Gajjala, Madhu Mohan and Ahmad, Aijaz (2023) A Novel Adaptive Restarting Genetic Algorithm Based Congestion Management. POLLACK PERIODICA : AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES, 18 (1). pp. 149-154. ISSN 1788-1994 (print); 1788-3911 (online)
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Abstract
This manuscript proposes a novel adaptive restarting genetic algorithm-based solution approach for rescheduling generation-based congestion control. The generator sensitivity values are considered to select generators to participate in the congestion management. The efficacy of the suggested technique is demonstrated on a 39-bus New England system and a modified IEEE 30 bus system, and a comparative study with other optimization strategies are established. The findings produced with the suggested technique for congestion management better the outcomes obtained with different methods. The presented approach ensures a superior convergence profile by eliminating local minima traps. This method also assists the independent system operator in managing congestion more efficiently.
| Item Type: | Article |
|---|---|
| Additional Information: | MTA KFB támogatási szerződés alapján archiválva |
| Uncontrolled Keywords: | genetic algorithms, deregulation, evolutionary algorithms, generator sensitivity factor, congestion |
| Subjects: | T Technology / alkalmazott, műszaki tudományok > TA Engineering (General). Civil engineering (General) / általános mérnöki tudományok |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 04 Aug 2023 12:37 |
| Last Modified: | 07 Mar 2025 00:15 |
| URI: | https://real.mtak.hu/id/eprint/170968 |
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