The objective of this award is to develop analytical and computational decision support tools to effectively manage the maintenance activities of wind energy systems. Degradation-based reliability models, based on specialized diffusion processes, will be developed to explicitly account for the influence of randomly-varying environment conditions on critical wind turbine components, condition-monitoring systems, and time- or weather-constrained maintenance scheduling. Subsequently, stochastic optimization models will be developed to minimize operating and maintenance costs over the life cycle of a wind turbine by adaptively scheduling maintenance activities under uncertain conditions. The analytical tools will: (1) determine the optimal timing of inspections, repairs or replacements; (2) prioritize service activities during scheduled outages; (3) determine which spare parts to order and when; and (4) decide how operating and environmental data should be used to assess the current and future health of critical wind turbine components. Specialized Markov decision process (MDP) and partially observable Markov decision process (POMDP) models with mixed (discrete and continuous) state spaces will be developed along with their associated solution techniques. The developed degradation-based reliability models will be validated using real wind turbine operating data, and the long-run average maintenance costs obtained using the optimization models will be compared with those of a computer simulation model.
If successful, the results of this research will lead to improvements in the operation and maintenance of wind energy systems that will soon supply a significant portion of electric power in the United States. A large fraction of the cost of producing wind energy is directly attributable to operating and maintenance costs stemming from scheduled and unscheduled maintenance activities. The primary goal of this work is to provide techniques that better manage environmental and wind turbine data to make cost-effective decisions about maintenance activities. Reducing the cost of wind energy will accelerate the design, analysis and installation of new land-based and offshore wind turbines. Increasing the share of electricity generated by wind resources will help stabilize energy prices, mitigate the effects of greenhouse gases and substantially reduce the nation's dependence on foreign natural resources. Furthermore, the development of a viable wind energy market will help stimulate the U.S. economy by creating jobs directly related to wind energy including turbine manufacturing and installation, as well as permanent jobs for wind turbine operators and maintenance workers.
