Cost-benefit analysis in demand response with penalty and grid management using blockchain
In a power system network, balancing energy demand is a difficult issue. In this case, a microgrid is a grid-connected system that combines wind and solar power. Demand response and renewables have a significant impact on how well electricity distribution networks operate. Here, three scenarios are...
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2025-01-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0224118 |
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| author | Manikandan Ramasamy Thenmalar Kaliannan Saravanakumar Ramasamy |
| author_facet | Manikandan Ramasamy Thenmalar Kaliannan Saravanakumar Ramasamy |
| author_sort | Manikandan Ramasamy |
| collection | DOAJ |
| description | In a power system network, balancing energy demand is a difficult issue. In this case, a microgrid is a grid-connected system that combines wind and solar power. Demand response and renewables have a significant impact on how well electricity distribution networks operate. Here, three scenarios are examined: microgrid energy management, consumer penalty, and grid management with blockchain (BC) technology advancements. Renewable energy sources, such as solar and wind units, with a curtailed incentive-based demand response scheme, are discussed in this paper along with economic dispatch. This study aims to optimize utility benefits while minimizing transaction and conventional power costs. Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. Three units with three customer test systems are proposed to implement this work. Customers are given penalties when they fail to use renewable energy. BC technology is offered as a way to safeguard energy transactions between the grid and microgrid. Ultimately, outcomes are acquired and compared using optimization methods for test system results. A 24-h scheduling interval is used to produce optimization results. |
| format | Article |
| id | doaj-art-2cbec8ee55e74d21976d35d92a5b138f |
| institution | Kabale University |
| issn | 2158-3226 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj-art-2cbec8ee55e74d21976d35d92a5b138f2025-02-03T16:40:43ZengAIP Publishing LLCAIP Advances2158-32262025-01-01151015333015333-1110.1063/5.0224118Cost-benefit analysis in demand response with penalty and grid management using blockchainManikandan Ramasamy0Thenmalar Kaliannan1Saravanakumar Ramasamy2Department of Electrical and Electronics Engineering, Vivekanandha College of Engineering for Women, Tiruchengode (Autonomous), Tamilnadu, IndiaDepartment of Electrical and Electronics Engineering, Vivekanandha College of Engineering for Women, Tiruchengode (Autonomous), Tamilnadu, IndiaMadanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, IndiaIn a power system network, balancing energy demand is a difficult issue. In this case, a microgrid is a grid-connected system that combines wind and solar power. Demand response and renewables have a significant impact on how well electricity distribution networks operate. Here, three scenarios are examined: microgrid energy management, consumer penalty, and grid management with blockchain (BC) technology advancements. Renewable energy sources, such as solar and wind units, with a curtailed incentive-based demand response scheme, are discussed in this paper along with economic dispatch. This study aims to optimize utility benefits while minimizing transaction and conventional power costs. Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. Three units with three customer test systems are proposed to implement this work. Customers are given penalties when they fail to use renewable energy. BC technology is offered as a way to safeguard energy transactions between the grid and microgrid. Ultimately, outcomes are acquired and compared using optimization methods for test system results. A 24-h scheduling interval is used to produce optimization results.http://dx.doi.org/10.1063/5.0224118 |
| spellingShingle | Manikandan Ramasamy Thenmalar Kaliannan Saravanakumar Ramasamy Cost-benefit analysis in demand response with penalty and grid management using blockchain AIP Advances |
| title | Cost-benefit analysis in demand response with penalty and grid management using blockchain |
| title_full | Cost-benefit analysis in demand response with penalty and grid management using blockchain |
| title_fullStr | Cost-benefit analysis in demand response with penalty and grid management using blockchain |
| title_full_unstemmed | Cost-benefit analysis in demand response with penalty and grid management using blockchain |
| title_short | Cost-benefit analysis in demand response with penalty and grid management using blockchain |
| title_sort | cost benefit analysis in demand response with penalty and grid management using blockchain |
| url | http://dx.doi.org/10.1063/5.0224118 |
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