Strategic and Fair Aggregator Interactions in Energy Markets: Mutli-agent Dynamics and Quasiconcave Games
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916439790714880 |
|---|---|
| author | Li, Jiayi Motoki, Matt Zhang, Baosen |
| author_facet | Li, Jiayi Motoki, Matt Zhang, Baosen |
| contents | The introduction of aggregator structures has proven effective in bringing fairness to energy resource allocation by negotiating for more resources and economic surplus on behalf of users. This paper extends the fair energy resource allocation problem to a multi-agent setting, focusing on interactions among multiple aggregators in an electricity market.
We prove that the strategic optimization problems faced by the aggregators form a quasiconcave game, ensuring the existence of a Nash equilibrium. This resolves complexities related to market price dependencies on total purchases and balancing fairness and efficiency in energy allocation. In addition, we design simulations to characterize the equilibrium points of the induced game, demonstrating how aggregators stabilize market outcomes, ensure fair resource distribution, and optimize user surplus. Our findings offer a robust framework for understanding strategic interactions among aggregators, contributing to more efficient and equitable energy markets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11296 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Strategic and Fair Aggregator Interactions in Energy Markets: Mutli-agent Dynamics and Quasiconcave Games Li, Jiayi Motoki, Matt Zhang, Baosen Computer Science and Game Theory Systems and Control The introduction of aggregator structures has proven effective in bringing fairness to energy resource allocation by negotiating for more resources and economic surplus on behalf of users. This paper extends the fair energy resource allocation problem to a multi-agent setting, focusing on interactions among multiple aggregators in an electricity market. We prove that the strategic optimization problems faced by the aggregators form a quasiconcave game, ensuring the existence of a Nash equilibrium. This resolves complexities related to market price dependencies on total purchases and balancing fairness and efficiency in energy allocation. In addition, we design simulations to characterize the equilibrium points of the induced game, demonstrating how aggregators stabilize market outcomes, ensure fair resource distribution, and optimize user surplus. Our findings offer a robust framework for understanding strategic interactions among aggregators, contributing to more efficient and equitable energy markets. |
| title | Strategic and Fair Aggregator Interactions in Energy Markets: Mutli-agent Dynamics and Quasiconcave Games |
| topic | Computer Science and Game Theory Systems and Control |
| url | https://arxiv.org/abs/2410.11296 |