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Journal ArticleDOI

Design of fuzzy power system stabilisers for multimachine power systems

Y.-Y. Hsu, +1 more
- Vol. 137, Iss: 3, pp 233-238
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TLDR
A new type of power system stabiliser based on fuzzy set theory is proposed to improve the dynamic performance of a multimachine power system and is of decentralised output feedback form and is easy for practical implementation.
Abstract
A new type of power system stabiliser based on fuzzy set theory is proposed to improve the dynamic performance of a multimachine power system. To have good damping character istic over a wide range of operating conditions, speed deviation (δω) and acceleration (δω) of a machine are chosen as the input signals to the fuzzy stabiliser on that particular machine. These input signals are first characterised by a set of linguistic variables using fuzzy set notations. The fuzzy relation matrix, which gives the relationship between stabiliser inputs and stabiliser output, allows a set of fuzzy logic operations that are per formed on stabiliser inputs to obtain the desired stabiliser output. Since only local measurements are required by the fuzzy stabiliser on each generating unit, the proposed stabiliser is of decentralised output feedback form and is easy for practical implementation. The effectiveness of the proposed fuzzy stabiliser is demonstrated by a multimachine system example.

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Citations
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Journal Article

Genetic Algorithm Based Design of Fuzzy Logic Power System Stabilizers in Multimachine Power System

TL;DR: It is shown in this paper that the system dynamic performance can be improved significantly by incorporating a genetic-based searching mechanism and this will add an intelligent dimension to the stabilizer and significantly reduces computational time in the design process.
Dissertation

On Power System Stabilizers: Genetic Algorithm Based Tuning and Economic Worth as Ancillery Services

TL;DR: In this paper, a GA-based method to simultaneously tune PSSs is developed in the first part of this thesis, while the second part is dedicated to developing a game theory based method to financially compensate the generators for the control effort they provide for the power system.
Book ChapterDOI

Chaos Control Using Fuzzy Controllers (Mamdani Model)

TL;DR: Controlling a strange attractsor, or say, a chaotic attractor, is introduced in this chapter and the idea of using the fuzzy logic concept for controlling chaotic behavior is presented.
Proceedings ArticleDOI

Cooperative control of AVR and GOV for improving transient stability of power systems using fuzzy controller

TL;DR: The authors propose the cooperative fuzzy controller of AVR and GOV to improve the transient stability of power systems and introduce the ideas of sliding mode control, so that the fuzzy rules can be constructed systematically.
Journal ArticleDOI

Anticipatory fuzzy control of power systems

TL;DR: The paper presents an anticipatory fuzzy control to improve the stability of electric power systems and requires a neural-network prediction routine using modified- Kalman-filter-based fast-learning algorithm.
References
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Book

Fuzzy Set Theory - and Its Applications

TL;DR: The book updates the research agenda with chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research.
Book

Power System Control and Stability

TL;DR: In this paper, the authors present a mathematical model of the Synchronous Machine and the effect of speed and acceleration on the stability of a three-phase power system with constant impedance load.
Journal ArticleDOI

Concepts of Synchronous Machine Stability as Affected by Excitation Control

TL;DR: In this article, the stability of synchronous machines under small perturbations is explored by examining the case of a single machine connected to an infinite bus through external reactance, and the results are shown to be similar to ours.
Journal ArticleDOI

Comparing fuzzy logic with classical controller designs

TL;DR: A unified approach for comparing the performance of fuzzy and nonfuzzy controller designs is presented and relationships are established between the gain parameters for the two classes of controller designs.
Journal ArticleDOI

Coordinated Application of Stabilizers in Multimachine Power Systems

TL;DR: The linear state space matrix is derived directly from perturbation of the states of a large scale power system dynamic simulation and a subset of this matrix is used to yield the sensitivity of damping ratios of eigenvalues to stabilization measures in individual machines.