On-line voltage stability assessment using radial basis function network model with reduced input features

In recent years, voltage instability has become a major threat for the operation of many power systems. This paper presents an artificial neural network (ANN)-based approach for on-line voltage security assessment. The proposed approach uses radial basis function (RBF) networks to estimate the voltage stability level of the system under contingency state. Maximum L-index of the load buses in the system is taken as the indicator of voltage stability. Pre-contingency state power flows are taken as the input to the neural network. The key feature of the proposed method is the use of dimensionality reduction techniques to improve the performance of the developed network. Mutual information based technique for feature selection is proposed to enhance overall design of neural network. The effectiveness of the proposed approach is demonstrated through voltage security assessment in IEEE 30-bus system and Indian practical 76 bus system under various operating conditions considering single and double line contingencies and is found to predict voltage stability index more accurate than feedforward neural networks trained by back propagation algorithm and AC load flow. Experimental results show that the proposed method reduces the training time and improves the generalization capability of the network than the multilayer perceptron networks.     

基于图卷积网络的快速暂态安全评估方法

快速、可靠的电力系统动态安全评估能够显著提高电力系统运行方式优化调整的效率。针对电力系统暂态稳定预想事故扫描需要完成大量仿真、过于耗时的问题,提出了基于图卷积网络的快速动态安全分析方法。该方法基于电力系统的潮流特征和拓扑特征构建电力系统潮流特征图。利用图卷积方法对电力系统运行状态进行特征挖掘与特征学习,将动态安全评估问题建模为图上节点分类问题。所得模型在读取电网拓扑与潮流运行状态后,仅须完成一次前向计算即可同时给出预想事故集中多个预想事故的稳定性预测结果,无须依赖仿真波形或量测数据,实现快速暂态稳定预想事故扫描。IEEE39节点系统算例测试表明,算法设计正确、高效、准确率高,能够显著提高暂态稳定预想事故扫描的效率,实现快速动态安全评估。     

在线暂态安全稳定评估的分类滚动故障筛选方法

为满足在线暂态安全稳定评估对计算时间的要求,提出了基于模式和裕度估算的在线暂态安全稳定故障筛选方法。分别基于上一轮在线暂态安全稳定评估结果中各个预想故障的暂态功角稳定、暂态电压跌落安全、暂态电压稳定和暂态频率偏移安全的裕度及模式信息,并结合各个故障安全稳定模式中相关元件的潮流变化和投/退等信息,估算出新一轮在线暂态安全稳定评估所对应的运行状态下各个故障的暂态安全稳定裕度,并确定其相应的安全稳定模式,从而筛选出本轮在线暂态安全稳定评估需详细计算的预想故障子集。通过对实际电网在线数据的仿真分析,验证了所述方法的有效性和实用性。     

N-1故障电压稳定极限高阶灵敏度快速计算

在利用连续潮流计算得到无故障网络的静态电压稳定临界点的基础上,提出一种快速计算线路故障下静态电压稳定临界点的可靠方法.该方法将单条线路运行状态参数化,通过求解原系统的静态电压稳定临界点对故障线路参数的1至N阶导数,用泰勒级数法进行逼近,从而快速精确的求解出线路故障情况下电压稳定临界点.在求解1至N阶导数时,系数矩阵是同一个矩阵,无需反复形成与分解.该方法计算量小,无需反复迭代.该文方法的可行性与高效性通过在IEEE 30及118母线系统上的算例得以验证.     

基于灰色关联分析法的电压稳定故障筛选与排序

故障筛选与排序是电力系统电压稳定评估的重要部分。针对以往基于潮流计算筛选方法的单一性,提出了一种新的故障筛选与排序方法。首先结合感应电动机特性、负荷大小、电源支撑及输电线路情况构建一套故障筛选指标体系;其次针对单一指标反映故障严重程度的局限性,采用灰色关联分析法计算综合指标,综合多方面因素评估故障严重程度。采用存在电压稳定问题的实际电网数据对所提方法进行验证,结果表明基于灰色关联分析法的电压稳定故障筛选与排序方法是合理和有效的。     

Effect of line contingency on static voltage stability and maximum loadability in large multi bus power system

Voltage instability is the phenomena associated with heavily loaded power systems. It is normally aggravated due to large disturbance. Due to deregulation of power system, the system has to cater for the load bids in open access. This may cause the increased transaction level leading to more stress on the power system. It has become an urgent need of today to address the voltage stability problems to keep the voltage profile under control. Several incidences of voltage instability have occurred worldwide recently. In the event of contingency, the most serious threat to operation and control of power system is insecurity. The estimation of the power system state under contingency is an essential task for the power system engineers. The contingency analysis technique is a prerequisite to predict the effects of various contingencies like failure of transformers, transmission lines, etc. It helps to initiate necessary control actions to maintain power system security, reliability and stability. In the present work, two kinds of performance indices viz. active power performance index and reactive power performance index are computed for a large power system using a special code written in MATLAB environment. Furthermore, a novel idea of static voltage stability analysis by incrementing the load in proportion to the original load on load buses along with the most vulnerable line outage using Newton Raphson (N–R) load flow is presented.     

Fast real power contingency ranking using counter propagation network: feature selection by neuro-fuzzy model

In deregulated operating regime power system security is an issue that needs due consideration from researchers in view of unbundling of generation and transmission. Real power contingency ranking is an integral part of security assessment. The objective of contingency screening and ranking is to quickly and accurately shortlist critical contingencies from a large list of credible contingencies and rank them according to their severity for further rigorous analysis. In the present work, modified counter propagation network (CPN) with neuro-fuzzy (NF) feature selector is used for real power contingency ranking of the transmission system. The CPN is trained to estimate the severity of a series of contingencies for given pre-contingencies line-flows. But for larger size system it becomes rather difficult to cope with the increased size of input pattern and network as well. And it adversely affected the performance of the network and computational overhead. The proposed NF feature selector prunes the size of input pattern by exploring the individual power of features to characterize/discriminate different clusters. The reduced set of discriminating inputs not only ensures saving in training time but also improves estimation accuracy and execution time and these are the deciding parameters in evaluating the performance of particular contingency ranking technique. The effectiveness of proposed approach is demonstrated on IEEE 30-bus test system and practical 75-bus Indian system.     

考虑二重预想事故的在线电压稳定预防控制

提出了一种基于原对偶内点算法的安全约束最优潮流的数学模型,以控制代价最小化为目标,不仅考虑了正常状态下的安全约束,还同时考虑到了预想事故后的安全约束以及电压稳定裕度的约束。在线电压稳定评估系统中,同时考虑单重预想事故及其引发的继发性二重预想事故,分别进行筛选和排序,综合形成预想事故集。根据预想事故集,基于上述模型依次对其中每一预想事故进行预防控制,构建在线电压稳定预防控制模块,当系统处于不安全状态时,能够及时提供合理的预防控制策略,保证系统安全运行。以IEEE 118节点测试系统为算例,验证了所提出模型的正确性。     

潮流不可解评估方法的比较

电力系统在线电压稳定监视与控制中,故障态潮流发散的情况经常出现。识别其是否确实为失稳故障、准确评估其不可解程度及其提供校正控制用的灵敏度信息是对不可解潮流解算技术的3个基本要求。最优乘子牛顿法、基于直接求解KKT条件的最优潮流法和新近提出的故障型连续潮流法是3个可以处理潮流不可解的技术。前两者提供了在功率注入空间某种距离最近的临界点,而故障型连续潮流法提供了故障参数空间最近的临界点。文中应用这3种方法对IEEE 118节点标准系统进行了计算,从识别的可靠性、不可解程度评估的准确性和灵敏度信息的合理性等方面对它们进行分析和比较,结果表明所得到的不可解程度评估和排序结果存在差异,都包含了控制灵敏度信息。     

电力系统N-K故障的风险评估方法

历次大停电事故表明,由简单故障触发的连锁故障会对电力系统造成灾难性的后果。识别和分析可能对电力系统造成大面积停电的严重N-K故障是进行电网安全评价和制定防御措施的必要步骤。文中在分析大停电演变过程的基础上,提出了一种电力系统N-K故障的风险评价方法：考虑故障间的相互影响和继电保护的隐藏故障,计及元件运行状态变化对其故障概率的影响,基于贝叶斯网络给出了N-K故障的概率计算模型;详细模拟了实际电力系统连锁故障过程中的控制措施,建立了计及电压稳定约束的最优控制模型,提出了N-K故障严重程度的确定方法;最后提出了N-K故障风险指标的计算方法。利用Python语言对PSS/E进行了二次开发,实现了所提方法,并以IEEE 30节点测试系统为例,识别出该系统中的严重N-K故障,验证了方法的正确性。     

基于最优潮流并计及静态电压稳定性约束的区域间可用输电能力计算

可用输电能力(ATC)是衡量电力系统在安全稳定运行的前提下区域间功率交换能力的指标。文中基于最优潮流(OPF)方法，建立起符合电力市场交易机制的ATC计算模型，其中考虑到输电线路故障对系统静态电压稳定性的影响，加入线路N-1故障时广义参数化形式的潮流方程及相应的不等式约束条件，使系统在故障时仍有负荷裕度，以保持电压稳定；以支路功率和系统负荷裕度之间的灵敏度指标进行预想故障选择，并用原对偶内点法计算得到输电线路N-1安全约束下的区域间可用输电能力。IEEE30和IEEE118节点系统算例表明该模型和算法的正确性与有效性。     

PSVSR:一种实用的静态电压安全性评估工具

介绍了一种基于“安全域”理论的静态电压安全性评估软件包——PSVSR的设计思想和实现方法。PSVSR具有友好的可视化交互界面,能够向电力运行人员提供正常及故障运行方式下有关电压稳定及支路热稳定极限的更为全面和系统的信息。PSVSR基于Windows操作系统,由Visual C 开发实现。PSVSR采用三层结构:用户界面层、核心计算层和后台支持层。这种三层结构使得PSVSR更加可靠、稳定、并易于扩展。最后基于EPRI 2000母线系统对PSVSR的特点及运行特性进行了说明。     

基于风险的电力系统安全预警的预防性控制决策分析

针对事故发生的可能性和严重性进行电力系统安全分析的风险评估,将基于风险的安全性评估指标应用到电力系统安全预警中定量分析电力系统的运行状态转换风险,并进行电力系统预防性控制研究.根据系统低电压风险指标、系统过负荷风险指标和系统电压失稳风险指标3种风险指标综合表征的系统安全等级,在事故发生前进行预防性控制决策分析,以灵敏度确定参与决策的关键节点,用遗传算法确定参与决策的节点的最优有功和无功的注入量,从而有效地降低电网的运行风险,提高电网的安全预警等级.以上海电网84节点系统的仿真表明算法的可行性和有效性.     

暂态电压稳定性及电压跌落可接受性

阐述了暂态电压稳定,暂态电压跌落可接受和暂态功角稳定三者之间的关系,把电力系统同时保持暂态电压稳定和暂态电压跌落可接受称之为暂态电压安全,把电力系统同时保持暂态功能稳定和暂态电压安全称之为暂态安全。     

Wavelet based feature extraction of voltage profile for online voltage stability assessment using RBF neural network

Online voltage stability assessment is one of the vital requirements for intricate electric power systems. Due to the restructuring and liberalization, modern power systems tend to operate close to their stability limits with small security margin. In such environment, online voltage stability evaluation plays a significant role in secure operation of power systems. This paper presents a new approach for estimating voltage stability margin VSM, based on application of wavelet feature extraction method to network voltage profile. Voltage profile is adopted as the original input data for VSM estimation, because it contains sufficient information concerning network topology, load level, load-generation patterns and all system controllers. In this approach, in order to provide high discrimination between network voltage profiles, Multi-Resolution Wavelet Transform (MRWT) is utilized to extract the features of voltage profiles. Also, in order to eliminate the redundant features, principle component analysis (PCA) is used to select the most relevant features extracted by MRWT. Radial Basis Function (RBF) neural network is adopted to estimate system VSM using the dominant extracted features of the voltage profile by MRWT and PCA. Using voltage profile as the original data makes the proposed approach capable of estimating system VSM in both static and quasi dynamic conditions. The proposed approach has been implemented in New England 39-bus test system with promising results demonstrating its effectiveness and applicability.     

Calculation of weighting factors of static security indices used in contingency ranking of power systems based on fuzzy logic and analytical hierarchy process

Contingency screening and ranking is one of the most important issues for security assessment in the field of power system operation. The objective of contingency ranking is to quickly and accurately select a short list of critical contingencies from a large list of potential contingencies and rank them according to their severity. Then suitable preventive actions can be implemented considering these contingencies that are likely to affect the power system performance. In this paper a novel approach is presented for contingency ranking based on static security assessment. This method employs weighted performance index with the application of fuzzy logic based analytical hierarchy process in order to select appropriate weighting factors to be imposed. The proposed method is applied to IEEE 30 bus system and the results are presented.     

Dynamic security constrained optimal power flow/VAr planning

Traditionally security constrained optimal power flow and VAr planning methods consider static security observing voltage profile and flow constraints under normal and post contingency conditions. Ideally, these formulations should be extended to consider dynamic security. This paper reports on a BC Hydro/CEPEL joint effort establishing a dynamic security constrained OPF/VAr planning tool which considers simultaneously static constraints as well as voltage stability constraints. This paper covers the details of formulation and implementation of the tool together with the test results on a large scale North American utility system and a reduced Brazilian system     

基于斜回归树及其集成算法的静态电压稳定规则提取

可再生能源渗透率的增加给电力系统安全稳定运行带来持续性的挑战,传统方法分析系统稳定性、控制电网稳定运行变得愈加困难。针对这一难题,提出了内嵌安全稳定约束的电力系统优化运行框架以及用于电力系统安全稳定规则提取的斜回归树及其集成算法。该算法首先优化斜划分系数以训练单棵斜回归树,然后利用boosting思想集成斜回归树,并通过正则化方法保证树的稀疏度,增强算法的可解释性。相比神经网络等黑箱模型,文中提出的方法能够提取显式安全稳定规则,为内嵌安全稳定约束的电力系统优化运行奠定了基础。最后,以静态电压稳定问题为例验证算法的有效性,算例验证结果表明所提算法具有良好的可解释性、较强的表示能力和较高的集成效率。     

An optimal pricing scheme in electricity markets by parallelizing security constrained optimal power flow based market-clearing model

To improve economic efficiency of electricity markets, the market-clearing model must be designed to give transparent information for pricing system security and to quantify the correlation between the market operations and the power systems operations, which is an immensely provocative and challenging issue in electricity markets. This paper sets out to propose a novel approach to pricing the system security by parallelizing the security constrained optimal power flow (SCOPF) based market-clearing model, while providing market solutions as a function of complying with the required voltage security margin and N-1 contingency criteria. The proposed SCOPF based market-clearing framework also takes into consideration the bilateral transaction information and, at the same time, optimal pricing expressions through computing locational marginal prices (LMPs) and nodal congestion prices (NCPs) for ensuring voltage security are derived. The results from a 129-bus model of the Italian HV transmission system turn out to be the validity of the proposed market-clearing model for managing and pricing the system security.     

Fast contingency screening and evaluation for voltage securityanalysis

The authors describe a fast security-analysis technique for voltage security assessment in an energy-management system. The proposed method identifies the location of buses with potential voltage problems and thereby defines a voltage-sensitive subnetwork for contingency screening. This allows the evaluation of a large number of contingencies. The efficiency of this method is derived from the use of a voltage subnetwork to drastically reduce the number of bus voltages to be solved; and subsequently from the use of compensation techniques and sparse-vector methods (including adaptive reduction) for screening and final solution of contingencies. Results demonstrating the effectiveness of the method on a small and a large power system are presented