Federated learning application in distributed energy trading in integrated energy system
Privacy protection in electricity market transactions is a long-term topic, and it must be considered in the application of any new power system project today. This paper explores a new welfare optimization method considering privacy protection in the field of energy trading based on federated learn...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-11-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723010594 |
| _version_ | 1797378697043378176 |
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| author | Haoyuan Cheng Qian Ai |
| author_facet | Haoyuan Cheng Qian Ai |
| author_sort | Haoyuan Cheng |
| collection | DOAJ |
| description | Privacy protection in electricity market transactions is a long-term topic, and it must be considered in the application of any new power system project today. This paper explores a new welfare optimization method considering privacy protection in the field of energy trading based on federated learning (FL). First, this paper models an integrated energy system (IES) with one distributed network manager (DNM) and multiple load aggregators (LAs). This model adopts the idea of Stackelberg game, makes DNM dominate the trading game, and makes LAs as followers. Then, it uses the FL-Stackelberg method proposed for the first time to solve the established individual welfare optimization model participating in the game and compares the results with those of the traditional hierarchical optimization method and the Mathematical Program with Equilibrium Constraint optimization method. Numerical results at the end of the paper prove the good accuracy and calculation speed of the proposed FL-Stackelberg optimization algorithm, and demonstrate the reliability of FL in engineering practice of IES. |
| first_indexed | 2024-03-08T20:11:25Z |
| format | Article |
| id | doaj.art-b1dc0a0e2d9b444e93971656b3a014b9 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-08T20:11:25Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-b1dc0a0e2d9b444e93971656b3a014b92023-12-23T05:21:05ZengElsevierEnergy Reports2352-48472023-11-0110484493Federated learning application in distributed energy trading in integrated energy systemHaoyuan Cheng0Qian Ai1School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaCorresponding author.; School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaPrivacy protection in electricity market transactions is a long-term topic, and it must be considered in the application of any new power system project today. This paper explores a new welfare optimization method considering privacy protection in the field of energy trading based on federated learning (FL). First, this paper models an integrated energy system (IES) with one distributed network manager (DNM) and multiple load aggregators (LAs). This model adopts the idea of Stackelberg game, makes DNM dominate the trading game, and makes LAs as followers. Then, it uses the FL-Stackelberg method proposed for the first time to solve the established individual welfare optimization model participating in the game and compares the results with those of the traditional hierarchical optimization method and the Mathematical Program with Equilibrium Constraint optimization method. Numerical results at the end of the paper prove the good accuracy and calculation speed of the proposed FL-Stackelberg optimization algorithm, and demonstrate the reliability of FL in engineering practice of IES.http://www.sciencedirect.com/science/article/pii/S2352484723010594Federated learning (FL)FL-Stackelberg gameIntegrated energy system (IES)Privacy protection |
| spellingShingle | Haoyuan Cheng Qian Ai Federated learning application in distributed energy trading in integrated energy system Energy Reports Federated learning (FL) FL-Stackelberg game Integrated energy system (IES) Privacy protection |
| title | Federated learning application in distributed energy trading in integrated energy system |
| title_full | Federated learning application in distributed energy trading in integrated energy system |
| title_fullStr | Federated learning application in distributed energy trading in integrated energy system |
| title_full_unstemmed | Federated learning application in distributed energy trading in integrated energy system |
| title_short | Federated learning application in distributed energy trading in integrated energy system |
| title_sort | federated learning application in distributed energy trading in integrated energy system |
| topic | Federated learning (FL) FL-Stackelberg game Integrated energy system (IES) Privacy protection |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723010594 |
| work_keys_str_mv | AT haoyuancheng federatedlearningapplicationindistributedenergytradinginintegratedenergysystem AT qianai federatedlearningapplicationindistributedenergytradinginintegratedenergysystem |