Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)

Research on Evaluation of Bidding Effect of Hydropower Participating in Power Spot Market

Authors
Liwei ZHAO1, 2, Weibin HUANG1, 2, *, Chunyang LAI1, 2, Shuai ZHANG1, 2, Xiangrui LI1, 2, Guangwen MA1, 2, Shijun Chen1, 2
1College of Water Resource and Hydropower, Sichuan University, 610065, Chengdu, Sichuan Province, China
2State Key Lab of Hydraulics & Mountain River Engineering (Sichuan University), 610065, Chengdu, Sichuan Province, China
*Corresponding author. Email: xhuang2002@163.com
Corresponding Author
Weibin HUANG
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-042-8_213How to use a DOI?
Keywords
evaluation of bidding effect; hydropower; grey correlation analysis; electricity spot market
Abstract

With the reform of Chinese electricity spot market, hydropower stations need to be responsible for their own profits and participate in market bidding. Due to the repeatability of spot market bidding, hydropower stations need to accurately evaluate their bidding effect to guide the improvement of their bidding strategies. Combined with the current hydropower bidding process, market clearing mode and hydropower operation characteristics, this paper constructed the evaluation index system of hydropower bidding effect in the electricity spot market. Based on the index system, the trading results of 8 hydropower stations in a certain basin of Sichuan Province were selected as the research objects, and the Grey Relation Analysis combined with Analytic Hierarchy Process was used to evaluate and analyse the bidding results. The results show that: in the current environment of Sichuan electricity spot market, hydropower stations tend to adopt the bidding strategy of low price; hydropower stations need to widely collect and analyse market supply and demand information, clearly understand their own generation ability, formulate reasonable bidding strategy, and give priority to long term contract electricity trading to ensure their own benefits. The evaluation system pro-posed in this paper has strong practicability, which is convenient for hydropower stations to comprehensively analyse the bidding effect from multiple dimensions, and provides reference for adjusting their bidding strategies.

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 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
Series
Advances in Computer Science Research
Publication Date
29 December 2022
ISBN
978-94-6463-042-8
ISSN
2352-538X
DOI
10.2991/978-94-6463-042-8_213How 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  - Liwei ZHAO
AU  - Weibin HUANG
AU  - Chunyang LAI
AU  - Shuai ZHANG
AU  - Xiangrui LI
AU  - Guangwen MA
AU  - Shijun Chen
PY  - 2022
DA  - 2022/12/29
TI  - Research on Evaluation of Bidding Effect of Hydropower Participating in Power Spot Market
BT  - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
PB  - Atlantis Press
SP  - 1467
EP  - 1479
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-042-8_213
DO  - 10.2991/978-94-6463-042-8_213
ID  - ZHAO2022
ER  -