Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis
Abstract Power system instability primarily results from the deviation of the frequency from its predefined rated value. This deviation causes voltage collapse, which further leads to sudden blackouts of the power system network. It is often triggered by a lack of reactive capacity. The solution to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-02-01
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| Series: | Energy Conversion and Economics |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/enc2.12048 |
| _version_ | 1797901492919730176 |
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| author | Rohit Babu Saurav Raj Bishwajit Dey Biplab Bhattacharyya |
| author_facet | Rohit Babu Saurav Raj Bishwajit Dey Biplab Bhattacharyya |
| author_sort | Rohit Babu |
| collection | DOAJ |
| description | Abstract Power system instability primarily results from the deviation of the frequency from its predefined rated value. This deviation causes voltage collapse, which further leads to sudden blackouts of the power system network. It is often triggered by a lack of reactive capacity. The solution to the reactive capacity problem can be obtained in two stages. In the first stage, the vulnerable buses, also known as ‘weak buses’, where voltage failure might occur are identified, and the Var compensating devices are mounted at those locations. The proposed approach utilizes three simple vulnerable bus detection methods: the fast voltage stability index, line stability index, and voltage collapse proximity index (VCPI). In the second stage, various optimization algorithms are implemented to determine the optimal setting of Var sources, such as particle swarm optimization, differential evolution, the whale optimization algorithm, the grasshopper optimization algorithm, the salp swarm algorithm, grey wolf optimization, and oppositional grey wolf optimization (OGWO). The results indicate that the best approach to poor bus recognition is the VCPI, and the OGWO technique provides a much less expensive system than other optimization strategies used for problems of optimal reactive power planning. |
| first_indexed | 2024-04-10T09:01:50Z |
| format | Article |
| id | doaj.art-10c9eed236b54a06b57b58274a8c2eec |
| institution | Directory Open Access Journal |
| issn | 2634-1581 |
| language | English |
| last_indexed | 2024-04-10T09:01:50Z |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Conversion and Economics |
| spelling | doaj.art-10c9eed236b54a06b57b58274a8c2eec2023-02-21T10:40:58ZengWileyEnergy Conversion and Economics2634-15812022-02-0131384910.1049/enc2.12048Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysisRohit Babu0Saurav Raj1Bishwajit Dey2Biplab Bhattacharyya3Department of Electrical and Electronics Engineering Lendi Institute of Engineering and Technology Jonnada Andhra Pradesh IndiaDepartment of Electrical Engineering Institute of Chemical Technology Marathwada Campus Jalna IndiaDepartment of Electrical and Electronics Engineering Gandhi Institute of Engineering and Technology (GIET) University Gunupur Odisha IndiaDepartment of Electrical Engineering Indian Institute of Technology (Indian School of Mines) Dhanbad IndiaAbstract Power system instability primarily results from the deviation of the frequency from its predefined rated value. This deviation causes voltage collapse, which further leads to sudden blackouts of the power system network. It is often triggered by a lack of reactive capacity. The solution to the reactive capacity problem can be obtained in two stages. In the first stage, the vulnerable buses, also known as ‘weak buses’, where voltage failure might occur are identified, and the Var compensating devices are mounted at those locations. The proposed approach utilizes three simple vulnerable bus detection methods: the fast voltage stability index, line stability index, and voltage collapse proximity index (VCPI). In the second stage, various optimization algorithms are implemented to determine the optimal setting of Var sources, such as particle swarm optimization, differential evolution, the whale optimization algorithm, the grasshopper optimization algorithm, the salp swarm algorithm, grey wolf optimization, and oppositional grey wolf optimization (OGWO). The results indicate that the best approach to poor bus recognition is the VCPI, and the OGWO technique provides a much less expensive system than other optimization strategies used for problems of optimal reactive power planning.https://doi.org/10.1049/enc2.12048Optimisation techniquesPower system controlPower system planning and layout |
| spellingShingle | Rohit Babu Saurav Raj Bishwajit Dey Biplab Bhattacharyya Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis Energy Conversion and Economics Optimisation techniques Power system control Power system planning and layout |
| title | Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis |
| title_full | Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis |
| title_fullStr | Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis |
| title_full_unstemmed | Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis |
| title_short | Optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis |
| title_sort | optimal reactive power planning using oppositional grey wolf optimization by considering bus vulnerability analysis |
| topic | Optimisation techniques Power system control Power system planning and layout |
| url | https://doi.org/10.1049/enc2.12048 |
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