Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023)

Trading Method of Electricity Spot Market Under High Penetration Ratio of New Energy

Authors
Xiaobo Ling1, *, Shengqi Cai1, Gongchang Zhou1, Yangsheng Sun1, Ming Chen1, Erxi Wang1, Qiyi Lu1
1Dsipatching Center, Shanghai Municipal Electric Power Company, Shanghai, 200000, China
*Corresponding author. Email: lingxb@sh.sgcc.com.cn
Corresponding Author
Xiaobo Ling
Available Online 30 November 2023.
DOI
10.2991/978-94-6463-298-9_27How to use a DOI?
Keywords
new energy; spot market of electricity; trading mode; technical method
Abstract

In this paper, the spot trading of electric power with high penetration ratio of new energy is taken as the research object, and all parties involved in the spot trading of electric power are investigated to form an electric energy trading chain. The decentralized blockchain technology is adopted to establish a trading model of the spot market of electric power, store the trading information of all parties involved, solve the model by using the strategy learning method, and analyze the market electric energy trading volume and the benefits of all parties. The research results show that the spot market transactions of electricity include energy suppliers, energy sellers and buyers, energy reserves and load aggregators. The spot trading chain of electric energy is built by using the platform of Ethereum blockchain, and the spot market of electric energy is simulated by strategy learning method. It is concluded that the installed capacity and clearing capacity of wind power suppliers are the largest, the maintenance cost is lower, the market income is the highest, but the maintenance cost far exceeds that of all energy suppliers; Using the spot trading method of electric energy trading chain to improve the income of each trading subject, the quotation of market subjects is more flexible and more in line with the relationship between supply and demand, and the clearing price of the market is basically positively correlated with the relationship between supply and demand; The credit value of each power trading entity is quantified as the default coefficient. When the default coefficient of each trading entity is larger, its income will gradually decrease, and the default of energy suppliers has the greatest impact on its income.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
30 November 2023
ISBN
10.2991/978-94-6463-298-9_27
ISSN
2352-5428
DOI
10.2991/978-94-6463-298-9_27How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Xiaobo Ling
AU  - Shengqi Cai
AU  - Gongchang Zhou
AU  - Yangsheng Sun
AU  - Ming Chen
AU  - Erxi Wang
AU  - Qiyi Lu
PY  - 2023
DA  - 2023/11/30
TI  - Trading Method of Electricity Spot Market Under High Penetration Ratio of New Energy
BT  - Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023)
PB  - Atlantis Press
SP  - 246
EP  - 253
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-298-9_27
DO  - 10.2991/978-94-6463-298-9_27
ID  - Ling2023
ER  -