The purpose of this paper is to introduce a holistic decision support system based on condition-based maintenance which utilizes meteorological forecasting information to support decision-making process in services of wind power enterprises.
A pilot conceptual system combining with meteorological information and operations management has been formulated in this study. The proposed system provides benchmarking to support decision making directly and indirectly basing on processing meteorological information and evaluating its impact on service operations. It collects meteorological data to predict failure probabilities in different areas which need corresponding maintenance service and schedule the optimal maintenance periods. In addition, it provides meteorological forecasting and decision support in case of extreme weather events (EWEs).
The conceptual study shows that there is a connection between the meteorological conditions and failures, and it is feasible to make service decisions based on the predictions of weather conditions and their impacts to failures.
The research presented at the present phase is not much beyond a conceptual framework. The actual implementation and all possible related practical issues will be dealt with in future research.
It helps decision makers to predict and identify possible categories of faults in wind turbine, make optimal service decisions to enhance the output performance of wind power generation, and take in advance emergency counteractions in case of EWEs.
It presents a novel concept and provides a roadmap to achieve optimal operations in wind park application through combining meteorological information system with service decision making.
The authors gratefully acknowledge the valuable advices and constructive comments given by Prof Petri Helo, University of Vaasa, and Prof. Angappa Gunasekaran, University of Massachusetts Dartmouth.
Liu, Y. and Yang, W. (2015), "Meteorological information service support system in wind park application", Benchmarking: An International Journal, Vol. 22 No. 2, pp. 222-237. https://doi.org/10.1108/BIJ-11-2012-0077Download as .RIS
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