下短路电流矢量占比系数的差异性构建了新的故障定位判据。通过将单相接地故障定位问题转化为故障位置模型系数的求解问题,提高了故障定位的准确性和实用性。理论和仿真分析表明,在不同故障位置、不同过渡电阻下均能准确定位单相接地故障,具有原理清晰、故障特征量采集便捷、灵敏性和可靠性高的优点。     

提升抗时延抖动和数据异常性能的配电网故障自同步5G差动保护方案

配电网5G差动保护信道的来回时延不等导致传统同步算法无法应用,需要增加额外的同步装置。另外,5G信道存在时延抖动和数据异常等问题会对保护的可靠性产生影响。针对这些问题,首先提出了基于变频插值的故障自同步法,在保护装置启动后利用插值法处理故障前特定时刻数据窗来实现同步误差校正。以此为基础,分析保护可能面临的异常数据特征,提出了考虑舍去极值的Hausdorff故障判别算法。最后设计了一种能够提升抗时延抖动和数据异常性能的配电网故障自同步5G差动保护方案。在PSCAD对方案进行仿真验证,结果表明所提方案能够在不增设额外同步装置的前提下有效提升抗时延抖动和数据异常的性能,保证发生各类故障和存在大噪声时的保护可靠性。该方案可为配电网5G差动保护的可靠性提供保障。     

Adaptive fault section estimation using matrix representation with fuzzy relations

In this paper, a method for the fault section estimation that considers the network topology under the influence of a circuit breaker tripped by the previous fault is proposed. The proposed method uses a three-dimensional (3-D) matrix to represent the network topology and the protection systems. The proposed network matrix describes the sections that are protected by particular protective devices that can be changed according to the network topology. To deal with the uncertainties imposed on the protection systems, the fuzzy set theory was applied to the network matrix in order to examine the relationships between the operated protective devices and the fault section candidates. A systematic method for the fuzzy membership function for each relation is proposed. In the proposed method, the operated time sequences of the protective devices were employed because either the network matrix or the network topology varied whenever the operations of the circuit breakers occur. The efficiency and adaptivity of the proposed method were demonstrated in experimental studies on real power systems in the Korean electric power system, particularly in case of complicated multiple faults.     

融合FTU和配变告警信息的有源配网故障定位方法

针对含分布式电源的有源配网相间短路故障定位问题,提出了一种融合FTU和配变告警信息的有源配网故障定位方法。首先,考虑配网故障后FTU和配变告警信息的不同特征,根据配网拓扑,动态生成不同告警信息对应的反映故障区段和告警信息关系的关联矩阵,并据此构造新的开关函数,有效避免了繁琐的逻辑运算。然后,根据两种信息源收到的实际告警信息分别建立优化模型,利用遗传算法求解,计算对应信息源下各区段的故障概率。最后,利用证据融合理论将两种信息源下的结果进行融合,得到最终的故障定位结果。以修改后的IEEE 33节点为例进行验证,结果表明,所提方法可对单点和双重故障实现定位,且具有较高的容错性。     

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.     

有源配电网分布式电源与智能软开关三层协调规划模型

当前配电系统调节能力的欠缺严重限制了高比例可再生分布式电源(DG)的广泛并网。在以智能软开关(SOP)为代表的电力电子装置接入系统的趋势下,考虑系统规划与运行优化相结合,协调DG运营商与配电公司的利益需求,提出一种有源配电网DG与SOP三层协调规划模型。上层以DG运营商单位容量收益最大化为目标进行DG规划,中层以配电公司年综合成本最小化为目标进行SOP规划,下层以场景内运行成本最小化为目标优化系统运行状态,决策DG消纳量返回上层与中层模型。采用场景分析法解决DG与负荷的随机性问题,基于并行遗传算法和锥规划的混合算法求解模型。最后以IEEE 33节点系统为例,与仅规划DG,DG和SOP先后规划的情况对比,结果表明兼顾系统运行优化的DG与SOP协调规划有利于满足不同主体的利益需求,提高规划方案可行性。     

基于BFOA算法的配电网DG选址定容方法

发展分布式能源系统对于实现的“碳达峰”和“碳中和”,提升可再生能源的开发利用具有重要意义。提出一种基于细菌觅食优化算法（BFOA）的配电网分布式电源（DG）选址定容方法。建立以配电网的功率损耗指数、电压偏差以及安装分布式电源所降低的净运行成本最小为目标的数学模型及约束条件,提出损耗敏感系数（LSF）来确定DG安装位置,并引用BFOA算法求解DG的最佳容量。仿真表明,相对于传统优化算法,BFOA算法在模型求解时间和收敛速度上具有明显优势,所提规划方法能够最大限度地降低功率损耗和运行成本,并提高系统的电压稳定性。     

基于人工鱼群算法的主动配电网故障定位

为有效解决主动配电网的故障定位问题,提出了一种基于人工鱼群算法的主动配电网故障定位新方法。首先,提出适用于主动配电网的整数规划故障模型,根据馈线终端单元上传的电流越限信息,将复杂的配电网架构等效为由整数表述的故障向量。其次,为解决不同规模的主动配电网故障定位问题,构建新的适应度函数,并利用改进人工鱼群算法根据等效后的故障向量进行迭代寻优定位故障。该方法主要根据配电网中故障电流的方向来定位故障位置,而不需要考虑DG出力的不确定性。最后,通过Matlab仿真验证所提方法,结果表明该算法准确率高、迭代速度快、对畸变信息具有高容错能力。     

基于多层模型的有源配电网故障区段定位

针对在实际工程中馈线终端装置（feeder terminal unit,FTU）上传信息误报、漏报以及保护装置拒动、误动给配电网故障定位与隔离带来的问题,提出了基于多层模型的有源配电网故障区段定位方法。利用多源信息进行故障区段定位,降低了单一故障信息畸变导致定位失败的概率。首先,利用保信系统收集的保护动作信息确定故障区域,然后基于改进免疫算法对故障区域内节点FTU遥信信息进行处理实现故障区段定位得到最终的定位结果。对含分布式电源（distributed generation,DG ）的IEEE 33节点配电网进行仿真测试,结果表明该方法能有效提高故障区段定位速度和准确率。