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

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

Author

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  • Zhehui Dang

    (Datang Sichuan Power Generation Co., Ltd. Renewable Power Branch Chengdu)

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.

Suggested Citation

  • Zhehui Dang, 2024. "Analysis of Factors Influencing Mountain Wind Power Generation Based on Grey Relational Analysis," Advances in Economics, Business and Management Research, in: Suhaiza Hanim Binti Dato Mohamad Zailani & Kosga Yagapparaj & Norhayati Zakuan (ed.), Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), pages 1047-1052, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-256-9_103
    DOI: 10.2991/978-94-6463-256-9_103
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