A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system
With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for s...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235248472202128X |
| _version_ | 1811159683087466496 |
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| author | Noor Najwa Husnaini Mohammad Husni Siti Rafidah Abdul Rahim Mohd Rafi Adzman Muhamad Hatta Hussain Ismail Musirin Syahrul Ashikin Azmi |
| author_facet | Noor Najwa Husnaini Mohammad Husni Siti Rafidah Abdul Rahim Mohd Rafi Adzman Muhamad Hatta Hussain Ismail Musirin Syahrul Ashikin Azmi |
| author_sort | Noor Najwa Husnaini Mohammad Husni |
| collection | DOAJ |
| description | With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique. |
| first_indexed | 2024-04-10T05:45:18Z |
| format | Article |
| id | doaj.art-64f0d6db8aef4ad2868ac2c847bb74d2 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-04-10T05:45:18Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-64f0d6db8aef4ad2868ac2c847bb74d22023-03-06T04:13:04ZengElsevierEnergy Reports2352-48472022-12-018169174A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution systemNoor Najwa Husnaini Mohammad Husni0Siti Rafidah Abdul Rahim1Mohd Rafi Adzman2Muhamad Hatta Hussain3Ismail Musirin4Syahrul Ashikin Azmi5Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, MalaysiaFaculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, Malaysia; Centre of Excellence for Renewable Energy (CERE), Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, Malaysia; Corresponding author at: Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, Malaysia.Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, MalaysiaFaculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, MalaysiaSchool of Electrical Engineering, College of Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor, MalaysiaFaculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP), Arau, 02600, Perlis, MalaysiaWith the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique.http://www.sciencedirect.com/science/article/pii/S235248472202128XDistributed GenerationMulti-objective optimizationLoss minimizationEvolutionary Programming |
| spellingShingle | Noor Najwa Husnaini Mohammad Husni Siti Rafidah Abdul Rahim Mohd Rafi Adzman Muhamad Hatta Hussain Ismail Musirin Syahrul Ashikin Azmi A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system Energy Reports Distributed Generation Multi-objective optimization Loss minimization Evolutionary Programming |
| title | A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system |
| title_full | A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system |
| title_fullStr | A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system |
| title_full_unstemmed | A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system |
| title_short | A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system |
| title_sort | hybrid multi objective evolutionary programming firefly algorithm for different type of distributed generation in distribution system |
| topic | Distributed Generation Multi-objective optimization Loss minimization Evolutionary Programming |
| url | http://www.sciencedirect.com/science/article/pii/S235248472202128X |
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