Image: Platforms Ellen and Elly offshore near Long Beach, Calif. Credit: US Bureau of Safety and Environmental Enforcement | Flickr.
ABS Group works with offshore oil and gas companies to deliver analytics services that help answer operational questions with the data those companies collect. The Houston-based solutions provider also works in the project certification phase for offshore wind to help developers identify and mitigate risk. ABS Group Vice President of Power Business Development Tom Adams believes that the company can leverage its experience in risk mitigation for offshore wind and its work with offshore oil and gas analytics to bring big data analytics to the operational phase of offshore wind projects.
"Our involvement in offshore wind in this particular area is early days - it's something of great interest to us and we think a growing focus and priority for the offshore wind industry globally," Adams said. "There are several drivers that lead us to believe that a high level of sophistication and analytical 'horse power' will be needed."
One of the main drivers he sees in the latest large-scale offshore wind projects is the very aggressive cost that the developers are bidding for their power.
"We see that on the front end on the capital investments side and the EPC phase, which we're more heavily involved in these days as a project certification service provider," he said.
The cost of building offshore wind farms is coming down tremendously as the scale of new projects has grown. Those costs are moving very aggressively through all parts of the supply chain, and ABS Group sees the same cost pressures and aggressive targets translating to the O&M phase of projects as well.
"Anything that can help achieve those targets or make them more certain to be achieved is going to be in demand," Adams said.
Srikanta Mishra, Ph.D., Institute Fellow and chief scientist for energy at Battelle, believes the application of data analytics in three specific areas of offshore oil and gas environments — forecasting, equipment performance and predictive maintenance — is "readily translated" to offshore wind energy.
In terms of forecasting, Mishra said, offshore wind farm operators would be interested in making predictions of weather, temperature or precipitation, for example, together with inputs such as wind speed and wind direction.
"You can learn from the past and build models that can say with some degree of accuracy what is going to be the wind speed and direction in the next hour and the next 24 hours," he said. "Those can be important inputs with respect to how the grid accepts what is coming from the wind energy generator."
With respect to performance, having sensors that monitor the behavior of turbines on an individual basis, and the wind farm collectively, can be a valuable process, he said. Analysis of that data can determine the conditions in which the turbines have under-performed in the past and be applied to operations in the future.
He said that the same type of analyses can be applied for predictive maintenance of individual turbine components to identify conditions, such as pressure, temperature, wind speed, and precipitation, when equipment has failed.
Battelle works with companies to bring multiple sources of data into one easy-to-use platform that allows operators to learn from their data and then use that knowledge to make decisions. Through its Elucidata service, Battelle gives energy companies access to a large group of subject matter experts across a variety of domains.
Data management provider OSIsoft's experience working with offshore oil rigs on condition-based maintenance helped the company support Dong Energy in using data and analytics to understand how to do the maintenance that was needed on its offshore wind turbines at the right time and the lowest cost.
According to Chris Crosby, principal - global nuclear and renewable energy for OSIsoft, Dong Energy took the data that was available on its wind turbine generators and moved it into OSIsoft's scalable, open data infrastructure, called PI, to do condition-based maintenance. Dong Energy also moved that data into its asset management system so that its managers could create work orders. In addition, the company used its data to established a map that provided a visual status of the wind turbines.
Integrating its data into the three technologies allowed the wind farm managers to have a visual of what was happening in a particular wind farm, and drill down into a specific wind turbine to see the work flow status on that machine, Crosby said. Dong Energy saved 20 million euro per year as a result of that integration initiative.
According to Crosby, monitoring and understanding the health of an asset, and bringing that visually to managers within an organization, supports similar business problems, no matter the business.
source: http://www.renewableenergyworld.com
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