Making Wind Power Competitive Using Risk-Informed and Performance-Based Maintenance Strategies


The objective of this project was to develop a new economic formula for maximizing present value of net benefits of wind farm investment. This research model offers the following advantages: a) the ability to evaluate the benefit of expenditure on maintenance activities not only in a given year, but also into the future; b) allowance for maintenance costs to vary over time; and c) a flexible design that allows maintenance costs to be estimated as a function of other characteristics such as wind turbine features and location.

As part of this project, the investigators developed two models: 1) the wind turbine (WT) reliability prediction model and 2) the “Four-Quadrant Component/Subsystem Maintenance Model.” The WT reliability prediction model was developed using ReliaSoft BlockSim-7 simulation software package. The reliability model contains the major WT components including the blades, bearings, gearbox, generator, hydraulic and mechanical breaks, main shaft, tower, and foundation. Each simulated sub-system of the wind turbine reliability model contains field component failure rates that were compiled from the literature review phase of this research.

The “Four-Quadrant Component/Subsystem Maintenance Model” was developed to analyze different WT maintenance strategies. Based on this model, strategies were proposed based on component reliability and its contribution to the energy generation loss in kilowatt-hours given the component failure. These four maintenance strategies include: i) time-based preventative maintenance using visual inspection; ii) scheduled condition-based maintenance (CBM); iii) on-line/continuous CBM; and iv) run-to-failure corrective maintenance strategy.

The investigators also developed an Excel-based program to estimate wind turbine cost. The user of this cost estimator only needs to enter specific parameters such as the blade radius, wind turbine rating (in kilowatts), hub height, and the rotor swept area. Lastly, the investigators compiled a comprehensive database of WT component failure rates based on review of the literature of field failure data. This database may be valuable for conducting WT risk and reliability analyses.

Project Outcomes

The overall formula of the project’s model can be applied to specific examples to quantify the net benefits and to benchmark the predictions versus published data. The results of the project allowed the investigators to perform design failure modes and effects analysis for the wind turbine system and identify critical failure mechanisms. As a result, a risk reduction method could be proposed for the identified critical risks and failure mechanisms. Additionally, this project allowed the investigators to propose a methodology for performing a wind turbine life cycle impact analysis and to quantify the environmental impacts (e.g., carbon footprint, global warning potential, ozone depletion potential, etc.).

Related Presentations

The interim results of this research were discussed during presentations made at the annual Climate Change Conference held at the University of Oxford in the United Kingdom (March 27–31, 2011 and March 19–23, 2012).

Use and Applications

Professor Khalil used the content of this research in three courses at the Yale School of Forestry & Environmental Studies: Air Pollution Control, Environmental Risk Assessment, and Introduction to Green Energy.

Future Activities

As a result of this project, the investigators are preparing a white paper to be presented to the U.S. Department of Energy’s National Energy Technology Laboratory in Pittsburgh, PA to gain support for continuing this research. This funding will be essential for completing the wind turbine life cycle impact analysis and quantifying the adverse environmental impacts.

Photo from Tobias von der Haar/flickr