A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks
Distribution networks are facing new challenges with the emergence of smart grids, such as capacity limitations, voltage instability, and many others. These challenges can potentially lead to brownouts and blackouts. This paper presents an innovative technique for optimal siting and sizing of distri...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9723069/ |
| _version_ | 1828816321098285056 |
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| author | Muhammad Imran Akbar Syed Ali Abbas Kazmi Omar Alrumayh Zafar A. Khan Abdullah Altamimi M. Mahad Malik |
| author_facet | Muhammad Imran Akbar Syed Ali Abbas Kazmi Omar Alrumayh Zafar A. Khan Abdullah Altamimi M. Mahad Malik |
| author_sort | Muhammad Imran Akbar |
| collection | DOAJ |
| description | Distribution networks are facing new challenges with the emergence of smart grids, such as capacity limitations, voltage instability, and many others. These challenges can potentially lead to brownouts and blackouts. This paper presents an innovative technique for optimal siting and sizing of distributed generators (DGs) in radial distribution networks (RDNs). The proposed technique uses a novel algorithm that combines improved grey wolf optimization with particle swarm optimization (I-GWOPSO) by incorporating dimension learning-based hunting (DLH). The proposed I-GWOPSO employs a novel aspect of DLH to reduce the gap between local and global searches to maintain a balance. The main optimization objectives aim to optimally site and size the DG with minimization of active power loss, voltage deviation, and improvement of voltage stability in RDNs. Case studies are simulated with IEEE 33-bus and IEEE 69-bus test systems, for the optimal allocation of DG units by considering various power factors. The results validate the efficacy of the proposed algorithm with a significant reduction in real power loss (up to 98.1%), improvement in voltage profile, and optimal reduced cost of DG operation with optimal sizing across all considered cases. A comparative analysis of the proposed approach with existing literature validates the improved performance of the proposed algorithm. |
| first_indexed | 2024-12-12T11:00:49Z |
| format | Article |
| id | doaj.art-971618e34b4a4253b41830ea6fd115b4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-12T11:00:49Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-971618e34b4a4253b41830ea6fd115b42022-12-22T00:26:32ZengIEEEIEEE Access2169-35362022-01-0110256692568710.1109/ACCESS.2022.31554849723069A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution NetworksMuhammad Imran Akbar0https://orcid.org/0000-0003-0030-4883Syed Ali Abbas Kazmi1Omar Alrumayh2https://orcid.org/0000-0002-3412-2853Zafar A. Khan3https://orcid.org/0000-0003-3149-6865Abdullah Altamimi4https://orcid.org/0000-0002-0236-7872M. Mahad Malik5U.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12 Campus, Islamabad, PakistanU.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12 Campus, Islamabad, PakistanDepartment of Electrical Engineering, College of Engineering, Qassim University, Unaizah, Saudi ArabiaDepartment of Electrical Engineering, Mirpur University of Science and Technology, Mirpur, Azad Jammu and Kashmir, PakistanDepartment of Electrical Engineering, College of Engineering, Majmaah University, Al-Majma’ah, Saudi ArabiaU.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12 Campus, Islamabad, PakistanDistribution networks are facing new challenges with the emergence of smart grids, such as capacity limitations, voltage instability, and many others. These challenges can potentially lead to brownouts and blackouts. This paper presents an innovative technique for optimal siting and sizing of distributed generators (DGs) in radial distribution networks (RDNs). The proposed technique uses a novel algorithm that combines improved grey wolf optimization with particle swarm optimization (I-GWOPSO) by incorporating dimension learning-based hunting (DLH). The proposed I-GWOPSO employs a novel aspect of DLH to reduce the gap between local and global searches to maintain a balance. The main optimization objectives aim to optimally site and size the DG with minimization of active power loss, voltage deviation, and improvement of voltage stability in RDNs. Case studies are simulated with IEEE 33-bus and IEEE 69-bus test systems, for the optimal allocation of DG units by considering various power factors. The results validate the efficacy of the proposed algorithm with a significant reduction in real power loss (up to 98.1%), improvement in voltage profile, and optimal reduced cost of DG operation with optimal sizing across all considered cases. A comparative analysis of the proposed approach with existing literature validates the improved performance of the proposed algorithm.https://ieeexplore.ieee.org/document/9723069/Distributed generationdimension learning-based huntinggrey wolf optimizationparticle swarm optimizationradial distribution networkvoltage deviation |
| spellingShingle | Muhammad Imran Akbar Syed Ali Abbas Kazmi Omar Alrumayh Zafar A. Khan Abdullah Altamimi M. Mahad Malik A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks IEEE Access Distributed generation dimension learning-based hunting grey wolf optimization particle swarm optimization radial distribution network voltage deviation |
| title | A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks |
| title_full | A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks |
| title_fullStr | A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks |
| title_full_unstemmed | A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks |
| title_short | A Novel Hybrid Optimization-Based Algorithm for the Single and Multi-Objective Achievement With Optimal DG Allocations in Distribution Networks |
| title_sort | novel hybrid optimization based algorithm for the single and multi objective achievement with optimal dg allocations in distribution networks |
| topic | Distributed generation dimension learning-based hunting grey wolf optimization particle swarm optimization radial distribution network voltage deviation |
| url | https://ieeexplore.ieee.org/document/9723069/ |
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