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A Spare Parts Demand Prediction Method for Wind Farm Based on Periodic Maintenance Strategy

[+] Author Affiliations
Chen Zhang, Tao Yang, Wei Gao

Huazhong University of Science and Technology, Wuhan, China

Weiqiu Chen, Jing He, Xingwang Yang

Guangdong Yudean Zhanjiang Wind Power Co. Ltd., Zhanjiang, China

Paper No. POWER-ICOPE2017-3077, pp. V002T09A001; 5 pages
doi:10.1115/POWER-ICOPE2017-3077
From:
  • ASME 2017 Power Conference Joint With ICOPE-17 collocated with the ASME 2017 11th International Conference on Energy Sustainability, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum
  • Volume 2: I&C, Digital Controls, and Influence of Human Factors; Plant Construction Issues and Supply Chain Management; Plant Operations, Maintenance, Aging Management, Reliability and Performance; Renewable Energy Systems: Solar, Wind, Hydro and Geothermal; Risk Management, Safety and Cyber Security; Steam Turbine-Generators, Electric Generators, Transformers, Switchgear, and Electric BOP and Auxiliaries; Student Competition; Thermal Hydraulics and Computational Fluid Dynamics
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: Power Division, Advanced Energy Systems Division, Solar Energy Division, Nuclear Engineering Division
  • ISBN: 978-0-7918-5761-8
  • Copyright © 2017 by ASME

abstract

Nowadays, the management level and information construction of wind power industry are still relatively backward, for example, the existing maintenance models for wind farm are much too single, and corrective maintenance strategy is the most commonly used, which means that maintenance measures are initiated only after a breakdown occurs in the system. Moreover, the wind farm spare parts management is out-dated, no practical and accurate spares demand assessment method is available. In order to enrich the choices of maintenance methods and eliminate the subjective influence in the demand analysis of spare parts, a spare parts demand prediction method for wind farm based on periodic maintenance strategy considering combination of different maintenance models for wind farms is proposed in this paper, which consists of five major steps, acquire the reliability functions of components, establish the maintenance strategy, set the maintenance parameters, maintenance strategy simulation and spare parts demand prediction. The discrete event simulation method is used to solve the prediction model, and results demonstrate the operability and practicality of the proposed demand forecasting method, which can provide guidance for the actual operation and maintenance of wind farms.

Copyright © 2017 by ASME

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