There are many ways to generate energy: wind, solar, the grid, etc. There are also many methods of controlling and automating how, when and where energy is used. Devices like smart thermostats and smart meters also fit into the energy management formula. This all equates to a lot of data that needs to by collected and analyzed by utilities to deliver the smartest, most efficient use of energy, allowing utilities to predict, optimize, and control distributed energy resources to balance supply and demand in real time and at scale.
AutoGrid is one company that is committed to making this happen through the development of advanced management software for the energy industry. Thanks to a new equity investment from Shell Ventures LLC, AutoGrid will be able to accelerate its deployment of the AutoGrid Energy Internet Platform and AutoGrid Flex for artificial intelligence (AI)-driven predictive controls of connected, distributed and flexible energy assets in real time and at scale.
The funding comes as an extension to the Series D investment round announced in September from energy companies including CLP Group, Innogy, National Grid, Total Energy Ventures and others.
“AutoGrid has pioneered the science of flexibility management that enables energy providers to mine and extract data to balance supply and demand in real time,” says Geert van de Wouw, VP Shell Ventures. “We are pleased to join AutoGrid’s investment round and looking forward to gaining insights on how to increase productivity and value across distributed energy assets.”
“We’re proud to have one of the leading global energy companies committed to the transition towards a low-carbon future as an investor and partner,” adds Dr. Amit Narayan, AutoGrid chief executive officer. “With the support of investors such as Shell, we’re significantly advancing our mission to transform the global new energy system.”
According to information from AutoGrid, its software can give utilities the flexibility to predict and optimize the following:
- All DERs and assets
- All programs
- All customer types
- Millions of participants
- Using trillions of data points.
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