Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)

<Previous Article In Volume
Next Article In Volume>

Analysis of Factors Influencing Mountain Wind Power Generation Based on Grey Relational Analysis

Authors
Zhehui Dang1, *
1Datang Sichuan Power Generation Co., Ltd. Renewable Power Branch Chengdu, Sichuan, 610031, China
*Corresponding author. Email: dangzhehui@cdt.com
Corresponding Author
Zhehui Dang
Available Online 9 October 2023.
DOI
10.2991/978-94-6463-256-9_103How to use a DOI?
Keywords
Mountainous wind farm; Grey relational analysis; Meteorological elements; Wind power
Abstract

With the growing demand for renewable energy, mountain wind farms have attracted significant attention as an important clean energy generation method. However, the rapid changes in mountainous meteorological data and the complexity of terrain pose challenges for wind power forecasting in these areas. This paper aims to analyze the characteristics of mountain wind farms and the key factors involved in predicting wind power. Based on the grey relational analysis method, this study explores the factors influencing the power generation of mountain wind farms.By collecting and preprocessing data such as wind speed, wind direction, temperature, air pressure, and air density, the grey relational analysis method is employed to calculate the correlation between the influencing factors and wind power generation. By comparing the impact weights of different terrains and meteorological elements on power prediction, suitable meteorological elements for wind power generation in high-altitude mountainous regions are determined. The results indicate that wind speed is the primary factor determining wind power output, while wind direction plays a secondary role. In mountainous scenarios, air density also emerges as one of the influencing factors affecting wind power generation.

Copyright
© 2024 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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
9 October 2023
ISBN
978-94-6463-256-9
ISSN
2352-5428
DOI
10.2991/978-94-6463-256-9_103How to use a DOI?
Copyright
© 2024 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

risenwbib
TY  - CONF
AU  - Zhehui Dang
PY  - 2023
DA  - 2023/10/09
TI  - Analysis of Factors Influencing Mountain Wind Power Generation Based on Grey Relational Analysis
BT  - Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
PB  - Atlantis Press
SP  - 1047
EP  - 1052
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-256-9_103
DO  - 10.2991/978-94-6463-256-9_103
ID  - Dang2023
ER  -