Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process

Zhouhe Zhang; Haochen Hua; Xingying Chen; Jia Shao; Jin Zheng; Bo Wang; Lei Gan; Kun Yu

doi:10.1109/EEM64765.2025.11050153

Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process

Zhouhe Zhang, Haochen Hua^*, Xingying Chen, Jia Shao, Jin Zheng, Bo Wang, Lei Gan, Kun Yu

^*Corresponding author for this work

School of Engineering Mathematics and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

2 Citations (Scopus)

Abstract

Spot market electricity price fluctuations can expose market participants to substantial financial risks if not accurately forecasted. Traditional statistical models (e.g., ARIMA) can capture linear trends but struggle with complex nonlinear relationships, while pure neural network models (e.g., Transformer) are insufficiently sensitive to random fluctuations. To address both persistent price trends and transient volatility, this paper combines Transformer with stochastic differential equations driven by Ornstein-Uhlenbeck process. Compared to ARIMA, the proposed model achieves an average MAE reduction of approximately 45 %, along with comparable improvements in RMSE and MAPE and a significant boost in R². Against a standalone Transformer, it also exhibits substantial performance gains across all key metrics.

Original language	English
Title of host publication	2025 21st International Conference on the European Energy Market (EEM)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	6
ISBN (Electronic)	979-8-3315-1278-1
ISBN (Print)	979-8-3315-1279-8
DOIs	https://doi.org/10.1109/EEM64765.2025.11050153
Publication status	E-pub ahead of print - 7 Jul 2025
Event	21st International Conference on the European Energy Market - Lisbon, Portugal Duration: 27 May 2025 → 29 May 2025 https://eem25.pt/

Publication series

Name	International Conference on the European Energy Market, EEM
ISSN (Print)	2165-4077
ISSN (Electronic)	2165-4093

Conference

Conference	21st International Conference on the European Energy Market
Country/Territory	Portugal
City	Lisbon
Period	27/05/25 → 29/05/25
Internet address	https://eem25.pt/

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Access to Document

10.1109/EEM64765.2025.11050153

Handle.net

Persistent link

Cite this

Zhang, Z., Hua, H., Chen, X., Shao, J., Zheng, J., Wang, B., Gan, L., & Yu, K. (2025). Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process. In 2025 21st International Conference on the European Energy Market (EEM) (International Conference on the European Energy Market, EEM). Institute of Electrical and Electronics Engineers (IEEE). Advance online publication. https://doi.org/10.1109/EEM64765.2025.11050153

@inproceedings{f901c8ffe95044399fb8d466f78f2c7d,

title = "Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process",

abstract = "Spot market electricity price fluctuations can expose market participants to substantial financial risks if not accurately forecasted. Traditional statistical models (e.g., ARIMA) can capture linear trends but struggle with complex nonlinear relationships, while pure neural network models (e.g., Transformer) are insufficiently sensitive to random fluctuations. To address both persistent price trends and transient volatility, this paper combines Transformer with stochastic differential equations driven by Ornstein-Uhlenbeck process. Compared to ARIMA, the proposed model achieves an average MAE reduction of approximately 45 \%, along with comparable improvements in RMSE and MAPE and a significant boost in R2. Against a standalone Transformer, it also exhibits substantial performance gains across all key metrics.",

author = "Zhouhe Zhang and Haochen Hua and Xingying Chen and Jia Shao and Jin Zheng and Bo Wang and Lei Gan and Kun Yu",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 21st International Conference on the European Energy Market ; Conference date: 27-05-2025 Through 29-05-2025",

year = "2025",

month = jul,

day = "7",

doi = "10.1109/EEM64765.2025.11050153",

language = "English",

isbn = "979-8-3315-1279-8",

series = "International Conference on the European Energy Market, EEM",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

booktitle = "2025 21st International Conference on the European Energy Market (EEM)",

address = "United States",

url = "https://eem25.pt/",

}

Zhang, Z, Hua, H, Chen, X, Shao, J, Zheng, J, Wang, B, Gan, L & Yu, K 2025, Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process. in 2025 21st International Conference on the European Energy Market (EEM). International Conference on the European Energy Market, EEM, Institute of Electrical and Electronics Engineers (IEEE), 21st International Conference on the European Energy Market, Lisbon, Portugal, 27/05/25. https://doi.org/10.1109/EEM64765.2025.11050153

Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process. / Zhang, Zhouhe; Hua, Haochen; Chen, Xingying et al.
2025 21st International Conference on the European Energy Market (EEM). Institute of Electrical and Electronics Engineers (IEEE), 2025. (International Conference on the European Energy Market, EEM).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process

AU - Zhang, Zhouhe

AU - Hua, Haochen

AU - Chen, Xingying

AU - Shao, Jia

AU - Zheng, Jin

AU - Wang, Bo

AU - Gan, Lei

AU - Yu, Kun

PY - 2025/7/7

Y1 - 2025/7/7

N2 - Spot market electricity price fluctuations can expose market participants to substantial financial risks if not accurately forecasted. Traditional statistical models (e.g., ARIMA) can capture linear trends but struggle with complex nonlinear relationships, while pure neural network models (e.g., Transformer) are insufficiently sensitive to random fluctuations. To address both persistent price trends and transient volatility, this paper combines Transformer with stochastic differential equations driven by Ornstein-Uhlenbeck process. Compared to ARIMA, the proposed model achieves an average MAE reduction of approximately 45 %, along with comparable improvements in RMSE and MAPE and a significant boost in R2. Against a standalone Transformer, it also exhibits substantial performance gains across all key metrics.

AB - Spot market electricity price fluctuations can expose market participants to substantial financial risks if not accurately forecasted. Traditional statistical models (e.g., ARIMA) can capture linear trends but struggle with complex nonlinear relationships, while pure neural network models (e.g., Transformer) are insufficiently sensitive to random fluctuations. To address both persistent price trends and transient volatility, this paper combines Transformer with stochastic differential equations driven by Ornstein-Uhlenbeck process. Compared to ARIMA, the proposed model achieves an average MAE reduction of approximately 45 %, along with comparable improvements in RMSE and MAPE and a significant boost in R2. Against a standalone Transformer, it also exhibits substantial performance gains across all key metrics.

UR - https://eem25.pt/

U2 - 10.1109/EEM64765.2025.11050153

DO - 10.1109/EEM64765.2025.11050153

M3 - Conference Contribution (Conference Proceeding)

SN - 979-8-3315-1279-8

T3 - International Conference on the European Energy Market, EEM

BT - 2025 21st International Conference on the European Energy Market (EEM)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 21st International Conference on the European Energy Market

Y2 - 27 May 2025 through 29 May 2025

ER -

Zhang Z, Hua H, Chen X, Shao J, Zheng J, Wang B et al. Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process. In 2025 21st International Conference on the European Energy Market (EEM). Institute of Electrical and Electronics Engineers (IEEE). 2025. (International Conference on the European Energy Market, EEM). Epub 2025 Jul 7. doi: 10.1109/EEM64765.2025.11050153

Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Handle.net

Other files and links

Fingerprint

Cite this