电力系统抗差状态估计研究综述

状态估计是电力系统能量管理系统的重要组成部分.传统加权最小二乘估计不具备抗差性,为此产生了抗差估计理论.本文介绍了抗差估计的定义、目标及基本类型,综述了电力系统抗差状态估计的经典方法和新方法.经典方法主要包括M估计、GM估计、高崩溃污染率估计等;新方法包括新息图状态估计、最大相关熵估计、最小信息损失状态估计、最多赞成状...     

Noise covariance matrix estimation with subspace model identification for Kalman filtering

A problem frequently encountered in Kalman filtering is the tuning of the noise covariance matrices. Indeed, misspecifying their values can drastically reduce the performance of the Kalman filter. Unfortunately, in most practical cases, noise statistics are not known a priori. This paper focuses on a method relying on subspace model identification theory to determine them accurately. This solution is developed for linear time invariant systems with stationary random disturbances having constant covariance matrices. Practically, these noise covariance matrices are determined from the comparison between an estimated state space representation and the discrete time state space representation involved in the Kalman filter equations. The method developed in this paper departs from most of the solutions available in the literature by the fact that it does not need any tuning parameter to be chosen by the user. After discussing theoretical results, several numerical examples are given to demonstrate the efficiency of the approach.     

基于等值信息交换的分布式抗差估计算法

提出了一种基于等值信息交换的分布式抗差状态估计算法。各子系统通过等值计算将自身量测信息浓缩成等值信息,协调层收集各子系统的等值信息计算出边界状态量进而实现分布式状态估计。此外,在分布式算法基础上实现了分布式抗差估计。采用等价权原理将指数型目标函数抗差估计方法转换成变权重的加权最小二乘估计,并基于不动点迭代的方法进行求解。在求解过程中,等值信息随着权重值的变化而不断更新,子系统得以综合全系统信息进行抗差估计。最后,构造了多子系统算例和含不良数据的算例对算法进行测试。测试结果表明分布式抗差估计算法具有很高的计算精度和很好的抗差性能。     

Extension of the tuning constant in the Huber's function for robust modeling of piezoelectric systems

This paper proposes a new modeling approach that is experimentally validated on piezoelectric systems in order to provide a black‐box pseudolinear model for complex systems control. Most of the time, one uses physical based approaches. However, sometimes complex phenomena occur in the system due to atypical changes of the process behavior, output noise or some hard nonlinearities. Therefore, we adopt identification methods to achieve the modeling task. The microdisplacements of the piezoelectric systems generate atypical data named outliers, leading to large estimated prediction errors. Since these errors disturb the classical normal probability density function, we choose here, as corrupted distribution model, the gross error model (GEM). In order to deal more efficiently with the outliers, we use the Huber's function, as mixed L₂/L₁ norms in which the tuning threshold named scaling factor is extended. From this function, a cost function also named PREC as parameterized robust estimation criterion is established. The identification is performed by choosing an Output Error model structure. In order to express the asymptotic covariance matrix of the robust estimator, we present a L finite Taylor's expansion to linearize the gradient and the hessian of the PREC. Experimental results are presented and discussed. Copyright © 2014 John Wiley & Sons, Ltd.     

基于抗差估计理论的输电线路故障定位新型算法

针对采样中出现的粗差,提出了一种基于抗差估计理论的故障定位算法。通过等价权原理,将抗差估计理论和最小二乘法有机的结合起来,有效地避免了粗差的影响。算法采用微分方程作为数学模型,并利用相模变换解耦;然后,在模域采用输电线路双端信号列写故障点方程;最后,用抗差最小二乘法求解。经过RTDS实验表明,该算法结果稳定,具有很好的准确性和抗干扰能力。     

电力系统中长期负荷预测的参数抗差估计研究

主要介绍提高中长期负荷预测结果的准确性和改善中长期负荷预测方法的抗粗差效果，对中长期负荷预测中参数的抗粗差估计进行了研究，提出了基于权函数的电力系统负荷预测参数抗差估计算法，通过对加权最小二乘法的修改，实现了负荷预报模型参数的抗差估计。算例表明，所提出的算法在处理中长期负荷预测中数据的粗差问题上效果较好，是改善预测精度的有益尝试。     

A recursive technique for tracking the feasible parameter set in bounded error estimation

In this paper, a new recursive algorithm is proposed for tracking parameter changes of a time‐varying linear system. Since a bounded error approach is adopted for both modeling the measurement noise and the parameter change process, the problem addressed amounts to the design of a procedure for updating an estimate of the feasible parameter set. The approximating regions considered are in the form of outbounding orthotopes. The novelty of the approach lies in the use of a selection technique which keeps track only of a special subset of the constraints defining the feasible set. These inequalities represent the binding constraints of suitable linear programs of limited size. The devised algorithm is tested on several numerical examples, showing remarkable performance both in computational burden, which is comparable to that of classical recursive estimation algorithms like recursive least squares (RLS) and quality of the set estimate as compared to alternative techniques available in the literature.     

Noise covariance matrices in state‐space models: A survey and comparison of estimation methods—Part I

This paper deals with the estimation of the noise covariance matrices of systems described by state‐space models. Stress is laid on the systematic survey and classification of both the recursive and batch processing methods proposed in the literature with a special focus on the correlation methods. Besides the correlation methods, representatives of other groups are introduced also with respect to their basic idea, estimate properties, assumptions and possible extensions, and user‐defined parameters. Common and dual properties of the methods are highlighted, and a simulation comparison using exemplary MATLAB implementations of the methods is provided.     

锂电池分段分数阶建模与荷电状态估计

为提高等效电路模型准确性,考虑等效电容分数阶本质和锂电池充放电不同阶段的不同变化特性,采用分数阶微积分理论建立了基于二阶RC模型的电池分段分数阶等效电路模型.用粒子群算法分段辨识分数阶阶数,通过混合脉冲功率特性(HPPC)实验辨识模型参数,使模型更符合电池实际工作状态.实验结果显示,新模型能够更准确地模拟电池充放电特性...     

用于配电网分布式抗差状态估计的自动分区

网络分区是进行配电网分布式状态估计的基础。分析配电网的网络结构特点,从各分区计算量均衡的角度出发,借助图论中网络的快速搜索能力,通过编程对配电网进行自动分区,从而实现状态估计的并行计算。为改善状态估计算法的抗差性,采用指数表达的权重系数,在迭代过程中降低不良数据在目标函数中权重值,从而减少不良数据对目标函数和估计结果的影响。这种基于分区的配电网分布式抗差状态估计算法可以实现对配电网的自动合理分区,有效地提高状态估计的计算速度,改善了算法对量测量的抗差性。通过IEEE-118节点算例的计算分析,说明了算法的可行性。     

基于抗差总体最小二乘法的电力系统谐波状态估计

介绍了谐波状态估计的数学模型及最小二乘和总体最小二乘的求解算法,综合考虑测量误差和参数误差的影响,利用总体最小二乘法进行谐波状态估计。分析了测量粗差对估计结果的影响,针对总体最小二乘法不具备抑制粗差能力的缺点,提出利用抗差总体最小二乘法进行谐波状态估计。用Matlab搭建了IEEE-14节点谐波测试系统仿真模型,在测量数据和参数矩阵中分别加入含有粗差的正态分布误差及正态分布误差,画出概率密度曲线图,并对总体最小二乘法、抗差最小二乘法和抗差总体最小二乘法进行比较,结果表明利用抗差总体最小二乘法能够得到更精确的谐波状态估计结果。     

基于Huber鲁棒估计的改进互补滤波姿态解算算法

针对站球机器人在坡面运动过程中,由于系统振荡倾向性导致的姿态估计不准确以及在估计中存在噪声等问题,设计了一种基于Huber鲁棒估计的改进互补滤波姿态解算算法。首先,对站球机器人在斜坡上进行了动力学分析和运动性能分析。其次,利用Huber鲁棒估计抑制站球机器人在坡面运动过程中由于机身振荡所引入的干扰噪声,并改进互补滤波进行姿态解算。最后,为了减少磁力计输出不稳定对姿态解算的干扰,设计了一种数据平滑切换方法。实物实验结果表明,设计的基于Huber鲁棒估计的改进互补滤波姿态解算算法相比于互补滤波算法,对俯仰角、横滚角和偏航角的估计精度分别平均提高19.21%、25.48%和36.04%,该算法可以有效地抑制站球机器人在坡面运动过程中由于机身振荡引入的噪声,能够保证姿态解算的准确性和实时性。     

船舶电力系统的数学建模和鲁棒控制器设计

为了提高船舶电力系统的稳定性,同时研究建立分散励磁式船舶电力系统数学模型的方法,以三台发电机并联运行的工况为例,考虑了发电机角速度、母线端电压以及电动机转子侧电流扰动等不确定性因素,以同步旋转坐标系为参考系分解,建立了解耦后的柴油发电机组、异步电动机、馈线、静态负载的数学模型.根据鲁棒控制理论,设计了船舶电力系统的H∞状态反馈控制器,并应用线性矩阵不等式求解了该控制器.仿真结果表明,当模型的各种扰动信号为脉冲信号时,系统响应能在较短的时间内收敛到0,稳定时间约为0.3s,表明所设计的控制器具有较好的实时性和较高的控制精确度.     

An adaptive robust observer for velocity estimation in an electro‐hydraulic system

This paper proposes the design of an observer to estimate the velocity of an electro‐hydraulic system by using pressure measurements only. The difficulties involved in the design of an observer for such a system include the highly nonlinear system dynamics, severe parametric uncertainties such as large variation of inertial load and unmatched model uncertainties. In order to address these issues, a nonlinear model‐based adaptive robust observer is designed to estimate the velocity. The contributions of the proposed work is twofold. First, it introduces a novel coordinate transformation to reconstruct the velocity estimate. And second, from a structural viewpoint, the design has two important features: (i) an underlying robust filter structure, which can attenuate the effect of uncertain nonlinearities such as friction and disturbances on the velocity estimation, and (ii) an adaptation mechanism to reduce the extent of parametric uncertainties. Experimental results on the swing motion control of an electro‐hydraulic robot arm demonstrate the effectiveness of the proposed observer. Copyright © 2012 John Wiley & Sons, Ltd.     

Fractional‐order multivariable composite model reference adaptive control

A novel multivariable composite model reference adaptive control scheme is developed for multivariable fractional‐order systems with arbitrary relative degree. Firstly, by introducing right gain matrix to substitute left gain matrix, the stringent symmetry assumption is no longer required. The design procedures of controller with certain and uncertain high‐frequency gain matrix are then provided, respectively. The (robust) stability of the resulting closed‐loop control system is investigated by indirect Lyapunov method. It is shown that the composite model reference adaptive control can achieve better performance on output tracking than that of model reference adaptive control. Finally, the effectiveness and applicability of the proposed control scheme are demonstrated in 3 numerical examples.     

Robust real-time parameter estimation for linear systems affected by external noises and uncertainties

A robust adaptive parameter estimation method, based on the application of a full-order filter capable of rejecting exogenous disturbances, is proposed in this article. A linear matrix inequality condition is proposed to synthesize the desired robust filter, assuming the presence of a known input control with constraints. The filter uses the output of the system to estimate the desired signal that will be employed in the adaptive estimation procedure and, to assure robustness to exogenous noise and unstructured uncertainties, the guaranteed cost is minimized in the synthesis condition. The filtered signals are then applied to an adaptive procedure to estimate the unknown system's internal parameters, which is also proposed in this article. It is shown that lower values for the guaranteed cost from the disturbance input to the error output of the filter imply more accurate estimations of the parameters. The efficiency of the proposed estimation technique is illustrated through a simulated model and a physical system has been considered to validate real-time estimation.     

参数不确定Chen混沌系统鲁棒模糊控制器的设计

基于TS(Takagi-Sugeno)模糊模型，研究具有参数不确定性Chert混沌系统的鲁棒控制器设计。首先构建含有参数不确定性的TS模糊模型：然后利用并行分布补偿的方法，设计使模糊系统在平衡点附近渐近稳定的鲁棒模糊控制器。该设计通过解一组线性矩阵不等式(LMI)得到局部区域控制器，进而设计TS模糊系统的鲁棒控制器。该鲁棒模糊控制器的渐近稳定性条件更为宽松，能够降低控制器设计的保守性。最后的仿真结果表明所设计的鲁棒模糊控制器对参数不确定Chert混沌系统具有良好的控制效果。     

基于Legendre多项式的锂离子电池降阶模型

在Newman模型以及单粒子模型(SPM)的基础上,提出基于Legendre正交多项式的电池模型降阶算法;同时,将固液相物理量的分布纳入模型算法,在提高运算速度的情况下,保证运算精度。以磷酸铁锂(Li Fe PO4)正极锂离子电池为例,对导出的降阶模型进行仿真验证。与全阶模型相比,该模型所计算的电池状态量误差均能保持在2%下。     

A design method for robust model matching control of nonminimum‐phase discrete‐time systems

This paper presents a design method for robust model matching control of nonminimum‐phase discrete‐time systems. This scheme can robustly control the nominal model in the presence of unmodeled dynamics and can achieve the desired model matching simultaneously. Furthermore, the sufficient condition for stabilizing the nominal model in the presence of the unmodeled dynamics is derived and the existence of bounds for all signals is proved. Finally, computer simulation results are presented to illustrate the effectiveness of the proposed method. © 1999 Scripta Technica, Electr Eng Jpn, 128(2): 36–44, 1999     

一种基于非线性模型的OFDM信道估计

导频辅助的信道估计方法是OFDM系统中应用最为广泛的一类信道估计方法,其中的2-D维纳滤波是最小均方误差意义下的最佳线性估计器,但是由于其计算量非常大,因而在实际中不能得到很好的应用。2×1-D的维纳滤波器利用信道相关函数的可分离性,对2-D维纳滤波器进行了简化,一定程度地降低了其复杂性,但仍然需要知道或估计信道的统计特性。文中介绍了一种基于非线性模型的信道估计方法,对其算法进行了仿真并与2×1-D维纳滤波的误比特率(BER)性能进行了比较。仿真结果表明,此方法能以较低的复杂性达到与2×1-D维纳滤波相近的性能,且无需对信道特性估计,是一种较实用的信道估计方法。