Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization
This paper presents an optimal Distribution Network Reconfiguration (DNR) framework and solution procedure that employ a novel modified Gray Wolf Optimization (mGWO) algorithm to maximize the power loss reduction in a Distribution System (DS). Distributed Generation (DG) is integrated optimally in t...
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| Format: | Article |
| Language: | English |
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Taiwan Association of Engineering and Technology Innovation
2019-09-01
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| Series: | International Journal of Engineering and Technology Innovation |
| Subjects: | |
| Online Access: | http://ojs.imeti.org/index.php/IJETI/article/view/2448 |
| _version_ | 1811202428106702848 |
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| author | Deepa Nataraj Rajaji Loganathan Moorthy Veerasamy Venkata Durga Ramarao Reddy |
| author_facet | Deepa Nataraj Rajaji Loganathan Moorthy Veerasamy Venkata Durga Ramarao Reddy |
| author_sort | Deepa Nataraj |
| collection | DOAJ |
| description | This paper presents an optimal Distribution Network Reconfiguration (DNR) framework and solution procedure that employ a novel modified Gray Wolf Optimization (mGWO) algorithm to maximize the power loss reduction in a Distribution System (DS). Distributed Generation (DG) is integrated optimally in the DS to maximize the power loss reduction. DNR is an optimization problem that involves a nonlinear and multimodal function optimized under practical constraints. The mGWO algorithm is employed for ascertaining the optimal switching position when reconfiguring the DS to facilitate the maximum power loss reduction. The position of the gray wolf is updated exponentially from a high value to zero in the search vicinity, providing the perfect balance between intensification and diversification to ascertain the fittest function and exhibiting rapid and steady convergence. The proposed method appears to be a promising optimization tool for electrical utility companies, thereby modifying their operating DS strategy under steady-state conditions. It provides a solution for integrating more DG optimally in the existing distribution network. In this study, IEEE 33-bus and 69-bus DSs are analyzed for maximizing the power loss reduction through reconfiguration, and the integration of DG is exercised in the 33-bus test system alone. The simulation results are examined and compared with those of several recent methods. The numerical results reveal that mGWO outperforms other contestant algorithms. |
| first_indexed | 2024-04-12T02:39:32Z |
| format | Article |
| id | doaj.art-377927c36b3c4453b3328e9a903b20b7 |
| institution | Directory Open Access Journal |
| issn | 2223-5329 2226-809X |
| language | English |
| last_indexed | 2024-04-12T02:39:32Z |
| publishDate | 2019-09-01 |
| publisher | Taiwan Association of Engineering and Technology Innovation |
| record_format | Article |
| series | International Journal of Engineering and Technology Innovation |
| spelling | doaj.art-377927c36b3c4453b3328e9a903b20b72022-12-22T03:51:22ZengTaiwan Association of Engineering and Technology InnovationInternational Journal of Engineering and Technology Innovation2223-53292226-809X2019-09-01943273432448Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf OptimizationDeepa Nataraj0Rajaji Loganathan1Moorthy Veerasamy2Venkata Durga Ramarao Reddy3St. Peter’s Institute of Higher Education and Research, Deemed to be University, Chennai, IndiaARM College of Engineering and Technology, Chennai, IndiaSwarnandhra College of Engineering and Technology, Narsapur Bhimavaram, IndiaVishni Institute of Technology, Bhimavaram, IndiaThis paper presents an optimal Distribution Network Reconfiguration (DNR) framework and solution procedure that employ a novel modified Gray Wolf Optimization (mGWO) algorithm to maximize the power loss reduction in a Distribution System (DS). Distributed Generation (DG) is integrated optimally in the DS to maximize the power loss reduction. DNR is an optimization problem that involves a nonlinear and multimodal function optimized under practical constraints. The mGWO algorithm is employed for ascertaining the optimal switching position when reconfiguring the DS to facilitate the maximum power loss reduction. The position of the gray wolf is updated exponentially from a high value to zero in the search vicinity, providing the perfect balance between intensification and diversification to ascertain the fittest function and exhibiting rapid and steady convergence. The proposed method appears to be a promising optimization tool for electrical utility companies, thereby modifying their operating DS strategy under steady-state conditions. It provides a solution for integrating more DG optimally in the existing distribution network. In this study, IEEE 33-bus and 69-bus DSs are analyzed for maximizing the power loss reduction through reconfiguration, and the integration of DG is exercised in the 33-bus test system alone. The simulation results are examined and compared with those of several recent methods. The numerical results reveal that mGWO outperforms other contestant algorithms.http://ojs.imeti.org/index.php/IJETI/article/view/2448radial distribution systemnetwork reconfigurationpower loss reductionmodified gray wolf optimizationdistributed generation |
| spellingShingle | Deepa Nataraj Rajaji Loganathan Moorthy Veerasamy Venkata Durga Ramarao Reddy Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization International Journal of Engineering and Technology Innovation radial distribution system network reconfiguration power loss reduction modified gray wolf optimization distributed generation |
| title | Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization |
| title_full | Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization |
| title_fullStr | Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization |
| title_full_unstemmed | Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization |
| title_short | Maximizing Power Loss Reduction in Radial Distribution Systems by Using Modified Gray Wolf Optimization |
| title_sort | maximizing power loss reduction in radial distribution systems by using modified gray wolf optimization |
| topic | radial distribution system network reconfiguration power loss reduction modified gray wolf optimization distributed generation |
| url | http://ojs.imeti.org/index.php/IJETI/article/view/2448 |
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