Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets
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 coo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/20/6781 |
| _version_ | 1797514728718729216 |
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| author | Zhenya Ji Zishan Guo Hao Li Qi Wang |
| author_facet | Zhenya Ji Zishan Guo Hao Li Qi Wang |
| author_sort | Zhenya Ji |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T06:35:49Z |
| format | Article |
| id | doaj.art-944fa1c032314b388a17b752e3f59910 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T06:35:49Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-944fa1c032314b388a17b752e3f599102023-11-22T18:08:42ZengMDPI AGEnergies1996-10732021-10-011420678110.3390/en14206781Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy MarketsZhenya Ji0Zishan Guo1Hao Li2Qi Wang3School of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210046, ChinaThe 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.https://www.mdpi.com/1996-1073/14/20/6781integrated energy systemschedulingenergy tradesmart contract |
| spellingShingle | Zhenya Ji Zishan Guo Hao Li Qi Wang Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets Energies integrated energy system scheduling energy trade smart contract |
| title | Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets |
| title_full | Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets |
| title_fullStr | Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets |
| title_full_unstemmed | Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets |
| title_short | Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets |
| title_sort | automated scheduling approach under smart contract for remote wind farms with power to gas systems in multiple energy markets |
| topic | integrated energy system scheduling energy trade smart contract |
| url | https://www.mdpi.com/1996-1073/14/20/6781 |
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