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Wind turbine reliability


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Wind turbine reliability

  1. 1. Wind Turbine Reliability: A Database and Analysis Approach Raghav Raghunathan
  2. 2. The Wind Energy Industry and Aim of Sandia Report 2008 <ul><li>Remarkable growth in </li></ul><ul><ul><li>US Wind Industry. </li></ul></ul><ul><ul><li>Physical size and electrical generation capabilities of the wind turbines. </li></ul></ul><ul><li>Goal of the report </li></ul><ul><ul><li>better understand and to improve the operable reliability of wind turbine installations. </li></ul></ul>
  3. 3. Introduction – Sandia into the Wind Turbine Reliability effort! <ul><li>Department of Energy has designated Sandia National Laboratories’ Wind Energy Technology Department to forefront the wind turbine reliability effort. </li></ul><ul><li>Sandia will actively seek industry involvement to collect, analyze, and disseminate reliability and performance data essential for determining fleet reliability issues. </li></ul><ul><li>Critical performance, design, and evaluation techniques will be shared between stakeholders to facilitate comparative evaluations, and identify critical failure modes and potential weak links. </li></ul><ul><li>This in turn will lead back to improved wind turbine design, as well as operations and maintenance practices. </li></ul>
  4. 4. Objectives of Wind Turbine Reliability effort <ul><li>Establish industry benchmarks for reliability performance </li></ul><ul><li>Identify failure trends </li></ul><ul><li>Document industry reliability improvements over time </li></ul><ul><li>Provide high quality information to support O&M practices </li></ul><ul><li>Improve system performance of wind assets through better asset management practices </li></ul><ul><li>Target efforts to address important component reliability problems </li></ul>
  5. 5. Definitions <ul><li>Reliability - The probability that a product will perform its intended function under stated conditions for a specified period of time </li></ul><ul><ul><li>Probability </li></ul></ul><ul><ul><li>Intended Functions </li></ul></ul><ul><ul><li>Stated Conditions </li></ul></ul><ul><ul><li>Time </li></ul></ul><ul><li>Bathtub Curve -Graphical representation to describe PLC of Wind Turbines </li></ul>
  6. 6. <ul><li>A principle system performance measure is system MTBF. </li></ul><ul><ul><li>MTBF= Operational Time/No. of failures </li></ul></ul><ul><li>Mean time to repair metric </li></ul><ul><ul><li>MTTR= Total repair time/No. of failures </li></ul></ul><ul><li>Availability – most closely related to energy production and revenues so it is of most significant in the operations of wind plants. It is the amount of time that a system or component is available for use divided by that total amount of time in the period of operation. </li></ul><ul><ul><li>Availability (A) = MTBF / [MTBF + MTTR+ PM] </li></ul></ul><ul><ul><li>The Availability of a Wind Farm Goes Up With Years in Operation as Operators Understand the System and Can Increase Efficiency in Repairs and Replacements. </li></ul></ul><ul><li>Preventative maintenance (PM) is included if it requires component outage. </li></ul><ul><li>Safety – Of course, most important in O&M activities. </li></ul>Key Metrics
  7. 7. The Costs of Operations and Maintenance (O&M) <ul><li>Total Operations and Maintenance Costs Increase with Age Due to Wear-Out Related Failures. </li></ul><ul><li>The annual O&M cost is indicated in $/kWh as the plant age ranges from the first year of operation through year 20 as shown in Figure </li></ul>
  8. 8. Annual Average Operations and Maintenance Costs by Project Age <ul><li>For plants installed in the 1998/1999 time frames it is evident that O&M costs have tended to increase as time goes by, even approaching $.02/kWh estimates of the previous chart. </li></ul><ul><li>Newer plants do not show such a distinctive trend although they typically are a level around $0.01/kWh. </li></ul><ul><li>The key to managing O&M costs may be in the reliability analysis of failures and corrective management practices. </li></ul>
  9. 9. Techniques available to analyze failure rates <ul><li>Failure rates can be determined in terms of MTBF, MTTR, and Availability. </li></ul><ul><li>Failures that require significant expenditures are readily revealed using Pareto analyses (the law of the vital few), focuses attention on the contributors to the causes that contribute most to the effects. (80% of the problems are caused by 20% of the causes). </li></ul>
  10. 10. Pareto Technique: <ul><li>Top Four maintenance categories </li></ul><ul><ul><li>Replacement of rotors, nacelles, gearboxes, and generators with external cranes </li></ul></ul><ul><ul><li>Replacement of large components with internal crane </li></ul></ul><ul><ul><li>Replacement of small parts </li></ul></ul><ul><ul><li>Inspection and repair </li></ul></ul><ul><li>Minimize costs and Optimization of O&M strategy </li></ul><ul><ul><li>Improvement of deployment of crew (maintenance strategy) </li></ul></ul><ul><ul><li>Reduction of failure rates </li></ul></ul><ul><ul><li>Fault tolerant operations </li></ul></ul><ul><ul><li>Improvement of accessibility </li></ul></ul>
  11. 11. Failure Characteristics – Sources for Reliability Information – IEEE <ul><li>IEEE Gold Book states “knowledge of the reliability of electrical equipment is an important consideration in the design and operation of industrial and commercial power distribution systems. </li></ul><ul><li>The failure characteristics of individual pieces of electrical equipment, (i.e. components) can be partially described by the following basic reliability statistics: </li></ul><ul><li>Failure rate, often expressed as failures per year per component (failures per unit year): </li></ul><ul><li>Downtime to repair or replace a component after it has failed in service, expressed in hours (or minutes) per failure” </li></ul>
  12. 12. <ul><li>For a system such as an electrical power facility, availability is a key measure of performance. </li></ul><ul><li>The IEEE Gold Book includes tables of Inherent Availability and Reliability Data . In these tables are listed items such as </li></ul><ul><ul><li>Component </li></ul></ul><ul><ul><li>Unit-years </li></ul></ul><ul><ul><li>Failures </li></ul></ul><ul><ul><li>Failure rate (failures/year) </li></ul></ul><ul><ul><li>MTBF </li></ul></ul><ul><ul><li>MTTR </li></ul></ul>
  13. 13. Failure Characteristics – Sources for Reliability Information – Paul Barringer <ul><li>Reliability expert Paul Barringer, P.E.has developed a Weibull Reliability Database for Failure Data for Various Components </li></ul><ul><li>This database lists components that are found in wind turbines including roller bearings, gears, lubrications pumps, couplings, </li></ul><ul><li>gaskets, circuit breakers, AC motors, and synthetic lubrications oils that all have typical Weibull Characteristic life in the 50,000 to 100,000 hours. If converted to years these components would experience lifetimes in the range of 6 to 12 years. </li></ul><ul><li>Considerable engineering judgment should be employed when using these numbers for analysis. </li></ul><ul><li>The environment in which wind turbines operates is much more severe than typical plant applications. </li></ul><ul><li> </li></ul><ul><li>Sample Weibull Reliability measuring Production Output Vs. Production Reliability is shown on this slide. </li></ul>
  14. 14. National Reliability Database (NRD) <ul><li>For a variable resource such as wind, the emphasis is on maximizing output when wind is available, and performing as much as is possible of the maintenance during periods of slight wind. </li></ul><ul><li>The NRD for the US is being created to understand where components and systems failures occur and to understand their consequences so that reliability can be improved. </li></ul><ul><li>The functional description of the Sandia Wind National Reliability Database is to: </li></ul><ul><li>Create a warehouse of all wind turbine data pertaining to events, timelines, and environments </li></ul><ul><li>Establish links between event times, and environments </li></ul><ul><li>Establish rules for determining failure rates, failure causes, availabilities, and repair times from database queries </li></ul><ul><li>Determine failure rates, failure causes, availabilities, and repair times for wind turbine components </li></ul><ul><li>Perform rudimentary parameter fitting: e.g. Weibull parameter values, strengths of trends </li></ul>
  15. 15. Objective of Sandia Wind National Reliability Database
  16. 16. National Reliability Database (NRD) <ul><li>The success of the database depends on the collection of statistically significant amounts of information and processing that data so that it can be used for reliability analyses and aggregation of individual inputs into industry baseline reports. </li></ul><ul><li>Through efforts with the American Wind Energy Association (AWEA) O&M Working Group and others, this process has started. </li></ul><ul><li>The figure here illustrates both the types of information for data collection, the database and analysis role of Sandia and the feedback loop of providing back synthesized information to the industry. </li></ul><ul><li>It is acknowledged that failure information is sensitive and throughout this process no individual wind plant, turbine manufacturer, or subcomponent vendor will have its reliability information released. </li></ul><ul><li>This whole process is still in the initial stage and the database will be used for broad reliability analyses that are expected to identify technology improvement opportunities that could spawn future individual component improvement activities. </li></ul>
  17. 17. Reliability Modeling <ul><li>Reliability modeling is a long-term activity involving the creation of a system taxonomy, which includes breaking the system down into its respective parts and failure modes, acquisition of information (population of the database), refinement of the reliability model, and improving system design. </li></ul><ul><li>There are two modeling techniques currently used at SNL for wind farm reliability modeling </li></ul><ul><ul><li>reliability block diagram (RBD) modeling </li></ul></ul><ul><ul><li>fault tree analysis. </li></ul></ul><ul><li>This process: </li></ul><ul><li>Improves understanding of the system </li></ul><ul><li>Allows for early evaluation of design alternatives </li></ul><ul><li>Identifies critical component failure modes and failure interactions </li></ul><ul><li>Guides resource allocations to parts of the system needing improvement </li></ul><ul><li>Enhances the interface between design and operations. </li></ul>
  18. 18. Reliability Block Diagram (RBD) <ul><li>A Reliability Block Diagram (RBD) performs the system reliability and availability analyses on large and complex systems using block diagrams to show network relationships. </li></ul><ul><li>The structure of the reliability block diagram defines the logical interaction of failures within a system that are required to sustain system operation. </li></ul>
  19. 19. Parallel Connection (RBD) <ul><li>The rational course of a RBD stems from an input node located at the left side of the diagram. </li></ul><ul><li>The input node flows to arrangements of series or parallel blocks that conclude to the output node at the right side of the diagram. A diagram should only contain one input and one output node. </li></ul><ul><li>The RBD system is connected by a parallel or series configuration. </li></ul><ul><li>A parallel connection is used to show redundancy and is joined by multiple links or paths from the Start Node to the End Node. </li></ul>
  20. 20. Series Connection (RBD) <ul><li>A series connection is joined by one continuous link from the Start Node to the End Node. </li></ul><ul><li>A reliability block diagram (RBD) is a drawing and calculation tool used to model complex systems. </li></ul><ul><li>An RBD is a series of images (blocks) representing portions of a system. </li></ul><ul><li>Once the images (blocks) are configured properly and image data is provided, the failure rate, MTBF, reliability, and availability of the system can be calculated. </li></ul><ul><li>As the configuration of the diagram changes, the calculation results also change. </li></ul>
  21. 21. Sample RBD for Wind Turbine Farm
  22. 22. Fault Tree Analysis <ul><li>Fault tree analysis (FTA) is a failure analysis in which an undesired state of a system is analyzed using boolean logic to combine a series of lower-level events. This analysis method is mainly used in the field of safety engineering to quantitatively determine the probability of a safety hazard. </li></ul><ul><li>The Fault Tree Interface provides various ways to examine system performance measures (MTBF, availability, downtime, reliability, failure probability, and cost). </li></ul>
  23. 23. Sample Fault Tree Analysis using Pro-Opta Toolset
  24. 24. Industry Interactions <ul><li>Sandia interacts with AWEA and UWIG that are interested in exchanging information and have both formed O&M working groups. These groups share experiences and explore issues related to wind turbine Operation and maintenance including: </li></ul><ul><ul><li>O&M of turbine and other plant components </li></ul></ul><ul><ul><li>Warranty and service contracts </li></ul></ul><ul><ul><li>Plant technician training </li></ul></ul><ul><ul><li>Condition monitoring and predictive maintenance </li></ul></ul><ul><ul><li>Operational issues </li></ul></ul>
  25. 25. Conclusions and Recommendations <ul><li>Wind turbines are getting bigger with time, in size and rated power, and this is reflected in their design. </li></ul><ul><li>In general, industry estimates show that failure rates of wind turbines decrease with time. </li></ul><ul><li>In general, literature is consistent in their conclusions about the lack availability of data, the multiple methods of data collection. </li></ul>
  26. 26. Future for System Reliability <ul><li>Already Started </li></ul><ul><ul><li>Reliability database and systems analysis (Sandia) </li></ul></ul><ul><ul><li>Gearbox Reliability Collaborative (NREL) </li></ul></ul><ul><li>Continuing and Future Collaborations </li></ul><ul><ul><li>Design Standards and Bearing Rating </li></ul></ul><ul><ul><li>Blade Reliability Collaborative </li></ul></ul><ul><ul><li>Operations and Safety Research </li></ul></ul><ul><ul><li>Reliability Centered Wind Plant Health Monitoring </li></ul></ul>
  27. 27. Thank you