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An optimized GRT model with blockchain digital smart contracts for power generation enterprises

Shanglei Chai, Xichun Zhang, Mohammad Abedin Orcid Logo, Huizheng Chen, Brian Lucey, Petr Hajek

Energy Economics, Volume: 128, Start page: 107153

Swansea University Author: Mohammad Abedin Orcid Logo

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DOI (Published version): 10.1016/j.eneco.2023.107153

Abstract

The traditional power generation rights trading (GRT) market is faced with the problems of weak interconnection of electricity-carbon market and low security. Using smart contracts in the blockchain, the idea of establishing a weakly centralized GRT structure is proposed in this paper. The carbon em...

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Published in: Energy Economics
ISSN: 0140-9883
Published: Elsevier BV 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64913
first_indexed 2023-11-03T23:39:31Z
last_indexed 2024-11-25T14:14:59Z
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spelling 2024-04-16T12:57:46.8202602 v2 64913 2023-11-03 An optimized GRT model with blockchain digital smart contracts for power generation enterprises 4ed8c020eae0c9bec4f5d9495d86d415 0000-0002-4688-0619 Mohammad Abedin Mohammad Abedin true false 2023-11-03 CBAE The traditional power generation rights trading (GRT) market is faced with the problems of weak interconnection of electricity-carbon market and low security. Using smart contracts in the blockchain, the idea of establishing a weakly centralized GRT structure is proposed in this paper. The carbon emission factor was introduced to improve the GRT model, and carbon emission market is used to further stimulate the emission reduction vitality of generating units. The empirical results show that compared with the benchmark model and improved model 1, the improved GRT model proposed by us has the best emission reduction effect. The contribution of this paper is to make up for the existing research that cannot fully consider the impact of carbon peak and carbon neutralization on the GRT market, as well as the information security issues brought by big data trading on the GRT platform. This paper puts forward some policy implications for the decarbonization and green development of the electricity market advocated by the Chinese government. Journal Article Energy Economics 128 107153 Elsevier BV 0140-9883 big data; blockchain; digital smart contract; generation rights transaction (GRT); power generation enterprises 1 12 2023 2023-12-01 10.1016/j.eneco.2023.107153 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University This work was supported by the National Social Science Foundation of China (No. 20BJL058), the National Natural Science Foundation of China (No. 72001191, 72104021) and the Natural Science Foundation of Shandong Province (No. ZR2023MG042, ZR2020MG074). 2024-04-16T12:57:46.8202602 2023-11-03T23:38:30.3576291 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Shanglei Chai 1 Xichun Zhang 2 Mohammad Abedin 0000-0002-4688-0619 3 Huizheng Chen 4 Brian Lucey 5 Petr Hajek 6 64913__29426__e6a7d26980e24177bba5a1b8fe5a0c15.pdf 64913.AAM.pdf 2024-01-10T13:30:19.7270701 Output 3123526 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention). true eng https://creativecommons.org/licenses/by/4.0/
title An optimized GRT model with blockchain digital smart contracts for power generation enterprises
spellingShingle An optimized GRT model with blockchain digital smart contracts for power generation enterprises
Mohammad Abedin
title_short An optimized GRT model with blockchain digital smart contracts for power generation enterprises
title_full An optimized GRT model with blockchain digital smart contracts for power generation enterprises
title_fullStr An optimized GRT model with blockchain digital smart contracts for power generation enterprises
title_full_unstemmed An optimized GRT model with blockchain digital smart contracts for power generation enterprises
title_sort An optimized GRT model with blockchain digital smart contracts for power generation enterprises
author_id_str_mv 4ed8c020eae0c9bec4f5d9495d86d415
author_id_fullname_str_mv 4ed8c020eae0c9bec4f5d9495d86d415_***_Mohammad Abedin
author Mohammad Abedin
author2 Shanglei Chai
Xichun Zhang
Mohammad Abedin
Huizheng Chen
Brian Lucey
Petr Hajek
format Journal article
container_title Energy Economics
container_volume 128
container_start_page 107153
publishDate 2023
institution Swansea University
issn 0140-9883
doi_str_mv 10.1016/j.eneco.2023.107153
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
document_store_str 1
active_str 0
description The traditional power generation rights trading (GRT) market is faced with the problems of weak interconnection of electricity-carbon market and low security. Using smart contracts in the blockchain, the idea of establishing a weakly centralized GRT structure is proposed in this paper. The carbon emission factor was introduced to improve the GRT model, and carbon emission market is used to further stimulate the emission reduction vitality of generating units. The empirical results show that compared with the benchmark model and improved model 1, the improved GRT model proposed by us has the best emission reduction effect. The contribution of this paper is to make up for the existing research that cannot fully consider the impact of carbon peak and carbon neutralization on the GRT market, as well as the information security issues brought by big data trading on the GRT platform. This paper puts forward some policy implications for the decarbonization and green development of the electricity market advocated by the Chinese government.
published_date 2023-12-01T08:25:55Z
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score 11.048171

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