基于轨迹灵敏度的电力系统动态安全预防控制算法研究

提出了一种基于轨迹灵敏度的动态安全调度新方法.该方法首先滤除系统中的无危害故障,通过故障排序选取最严重故障并鉴别最领先发电机,然后依据最严重故障的临界切除时间和其最领先发电机有功输出的近似线性关系,计算最领先发电机至少需要调整的有功输出量,以使最严重故障的临界切除时间大于实际故障切除时间,通过故障中及故障后的系统仿真计算轨迹灵敏度,并依据故障切除后设定时刻领先发电机功角对各发电机有功输出的灵敏度数值,计算全系统内各发电机有功输出的调整量.最后通过对新英格兰10机39节点系统的计算验证了算法的有效性.     

一种临界故障切除时间概率分布的求解方法

稳定性分析是电力系统运行与控制中必须考虑的一个以及半不变量的性质，在敏感度计算的基础上，将临界故障最基本的问题。传统稳定分析是在确定系统初始参数后进行的。由于某些原因，电力系统的初始参数，如母线负荷等，因得不到其确定值而只能知道其可能分布。这使得传统的稳定分析方法已不能适用于新的形势，为此提出了概率稳定分析这一新的课题。该文提出一种新的临界故障切除时间概率分布的求取方法，利用随机变量的Cram-Charlier级数展开式切除时间概率分布的求取转化为对初始参数的半不变量的求取。该算法在39机系统中进行了测试，与Monte-Carlo仿真结果相比，该算法不需要反复进行大量的数值仿真的采样计算，而只需在确定临界故障切除时间的灵敏度时进行一次数值仿真；计算结果能很好地描述临界故障切除时间的实际概率分布，且能显著地减少计算量，提高计算速度。利用该方法，可根据故障后临界故障切除时间的概率分布，确定临界故障切除时间分布在期望值附近某区间内的概率，为稳定分析提供了判断的依据。     

基于故障后最小动能轨迹的同步发电机暂态稳定性分析方法

为了简单并准确地分析同步发电机暂态稳定性,提出结合时域仿真,并分别利用故障后系统稳定和不稳定时的故障切除时间和最小动能线性连接的交点,得到同步发电机的故障临界切除时间的混合评价方法。针对同步发电机模型不考虑阻尼和考虑阻尼2种情况,对提出的基于故障后最小动能轨迹暂态稳定性混合评价方法,分别进行了故障临界切除时间的计算,并和传统的故障后最小动能轨迹方法、时域仿真方法结果进行了比较。结果表明混合方法计算精度优于传统的故障后最小动能轨迹方法,该计算方法比时域法更简单。     

基于故障后最小动能轨迹的同步发电机暂态稳定性分析方法

为了简单并准确地分析同步发电机暂态稳定性,提出结合时域仿真,并分别利用故障后系统稳定和不稳定时的故障切除时间和最小动能线性连接的交点,得到同步发电机的故障临界切除时间的混合评价方法。针对同步发电机模型不考虑阻尼和考虑阻尼2种情况,对提出的基于故障后最小动能轨迹暂态稳定性混合评价方法,分别进行了故障临界切除时间的计算,并和传统的故障后最小动能轨迹方法、时域仿真方法结果进行了比较。结果表明混合方法计算精度优于传统的故障后最小动能轨迹方法,该计算方法比时域法更简单。     

电力系统暂态稳定混合分析法的研究

本文从两个方面对传统暂态稳定混合分析法进行了改进：一是提出一种根据仿真结果快速确定系统临界切除时间的方法,再根据临界切除时间下的故障清除后轨迹确定系统势能峰值点;二是引入修正势能和修正势能界面的概念。本算法所有分析都建立在仿真结果基础上,具有较高的可靠性。     

基于PEBS法的暂态能量裕度灵敏度快速计算

提出了一种基于PEBS法暂态稳定分析的能量裕度灵敏度计算方法。该方法以系统故障前稳定平衡点作为暂态势能参考点,沿持续故障轨迹采用数值方法计算暂态势能。在系统持续故障仿真和灵敏度动态方程计算过程中,引入高阶Taylor级数展开技术,可以在保持计算精度的前提下提高计算步长,显著提高计算速度。将到达临界势能点的判据展开以时间为自变量的多项式形式,通过解方程求得到达临界势能点的时间,从而快速确定临界势能点的位置。提出的能量裕度灵敏度分析方法包括两方面:计算故障前机组机械注入功率变化对能量裕度的灵敏度,用于指导预防控制;计算故障切除后的控制措施对稳定裕度的影响,用于指导紧急控制。New England 10机系统算例验证了该方法的有效性。     

基于PEBS法的暂态能量裕度灵敏度快速计算

提出了一种基于PEBS法暂态稳定分析的能量裕度灵敏度计算方法.该方法以系统故障前稳定平衡点作为暂态势能参考点,沿持续故障轨迹采用数值方法计算暂态势能.在系统持续故障仿真和灵敏度动态方程计算过程中,引入高阶Taylor级数展开技术,可以在保持计算精度的前提下提高计算步长,显著提高计算速度.将到达临界势能点的判据展开以时间为自变量的多项式形式,通过解方程求得到达临界势能点的时间,从而快速确定临界势能点的位置.提出的能量裕度灵敏度分析方法包括两方面:计算故障前机组机械注入功率变化对能量裕度的灵敏度,用于指导预防控制;计算故障切除后的控制措施对稳定裕度的影响,用于指导紧急控制.New England 10机系统算例验证了该方法的有效性.     

基于单机无穷大母线等值和轨迹灵敏度的暂态稳定约束最优潮流

在分析多故障暂态稳定约束最优潮流(transient stability constrained optimal power flow,TSCOPF)轨迹灵敏度法存在问题的基础上,提出基于单机无穷大母线等值和轨迹灵敏度的暂态稳定度约束最优潮流计算方法.根据单机无穷大母线等值,在暂态稳定约束最优潮流模型中引入严格的暂态稳定判据,并应用轨迹灵敏技术提高计算效率.将故障分为稳定故障、极度稳定故障、一般不稳定故障和极度不稳定故障,分别在暂念稳定约束中分别加以处理,可快速地进行放障筛选.同时,对于小稳定故障不需要寻找临界稳定轨迹,可节省大量的仿真时间.在3机、10机和20机系统上的仿真结果验证了所提出算法的有效性.     

基于稳定域边界二次近似的故障临界切除时间估计

基于故障后电力系统稳定域边界的二次近似来估计临界切除时间。在计算中,通过二次项系数矩阵分块来降维计算二次项系数,大大降低了二次项系数的计算量。临界切除时间由持续故障轨迹和主导不稳定平衡点(CUEP)所决定的稳定域边界二次近似的交点确定。在IEEE3机9节点系统和新英格兰10机39节点系统中的仿真表明了该方法的有效性,特别是对非发电机节点故障临界切除时间的估计精度较高,能够满足工程要求。     

临界切除时间的解析灵敏度分析

本文首次推导了保留结构模型下临界切除时间对发电机出力灵敏度的解析表达式，详细地给出了用势能界面法（PEBS）求临界切除时间灵敏度的计算方法和过程。根据此灵敏度，可求出临界切除时间与发电机有功出力之间的关系，对系统进行暂态稳定预防控制，以提高系统的暂态稳定性。对两个试验系统计算的结果表明了本文方法的有效性和可行性。     

A new trajectory sensitivity approach for computations of critical parameters

An approach is proposed to assess critical parameters in power system through an evaluation of trajectory sensitivity factors, such as fault critical clearing time (CCT), stability limit generation of generator. Firstly, new formulations for analysis of trajectory sensitivity with respect to fault clearing time are developed. And then, an approach to map the trajectory sensitivity to a sensitivity factor of minimum corrected kinetic energy to fault clearing time is introduced. Directed by the sensitivity factor, CCTs of contingencies are evaluated through an iterative process. It is the advantage that the CCT approach can be used for power systems represented by complex models. Combined with α sensitivity, similar technique can be used to compute generation limit of generators. Case studies for both CCT and generation limit assessments are performed on the 10-generator New England test system to verify the effectiveness and accuracy of the approach.     

Dynamic single machine equivalent techniques for on-line transient stability assessment

According to the post-fault trajectory duration characteristics, power system disturbances, which may cause transient stability problems, are classified into three types: short, long and extremely long duration ones. An improved method using dynamic single machine equivalent system (SMES) model for on-line first swing critical clearing time (CCT) estimation for both short and long duration disturbances on multi-machine power systems is developed in this paper. This dynamic SMES model substitutes for a large power system to provide fast, on-line transient stability assessment (TSA). Techniques such as assessment of energy margin, identification of a group of machines called the ‘dominant critical machines’ and an interpolation formula for CCT evaluation are proposed in this method to achieve high speed and accuracy in TSA. Test results on real size power systems are reported to show that the method is reliable for CCT assessment of both short and long post-fault duration disturbances.     

A fast approach to transient stability estimation using an improved potential energy boundary surface method

In this paper, a new fast algorithm to perform online transient stability assessment (TSA) in a power system is proposed. The TSA is concerned with finding the critical clearing time (CCT), the stability limit, for a specified fault. The method possesses the merits of the fast speed of the potential energy boundary surface method and the accuracy of the conventional time domain simulation technique. To expedite the algorithm, an efficient stopping criterion for postfault trajectory simulation is developed. Examples are given to show the problems of integration stopping criteria published in recent papers and how they are tackled. Extensive test results on several systems, including the 10-generator New England system, the 17-generator Iowa system and the IEEE 50-generator system, are reported.     

A new power system transient stability assessment method based on Type-2 fuzzy neural network estimation

Transient stability assessment (TSA) of large power systems by the conventional method is a time consuming task. For each disturbance many nonlinear equations should be solved that makes the problem too complex and will lead to delayed decisions in providing the necessary control signals for controlling the system. Nowadays new methods which are devise artificial intelligence techniques are frequently used for TSA problem instead of traditional methods. Unfortunately these methods are suffering from uncertainty in input measurements. Therefore, there is a necessity to develop a reliable and fast online TSA to analyze the stability status of power systems when exposed to credible disturbances. We propose a direct method based on Type-2 fuzzy neural network for TSA problem. The Type-2 fuzzy logic can properly handle the uncertainty which is exist in the measurement of power system parameters. On the other hand a multilayer perceptron (MLP) neural network (NN) has expert knowledge and learning capability. The proposed hybrid method combines both of these capabilities to achieve an accurate estimation of critical clearing time (CCT). The CCT is an index of TSA in power systems. The Type-2 fuzzy NN is trained by fast resilient back-propagation algorithm. Also, in order to the proposed approach become scalable in a large power system, a NN based sensitivity analysis method is employed to select more effective input data. Moreover, In order to verify the performance of the proposed Type-2 fuzzy NN based method, it has been compared with a MLP NN method. Both of the methods are applied to the IEEE standard New England 10-machine 39-bus test system. The simulation results show the effectiveness of the proposed method in compare to the frequently used MLP NN based method in terms of accuracy and computational cost of CCT estimation for sample fault scenarios.     

基于混合方法的电力系统暂态稳定性分析

本文将数值仿真方法和暂态能量函数法相结合,提出了一种分析出力系统暂态稳定性的混合求解方法。该方法首先通过数值积分计算出系统的运行轨迹,然后利用暂态能量函数法判别出系统的稳定性。 为了避免不必要的、费时的数值积分计算,本文提出了一种仿真计算终止判据。另外,本文提出了一种曲线拟合技术,不仅可以快速地求解出系统在稳定情况下的稳定裕度,而且还可以估计出系统的极限切除时间等。 这种混合方法结合了数值仿真方法和暂态能量函数法两者的优点,为在线暂稳分析和控制提供了一个有力工具。     

考虑暂态电压跌落限制的直接法暂态稳定分析

提出了一种考虑暂态电压跌落限制的直接法,快速求取保证故障后电力系统电压高于限值的故障临界清除时间(CCT).根据带约束动力系统稳定域理论,其受限稳定边界由边界上不稳定平衡点、周期轨和半鞍点的稳定流形以及部分可行域边界构成.半鞍点的稳定流形是系统受限稳定边界的重要部分,并且可以用半鞍点处的等能量面来近似.暂态电压跌落限制可以考虑为对故障后电力系统的一个约束.基于电力系统结构保持模型,寻找到了和故障相关的一个半鞍点,将持续故障轨迹和可行域边界交点的发电机角速度变为0后,就得到一个半鞍点.然后,以该点能量作为临界能量确定CCT,保证故障后系统满足暂态电压跌落约束.采用了迭代方法提高计算精度.仿真结果验证了所提出方法的有效性.     

Online critical clearing time estimation using an adaptive neuro-fuzzy inference system (ANFIS)

This paper describes an approach using an adaptive neuro-fuzzy inference system (ANFIS) for the assessment of online critical clearing time (CCT). The ANFIS can integrate neural networks and fuzzy logic principles, and has a potential to combine the advantages of both in a single framework. In this paper, the ANFIS is applied for the prediction of CCT by varying load levels and fault locations in buses and transmission lines. The IEEE 39-bus system and 9-bus western system coordinating council are tested and implemented in this study. All machines of the IEEE 39-bus system are considered as the classical model without considering any generator’s exciters. While three machines in the 9-bus western system coordinating council are considered as detailed models, forth-order differential equation is described for all machines by considering the excitation system controller. CCT values obtained by the time domain simulation method using step-by-step calculation are used as the benchmark. The power world version 17 is used for transient simulation, and the ANFIS is implemented using MATLAB version 2014B. The results obtained from the ANFIS approach are quite satisfied with high accurate solutions and much lower computation time. Finally, the graphical user interface in MATLAB is applied for the online CCT estimation of two test power systems by using appropriate ANFIS models obtained from simulations.