LAPSE:2023.18742
Published Article

LAPSE:2023.18742
Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets
March 8, 2023
The promising power-to-gas (P2G) technology makes it possible for wind farms to absorb carbon and trade in multiple energy markets. Considering the remoteness of wind farms equipped with P2G systems and the isolation of different energy markets, the scheduling process may suffer from inefficient coordination and unstable information. An automated scheduling approach is thus proposed. Firstly, an automated scheduling framework enabled by smart contract is established for reliable coordination between wind farms and multiple energy markets. Considering the limited logic complexity and insufficient calculation of smart contracts, an off-chain procedure as a workaround is proposed to avoid complex on-chain solutions. Next, a non-linear model of the P2G system is developed to enhance the accuracy of scheduling results. The scheduling strategy takes into account not only the revenues from multiple energy trades, but also the penalties for violating contract items in smart contracts. Then, the implementation of smart contracts under a blockchain environment is presented with multiple participants, including voting in an agreed scheduling result as the plan. Finally, the case study is conducted in a typical two-stage scheduling process—i.e., day-ahead and real-time scheduling—and the results verify the efficiency of the proposed approach.
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Keywords
energy trade, integrated energy system, Scheduling, smart contract
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Suggested Citation
Ji Z, Guo Z, Li H, Wang Q. Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets. (2023). LAPSE:2023.18742
Author Affiliations
Ji Z: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Guo Z: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Li H: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Wang Q: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Guo Z: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Li H: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Wang Q: School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, China
Journal Name
Energies
Volume
14
Issue
20
First Page
6781
Year
2021
Publication Date
2021-10-18
ISSN
1996-1073
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Original Submission
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PII: en14206781, Publication Type: Journal Article
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LAPSE:2023.18742
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https://doi.org/10.3390/en14206781
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Mar 8, 2023
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