一种饱和电力系统稳定器控制效果的判断方法

针对饱和线性系统，借助二次型Lyapunov函数，估计稳定域的一个严格子集。同时为了减少保守性，利用矩阵的Schur补性质，将如何选取该二次型Lyapunov函数的问题转化为标准的LMI凸优化问题。将该方法应用于电力系统，提出一种判断饱和PSS控制是否有效的方法。其主要思路是估计出饱和系统的稳定域，通过分析预想扰动的状态量是否位于估计的稳定域内，从而为判断此饱和PSS控制是否能有效镇定预想的扰动提供判据，利用算例验证了方法的有效性。     

考虑控制器饱和与扰动的电力系统稳定域估计

针对含有控制器饱和与扰动的电力系统线性模型,提出一种基于二次型李亚普诺夫函数的实用稳定域估计新方法。首先通过引入死区函数建立控制器输出饱和且存在扰动的闭环电力系统模型;然后给出估计该系统稳定域的方法。为了减小估计结果的保守性,引入一个新的自由度,并将李亚普诺夫函数的选择转化为标准线性矩阵不等式约束优化问题,进一步利用矩阵的Schur补性质对该问题进行简化以便于直接利用Matlab软件进行求解;最后,将该方法应用于3机5节点电力系统的稳定域估计,证明了该方法具有简单实用且严格可靠的优点。     

运用饱和关联函数分析扰动离散控制饱和系统

为探讨舍饱和状态反馈扰动离散控制饱和系统的稳定性问题，运用饱和关联Lyapunov函数、LQR方法设计控制器，结合LMI给出一集合在系统吸引域内的充分条件。该函数包含了系统控制器饱和程度的实时信息，所估计的系统吸引域具有较少的保守性，该分析和设计方法被推广到无扰动的离散控制饱和系统，算例说明了该方法的有效性。     

电力系统强迫功率扰动源波形与大小估计

强迫功率扰动源波形与大小对电力系统稳定性有重要影响。在电力系统原状态方程基础上,引入一个用以代表系统中实际发生扰动的虚拟扰动,以此构建扰动观测器。通过扰动观测器的输出与系统真实输出进行比较,形成残差,采用迭代算法进行求解,从而实现对系统扰动的准确估计。在此基础上,研究了不同扰动源特性对系统稳定性的影响。最后,通过时域仿真对该方法的有效性进行了验证。结果表明,该观测器能够同时实现对强迫功率扰动源和系统状态估计,随机扰动源相比规则扰动源更易引起系统的不稳定。     

具有饱和输入变时滞系统的自适应滑动模控制

研究了一类具有饱和执行器且含不匹配不确定性和匹配外界扰动的变时滞系统的稳定性问题。基于滑模控制原理提出了一种自适应控制方法。该方法不仅取消了饱和界已知的条件,而且给出了滑动模态存在性和可达性的条件。     

鲁棒优化在电力系统调度决策中的应用研究综述

鲁棒优化是一种利用区间扰动信息,在最劣扰动条件下进行最优决策的优化方法,因其具有基础数据易得、计算效率高、适用于大规模系统求解等优点,近来,被应用于电力系统的调度决策问题。文中在阐明鲁棒优化自身特点的基础上,首先,对鲁棒优化方法在电力系统机组组合问题中的应用进行了介绍,阐述了连续性、偶发性扰动模式下的鲁棒优化方法建模规律,讨论了常用不确定集的形式和保守度的控制方法;其次,介绍了鲁棒优化方法在经济调度问题中的研究现状,介绍了三类典型方法,包括自适应鲁棒优化方法、含仿射矫正过程的实时调度鲁棒优化方法和最大化可接受扰动范围鲁棒优化方法,并对其各自的特点进行了阐述;最后,对该领域研究面临的关键问题和未来的发展方向进行了探讨和分析。     

具有执行器饱和与随机非线性扰动的离散系统模型预测控制

针对具有执行器饱和与随机非线性扰动的离散系统,提出一种模型预测控制器设计方法。通过引入一个服从Bernoulli分布且已知条件概率的随机变量描述系统的随机非线性扰动,根据预测控制的滚动优化原理,在每一采样时刻,求解保证无穷区域二次性能指标期望值的上界达到最小的优化问题。运用Lyapunov稳定性理论,给出了保证控制算法可行性和闭环系统随机稳定性的充分条件。最后通过仿真验证了所提控制方法的有效性。     

基于饱和控制理论的储能装置容量配置方法

采用饱和控制理论求解保持系统稳定的储能装置（energy storage device,ESD）最小容量,为电力系统储能装置的配置提供依据。从稳定域及总体收敛速度2方面分析了储能容量对含储能装置的电力系统稳定性的影响,提出了一种储能装置最小容量配置方法。构建了以储能装置容量最小为目标函数,以饱和系统稳定域和总体收敛速度指标为约束条件的优化模型。通过矩阵Schur补性质将模型求解转化为标准的线性矩阵不等式（linear matrix inequalities,LMI）问题,利用内点法进行求解,可得储能装置的最小容量。该方法求解最小储能容量简便易行,不需进行大量的时域仿真。WSCC3机9节点系统算例验证了该方法的有效性和灵活性。     

基于暂态稳定裕度指标的最优潮流求解

基于一种新型暂态稳定裕度指标，提出了求解含暂态稳定约束的最优潮流（SCOPF）新方法。该方法利用暂态稳定裕度指标及其灵敏度组成的不等式代替暂态稳定约束，将针对预想故障的优化潮流问题转化为常规非线性规划问题。所用的暂态稳定裕度指标基于故障后电力系统稳定域边界隐式方程，可由稳定域二次近似获得其近似估计。所提出的SCOPF求解方法易于实现，可处理多个预想故障，算法具有良好的收敛性和合理的计算时间。在新英格兰10机39节点系统中进行的仿真验证了该方法的有效性。     

一种求解最优机组组合问题的随机扰动蚁群优化算法

针对蚁群优化算法中易出现的停滞现象，设计出一种新颖的随机扰动蚁群优化算法。该算法包含了两个重要方面：一是提出了采用倒指数曲线来描述的扰动因子；二是设计出了相应的随机选择策略和扰动策略。此外，还对该算法中参数的选取方法及取值范围进行了研究和探讨。利用该算法求解最优机组组合问题，并在模型的转化、约束项的处理等方面进行了深入的分析。通过对两个测试系统进行计算，并与基本蚁群算法进行比较，证明了该算法可以有效地克服基本蚁群算法计算时间较长和容易出现停滞现象的缺陷，具有更好的全局优化能力。     

Impact of saturation nonlinearities/disturbances on the small-signal stability of power systems: An analytical approach

In this paper, a multi-objective optimization model is presented to estimate the practical stability region and maximum endurable disturbance rejection for a small-signal power system dynamic model with saturation nonlinearities and disturbance rejection. Iterative algorithms are developed to solve for Pareto optimized solutions (POS) of this optimization. Furthermore, as an application of this approach to power systems, a method to analyze the impact of saturation nonlinearities and disturbance rejection on power system small-signal stability is introduced based on the estimated stability region and maximum endurable disturbance rejection. Numerical results of a test power system with detailed saturated PSS controllers are described, indicating the reliability and simplicity of the method.     

A method for evaluating the performance of PSS with saturated input

In this paper, we report upon a method for estimating an ellipsoid, which resides entirely in the stability region of a linear system with saturation nonlinearities. To reduce the conservatism in the estimation, a procedure to transform the estimation problem into a simple convex optimization with linear matrix inequality (LMI) constraints is presented. As an application of this development, a method is introduced to estimate the stability region of a multi-machine power system with power system stabilizers (PSS) subject to saturated feedback. The idea is to check if the system state after a disturbance resides inside the estimated stability region. Thereby a sufficient condition is derived to conclude the effectiveness of saturated PSS controls. Numerical results of a test power system with three generators and five buses are described, indicating the reliability and simplicity of this approach.     

Power System Control With an Embedded Neural Network in Hybrid System Modeling

Output limits of the power system stabilizer (PSS) can improve the system damping performance immediately following a large disturbance. Due to nonsmooth nonlinearities arising from the saturation limits, these values cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures can been used. A feedforward neural network (with a structure of multilayer perceptron neural network) is applied to identify the dynamics of an objective function formed by the states and, thereafter, to compute the gradients required in the nonlinear parameter optimization. Moreover, its derivative information is used to replace that obtained from the trajectory sensitivities based on the hybrid system model with the differential-algebraic-impulsive-switched structure. The optimal output limits of the PSS tuned by the proposed method are evaluated by time-domain simulation in both a single-machine infinite bus system and a multimachine power system.      

一种地区电网分布式无功优化方法

针对地区电网的特点，提出一种分布式无功优化的新方法。考虑到各级网络结构的差异及其无功优化的特点，采用分层分区的思想，将地区电网分成次输电网络和中低压配电网两层子系统。这样，整个大规模地区电网的优化问题被分解为若干个小规模系统的优化子问题，降低了优化问题的复杂度。次输电网络和配电网可以根据自身网络特点，选用不同的潮流算法、优化数学模型、优化算法进行无功优化。各层之间通过Internet进行数据的交互，利用分布式计算的方法实现整个网络无功资源的优化。仿真结果验证了这种分布式无功优化方法是可行、有效的。     

LINGO在电力系统机组组合优化中的应用

电力系统机组组合是一个高维数、非凸、离散、非线性的混合整数优化问题。本文介绍了LINGO软件优化方法及在电力机组组合优化中的应用。建立电力系统机组组合的优化模型,结合3母线电力系统实例,采用LINGO求解优化模型,验证了该方法的可行性和有效性。LINGO为电力机组组合优化提供了一个新的方法,具有很好的应用前景。     

System identification of a class of Wiener systems with hysteretic nonlinearities

Existing works on Wiener system identification have essentially been focused on the case where the output nonlinearity is memoryless. When memory nonlinearities have been considered, the focus has been restricted to backlash like nonlinearities. In this paper, we are considering Wiener systems where the output nonlinearity is a general hysteresis operator captured by the well‐known Bouc–Wen model. The Wiener system identification problem is addressed by making use of a steady‐state property, obtained in periodic regime, referred to as ‘hysteretic loop assumption’. The complexity of this problem comes from the system nonlinearity as well as its unknown parameters that enter in a non‐affine way in the model. It is shown that the linear part of the system is accurately identified using a frequency method. Then, the nonlinear hysteretic subsystem is identified, on the basis of a parameterized representation, using a prediction‐error approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Transient stability hierarchical control in multimachine powersystems

The authors present the optimal transient stability control problem in a hierarchical structure for multimachine power systems. The two-level structure retains the local closed-loop controls, thereby easing its implementation on existing systems. The formulation accounts for nonlinearities and interconnections, and the optimization of the system transient performance is obtained with less computational effort. Since the computations are distributed among the many local feedback subsystems, the storage and solution times are considerably less than those required by a single overall centralized controller. This advantage becomes much stronger as the system size increases. For illustration purposes, this technique was applied successfully to a four-machine system     

Permutation-based Power System Restoration in Smart Grid Considering Load Prioritization

Abstract

In the smart grid environment, a power system restoration plan with flexibility is needed to improve reliability and efficiency in an automated way. Traditional system restoration methods based on fixed time intervals may not meet the requirement. This article proposes a new permutation-based model for power system restoration within an optimized flexible duration considering available generator capability and load prioritization. By utilizing this new model, power system restoration is formulated as a permutation-based combinatorial optimization problem to maximize the restored load per unit time. Finally an action-by-action flexible time schedule is obtained for generator startup. A novel quantum-inspired evolutionary algorithm, called the quantum-inspired differential evolutionary algorithm, has been applied to solve this problem due its to high population diversity and fast convergence. The effectiveness of the proposed restoration approach has been validated using IEEE 39- and 57-bus systems.     

基于过程状态特征化的电容器动态规划与控制

研究了电容器规划与动态控制问题,首先建立了给定时段内配电网有功能量损耗的评估模型,并在考虑负荷变化的情况下,依靠过程状态特征化的概念构造了一个以系统能量损耗最小为目标的无功优化策略,适当的线性化处理和逐步修正思想大大简化了电容器规划与动态控制问题的数学模型,降低了求解难度,运用静态计算方法解决了动态优化问题,有效降低了动态无功优化所需的计算量。应用所提出的策略对IEEE-69节点配电系统进行了仿真计算,验证了所述方法的合理性和有效性。