As America's energy demand continues to grow, meeting the energy needs of the future requires maintaining existing infrastructure and integrating renewable energy sources such as wind, solar, and hydropower, which are expected to supply 44% of U.S. power by 2050. Meanwhile, parts of the existing grid are old and starting to fail. But power companies may not know there is a problem with their equipment until it fails.

Researchers at the U.S. Department of Energy’s Argonne National Laboratory are stepping in to address this need. Working closely with power companies across the energy sector, from aging hydropower plants to massive solar installations, they are transforming energy grid maintenance through cutting-edge Artificial Intelligence (AI) technology, helping U.S. power companies identify and address problems before they occur.

Argonne’s AI-enabled software predicts grid component failures by analyzing data from existing sensors across the grid. This predictive model forecasts wear and tear, allowing for timely repairs and replacements. "Companies want to know the health of their assets," says Feng Qiu, head of Argonne’s Advanced Grid Modeling group. "Our models can tell them the useful remaining time of their equipment—how many years, months, and weeks it has left."

This allows power companies to proactively identify potential issues and schedule just-in-time maintenance, saving time and money. In one project on solar inverters, AI models reduced maintenance costs by 43-56%, unnecessary crew visits by 60-66%, and increased profit by 3-4%.

The benefits of this research extend far beyond cost savings and efficiency gains. By minimizing downtime and addressing maintenance issues before they escalate, energy providers can enhance grid reliability and resilience, crucial factors in an era of increasing energy demand and an evolving energy landscape.

Shijia Zhao, an Energy Systems Scientist at Argonne, said collaboration between Argonne and industry partners, including power companies and academic institutions like Wayne State University and Iowa State University, has been pivotal. "Together, we're driving positive change and shaping the future of energy grid maintenance," said Zhao.

This is just one of the ways Argonne is tackling today's grid challenges. By harnessing the power of artificial intelligence and real-world data, energy providers using prognostics-based maintenance technology can maximize the lifespan of existing infrastructure, minimize downtime, and ensure a reliable energy supply for generations to come. With continued innovation and collaboration, the future of energy grid maintenance looks brighter than ever before.

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