UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 4 Issue 2
March-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1702019


Registration ID:
170060

Page Number

80-90

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Title

Comparative study of Fuzzy Logic Using different Fuzzy inference systems and Conventional Methods for constrained power flow solutions and Contingency Evaluation in power systems

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Abstract

This research provides a comparison between the performances of Sugeno type versus Mamdani-type fuzzy load flow (FLF) inference systems, a fuzzy contingency evaluation (FCE) algorithm of electrical power systems using Triangular and Guassian membership functions based on fuzzy control theory. Fuzzy logic is used to deal with uncertainties such as bus injected active and reactive powers, and lines data in a simple manner thereby reducing the system complexity and the time required for calculations. In the fuzzy load flow methods, the real and reactive power mismatches per voltage magnitude at each bus of the power system are chosen as the crisp input values, which are fuzzified into the fuzzifier. The process logic uses a rule base to explode the fuzzy output signals which are defuzzified as crisp output values to be chosen as the corrections of voltage angle and magnitude at each bus of the system. A sparsity technique is implemented for the sparse matrices as input data in order to reduce the overall computation time and storage requirements. The performance of the proposed method have been tested on the IEEE 14-bus, and 30-busbar IEEE International test system. Results are compared to other powerful methods according to the following criteria namely, number of iterations, total computation time, storage requirements, and reliability of solving ill-conditioned power systems under normal operation and contingency conditions. The proposed method is faster (in overall computation time) than the fast decoupled load flow method by about 65% for the same power mismatch accuracy. Two characteristic features of the proposed fuzzy load flow are the real-time (on-line) applicability for small- as well as large-scale power systems. Also, the fuzzy system has many advantageous features such as optimized system complexity, control of power flow, control of nonlinear system, and its durability to include uncertainty in input data.

Key Words

Fast decoupled method, Fuzzy Load Flow, Fuzzy Logic, Newton-Raphson Method, Sugeno Fuzzy Inference System, Mamdani Fuzzy Inference systems, Load flow analysis, Contingency evaluation, Sparsity Technique

Cite This Article

"Comparative study of Fuzzy Logic Using different Fuzzy inference systems and Conventional Methods for constrained power flow solutions and Contingency Evaluation in power systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 2, page no.80-90, March-2017, Available :http://www.jetir.org/papers/JETIR1702019.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Comparative study of Fuzzy Logic Using different Fuzzy inference systems and Conventional Methods for constrained power flow solutions and Contingency Evaluation in power systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 2, page no. pp80-90, March-2017, Available at : http://www.jetir.org/papers/JETIR1702019.pdf

Publication Details

Published Paper ID: JETIR1702019
Registration ID: 170060
Published In: Volume 4 | Issue 2 | Year March-2017
DOI (Digital Object Identifier):
Page No: 80-90
Country: Baghdad, Aljadrieah, Iraq .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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