A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants
As energy and carbon markets evolve, it has emerged as a prevalent trend for multiple virtual power plants (VPPs) to engage in market trading through coordinated operation. Given that these VPPs belong to diverse stakeholders, a competitive dynamic is shaping up. To strike a balance between the inte...
| Auteurs principaux: | , |
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| Format: | Article |
| Langue: | English |
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MDPI AG
2025-02-01
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| Collection: | Inventions |
| Sujets: | |
| Accès en ligne: | https://www.mdpi.com/2411-5134/10/1/16 |
| _version_ | 1826582334534582272 |
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| author | Dayong Xu Mengjie Li |
| author_facet | Dayong Xu Mengjie Li |
| author_sort | Dayong Xu |
| collection | DOAJ |
| description | As energy and carbon markets evolve, it has emerged as a prevalent trend for multiple virtual power plants (VPPs) to engage in market trading through coordinated operation. Given that these VPPs belong to diverse stakeholders, a competitive dynamic is shaping up. To strike a balance between the interests of the distribution system operator (DSO) and VPPs, this paper introduces a bi-level energy–carbon coordination model based on the Stackelberg game framework, which consists of an upper-level optimal pricing model for the DSO and a lower-level optimal energy scheduling model for each VPP. Subsequently, the Karush-Kuhn-Tucker (KKT) conditions and the duality theorem of linear programming are applied to transform the bi-level Stackelberg game model into a mixed-integer linear program, allowing for the computation of the model’s global optimal solution using commercial solvers. Finally, a case study is conducted to demonstrate the effectiveness of the proposed model. The simulation results show that the proposed game model effectively optimizes energy and carbon pricing, encourages the active participation of VPPs in electricity and carbon allowance sharing, increases the profitability of DSOs, and reduces the operational costs of VPPs. |
| first_indexed | 2025-03-14T15:04:19Z |
| format | Article |
| id | doaj.art-dbdb1e47a98c4b6c9f006bfd9dc6fe6e |
| institution | Directory Open Access Journal |
| issn | 2411-5134 |
| language | English |
| last_indexed | 2025-03-14T15:04:19Z |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Inventions |
| spelling | doaj.art-dbdb1e47a98c4b6c9f006bfd9dc6fe6e2025-02-25T13:32:33ZengMDPI AGInventions2411-51342025-02-011011610.3390/inventions10010016A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power PlantsDayong Xu0Mengjie Li1Huizhou Electric Power Supply Bureau of Guangdong Power Grid Corporation, Huizhou 516003, ChinaHuizhou Electric Power Supply Bureau of Guangdong Power Grid Corporation, Huizhou 516003, ChinaAs energy and carbon markets evolve, it has emerged as a prevalent trend for multiple virtual power plants (VPPs) to engage in market trading through coordinated operation. Given that these VPPs belong to diverse stakeholders, a competitive dynamic is shaping up. To strike a balance between the interests of the distribution system operator (DSO) and VPPs, this paper introduces a bi-level energy–carbon coordination model based on the Stackelberg game framework, which consists of an upper-level optimal pricing model for the DSO and a lower-level optimal energy scheduling model for each VPP. Subsequently, the Karush-Kuhn-Tucker (KKT) conditions and the duality theorem of linear programming are applied to transform the bi-level Stackelberg game model into a mixed-integer linear program, allowing for the computation of the model’s global optimal solution using commercial solvers. Finally, a case study is conducted to demonstrate the effectiveness of the proposed model. The simulation results show that the proposed game model effectively optimizes energy and carbon pricing, encourages the active participation of VPPs in electricity and carbon allowance sharing, increases the profitability of DSOs, and reduces the operational costs of VPPs.https://www.mdpi.com/2411-5134/10/1/16virtual power plantsStackelberg gamepricingenergy-carbon coordinationKarush-Kuhn-Tucker conditions |
| spellingShingle | Dayong Xu Mengjie Li A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants Inventions virtual power plants Stackelberg game pricing energy-carbon coordination Karush-Kuhn-Tucker conditions |
| title | A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants |
| title_full | A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants |
| title_fullStr | A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants |
| title_full_unstemmed | A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants |
| title_short | A Stackelberg Game Model for the Energy–Carbon Co-Optimization of Multiple Virtual Power Plants |
| title_sort | stackelberg game model for the energy carbon co optimization of multiple virtual power plants |
| topic | virtual power plants Stackelberg game pricing energy-carbon coordination Karush-Kuhn-Tucker conditions |
| url | https://www.mdpi.com/2411-5134/10/1/16 |
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