Why Edge Computing and AI May Be Key To Renewable Energy Adoption

May 25, 2023

In our rapidly evolving energy landscape, accompanied by escalating environmental concerns, incorporating renewable energy sources into our power grid is a significant challenge. One solution may lie in edge computing, powered by artificial intelligence (AI). Here’s why:

Power grids, the largest man-made structures globally, necessitate a delicate balance between electricity supply and demand. This balance has always been a complex task, even with centralized, large-scale power plants.

However, energy sources are shifting. Wind and solar power are gaining traction, sometimes supplying energy when it isn’t needed. The rise of electric vehicles could exacerbate demand and unpredictability. Furthermore, these vehicles might eventually serve as batteries during peak demand periods.

Moreover, the growing popularity of rooftop solar power signifies a future where energy sources are decentralized. This change complicates the prediction of precisely when and how much power to generate.

Why Does Edge Computing Matter?

Edge computing brings computing resources closer to where they are needed. As this IEEE Innovation at Work article explains, a significant amount of data processing that seems to occur on your smartphone or connected device is actually done in a data center. This process implies data must travel to the cloud and back, which takes time. Edge computing addresses this by placing a network of distributed computing resources next to where decisions are made.

“Edge computing can make the integration of renewables in the electricity grid more effective,” said IEEE Member Mauricio Salles. “It can enable better monitoring and control, including real-time, and the generated data can be processed and analyzed locally in real-time to reduce the traffic of data. With this data, it is possible to improve grid stability, enhance predictive maintenance and optimize energy management.”

How AI Helps

AI advancements offer new ways to make optimal decisions in a computationally efficient manner, said IEEE Member Kyri Baker.

This optimization isn’t just for grid stability – although that’s a substantial benefit.

“The power grid has an increasing number of sensors and therefore measurements which are currently under-utilized in grid planning and operation,” Baker said. “With AI, we can more effectively use this data to make decisions, predictions and forecasts.”

The December 2022 edition of IEEE Electrification Magazine, the article, “Bringing Artificial Intelligence to the Grid Edge,” provides an example, highlighting that “the estimated 185 million utility poles in the United States can reduce the tens of millions of dollars spent each year by utilities to manually track and maintain grid infrastructure.”

Efficiency, Resiliency and Cybersecurity

Baker notes that electricity traveling over long distances incurs minor losses. These losses can be mitigated when power is generated closer to demand.

“Fewer losses result in improved energy efficiency, and often, in carbon emission reductions,” Baker said. “And being able to process that data more locally can result in less reliance on communication systems or cloud-based computing, making the system more robust overall.”

Learn more: Want to see scholarly research on climate change all in one place? Check out the IEEE Xplore Climate Change Collection.