A mathematical model of an electric power system for dynamic state estimation

In this paper the derivation of a mathematical model of power system state-time behaviour is treated. A power system under normal operating conditions is considered. The mathematical model of the system state behaviour is expressed in terms of the state transition matrix. This model enables future system states to be predicted. The Kalman filter is utilized for the power system dynamic state estimation. A brief summary of representative test results is given.     

基于自适应SRUKF算法的电力系统动态谐波状态估计

针对传统无迹卡尔曼滤波(unscented kalman filter, UKF)谐波状态估计算法存在时变噪声和异常数据时估计准确度较差的情况,提出了一种基于自适应平方根无迹卡尔曼滤波(square-root UKF, SRUKF)的电力系统谐波状态估计算法。首先,针对时变噪声干扰,引入改进的Sage-Husa噪声估计方法实时估计噪声协方差。其次,针对异常数据干扰,引入异常数据修正方法,通过修正系数来降低异常数据对状态估计结果的影响。最后,通过搭建IEEE14节点系统验证自适应SRUKF算法的估计性能,能够有效地应用于电力系统的动态谐波状态估计。仿真结果表明,该算法在时变噪声和异常数据干扰时仍具有良好的估计性能。     

基于非线性理论的的电力谐波检测与估计

为了解决现有电力系统谐波检测方法普遍存在的对频率相近的谐波和间谐波分辨力不足和抗噪声干扰能力弱的问题,首次引入间歇混沌振子列方法解决以上两个问题,并介绍了两种应用间歇混沌振子列进行频率估计的方法。此外,还提出了一种基于Holmes-Duffing方程的Floquet指数的对待测信号的幅值和相位简化估计方法。最后用一组仿真信号的检测结果,验证了间歇混沌振子列方法检测电力系统谐波间谐波的有效性和提出的信号参数估计方法的准确性。     

Hierarchical static state estimation in a large-scale electric power system: Estimation error analysis

This paper discusses the hierarchical state estimation method for a large-scale power system from the point of view of the estimation error. It is shown that the error is bounded and depends on the number of subsystems comprising the power system, on the subsystem state estimation errors, on the number of measured lines coupling individual subsystems, and on the kind of power flow measurements from those lines used in the calculations. Theoretical considerations are illustrated by use of numerical results.     

Integral state estimation for well-conditioned and ill-conditioned power systems

This paper describes a generalized integral solution method to solve the power system state estimation problems for well-conditioned and ill-conditioned power systems. By simple graph analysis, the condition number, which is derived from the simple graph analysis, can be used for justification and determination of various power system operating situations. The modified fast decoupled state estimation method for well-conditioned power systems and the Crout decomposition method for ill-conditioned power systems are formulated and discussed in this paper. Simulations and results are discussed to support the feasibility and effectiveness of the proposed methods for well- and ill-conditioned power system state estimation.     

基于影响因子的电力通信网络节点检测方法

针对电力通信网络节点检测方法存在节点检测工作效率低的缺陷,提出基于影响因子的电力通信网络节点检测方法.将通信影响因子融入检测系统中,建立电力通信网络节点模型,设置检测路径.通过数据处理和故障定位设计仿真试验,证明该方法与传统方法相比,检测召唤率更稳定、检测时间更短、效率更高.     

Sliding–window neural state estimation in a power plant heater line

The state estimation problem for a section of a real power plant is addressed by means of a recently proposed sliding‐window neural state estimator. The complexity and the nonlinearity of the considered application prevent us from successfully using standard techniques as Kalman filtering. The statistics of the distribution of the initial state and of noises are assumed to be unknown and the estimator is designed by minimizing a given generalized least‐squares cost function. The following approximations are enforced: (i) the state estimator is a finite‐memory one, (ii) the estimation functions are given fixed structures in which a certain number of parameters have to be optimized (multilayer feedforward neural networks are chosen from among various possible nonlinear approximators), (iii) the algorithms for optimizing the parameters (i.e., the network weights) rely on a stochastic approximation. Extensive simulation results on a complex model of a part of a real power plant are reported to compare the behaviour of the proposed estimator with the extended Kalman filter. Copyright © 2001 John Wiley & Sons, Ltd.     

Application of DA‐preconditioned FINN for electric power system fault detection

This paper proposes a hybrid method of deterministic annealing (DA) and fuzzy inference neural network (FINN) for electric power system fault detection. It extracts features of input data with two‐staged precondition of fast Fourier transform (FFT) and DA. FFT is useful for extracting the features of fault currents while DA plays a key role in classifying input data into clusters in a sense of global classification. FINN is a more accurate estimation model than the conventional artificial neural networks (ANNs). The proposed method is successfully applied to data obtained by the Tokyo Electric Power Company (TEPCO) power simulator. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 166(2): 39– 46, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20497     

考虑量测相关性的容积卡尔曼滤波动态状态估计

针对电力系统动态状态估计中SCADA量测量间存在相关性的实际情况,文中提出了一种考虑量测相关性的容积卡尔曼滤波动态状态估计方法。首先进行了SCADA量测相关性分析,然后基于状态转移方程推导过程噪声协方差矩阵,基于容积变换方法计算考虑SCADA量测相关性的量测误差协方差矩阵,并提出了考虑量测相关性的电力系统动态状态估计流程,每次估计实时修正量测误差协方差矩阵及过程噪声协方差矩阵。IEEE-39节点系统的仿真结果表明,相较于不考虑量测相关性的容积卡尔曼滤波算法,文中方法能够明显提高状态估计结果的精度。     

A method for determining pseudo‐measurement state values for topology observability of state estimation in power systems

This paper proposes a new technique for determining state values in power systems. Recently, it has been useful for carrying out state estimation with PMU (Phasor Measurement Unit) data. The authors have developed a method for determining state values with an artificial neural network (ANN) considering topology observability in power systems. The ANN has the advantage of approximating nonlinear functions with high precision. The method evaluates pseudo‐measurement state values of data which are lost in power systems. The method has been successfully applied to the IEEE 14‐bus system. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 179(2): 27–34, 2012; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21235     

高压开关设备电力行业标准发展趋势

本文介绍了高压开关设备IEC标准、国家标准和电力行业标准近十多年来的变化、现状和存在的问题，提出了高压开关设备电力行业标准的发展趋势。     

我国电力工业资本的构成及走势分析

我国电力工业资本构成和走势已经发生了很大的变化,研究表明:计划体制下的国家拨款已由主导走向引导,估计维持在3%的比例;市场化、多元化的资本构成已经形成,银行贷款约占30%;外资增势迅速;地方集资和企业自筹近几年有所下滑;股票债券及基金等起伏较大。     

电力通信设备状态管理模型

在电力通信网监测系统中，需要对大量的告警信息进行总结和概括，以得到设备的运行状态。并根据设备运行状态记录，实现统计和分析功能。论文提出了一种适用于电力通信设备的状态管理模型，给出了关于模型的有限状态机，并说明了实现方法。算法简单实用，对并发告警具有较强的处理能力。利用该模型可以有效地解决设备状态分析问题。     

Application of sliding surface-enhanced fuzzy control for dynamic state estimation of a power system

This paper presents an algorithm for dynamic state estimation of a power system, utilizing the concept of sliding surface for the enhancement of fuzzy control to improve the estimation performance. In this proposed method, with the aid of fuzzy theory, the uncertainty of state estimation can be solved more effectively. In addition, different from the traditional fuzzy control design, the sliding mode control is embedded into this scheme that combines the error and the rate of error as an integrated input variable. With the estimator design, the number of fuzzy rules will be decreased. The computation time can be also effectively reduced. This proposed method has been applied to test systems and the results are compared with other published techniques.     

一种电动汽车动力锂电池组状态监控系统设计

电动汽车的快速发展,对于电池进行管理是必不可少的。在电池进行充电时,对电池状态的监控及均衡充电可以很好地保护电池的寿命和安全。在需要对大量电池进行管理时,可以通过通信总线将需要监控的电池进行统一管理。为了更好地管理电池,采用了液晶显示器和上位机对电池进行监控。当电池充电发生故障或者电池充满时,通过电压组的均衡来保护电池组,并发出相应的提示信号。在控制方面,主控制处理器采用的是DSP处理器,由TMS320F28055与LTC6804-1电池管理芯片共同构成系统控制核心;上位机软件是在Lab VIEW开发平台上进行设计。