Environmental Condition Boundary Design for Direct-Drive Permanent Magnet (DDPM) Wind Generators by Using Extreme Joint Probability Distribution

Tian De, Jing Xia (), Xiaoya Liu, Jingjing Hao, Yan Li and Peng Li
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Tian De: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Jing Xia: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Xiaoya Liu: Beijing Goldwind Science & Creation Windpower Equipment Co., Ltd., Beijing 100176, China
Jingjing Hao: Beijing Goldwind Science & Creation Windpower Equipment Co., Ltd., Beijing 100176, China
Yan Li: Beijing Goldwind Science & Creation Windpower Equipment Co., Ltd., Beijing 100176, China
Peng Li: School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Sustainability, 2023, vol. 15, issue 5, 1-17

Abstract: In future engineering applications, it is important for a direct-drive permanent magnet (DDPM) wind generator to be designed with optimized environmental condition boundary. This paper presents a novel extreme joint probability distribution method of boundary design to formulate the evaluation model and correlation between component design and environmental conditions. With this method, the joint probability distributions of multidimensional parameters for typical wind resource areas in China are studied. A 3.3-MW DDPM wind generator is involved in the case study to validate the superiority of the method. Furthermore, to improve the generalizability of the method, some typical wind resource data platforms are calibrated regarding the measured data. It is shown that the ERA5 dataset can be used as a supplement to enhance the representativeness of the measured data for the joint probability distributions. Therefore, the proposed method can be potentially used to optimize the system design of future DDPM wind generators.

Keywords: wind generator; probability distribution; environmental condition; boundary design; data process (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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