Showing papers by "Zhao Yang Dong published in 1998"

A general method for small signal stability analysis

Abstract: This paper presents a new general method for computing the different specific power system small signal stability conditions The conditions include the points of minimum and maximum damping of oscillations, saddle node and Hopf bifurcations, and load flow feasibility boundaries All these characteristic points are located by optimizing an eigenvalue objective function along the rays specified in the space of system parameters The set of constraints consists of the load flow equations, and requirements applied to the dynamic state matrix eigenvalues and eigenvectors Solutions of the optimization problem correspond to specific points of interest mentioned above So, the proposed general method gives a comprehensive characterization of the power system small signal stability properties The specific point obtained depends upon the initial guess of variables and numerical methods used to solve the constrained optimization problem The technique is tested by analyzing the small signal stability properties for well-known example systems

Analysis of small signal stability margins using genetic optimization

Abstract: Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc.

Advanced methods for small signal stability analysis and control in modern power systems

Abstract: This thesis is aimed at exploring issues relating to power system security analysis particularly arising under an open access deregulated environment. Numerical methods and computation algorithms locating the critical security condition points and visualizing the security hyper-plane in the parameter space are proposed. The power industry is undergoing changes leading to restructuring and privatizing in many countries. This restructuring consists in changing the power industry from a regulated and vertically integrated form into regional, competitive and functionally separate entities. This is done with the prospect of increasing efficiency by better management and better usage of existing equipment and lower price of electricity to all types of customers while maintaining a reliable system. As a result of deregulation and restructuring, power suppliers will increasingly try to deliver more energy to customers using existing system facilities, thereby putting the system under heavy stress. Accordingly, many technical and economic issues have arisen, for example, all or some of transient instability, aperiodic and oscillatory instability, insufficient reactive power supply, and even voltage collapse problems may coexist. This situation introduces the requirement for comprehensive analytical tools to assess the system security conditions, as well as to provide optimal control strategies to overcome these problems. There are computational techniques for assessing the power system stability critical conditions in given loading directions, but it is not enough to just have a few critical points in the parameter space to formulate an optimal control to avoid insecurity. A boundary or hyper-plane containing all such critical and subcritical security condition points will provide a comprehensive understanding of the power system operational situation and therefore can be used to provide a global optimal control action to enhance the system security. With the security boundary or hyper-plane available, the system operators can place the power system inside the security boundaries, away from instability, and enhance its security in an optimal way. Based on proper power system modelling, a general method is proposed to locate the power system small signal stability characteristic points, which include load flow feasibility points, aperiodic and oscillatory stability points, minimum and maximum damping points. Numerical methods for tracing the power system bifurcation boundaries are proposed to overcome nonconvexity and provide an efficient parameter continuation approach to trace stability boundaries of interest. A Delta-plane method for visualizing the power system load flow feasibility and bifurcation boundaries is proposed. The optimization problem defined by assessing the minimal distance from an operating point to the boundaries is considered. In particular, emphasis is placed on computing all locally minimal and the global minimum distances. Due to the complexity of any power system, traditional optimization techniques sometimes fail to locate the global optimal solutions which are essential to power system security analysis. However, genetic algorithms, due to their robustness and loose problem pre-requisites, are shown to fulfill the task rather satisfactorily. Finally, a toolbox is described which incorporates all these proposed techniques, and is being developed for power system stability assessment and enhancement analysis.