An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming

Wenwen He; Xiong Wu; Xiaofei Li; Mingkang He; Binrui Cao; Ziyu Zhang

doi:10.1109/CEEPE55110.2022.9783427

An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming

Wenwen He
, Xiong Wu
, Xiaofei Li
, Mingkang He
, Binrui Cao
, Ziyu Zhang

School of Electrical Engineering

Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

As more polices are being applied to reduce the green gas emission, the construction of On-site Hydrogen Refueling Stations (OHRS) is necessary for the popularization of hydrogen powered vehicles. One of the most reliable energy resources for an OHRS would be the electric energy purchased from the grid. The electricity market is divided into day-ahead market and real-time market. Considering volatility electricity prices, and uncertainty of hydrogen demand, the paper presents an electricity transaction strategy model for a single OHRS. To avoid the combinatorial "explosion"with the number of uncertainties, by using Stochastic Dual Dynamic Programming (SDDP) algorithm, the expected cost-to-go function is approximated by piecewise linear functions, which improves the solution time. Real historical market data are used in case study. The results show that when the electricity prices and hydrogen loads fluctuate, the proposed model can optimize the electricity transaction strategy for OHRS under the condition of meeting the safety criteria. The study can provide a theoretical method for OHRS for the transaction strategies.

Original language	English
Title of host publication	2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	956-961
Number of pages	6
ISBN (Electronic)	9781665479059
DOIs	https://doi.org/10.1109/CEEPE55110.2022.9783427
State	Published - 2022
Event	5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022 - Chongqing, China Duration: 22 Apr 2022 → 24 Apr 2022

Publication series

Name	2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022

Conference

Conference	5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022
Country/Territory	China
City	Chongqing
Period	22/04/22 → 24/04/22

Keywords

OHRS
SDDP
electricity market
hydrogen power

Access to Document

10.1109/CEEPE55110.2022.9783427

Cite this

He, W., Wu, X., Li, X., He, M., Cao, B., & Zhang, Z. (2022). An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming. In 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022 (pp. 956-961). (2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEEPE55110.2022.9783427

He, Wenwen ; Wu, Xiong ; Li, Xiaofei et al. / An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming. 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 956-961 (2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022).

@inproceedings{7f779dc46ceb4336a95ad49b4166c95c,

title = "An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming",

abstract = "As more polices are being applied to reduce the green gas emission, the construction of On-site Hydrogen Refueling Stations (OHRS) is necessary for the popularization of hydrogen powered vehicles. One of the most reliable energy resources for an OHRS would be the electric energy purchased from the grid. The electricity market is divided into day-ahead market and real-time market. Considering volatility electricity prices, and uncertainty of hydrogen demand, the paper presents an electricity transaction strategy model for a single OHRS. To avoid the combinatorial {"}explosion{"}with the number of uncertainties, by using Stochastic Dual Dynamic Programming (SDDP) algorithm, the expected cost-to-go function is approximated by piecewise linear functions, which improves the solution time. Real historical market data are used in case study. The results show that when the electricity prices and hydrogen loads fluctuate, the proposed model can optimize the electricity transaction strategy for OHRS under the condition of meeting the safety criteria. The study can provide a theoretical method for OHRS for the transaction strategies.",

keywords = "OHRS, SDDP, electricity market, hydrogen power",

author = "Wenwen He and Xiong Wu and Xiaofei Li and Mingkang He and Binrui Cao and Ziyu Zhang",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022 ; Conference date: 22-04-2022 Through 24-04-2022",

year = "2022",

doi = "10.1109/CEEPE55110.2022.9783427",

language = "英语",

series = "2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022",

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He, W, Wu, X, Li, X, He, M, Cao, B & Zhang, Z 2022, An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming. in 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022. 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022, Institute of Electrical and Electronics Engineers Inc., pp. 956-961, 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022, Chongqing, China, 22/04/22. https://doi.org/10.1109/CEEPE55110.2022.9783427

An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming. / He, Wenwen; Wu, Xiong; Li, Xiaofei et al.
2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 956-961 (2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming

AU - He, Wenwen

AU - Wu, Xiong

AU - Li, Xiaofei

AU - He, Mingkang

AU - Cao, Binrui

AU - Zhang, Ziyu

PY - 2022

Y1 - 2022

N2 - As more polices are being applied to reduce the green gas emission, the construction of On-site Hydrogen Refueling Stations (OHRS) is necessary for the popularization of hydrogen powered vehicles. One of the most reliable energy resources for an OHRS would be the electric energy purchased from the grid. The electricity market is divided into day-ahead market and real-time market. Considering volatility electricity prices, and uncertainty of hydrogen demand, the paper presents an electricity transaction strategy model for a single OHRS. To avoid the combinatorial "explosion"with the number of uncertainties, by using Stochastic Dual Dynamic Programming (SDDP) algorithm, the expected cost-to-go function is approximated by piecewise linear functions, which improves the solution time. Real historical market data are used in case study. The results show that when the electricity prices and hydrogen loads fluctuate, the proposed model can optimize the electricity transaction strategy for OHRS under the condition of meeting the safety criteria. The study can provide a theoretical method for OHRS for the transaction strategies.

AB - As more polices are being applied to reduce the green gas emission, the construction of On-site Hydrogen Refueling Stations (OHRS) is necessary for the popularization of hydrogen powered vehicles. One of the most reliable energy resources for an OHRS would be the electric energy purchased from the grid. The electricity market is divided into day-ahead market and real-time market. Considering volatility electricity prices, and uncertainty of hydrogen demand, the paper presents an electricity transaction strategy model for a single OHRS. To avoid the combinatorial "explosion"with the number of uncertainties, by using Stochastic Dual Dynamic Programming (SDDP) algorithm, the expected cost-to-go function is approximated by piecewise linear functions, which improves the solution time. Real historical market data are used in case study. The results show that when the electricity prices and hydrogen loads fluctuate, the proposed model can optimize the electricity transaction strategy for OHRS under the condition of meeting the safety criteria. The study can provide a theoretical method for OHRS for the transaction strategies.

KW - OHRS

KW - SDDP

KW - electricity market

KW - hydrogen power

UR - https://www.scopus.com/pages/publications/85132296163

U2 - 10.1109/CEEPE55110.2022.9783427

DO - 10.1109/CEEPE55110.2022.9783427

M3 - 会议稿件

AN - SCOPUS:85132296163

T3 - 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022

SP - 956

EP - 961

BT - 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022

Y2 - 22 April 2022 through 24 April 2022

ER -

He W, Wu X, Li X, He M, Cao B, Zhang Z. An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming. In 2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 956-961. (2022 5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022). doi: 10.1109/CEEPE55110.2022.9783427

An Electricity Transaction Strategy Model for On-site Hydrogen Refueling Stations Based on Stochastic Dual Dynamic Programming

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