The second annual 2012 Wind Plant Reliability Benchmark was just published on October 1st by Sandia National Laboratories, the results of which will give the rapidly growing wind industry in the US an important wind power benchmark, allowing for an accurate understanding of its performance and the best ways to improve productivity.
There hasn’t been, until now, a way for the owners and operators of wind farms to objectively compare their farms’ productivity with the productivity of similar farms. In order to do this, in 2010, the DOE commissioned Sandia to create a database, the Continuous Reliability Enhancement for Wind, or CREW. It’s the first time a comprehensive, ‘operator-independent’ dataset has been created to accurately portray the performance of the US wind fleet, creating a benchmark for the reliability of US wind farms and identification of the major causes of downtime and failures.
For this year’s report, there were more than 800 wind turbines studied, producing electricity, or able to do so, 97% of the time, that’s up considerably since 2011, when it was 94.8%.
The DOE/Sandia National Laboratories press release continues:
In 2008, a DOE collaborative published “20% Wind Energy by 2030.” The report suggests that by 2030, wind could supply 20 percent of the nation’s electricity, compared to less than 1 percent in 2007 and 3 percent in 2011. The report also discussed industry-wide risks related to lower-than-expected reliability and growing costs of operations and maintenance.
“Our assignment from DOE is to objectively characterize the national fleet,” said Valerie Peters, CREW lead reliability analyst. “We’re looking across technologies, locations and companies to create benchmarking statistics for the entire U.S. wind turbine fleet.”
Major turbine systems include a set of three blades, rotor, shaft, generator and gearbox, and all of those components might break or otherwise need maintenance. Sandia’s team is working to determine which components are the most vulnerable and help industry address those concerns to prevent downtime. The costs associated with a turbine going offline add up quickly. The owner not only loses productivity, but the cost of hiring a crane for repairs can be upward of $250,000. Since only a few cranes in the nation are large enough to handle turbine heights and component weights, it may be months before the turbine is up and running again.
Four wind plant owner/operators are participating in the development phase of the CREW project: EDF Renewable Energy (formerly enXco Service Corporation), ShellWind Energy, Wind Capital Group and Xcel Energy. The CREW team taps into turbines’ existing Supervisory Control and Data Acquisition (SCADA) industrial control systems, and Sandia researchers are able to collect high-resolution data from key operating parameters such as wind speed, ambient temperatures, blade angles, component temperatures and torques. Every few seconds, a wind turbine’s SCADA system captures a complete picture of how the turbine and its components are performing, compared to a defined operating environment.
Each plant is providing SCADA data to Sandia through a software tool developed by Strategic Power Systems (SPS). SPS developed the automated data collection software originally to collect high-volume data from steam and gas turbines. SPS reengineered its Operational Reliability Analysis Program, or ORAP®, tool to ORAPWind®, which collects data from wind turbines and creates detailed event logs for all non-operating time, in addition to daily summaries of operating time.
Sandia’s CREW database contains data for more than 800 turbines, which have generated two terabytes of raw data, about 20 percent as large as the entire print collection of the Library of Congress. Sandia’s Enterprise Database Administration Team is processing this enormous dataset into a usable database that can readily support a wide range of rapid queries.
All of this gathered data is being used for a variety of different analyses — this includes the annual public benchmark reporting and various DOE reports. One of the main uses that the DOE has for the data is to help to direct future research towards the most effective paths and to identify good development investments.
“We’re excited about the results so far and look forward to the next few years as we make an important contribution to our industry to improve reliability through a component-level focus,” Ogilvie said. “It’s an important project that will help encourage increased use of a low-carbon power source, and it could not have succeeded without the outstanding support and leadership of the wind industry and DOE. Together we can share our expertise to help shape the future of the nation’s wind energy generation.”