Page 18 - North American Clean Energy January February 2018 Issue

wind power
Renewables Turn to Innovation Amid Growing Uncertainty in 2018
by Ryan Blitstein
THE RENEWABLE ENERGY SECTOR CAN COUNT ON ONE THING IN 2018:
uncertainty. e wake from last year’s proposed changes in policy and taxes by regulators and Congress, will continue to ripple across the industry—an industry already undergoing signi cant change. But in this uncertain environment, renewable energy sources are turning to innovation to stay competitive, and to continue growing their share of electricity generation.
At the center of that innovation is data. Once largely con ned to the consumer world, the internet has expanded its reach into industrial machines and equipment, over the last ve to ten years. Today’s wind turbines and solar panels are out tted with dozens
of sensors. Data generated from those sensors can now be transmitted over an ever- faster wireless spectrum, and housed in cheap cloud storage. Combined with additional data from a number of other sources, this information helps owners and operators of renewables achieve greater transparency, reliability, and energy production.
In the Midwest, one eet operator had a wind turbine reporting it was unavailable to produce energy because there was no wind. Initially, the site supervisor had no reason to doubt the turbine’s declared status. Turbines within the same park can be spread across acres of land, which means that each turbine experiences di erent weather conditions that a ect wind speeds. Upon further investigation of this particular turbine, however, and when geospatial data was layered on top of the turbine data, something appeared o .
e turbine that reported no wind was next to another turbine that was producing energy. e culprit turned out to be a miscalibrated anemometer on the turbine. An anemometer measures wind speed - this single error prevented the turbine’s control system from allowing it to produce energy.
e service provider didn’t spot the problem, likely because the data was located in separate, disparate systems. Integrating di erent sources of data together allows for more accuracy, which gives the owner of the turbine more transparency and control. at capability alone has the potential to lead to better operations, and more energy production. It also allows operators to independently con rm that the machine is performing to its potential.
While data can better describe what’s happening today, it can also predict what will happen tomorrow. By combining the massive amounts of information from machines with data science models, operators can see predictions of a component failure before it happens. Having more time and exibility allows the repair to be made when the sun isn’t shining or the wind isn’t blowing. is signi cantly increases energy production and savings, while decreasing downtime.
Beyond increase energy production, data helps increase the reliability and predictability of intermittent energy sources, weakening the argument that wide scale adoption is not possible. When utilities know that they can count on this renewable wind energy, they don’t have to re up as many coal or gas plants to maintain base load energy levels. Greater reliability also leads to more pro table power purchasing agreements for renewable energy sources.
ese changes have provided opportunities for renewable energy that, even a few years ago, seemed out of reach. Across the United States, energy utilities have received
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