By Michelle Froese, Senior Editor
Windpower Engineering & Development
Wind technicians face hazards every time they climb atop a wind turbine. Techs must contend with heights, high voltage, overhead and rotating equipment, and exposure to unforgiving weather. Such challenges may be unpreventable, but digitalization (think IoT-connected software and virtual reality) is changing how often techs must climb uptower and how they train to do so. The result: a safer industry.
There’s much data to support the digitalization of wind farms through monitoring software and the internet of things (IoT). IoT lets equipment connect and communicate (such as one wind turbine to another), or remotely (a wind farm to a distant control center). When combined with predictive monitoring software with real-time access, such intelligence can significantly increase the generation capacity of a wind farm.
Typically, advanced control software and remote connections are promoted for their production value. You’ve likely heard of GE’s Digital Wind Farm, which lets wind owners and operators collect and analyze asset and site-level data in real time, thanks to intelligent, cloud-based software. GE says its system can increase energy production by as much as 20%, which translates to many millions in extra revenue over the lifetime of a wind turbine.
While there’s great value in increasing the levelized cost of energy for a project, and that is likely every wind-farm owner’s goal, a little mentioned but important benefit of digitalization is the increased safety for wind technicians.
Prior to the digital era, when a turbine component began to fail or production from the turbine slowly degraded, a wind tech would climb uptower to investigate why. Now, software can tell what component is causing the problem (sometimes before it becomes one), and how to fix it. This may save time uptower, or possibly an entire trip uptower if the problem can be solved remotely. Of course, the less time a technician spends climbing up and down a wind turbine, the more safety risks he or she mitigates.
Advancements in digital software are affecting all stages of a wind farm’s lifecycle. For example, GE says that by using its digital program during the design stage of a wind project, engineers can mix and match up to 20 different turbine configurations to ensure they build the ideal wind turbines for the farm, based on its location, weather conditions, and so on. A better design should lead to a more effective turbine that experiences less downtime — and less downtime means fewer unscheduled O&M checks.
Although wind techs must be protected from the risk of falling when they work at heights of six feet or greater, according to the Occupational Safety and Health Administration’s construction industry’s fall-protection standard (and four feet by general industry standards), every climb uptower presents a risk.
Risk comes many ways. One is in variations in the design of turbine towers between models and manufacturers. Such differences may include the shape and size of ladder rungs, and interior nacelle space and height (which may force a tech to crouch down or work on his or knees). Certain tasks that techs perform require prolonged kneeling, followed by climbing down a vertical ladder. Industry approved fall-protection equipment (when fitted and applied properly) certainly mitigates many risks but slips and strains are still possible, even with the best gear.
In 2015, researchers at the University of Wisconsin-Milwaukee examined factors that contribute to climbers falling from fixed industrial ladders. Strains, sprains, falls, and even fatalities were reported as a possible consequence of climbing and working at heights in the construction and wind-power industries, but could be prevented.
For example, the researchers found that a ladder with limited foot (or toe) clearance increased a climber’s slip risks by about six times compared to unrestricted clearance. A technician’s hand and feet responses after a ladder fall can also affect fall severity. In addition, the study found that descending a ladder is a more hazardous task than ascending a ladder.
To better predict and prevent potential workplace hazards two Minnesota-based companies are teaming up to develop a platform that lets safety gear connect and communication through the IoT. The aim is to provide workers, such as wind techs, intelligent safety gear that facilitates immediate, remote communication between safety professionals and workers.
“Advancements in sensor technologies and IoT ecosystems have opened the door to obtaining real-time data at the point of safety –- the worker. Safety happens in real time, and the data we use to prevent injuries should also be the same,” says Ted Smith, CEO of Corvex.
The IoT company is working with safety gear manufacturer, Ergodyne, to develop the Personal Protective Equipment (PPE) platform, which will provide near instant data to and from workers relating to safety and risk management. This is important because jobsite injury rates over the past several years have remained fairly stagnant.
“For the past three years, we have been actively exploring opportunities to take our products to the next level: from inert to intelligent and connected. We see it as the next logical step in our somewhat utopian-sounding, but very real mission of driving toward zero workplace injuries,” explains Tom Votel, president and CEO of Ergodyne.
An IoT-connected safety platform allows insight and analysis of safety conditions in real time, so that management can make appropriate decisions to reduce and mitigate risk exposure or refine jobsite training.
According to Corvex, an IoT-driven PPE platform offers three benefits.
1. Worker engagement. When communication is easy and accessible, workers are more likely to report risks and safety incidences. Increased worker engagement also leads to improved safety measures, finds Corvex.
2. Proactive decision-making. Connected safety environments can provide key risk indicators on a 24/7 basis, so hazards can be identified and eliminated more quickly. A better understanding of a site, can also lead to predictive data management that may prevent injuries and incidents before they occur.
3. Enhanced safety analytics. Typically, safety data is lagging and only sometimes reported by site workers. An IoT-connected platform allows for more accurate metrics, which should lead to better safety management and training.
Corvex and Ergodyne’s IoT-driven platform is still in the works but the companies believe that a measurable safety strategy is the best way to improve workplace safety and productivity. “We’re still in the early stages, but already working diligently on building connected intelligent safety solutions that are pretty exciting,” says Votel. “At the same time, we’re aware that this exciting leap forward needs to be grounded in real world applications…so stay tuned.”
While little replaces the data or experience gained from an onsite wind-farm visit, another method the wind industry is testing to enhance the training of wind technicians is virtual reality or VR. Fife College in Scotland recently unveiled an Immersive Hybrid Reality (iHR) laboratory, which provides VR training environments for offshore wind turbine technicians. The system lets students conduct detailed fault-finding inspections atop a virtual 7-MW offshore wind turbine, modeled after ORE Catapult’s Levenmouth Demonstration Turbine.
Students using VR systems are placed virtually at the turbine site and able to “see” the life-like surroundings, including their own hands and feet. They can also select from virtual tools or the manuals necessary to diagnose and repair the turbine — which is set over 110 m above the water. The realistic site conditions are combined with the sounds of the wind and changing weather conditions. According to Fife College, the system provides one of the most realistic training environments for wind technicians anywhere in the world.
“It is important that we continue to develop a workforce that is properly skilled and one that is familiar with new technologies and innovative practices that lead the way,” said Shirley-Anne Somerville, Minister for Further Education, Higher Education and Science, in a press statement. “It will no doubt be the skills and confidence of our workforce that help us build a stronger economy going forward and it is therefore right that we continue to invest in projects like this.”
The iHR system was developed by the Energy Skills Partnership, Heriot-Watt University, and visualization specialists at Animmersion UK, in partnership with the Offshore Renewable Energy Catapult. The first phase of the system is a top-of-turbine inspection and phase two, which is currently under development, will let students inspect the internal workings of the turbine to locate potential component failures.
Reducing unscheduled downtime
The more software developers and machine-learning experts refine their wind-farm O&M programs, the less time wind technicians will likely spend atop a turbine. This is because predictive analytics can diagnose a turbine problem remotely and without the need for an engineer onsite.
Earlier this year, for example, renewable developer Invenergy completed a two-part, 60-day pilot of software from NarrativeWave, an IoT software company, to optimize its fleet of wind turbines. According to Invenergy, the first use case focused on “Reducing Lost Production,” and the second on “Reducing Unscheduled Downtime” (meaning fewer trips uptower)
As part of the pilot testing, turbine experts including mechanical and electrical engineers, were asked to build analytic models and deploy them across a fleet of turbines, without the need for data scientists. Through these pilots, operators in the 24/7 Invenergy Control Center used NarrativeWave to fully automate time-consuming manual processes and accelerate return-to-service times on wind turbines and, in some cases, by more than 50%.
For example, if the temperature on a high-speed generator bearing has signaled an alarm, a control room operator would typically log into a web page and manually analyze a host variables, such as temperature, wind speed, and power production to decipher a next course of action. However, with NarrativeWave, this process is fully automated, providing the operator a recommendation in mere seconds.
Invenergy refers to such advanced software as a “self-operating” model because it lets the company automate much of its actions without outside support, such as input from an engineer. This also means that, for the most part, a wind tech need no longer visit a wind site or climb uptower to determine why a turbine is failing to produce as expected.
Although engineers and wind techs are still required for scheduled maintenance visits and repairs, one could imagine a future that’s eventually highly automated saving techs many unnecessary climbs or time uptower.