C3.ai DTI energy research led by Principal Investigator Qianwen Xu of the KTH Royal Institute of Technology in Stockholm, Sweden, has resulted in the development of AI algorithms to prevent power grid failure when electrification is increasingly supplied by variable sources like solar and wind.

“Wind power and solar radiation are not consistent from hour to hour,” says Xu. “And demand for charging EVs is based on people’s personal needs and habits. So, you have a high level of stochastics and uncertainties. Their integration will lead to voltage fluctuations, deviations and even voltage security violation challenges.” The new open-source deep reinforced learning (DRL) algorithms are designed to solve this challenge.

The open-source software package is published in GitHub.

Read the full TechXplore story: “Researchers design open-source AI algorithms to protect power grid from fluctuations caused by renewables and EVs.”

See the IEEE Transactions on Sustainable Energy research paper: “Data Driven Decentralized Control of Inverter based Renewable Energy Sources using Safe Guaranteed Multi-Agent Deep Reinforcement Learning.”

Photo by David Callahan, KTH Royal Institute of Technology