Picture of smart phone in human hand

World leading smartphone and mobile technology research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers from the Department of Computer & Information Sciences involved in researching exciting new applications for mobile and smartphone technology. But the transformative application of mobile technologies is also the focus of research within disciplines as diverse as Electronic & Electrical Engineering, Marketing, Human Resource Management and Biomedical Enginering, among others.

Explore Strathclyde's Open Access research on smartphone technology now...

Availability growth and state-of-knowledge uncertainty simulation for offshore wind power plants

Zitrou, Athena and Bedford, Tim and Walls, Lesley and Wilson, Kevin and Bell, Keith (2014) Availability growth and state-of-knowledge uncertainty simulation for offshore wind power plants. In: Proceedings of the 12th Wind Integration Workshop. UNSPECIFIED, pp. 785-788. ISBN 9783981387070

Full text not available in this repository. (Request a copy from the Strathclyde author)


The use of new offshore wind turbine designs in uncertain environments introduces considerable systemic performance risks. Current availability models fail to represent these risks adequately even though they could lead to significant under-performance of windfarm availability. Serial early failures lead to loss of generation and costly mitigation activities. In this paper we present a model for offshore wind power plant availability growth that captures both systemic uncertainty and natural variability on availability assessments, and represents the effect of interventions in the failure and repair processes. Our model is a decision-support tool designed to inform management decisions to implement measures to reduce uncertainties and grow availability more effectively and efficiently. We demonstrate the use of the model, which is developed in MATLAB, by using an illustrative example of a fictitious offshore wind power plant.