Combining AI With Renewable Energy Can Offset Challenges

Comrent is providing solutions for mission-critical power testing infrastructure.

How AI Can Help Change the Renewable Landscape

Right now, the world is advancing technology at lightning-fast speeds. Yet, while there have been great strides in renewable energy and battery energy storage systems (BESS) technology, the United States’ aging power grid has been the biggest obstacle to fully realizing the potential of renewables.

However, industries across the globe have been turning to artificial intelligence (AI) technology to help fill the gaps left by a lack of innovation and slow-moving political climates. Using big data and predictive models, AI in renewable energy systems can help limit energy waste, forecast high-demand energy needs, and improve maintenance and worker safety.

Data Centers Already See the Benefits of AI

Google’s DeepMind AI system has already proven how machine learning can be used to enhance energy efficiency. Over the years, Google has invested heavily in renewable energy sources to power its data centers. DeepMind’s machine learning reduced their overall cooling by 40 percent, leading to a 15 percent reduction in power usage effectiveness (PUE) overhead.

This is just one way companies use AI to manage their energy usage, and results like these are promising. Ultimately, similar AI machine learning programs should allow utility supervisors to predict renewable energy output better and improve battery operation.

How AI Can Help Renewable Energy Systems

It's no secret that the U.S. utility industry desperately needs modernization. Unfortunately, the U.S. continues to lag behind Europe regarding renewables. While the U.S. and Europe have nearly halved their coal-fired electricity generation since 2007, the U.S. has largely replaced that with natural gas. In contrast, the E.U. has replaced it with solar and wind generation.

Unfortunately, the U.S. energy grid is not set up to accommodate large-scale renewable energy. In addition, the variable nature of renewables makes them unpredictable, challenging utility operators tasked with distributing energy region-to-region. Through machine learning, AI can use similar predictive models now available in data centers, manufacturing, and finance to better manage the unpredictability of renewable-connected electrical grids.

Better Predictive Models

In 2019, Google began applying its DeepMind machine learning algorithms to 700 megawatts of wind power in the central U.S. Using a combination of weather patterns and historical turbine data, Google could predict wind power output by 36 hours, allowing operators to power the grid a day in advance.

The wind industry is not the only one that can benefit from AI. Using an AI-driven approach, utility operators can also better manage the intermittent nature of solar energy. Since traditional inverters have difficulty handling unsteady outputs, AI renewable energy models can help operators predict spikes and drops in power common with solar energy. From there, operators can make appropriate adjustments to prevent equipment burn-outs and deploy energy when and where needed.

Combining AI with renewable energy can provide real-time data modeling of weather patterns to help solar and wind facilities optimize for future demand needs, assure the reliability of distributed energy resources (DERs), and reduce operational costs, increasing ROI.

Improved Safety and Efficiency for Energy Workers

Wind farms are already using drones to assist in turbine and blade repairs, which require workers to work over 200 feet above the ground. AI technology can automate robotic assistants to take on more complex jobs, putting workers at higher risk of injury.

From an efficiency standpoint, AI and machine learning can better predict when grid maintenance will be needed, deploying repairs crews proactively to perform critical repairs. AI can also alert customers to upcoming grid maintenance that may cause power cuts in their area.

The experts at Comrent use the latest technology and load testing equipment backed by over 25 years of experience testing critical power systems. After a complimentary consultation, we’ll determine the best solutions for your system’s needs, providing expert guidance and quality testing of every component. Contact us today to get started.

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