Low voltage ride-through strategies for doubly fed induction machine pumped storage system under grid faults

Pumped storage units bring stability to the electrical power system, so they must remain connected to the grid even during grid faults. In this paper, the authors propose efficient and simple solutions for a doubly fed induction machine pumped storage (DFIMPS) system during grid faults. In case of balanced grid faults, a control reconfiguration strategy is introduced and a hardware solution is applied in the case of unbalanced grid faults. The reconfiguration strategy consists of a commutation between different control strategies; when a balanced grid voltage fault occurs during pumping mode, the control algorithm switches to the synchronization one but based on the new grid conditions. So the proposed reconfiguration method reduces the negative impacts of grid fault occurrence on the DFIMPS system by cancelling rotor and stator over-currents and decreasing the electromagnetic torque and stator power oscillations. Simulation results carried out on a 4 kW DFIMPS system illustrate the effectiveness of the proposed approach.     

基于复杂网络理论与风险理论的地区电网脆弱性评估

电网脆弱性不仅与电网的网络结构及其电气参数有关,还与电网的实时运行状况及约束条件有关。基于复杂网络理论与风险理论,提出了一种新的电网脆弱性评估方法。首先以节点重要度指标和线路改进介数指标对电网中的脆弱源进行识别;再利用设备状态检修数据建立起脆弱源元件的故障模型,依据设备的健康指数推算出设备的故障可能性,并引入效用理论来评估故障严重度,得到相应的综合静态风险指标;最后基于网络结构特性指标和综合静态风险指标定义了节点脆弱度和线路脆弱度指标,并以某一地区电网为例进行分析,结果表明,文中定义的脆弱度指标能有效地克服以往从单一角度去评估电网脆弱性的弊端,提高了辨识精度与辨识效果,验证了该脆弱性评估方法的合理性及有效性。     

Analysis of cascading failures of power cyber-physical systems considering false data injection attacks

This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system, and identifies vulnerable nodes. First, considering the monitoring and control functions of a cyber network and power flow characteristics of a power network, a power cyber-physical system model is established. Then, the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied, and a cascading failure analysis process is proposed for the cyber-attack environment. In addition, a vulnerability evaluation index is defined from two perspectives, i.e., the topology integrity and power network operation characteristics. Moreover, the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyber- physical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index. Finally, an IEEE14-bus power network is selected for constructing a power cyber-physical system. Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks, which affect the ability of the cyber network to suppress the propagation of cascading failures, and expand the scale of the cascading failures. The vulnerability evaluation index is calculated for each node, so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.     

智能电网背景下的节点类型扩展潮流计算

随着智能电网的建设,大规模新能源机组并网运行,使电力系统运行更加复杂,对电网的稳定性提出更高的要求。先导节点的选择及其电压的控制是电力系统稳定性研究的重要方面,节点类型和状态变量扩展潮流计算能为经济调度、参数整定、在线分析估计等提供更全面可靠的参考。以此为目的,建立了一种拓展潮流计算模型。提出通过标准粒子群优化算法在电压控制分区中选择先导节点。提出含P、PV、PQ、PQV、Vθ等多节点类型及拓展变量的潮流计算模型,计及发电机机端电势变量,将已选中枢点设为PQV节点,选择等量的发电机组为P节点。利用IEEE 39节点输电网络选择先导节点和潮流计算仿真,结果验证了该模型的有效性。常规潮流模型与该模型仿真比较表明该模型在今后智能电网背景下离线和在线实时潮流计算中将有很好的应用前景。     

基于改进布谷鸟算法含光伏电站的无功优化

针对光伏电站并网运行给配电网无功优化带来的问题,根据光伏发电的运行特性,构建了含光伏电站的配电网无功优化数学模型,并提出改进的布谷鸟算法求解无功优化模型的方法,对含光伏出力的IEEE 33节点配电系统进行无功优化。结果表明,所提出的改进算法能有效降低配电网的有功网损,各节点远离电压崩溃点。     

Artificial intelligence based active and reactive power control method for single-phase grid connected hydrogen fuel cell systems

In grid-connected power generation systems, power factor fluctuations caused by non-linear power circuits used between the grid and source should be controlled with the help of voltage source inverters (VSI). In addition, in order to improve the quality of the electrical energy injected into the grid and to prevent possible electrical faults, the total harmonic distortion (THD) in the grid current should be controlled in accordance with IEEE-519 standards. In other respects, uncontrolled injected energy may causes losses, excessive electrical energy demand and overloading. In this study, an artificial neural network based active and reactive power control method is proposed for grid-connected single-phase Proton Exchange Membrane Hydrogen Fuel Cell (PEMFC). The aim of the proposed control structure is to have low harmonic distortion, high power factor performance as well as an easy and understandable structure. The proposed method was applied to a 6 kW prototype. Five different scenarios and nine different activation function were tried to verify the performance of the proposed control method. As a result of these processes, the power factor was measured as unity (>0.99) and the total harmonic distortion (THD) of the grid current, under all operation states, is <2%. In addition, it has been observed that the success rate of artificial neural networks is >97%.     

Design of a cost-effective on-grid hybrid wind–hydrogen based CHP system using a modified heuristic approach

An economic model and optimization procedure is developed in this paper for grid-connected hybrid wind–hydrogen combined heat and power systems for residential applications in northeastern Iran. The model considers various significant factors: energy production cost, electrical trade with local grid, electrical power generation from the wind/hydrogen energy system, thermal recovery from the fuel cell, and maintenance. Also, various tariffs for purchasing and selling electrical energy from the local grid are considered for the hybrid system operation. The optimization objective is to minimize the system total cost subject to relevant constraints for residential applications. To achieve this aim, an efficient optimization method is proposed based on particle swarm optimization. The proposed algorithm performance is compared with that for the imperialist competition algorithm. The results show that the hybrid system is the most cost-effective for the residential load, and the results of the proposed algorithm are more promising than those for the alternative algorithm.     

基于改进结构熵的电力信息物理系统脆弱性分析

随着电网与信息网的不断融合,考虑两网之间交互关系的电力信息物理系统脆弱性分析对保障电力系统稳定运行具有重要的实用价值.文章基于复杂网络理论,建立了电力信息物理系统拓扑模型,并提出了一种综合考虑节点差异性、边差异性和节点相依关系的电力信息物理系统拓扑改进结构熵指标.该指标可克服单层网络结构熵指标的局限性,并能识别电力信息...     

Fault ride-through capability of DFIG wind turbines

This paper concentrates on the fault ride-through capability of doubly fed induction generator (DFIG) wind turbines. The main attention in the paper is, therefore, drawn to the control of the DFIG wind turbine and of its power converter and to the ability to protect itself without disconnection during grid faults. The paper provides also an overview on the interaction between variable-speed DFIG wind turbines and the power system subjected to disturbances, such as short circuit faults. The dynamic model of DFIG wind turbine includes models for both mechanical components as well as for all electrical components, controllers and for the protection device of DFIG necessary during grid faults. The viewpoint of the paper is to carry out different simulations to provide insight and understanding of the grid fault impact on both DFIG wind turbines and on the power system itself. The dynamic behaviour of DFIG wind turbines during grid faults is simulated and assessed by using a transmission power system generic model developed and delivered by the Danish Transmission System Operator Energinet.dk in the power system simulation toolbox PowerFactory DIgSILENT. The data for the wind turbines are not linked to a specific manufacturer, but are representative for the turbine and generator type used in variable-speed DFIG wind turbines with pitch control.     

考虑连锁故障的发输电系统可靠性评估

为在发输电系统可靠性评估中考虑连锁故障的影响,提出了评估连锁故障风险的混合算法.该算法结合了解析法和模拟法的优点,在计算精度和效率上均有一定的优势.由于实际切负荷时负荷节点功率因数保持恒定,因此在最优切负荷模型中引入了负荷节点功率因数恒定约束,使得该模型更加贴近实际情况.此外,为了提高发输电系统可靠性评估的效率,采用基...     

Nonlinear system identification for model-based condition monitoring of wind turbines

This paper proposes a data driven model-based condition monitoring scheme that is applied to wind turbines. The scheme is based upon a non-linear data-based modelling approach in which the model parameters vary as functions of the system variables. The model structure and parameters are identified directly from the input and output data of the process. The proposed method is demonstrated with data obtained from a simulation of a grid-connected wind turbine where it is used to detect grid and power electronic faults. The method is evaluated further with SCADA data obtained from an operational wind farm where it is employed to identify gearbox and generator faults. In contrast to artificial intelligence methods, such as artificial neural network-based models, the method employed in this paper provides a parametrically efficient representation of non-linear processes. Consequently, it is relatively straightforward to implement the proposed model-based method on-line using a field-programmable gate array.     

兼顾系统侧和用户侧的节点电压暂降严重程度综合评估方法

针对现有的节点电压暂降评估方法忽略了节点负荷对评估结果影响的问题,提出一种兼顾系统侧和用户侧的电压暂降严重程度综合评估方法。首先,利用层次分析法确定敏感负荷的暂降影响权重系数,提取系统侧指标;然后,根据熵权法加权综合典型敏感设备的故障率作为用户侧指标;最后,基于灰色关联分析法计算各节点评估指标构成的样本序列与参考序列的关联度大小,判断节点暂降严重程度。将该方法用于某城市电网的电压暂降评估,结果表明,该方法能合理修正负荷对暂降严重程度评估结果的影响,对节点暂降严重程度的排序更符合客观实际。     

Assessing transient response of DFIG based wind turbines during voltage dips regarding main flux saturation and rotor deep-bar effect

With increasing wind power penetration, transient responses of doubly-fed-induction-generator (DFIG) based wind turbines gain attentive focus. Accurate prediction of transient performance of DFIG under grid faults is required with increasing wind power penetration. Taking into account the main flux saturation and deep-bar effect, this paper concentrates on transient responses and stability of the DFIG system under symmetrical grid faults. Their roles played in the enhancement of system transient stability are clarified. The analyses proposed contribute greatly to proper selection, design and coordination of protection devices and control strategies as well as stability studies.     

Zero non‐detection zone assessment for anti‐islanding protection in rotating machines based distributed generation system

The challenges for a reliable operation of electrical power system have increased due to the presence of multi‐distributed generation units (DGs) in the distribution systems in order to meet the increase of the load demand. Detection of unintentional islanding situation is very important as non‐detection of islanding situation could result in a cascaded failure of the system. If the islanding situation remains undetected, the instability in the islanded part can lead to a complete failure of the electrical power system. This paper introduces a new passive scheme for islanding detection, which is suitable for multi‐distributed generation units based on rotating machines. The proposed method is based on the measurements of the system voltage and frequency to compute two indices called the islanding index and harmonics index. The islanding index is the main index used to discriminate and identify the islanding situation. However, the harmonics index in conjunction with a strategy called speed reduction strategy assists the islanding index to discriminate between islanding situation in case of a close power match and system disturbances. The simulation studies were conducted in MATLAB/SIMULINK environment, and various cases have been considered, such as normal operation, islanding operation, sudden load change, DG tripping, separation of some DG units, faults, etc. The novelty of the proposed strategy is that it provides fast detection and has zero nondetection zone compared with the existing detection methods. Moreover, the proposed strategy has no effect on the power quality, and the maximum detection time is almost 350 ms at a close power match. The results indicate that the proposed scheme is successful in discrimination of the islanding conditions from other grid disturbances, revealing its great potential to be able to detect islanding events. Finally, the proposed method is applied only for rotating machine based DGs, such as wind turbines. Wind farms' power generation system based on doubly‐fed induction generators is introduced in this paper as an example of DGs units.     

基于模态法的静态电压稳定性分析

提出了基于模态法的静态电压稳定性分析的新方法,通过建立模态法的静态电压稳定分析数学模型,求取潮流方程雅可比矩阵的最小特征值及其相对应的特征向量,以最小模特征值来间接评估系统的静态电压稳定裕度,并在此基础上提出了参与因子指标,计算各个节点在最小特征值下的节点参与因子来找出哪些节点或区域的电压稳定性较差.通过对某大型电网进行研究,得到其相应的电压薄弱区域,并与灵敏度分析法所得到的结果进行对比,结果基本一致,从而验证了本文方法的合理性与有效性。     

Identification of vulnerable lines in power grids with wind power integration based on a weighted entropy analysis method

Vulnerable overhead electricity lines are a cause of serious risk to power distribution grids as damage can be the cause of large scale blackouts and cascading failures. With the integration of large scale wind power into generating capacity, both the topology structure and the distribution characteristics of power flow in distribution grid have undergone various changes that have increased line vulnerability. A novel approach to identify vulnerable lines based on the weighted entropy analysis method is proposed in this paper. In this approach, an assessment index, named the incremental power flow entropy, is first developed, which is used to describe influences caused by variation of the lines' capability of carrying power flow transfers on the vulnerability of the lines themselves at the same aggregation level. A second assessment index, named structural importance, describes the structural changes of a power grid that are caused by the integration of wind-generated electric power. The two assessment indices then are merged into one index by using the entropy weight analysis method, which can assess the vulnerability of the lines from the two aspects of power flow transmission and structural links. Vulnerability analysis under different situations, such as with and without the integration of the wind farm, and sharp fluctuations in wind speed at the wind farm, were carried out on an IEEE 39-bus system integrated with a 75 MW wind farm. Simulation results verified that the proposed assessment index not only can identify the vulnerable lines in a power grid with wind farm integration but also accurately reflected the vulnerability of the internal lines of the wind farm itself.     

多能源数据驱动的电力信息物理系统综合态势感知模型

针对高比例可再生能源以及多类型能源设备接入的电网,以电力信息物理融合为基础,研究面向可靠性评估的电力信息物理系统运行状态综合分析方法,提出多能源数据驱动的电力信息物理系统综合态势感知模型。首先,考虑电力信息物理系统中影响系统运行状态的关键因素,研究面向可靠性评估的电力信息物理系统运行状态变化过程;其次,针对电力信息物理系统不同运行状态下关键设备扰动问题,研究基于改进鲁棒估计的电力信息物理系统正常状态、临界状态、紧急状态和恢复状态辨识方法,在此基础上,建立多能源数据驱动的电力信息物理系统综合态势感知模型;最后,以东北某地区电网运行数据为例进行验证。仿真结果表明,文章所提出的方法能够实现以可靠性辨识为目标的电力信息物理系统综合态势感知,并能保证较高的准确性和实时性。     

风光并网对河南电网系统稳态影响

大规模风光发电并网是未来电网发展的必然趋势,然而,风光发电功率的强间歇性与随机性势必会对电网的稳定运行和优化控制带来影响。以河南电网冬季大运行方式下的规模风电、光伏电源联合接入电网为研究背景,利用连续潮流法,计算在新能源发电接入系统后的区域电网潮流分布;考虑区域电网未来发展趋势,逐步增加新能源的渗透率,对系统内多类型节点电压越界情况分析,判断区域内电压薄弱节点,并计算系统风电与光伏发电的最大消纳量;应用P-V曲线潮流分析方法测算出电压稳定极限及对应的有功功率,得到不同渗透率下系统所对应的静态电压稳定性;同时结合日负荷曲线,分析在目前状态下及所计算的最大渗透率下,系统任一时刻各中枢点电压水平。结果表明：在目前及新能源最大渗透率下,系统各节点电压值均处于正常范围。     

基于自适应改进K-Means聚类算法的黑启动分区方法

针对目前黑启动分区方法中大多利用边介数法对系统进行划分并不能很好地满足系统恢复的时间性和安全性要求,在分析黑启动系统特点和分区要求的基础上,对K-Means算法进行了自适应改进,根据电网的拓扑和电气特性将系统简化为无向有权网络,利用改进后的K-Means算法对系统进行黑启动分区,并以IEEE 39节点和118节点系统为例对所提算法进行验证。结果表明,改进后的K-Means算法的分区结果更为合理,且降低了计算难度、减少了计算量。     

基于二阶广义积分的风电系统电压跌落检测法

随着风力发电装机容量的不断增大,风电在电网中所占比重也越来越高,这就要求并网风电系统应具有低电压穿透能力。在电网电压发生跌落的情况下,为了使风电系统保持并网状态,对电网进行支撑并穿越故障,文章提出一种准确的、快速的电网故障电压检测方法——正序电压检测方法。该方法能在电网电压发生故障下做出快速的、精准的频率自适应响应。该电压检测系统包括正交信号发生器(QSG)、正序分量计算(PSC)和锁相环(PLL)3部分,系统中应用了二阶广义积分正交信号发生器。系统的输入为电网电压,输出为实时的相位角、正序电压分量和故障信号。通过对系统研究和仿真,表明该系统在电网发生故障时可有效地检测到故障信号。