Online Learning-Based Optimal Bidding Approach for FTR Market Participants

Guibin Chen; Ye Guo; Wenjun Tang; Qinglai Guo; Hongbin Sun; Wenqi Huang

doi:10.17775/CSEEJPES.2021.05390

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Online Learning-Based Optimal Bidding Approach for FTR Market Participants

Regular Papers | 更新时间：2025-11-16

- Online Learning-Based Optimal Bidding Approach for FTR Market Participants
- CSEE Journal of Power and Energy Systems Vol. 11, Issue 4, Pages: 1501-1511(2025)
- 作者机构：
  
  1. Tsinghua-Berkeley Shenzhen Institute, Tsinghua University,Guangdong,Shenzhen,China
  2. Department of Electrical Engineering, Tsinghua University,Beijing,China
  3. Digital Grid Research Institute, China Southern Power Grid,Guangzhou,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2021.05390
  CLC：
- Published：2025
- 稿件说明：
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Guibin Chen, Ye Guo, Wenjun Tang, et al. Online Learning-Based Optimal Bidding Approach for FTR Market Participants[J]. CSEE Journal of Power and Energy Systems, 2025, 11(4): 1501-1511.
DOI：

Guibin Chen, Ye Guo, Wenjun Tang, et al. Online Learning-Based Optimal Bidding Approach for FTR Market Participants[J]. CSEE Journal of Power and Energy Systems, 2025, 11(4): 1501-1511. DOI： 10.17775/CSEEJPES.2021.05390.

摘要

Abstract

We consider the problem of optimal bidding and portfolio optimization for bidders in the financial transmission rights (FTR) auction market. Based on the price-taker assumption

each FTR market participant aims to maximize the profit

which is the difference between the clearing price and FTR revenue. However

both clearing price and the FTR revenue are random and unknown. An online learning methodology is proposed to learn optimal bidding by updating its policy with the newest observations of clearing results. With bidding prices derived by the online learning algorithm

a budget-constrained portfolio optimization problem is solved to distribute the budget among profitable FTRs. Compared to other state-of-the-art online learning approaches

the proposed tree-based bid searching (TBS) algorithm converges faster to the optimal bidding price and has favourable linearithmic time complexity.

关键词

Keywords

references

7. PJM. “Financial transmission rights,” Audubon, PA, USA, 2020. [Online]. Available: https://www.pjm.com/-/media/documents/manuals/m06.ashx.

11. S. M. Harvey, W. W. Hogan, and S. L. Pope, “Transmission capacity reservations and transmission congestion contracts,” Harvard University, Cambridge, MA, USA. 1996. [Online]. Available: https://scholar.harvard.edu/whogan/files/tccoptr3.pdf.

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