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Fuzzy adaptive bacterial foraging congestion management using sensitivity based optimal active power re-scheduling of generators
This paper presents a new method of fuzzy adaptive bacterial foraging (FABF) based congestion management (CM) for the first time by optimal rescheduling of active powers of generators selected based on the generator sensitivity to the congested line. In the proposed method, generators are selected b...
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Published in: | Applied soft computing 2011-12, Vol.11 (8), p.4921-4930 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper presents a new method of fuzzy adaptive bacterial foraging (FABF) based congestion management (CM) for the first time by optimal rescheduling of active powers of generators selected based on the generator sensitivity to the congested line. In the proposed method, generators are selected based on their sensitivity to the congested line to utilize the generators efficiently and optimal rescheduling of the active powers of the participating generators was attempted by FABF. The FABF algorithm is tested on IEEE 30-bus system and Practical Indian 75-bus system and the results are compared with the Simple Bacterial Foraging (SBF) and Particle Swarm Optimization (PSO) algorithms for robustness and effectiveness of congestion management. It is observed from the results that FABF is effectively minimizing the cost of generation in comparison with SBF and PSO for optimal rescheduling of generators to relieve congestion in the transmission line. |
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ISSN: | 1568-4946 1872-9681 |
DOI: | 10.1016/j.asoc.2011.06.007 |