Maintenance of wind turbine scheduling based on output power data and wind forecast

Abstract

Maintenance of a wind turbine is a combination of all technical, administrative and managerial actions intended to retain it in, or restore it to, a state in which the turbine is able to generate power. This paper presents an influence diagram to estimate the expected utility that represents wind turbine energy to be produced given period of time in the future. The conditional probability distribution of a chance node of the diagram is obtained relying on Bayesian networks, whereas the utilities of value node are calculated thanks to the second order semi-Markov chains. The example shows the application of the models in the real case of one wind turbine E48 by Enercon located in northern part of Poland. Both Bayesian network parameters and kernel of semi-Markov chain are derived from real data recorded by SCADA system of the turbine and weather forecast.