Predicting the stability of smart grid for improving the sustainability using distributed generation technology
Distributed Generation balances the supply in the grid effectively. Numerous distributed power generation technologies need more efficiency, cost, and power output to meet the energy requirements. Hence, this paper has aimed to provide an efficient DG system by integrating a PV module with a smart g...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | e-Prime: Advances in Electrical Engineering, Electronics and Energy |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772671123000803 |
| _version_ | 1797674880910491648 |
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| author | Medan Kumar Gauli Khamphe Phoungthong Kuaanan Techato Saroj Gyawali |
| author_facet | Medan Kumar Gauli Khamphe Phoungthong Kuaanan Techato Saroj Gyawali |
| author_sort | Medan Kumar Gauli |
| collection | DOAJ |
| description | Distributed Generation balances the supply in the grid effectively. Numerous distributed power generation technologies need more efficiency, cost, and power output to meet the energy requirements. Hence, this paper has aimed to provide an efficient DG system by integrating a PV module with a smart grid through a 3-phase AC-DC converter. Numerous PV modules are combined through DC linking, and different inverter control strategies are used to control the network. The ANN algorithm is used to optimize the demand and supply in the network. PV modules are included in the network to boost up the renewable energy source for the network. The power generated from the PV module is converted to DC through 3 phase AC-DC converter. A DC-link modeling is carried out between various converters and PV modules. It helps balance the variation in the DC input from the PV modules converted by AC-DC converters. The input current is again sent into a closed-loop inverter system to control the input current appropriately based on the demand. The problems between demand and supply are sorted through an ANN algorithm that optimizes the whole model based on supply and demand. The whole is simulated, and the results obtained are discussed in detail. The results are compared with similar Distributed power generation technologies to compare their efficiency. The comparison clearly shows that the proposed model provides better environmental sustainability and expandability to the system. |
| first_indexed | 2024-03-11T22:06:36Z |
| format | Article |
| id | doaj.art-157aeedc26a2470583764bd2eae36950 |
| institution | Directory Open Access Journal |
| issn | 2772-6711 |
| language | English |
| last_indexed | 2024-03-11T22:06:36Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | e-Prime: Advances in Electrical Engineering, Electronics and Energy |
| spelling | doaj.art-157aeedc26a2470583764bd2eae369502023-09-25T04:12:37ZengElseviere-Prime: Advances in Electrical Engineering, Electronics and Energy2772-67112023-09-015100185Predicting the stability of smart grid for improving the sustainability using distributed generation technologyMedan Kumar Gauli0Khamphe Phoungthong1Kuaanan Techato2Saroj Gyawali3Corresponding author.; Faculty of Environmental Management, Prince of Songkla University (Hat Yai campus), Hat Yai, Songkhla 90110, ThailandFaculty of Environmental Management, Prince of Songkla University (Hat Yai campus), Hat Yai, Songkhla 90110, ThailandFaculty of Environmental Management, Prince of Songkla University (Hat Yai campus), Hat Yai, Songkhla 90110, ThailandFaculty of Environmental Management, Prince of Songkla University (Hat Yai campus), Hat Yai, Songkhla 90110, ThailandDistributed Generation balances the supply in the grid effectively. Numerous distributed power generation technologies need more efficiency, cost, and power output to meet the energy requirements. Hence, this paper has aimed to provide an efficient DG system by integrating a PV module with a smart grid through a 3-phase AC-DC converter. Numerous PV modules are combined through DC linking, and different inverter control strategies are used to control the network. The ANN algorithm is used to optimize the demand and supply in the network. PV modules are included in the network to boost up the renewable energy source for the network. The power generated from the PV module is converted to DC through 3 phase AC-DC converter. A DC-link modeling is carried out between various converters and PV modules. It helps balance the variation in the DC input from the PV modules converted by AC-DC converters. The input current is again sent into a closed-loop inverter system to control the input current appropriately based on the demand. The problems between demand and supply are sorted through an ANN algorithm that optimizes the whole model based on supply and demand. The whole is simulated, and the results obtained are discussed in detail. The results are compared with similar Distributed power generation technologies to compare their efficiency. The comparison clearly shows that the proposed model provides better environmental sustainability and expandability to the system.http://www.sciencedirect.com/science/article/pii/S2772671123000803Distributed generationSmart gridRenewable energy sourcesDeep LearningSupply-Demand |
| spellingShingle | Medan Kumar Gauli Khamphe Phoungthong Kuaanan Techato Saroj Gyawali Predicting the stability of smart grid for improving the sustainability using distributed generation technology e-Prime: Advances in Electrical Engineering, Electronics and Energy Distributed generation Smart grid Renewable energy sources Deep Learning Supply-Demand |
| title | Predicting the stability of smart grid for improving the sustainability using distributed generation technology |
| title_full | Predicting the stability of smart grid for improving the sustainability using distributed generation technology |
| title_fullStr | Predicting the stability of smart grid for improving the sustainability using distributed generation technology |
| title_full_unstemmed | Predicting the stability of smart grid for improving the sustainability using distributed generation technology |
| title_short | Predicting the stability of smart grid for improving the sustainability using distributed generation technology |
| title_sort | predicting the stability of smart grid for improving the sustainability using distributed generation technology |
| topic | Distributed generation Smart grid Renewable energy sources Deep Learning Supply-Demand |
| url | http://www.sciencedirect.com/science/article/pii/S2772671123000803 |
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