By Barbara Rook Contributor
A digital twin refers to a digital replica of process, system, or physical asset. For turbine manufacturers and wind-farm operators, a twin can simulate component wear and predict overall turbine health for better O&M strategies and ROI expectations.
Although relatively new to the wind industry, digital twins are generating significant buzz. The technology, which involves creating a digital copy — or “twin” — of physical assets, processes, systems, and devices, allows real-time remote monitoring that can save the wind industry significant downtime and maintenance costs while increasing production.
“Within three to five years, hundreds of millions of things will be represented by digital twins,” notes research and advisory guru Gartner, which named digital twins as one of its Top 10 Strategic Technology Trends for 2017. “Organizations will use digital twins to proactively repair and plan for equipment service, plan manufacturing processes, operate factories, predict equipment failure, or increase operational efficiency, and perform enhanced product development.”
For the wind industry, a digital twin’s value lies in using the data to understand the health condition of a wind turbine or a full fleet. The data provides valuable insight into when turbine maintenance is anticipated so operators can plan O&M well in advance.
“The digital twin will give you the remaining useful life of your components and, based on that, you can optimize your maintenance schedule to determine when to repair or replace components,” explains Xioaqin Ma, Head of Technology at ONYX Insight, which is building a digital twin of an existing offshore wind farm.
The goal, adds Brian Case, VP, Product at GE Renewable, is to convert unplanned maintenance into planned activities, thereby minimizing turbine downtime and reducing tower climbs. “We think about it in the core outcomes — increased revenue, reduced risk, and reduced cost. Having a digital wind farm with advanced analytics allows us to attack of all those,” he says.
GE Renewable claims the first digital wind farm, built in 2015, in North America. Using the company’s Predix software platform, the digital twin lets wind-farm operators collect, visualize, and analyze unit and site-level data. GE now has three test sites worldwide, where digital capabilities and advanced analytics are tested. In addition, GE’s more than 15,000 wind turbines operating under long-term agreements are optimized digitally in some capacity.
GE Energy — one of the first turbine manufacturers to digitize wind farms — says its Digital Wind Farm is a connected and adaptable wind-energy system that leverages big data and analytics, and pairs it with a reliable turbine that has a digital infrastructure. Essentially, digitalization lets wind-farm operators optimize maintenance strategies, improve turbine reliability and availability, and increase annual energy production.
In addition to improving O&M and reliability, the digital model increases annual energy production. GE’s installations have experienced increased megawatt-hour output in the 5 to 7% range, says Case.
Twin benefits A digital twin also enables low-risk “what if” scenarios to predict possible outcomes. “For example, what would happen if I increase the power rate of my turbine from 100 to 110% when the electricity price is at peak price?” asks Ma. “It’s a balance between over-running my turbine at the higher power rate to generate more electricity at a higher electricity rate.”
She adds: “This is an economic equation that digital twin will allow customers to calculate how they are going to make the most optimized decision to optimize the fleet.”
While late to adopt the technology, the wind industry has begun reaping the benefits of digital wind farms in the last few years. In fact, ONYX Insight’s second-generation digital wind farm, in development with SSE Renewable’s Greater Gabbard 504-MW offshore wind farm near England’s Southeast coast, could save up to 30% of opportunity expense (OPEX) costs, based on case studies, says Ma.
“In UK offshore, OPEX cost is split between planned and unplanned maintenance,” Ma explains. “The unplanned maintenance accounts for 65% of the whole OPEX cost; we believe we can save 30 of that 65%.”
ONYX was recently awarded the Innovate UK research grant for the Greater Gabbard project, expected to last about two years. Likewise, GE currently is commissioning an offshore installation in Europe.
Wind, meet cloud Technologies such as cloud infrastructure and data analytics make it possible to communicate and collaborate globally across time zones, explains Jeff Hojlo, Program Director, Product Innovation Strategies at International Data Corporation (IDC), a global provider of market intelligence, advisory services, and events.
Importantly, they also add a visual layer on top of the information being communicated.
“You have non-engineers or non-technical people — marketing, product management, sales, even customers — involved the early stage of asset development,” Hojlo says. “You may not want to communicate the entire model to those people. Digital twin allows sending briefcases of information selectively.”
Cloud computing makes data storage and access less costly and more accessible. “Without the cloud, how do we collect and save the data?” asks Ma. “Cloud computing makes the data computation cheap to use.”
It is also making condition-monitoring systems (CMS) easier to access and decipher. “CMS provide a lot of data. However, digital transformation allows users to quickly visualize what’s going on and pinpoint or predict the problem,” says Hojlo.
“People think that digital twin has to be an overly complex model and that’s untrue,” says Jeff Hojlo of IDC, a global provider of market intelligence. IDC’s Maturity Model explains the stages of digital twin complexity, depending on need. Digital visualization and development of products or projects (which Hojlo says should be part of a digital twin strategy) have been happening in engineering workgroups for years.
“There is often a disconnect between the design stage and O&M stage aftermarket,” says Ma, and twins are closing this gap. For example, rather than making assumptions during the design stage of a turbine (such as how loads will typically behave over 20 years), a digital twin lets operators use real-life data to predict the actual remaining life of the turbine — before it’s ever in use.
“This is where we can combine sensory data together with the design knowledge and the real engineering experience in one digital model for people to access,” says Ma.
What’s next “The starting points for using digital twins of product and assets will differ by company size, industry, and need, but the value derived by all manufacturers will be similar: clarity of communication, rapid collaboration, holistic visibility, and accurate and efficient response to demand,” says IDC’s Hojlo. He adds that the main goals are for predictive and proactive services, as well as closer collaboration with customers.
It’s important to note that a digital twin is only an enabler, points out Case. People and process transformation will be the true drivers.
“Using digital applications to predict faults and plan maintenance activities can help drive down LCOE (levelized cost of electricity), he explains. “But if we don’t change the processes of how we’re working — and how do we incorporate that advance knowledge — then it’s harder to realize the true benefits.”
Still, the potential is limitless. “We’re really in the early days of digital transformation,” he says. “We’re just scratching the surface.”
The post How digital twins are transforming wind operations appeared first on Windpower Engineering & Development.
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