Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory
Due to global warming and climate change, it is essential to produce power using renewable sources, such as solar, wind, fuel cells, etc. The traditional grid shifts towards the smart grid by infusing digital communication techniques and information technology. As the current power system is shiftin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/11/4278 |
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| author | Nongmaithem Nandini Devi Surmila Thokchom Thoudam Doren Singh Gayadhar Panda Ramasamy Thaiyal Naayagi |
| author_facet | Nongmaithem Nandini Devi Surmila Thokchom Thoudam Doren Singh Gayadhar Panda Ramasamy Thaiyal Naayagi |
| author_sort | Nongmaithem Nandini Devi |
| collection | DOAJ |
| description | Due to global warming and climate change, it is essential to produce power using renewable sources, such as solar, wind, fuel cells, etc. The traditional grid shifts towards the smart grid by infusing digital communication techniques and information technology. As the current power system is shifting towards a smart grid, the utility and prosumers participate in the energy trading process. Due to the distributed nature of the smart grid, providing a fair price among them is becoming a difficult task. The article introduces a model for energy trading in a smart grid by allowing participants to negotiate in multiple stages using a game-theory-based multi-stage Nash Bargaining Solution (NBS). The model’s application of game theory enables the participants to decide on a mutually acceptable price, thereby encouraging the utility, private parties and prosumers (those who are able to generate and consume energy) to participate in the trading process. Since all parties participate in the trading procedure, greenhouse gas emissions are reduced. The proposed model also balances the benefits of consumers and producers in the final agreed fixed price. To demonstrate the efficacy of the proposed work, we compare the analytical results with feed-in-tariff (FiT) techniques in terms of consumers’ energy bills and producers’ revenue. For experimental analysis, 20 participants are considered, where the percentage reduction in the bill of each consumer and the percentage increment of revenue of each producer are compared to FiT. On average, the overall bill of the consumer is reduced by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>32.8</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and the producers’ revenue is increased by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>64.83</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to FiT. It has been shown further that the proposed model shows better performance as compared to FiT with an increase in the number of participants. The analysis of carbon emission reduction in the proposed model has been analyzed, where, for 10 participants, the carbon emission reduction is approximately 28.48 kg/kWh, and for 100 participants is 342.397 kg/kWh. |
| first_indexed | 2024-03-11T03:08:37Z |
| format | Article |
| id | doaj.art-6ce4014ed056460289d9a81e69177970 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T03:08:37Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-6ce4014ed056460289d9a81e691779702023-11-18T07:46:42ZengMDPI AGEnergies1996-10732023-05-011611427810.3390/en16114278Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game TheoryNongmaithem Nandini Devi0Surmila Thokchom1Thoudam Doren Singh2Gayadhar Panda3Ramasamy Thaiyal Naayagi4Department of Computer Science and Engineering, National Institute of Technology Meghalaya, Shillong 793003, IndiaDepartment of Computer Science and Engineering, National Institute of Technology Meghalaya, Shillong 793003, IndiaDepartment of Computer Science and Engineering, National Institute of Technology Silchar, Silchar 788010, IndiaDepartment of Electrical Engineering, National Institute of Technology Meghalaya, Shillong 793003, IndiaSchool of Electrical and Electronic Engineering, Newcastle University in Singapore, Singapore 567739, SingaporeDue to global warming and climate change, it is essential to produce power using renewable sources, such as solar, wind, fuel cells, etc. The traditional grid shifts towards the smart grid by infusing digital communication techniques and information technology. As the current power system is shifting towards a smart grid, the utility and prosumers participate in the energy trading process. Due to the distributed nature of the smart grid, providing a fair price among them is becoming a difficult task. The article introduces a model for energy trading in a smart grid by allowing participants to negotiate in multiple stages using a game-theory-based multi-stage Nash Bargaining Solution (NBS). The model’s application of game theory enables the participants to decide on a mutually acceptable price, thereby encouraging the utility, private parties and prosumers (those who are able to generate and consume energy) to participate in the trading process. Since all parties participate in the trading procedure, greenhouse gas emissions are reduced. The proposed model also balances the benefits of consumers and producers in the final agreed fixed price. To demonstrate the efficacy of the proposed work, we compare the analytical results with feed-in-tariff (FiT) techniques in terms of consumers’ energy bills and producers’ revenue. For experimental analysis, 20 participants are considered, where the percentage reduction in the bill of each consumer and the percentage increment of revenue of each producer are compared to FiT. On average, the overall bill of the consumer is reduced by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>32.8</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and the producers’ revenue is increased by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>64.83</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to FiT. It has been shown further that the proposed model shows better performance as compared to FiT with an increase in the number of participants. The analysis of carbon emission reduction in the proposed model has been analyzed, where, for 10 participants, the carbon emission reduction is approximately 28.48 kg/kWh, and for 100 participants is 342.397 kg/kWh.https://www.mdpi.com/1996-1073/16/11/4278smart gridenergy tradingdistributed energy resourcesrenewable energyprosumerscooperative game theory |
| spellingShingle | Nongmaithem Nandini Devi Surmila Thokchom Thoudam Doren Singh Gayadhar Panda Ramasamy Thaiyal Naayagi Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory Energies smart grid energy trading distributed energy resources renewable energy prosumers cooperative game theory |
| title | Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory |
| title_full | Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory |
| title_fullStr | Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory |
| title_full_unstemmed | Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory |
| title_short | Multi-Stage Bargaining of Smart Grid Energy Trading Based on Cooperative Game Theory |
| title_sort | multi stage bargaining of smart grid energy trading based on cooperative game theory |
| topic | smart grid energy trading distributed energy resources renewable energy prosumers cooperative game theory |
| url | https://www.mdpi.com/1996-1073/16/11/4278 |
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