Electric Power Applications of Fuzzy Systems (IEEE Press by Mohamed E. El-Hawary

By Mohamed E. El-Hawary

This ebook deals an creation to functions of fuzzy approach concept to chose parts of electrical strength engineering. It offers theoretical history fabric from a pragmatic viewpoint after which explores a few functions of fuzzy structures. such a lot lately, there was a big surge in learn and alertness articles in this topic. earlier although, there were no books that prepare a realistic advisor to the basics and purposes elements. electrical strength functions OF FUZZY platforms provides, lower than one hide, unique contributions by way of authors who've pioneered within the program of fuzzy method concept to the electrical strength engineering box. each one bankruptcy comprises either an advent to and a state of the art assessment of every software sector.

backed via: IEEE strength Engineering Society.

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Extra info for Electric Power Applications of Fuzzy Systems (IEEE Press Series on Power Engineering)

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Signature signals could be collected before the suspect rotor is dismantled for maintenance. After the rotor is repaired and brought back on line, healthy signature signals can be collected. The healthy regions and thresholds can then be established using the proposed techniques. The signature signals recorded before correction of the fault can then be processed by the detection algorithm. Low-frequency oscillations are a common problem in large power systems. A power system stabilizer (PSS) can provide supplementary control signals to the excitation system and/or the speed governor system of the electric-generating unit to damp these oscillations and to improve its dynamic performance.

2. 5. Convexity Convexity of fuzzy sets plays an important role in fuzzy set theory, and it can be defined in terms of a-cuts or membership functions. A fuzzy set is convex if and only if each of its a-cuts is a convex set. 4(a) is convex, but it is not normalized. 4(b) is not convex, but it is normalized. Note that the convexity definition does not imply that the membership function of a convex fuzzy set is a convex function [see Fig. 4(c)]. 1 ..................... 4 Convex and nonconvex fuzzy sets.

B , ~ ) = O m i n { a , b } + ~- (Pl ) ( a + b ) with p E [0, 11. 4. Aggregation 35 The parameter p indicates how close the operator is to the strict logical meaning of “and” and “or,” respectively. For ,B = 1 , the “fuzzy and” becomes the minimum operator, and the “fuzzy or” reduces to the maximum operator. ” Additional averaging aggregation procedures are symmetric summation operators, which, like the arithmetic or geometric mean operators, indicate some degree of compensation, but in contrast to the latter, these procedures are not associative.

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