Machine learning models can analyze extensive data to determine the best locations for geothermal drilling, reducing exploration costs. AI-powered drilling technology could make geothermal energy more ...
The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...
EPFL researchers developed optimal pitch profiles for vertical-axis wind turbines using a genetic learning algorithm. The new pitch profiles resulted in a 200% increase in turbine efficiency and a 77% ...
A new machine learning approach developed through an international collaboration between Polytechnic University of Milan and Drexel University could help architects and urban planners better predict ...
Know how AI-agents in the grid optimize peer-to-peer pricing. Learn how automated trading bots within the energy stack analyze data to create efficient, decentralized electricity markets.
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Machine learning could yield faster, cheaper lithium-ion battery development
Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could dramatically slash the cost and energy required to develop new lithium-ion ...
Digital twins, private 5G networks and federated learning help energy companies improve grid resilience, optimize distributed assets and strengthen real-time operational performance.
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