A Markov model for a wind energy conversion system with condition monitoring

Wind power is one of the most economical sources of energy. Wind Energy Conversion System (WECS) comprises of several components with diverse characteristics that affect system reliability at different level. In order to operate WECS reliably and economically, accurate modeling of a WECS is needed to study the effects of, and possibly identify, components that lead the system to fail. This paper proposes a suitable Markov model for a WECS with condition monitoring (CM). A sensitivity analysis is carried out using the developed model to identify the characteristics of components that are likely to affect system reliability the most. Results show that the components with high mean down times and high failure frequencies are more critical to the availability of a WECS than the others.