PHM Based Predictive Maintenance Option Model for Offshore Wind Farm O&M Optimization

Abstract

A simulation-based real options analysis (ROA) approach is used to determine the optimum predictive maintenance opportunity for multiple wind turbines with remaining useful life (RUL) predictions in offshore wind farms managed under outcome-based contracts, i.e., power purchase agreements (PPAs). When an RUL is predicted for a subsystem in a single turbine using PHM, a predictive maintenance option is triggered that the decision-maker has the flexibility to decide if and when to exercise before the subsystem or turbine fails. The predictive maintenance value paths are simulated by considering the uncertainties in the RUL predictions and wind speeds (that govern the turbine’s revenue earning potential). By valuating a series of European options expiring on all possible predictive maintenance opportunities, a series of option values can be obtained, and the optimum predictive maintenance opportunity can be selected. The optimum predictive maintenance opportunity can also be determined using a stochastic discounted cash flow (DCF) approach that assumes the predictive maintenance will always be implemented on the selected opportunity. For a wind farm managed via a PPA with multiple turbines indicating RULs concurrently, the predictive maintenance value for each turbine depends on the operational state of the other turbines, the amount of energy delivered and to be delivered by the whole wind farm. A case study is presented in which the stochastic DCF and European ROA approaches are applied to a single turbine and to a wind farm managed via a PPA. The optimum predictive maintenance opportunities obtained from the two approaches are compared and it is demonstrated that the European ROA approach will suggest a more conservative opportunity for predictive maintenance with a higher expected option value than the expected net present value (NPV) from the stochastic DCF approach.