This thesis deals with various aspects of coordinated voltage control in electric power systems. It consists of an introduction and six papers. The introduction contains a summary of the thesis and tutorials on voltage control and the search methods that have been applied.

The first part deals with the coordination of cascaded tap changers in radial distribution feeders. A tuning rule for the conventional (local) controllers as well as two new (centralized) schemes are proposed: firstly, an optimal controller based on on-line optimization and secondly, a rule based controller based on a fuzzy inference system. A prototype of the fuzzy-rule based controller has been installed and successfully tested in a distribution feeder in the south of Sweden.

The second part of the thesis describes a coordinated system protection scheme (SPS) against voltage collapse based on model predictive control. Using combinatorial optimization and predictions of the system's future behaviour, the SPS optimally coordinates dissimilar and discrete controls such as generator, tap changer and load shedding controls in presence of load dynamics and constraints on controls as well as voltages and currents in the network.

Modelling of power systems has also been addressed. The third part describes a freely available power system library called ObjectStab intended for voltage and transient stability analysis and simulation written in Modelica--a general-purpose object-oriented modelling language. All component models are transparent and can be modified or extended. Power system topology and parameter data are entered in one-line diagram form using a graphical editor. The component library has been validated using comparative simulations with Eurostag.

Coordinated Voltage Control in Electric Power Systems

This paper presents a method to stabilize a power system with long distance bulk power transmission from an isolated large power plant by a synchronous condenser with fast excitation control. Excitation controls of a generator have achieved great success as a power system stabilizer (PSS). Synchronous condensers have been applied in large numbers to power systems for the control of system voltage and reactive power with high reliability so far. In this study the synchronous condenser with a devised excitation control has been applied for the stabilization of a generator power swing by installing the synchronous condenser at a bus in the transmission line near the generator. A design method based on the damping and synchronizing torques is proposed. The application of H-infinity control is also considered to develop a robust control system.

Power system stabilization by synchronous condenser with fast excitation control

Interconnected power systems are critically vulnerable to instability due to the disturbances in any one portion of the system. Even low-frequency oscillations and small disturbances may lead to an outage of the system. Properly tuned Power System Stabilizer (PSS) is an effective tool for the suppression of these oscillations. This paper proposes a novel approach to tune proportional-integral (PI), proportional-integral-derivative (PID) and lead-lag PSS for a single machine infinite bus (SMIB) network by using backtracking search algorithm (BSA) to damp out low-frequency oscillation. The efficacy of BSA tuned PSS has been investigated by comparing the simulation results with fixed gain conventional PSS. In addition, the damping ratio and Eigenvalues of the same network have been compared with genetic algorithm (GA) based tuned PSS.

Power system stability enhancement by designing optimal PSS employing backtracking search algorithm

The paper presents an algorithm for fast power system contingency analysis using pattern recognition. The pattern space is clustered into data boxes for ease of search and flexibility of programming. The addressable memory structure of the pattern space decouples the voltage prediction problem into subproblems for one busbar and one contingency at a time. To reduce the working memory, the algorithm learns from the short-term load trend and selects only a few data boxes for on-line processing. Further computational savings and improvements in accuracy are achieved by adopting an innovative wafer data box structure that also facilitates subsequent refinement by additions/deletions of patterns acquired from real-time operational experience. Other techniques, with the same objectives, include a procedure for eliminating insignificant features from data boxes and clumping their effects into correction terms; a methodology for selecting the best expression for voltage prediction; and a pattern filter for placing the target state at the geographical centre of the training set nearest neighbourhood patterns.

http://ieeexplore.ieee.org/iel1/2205/800/00020225.pdf

Fast power system voltage prediction using knowledge-based approach and on-line box data creation

The pattern recognition method is applied to the related power system problems of security analysis and security constrained optimum power dispatch. Various techniques, such as box data creation and wafer structure, the method of search, short-term load trend prediction, feature reduction, and on-line training set creation, have been developed to achieve high evaluation accuracies as well as computational savings. The formulation of the method used is discussed, and several study cases are presented to demonstrate the feasibility of its possible implementation in real systems. These study cases include an application of the method to evaluate post-contingency voltage prediction in the Hong Kong transmission network and the optimum power dispatch in typical IEEE networks. >

Application of pattern recognition technique to power system security analysis and optimization

In this paper, dynamic stability assessment of electrical power systems is formulated as a pattern recognition problem so that it is fast and accurate enough for on-line applications. The problem concerned is the potentially hazardous dynamic instability of the interconnected power system between Hong Kong and China. New techniques, such as the Branch and Bound Search, are employed to achieve optimality in Feature Selection. In Feature Extraction where further dimensionality reduction is made, matrix augmentation is used to extract information content in class-centralised vectors as well as in class-mean vectors. Finally, for improvement of classification efficiency, an innovative approach making use of partitioning and decision tree search is pursued to tackle the non- linearly separable patterns which exist uniquely in the study of dynamic stability.

C.S. Chang

Papers

Electrical Power System Dynamic Stability Evaluation using a Knowledge-Based Approach