Michael Pecht1 , Gilbert Haddad1, Peter Sandborn1
1CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
Abstract:
This paper provides an optimization model based on Real Options (RO) and
stochastic dynamic programming for the availability maximization of an offshore wind
farm with prognostic capabilities. Alternative energy sources such as offshore wind
turbines are promising technologies, but they are capital intensive projects, and the
economics of the project depend heavily on the wind resources, and the availability of the
turbines. Prognostics and health management (PHM) is an enabling technology that
potentially allows for reduced life cycle cost through a transition from cycle or time
based to demand-based maintenance, performance based logistics, and condition-based
maintenance. This is especially important for offshore wind farms that require nontraditional
resources for maintenance, and are often located in sites that are not always
accessible. The proposed model uses information from the PHM system in order to
allocate appropriate investments in maintenance while maintaining a specified
availability requirement. The RO theory provides promising means to address the
economic aspects of PHM after prognostic indication, and assessing the cost required for
meeting availability requirements.