Myst AI claims that its AI energy prediction technology increases utility company reliability

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Myst AI, a startup developing a predictive energy usage platform, today closed a $ 6 million financing round. The proceeds will be used to expand Myst’s “forecast as a service” offering to attract new customers, a VentureBeat spokesperson said via email.

The pandemic has led governments to issue orders for shelters, quarantine mandates, and shop closings. With millions still locked in their homes, the shift is putting a strain not only on internet service providers, streaming platforms, and online retailers, but also on the utilities that power the country’s electrical grid. Load forecasts like Myst ‘could ensure operations will not be disrupted in the coming months, preventing blackouts and brownouts while increasing the efficiency of utilities’ internal processes after the pandemic is over.

Myst claims to combine AI techniques with “highly localized” time series data from a number of vendors, improving forecasting accuracy by 30 to 60%. The company says this means “millions of dollars” in value to its customers; Optionally, companies can use the Myst platform to create and deploy their own state-of-the-art forecast models.

Myst suggests several use cases for its short-term energy forecasting technology, including electricity demand, renewable production, and market prices. The intent is to help renewable energy investors increase solar and wind revenue by streamlining wholesale market planning. On the load handling unit side, Myst claims it will help utility companies and municipal decision-makers cut energy costs and reduce carbon emissions.

By adjusting positions in the electricity markets based on forecasts, Myst suggests, load utilities could save up to 1% on procurement costs while renewables increase their profits by more than 5%.

Giving machine learning systems responsibility for energy forecasting is not a hideous notion. In 2016, Google implemented a system developed by DeepMind that provided energy recommendations for human data center supervisors. In the company’s tests, it achieved a 40 percent reduction in energy consumption for cooling and a 15 percent reduction in overall energy use efficiency – the ratio of the building’s total energy consumption to its IT energy consumption. Carbon Relay, a Foxconn-backed company based in Boston and Washington, DC, claims to be accomplishing the same through a suite that uses data gathered from thousands of sensors to predict data center power consumption.

Beyond profitability, there is an urgent environmental need for systems like Myst’s – provided they work as promised. It is accepted science that carbon dioxide emissions contribute to climate change. CO2 molecules trap heat in the atmosphere and last for decades – 40% stay 100 years and 20% 1,000 years. If wood, coal, natural gas, oil and gasoline consumption stays on its current path, global temperature will rise between 2.5 and 10 degrees Fahrenheit over the next century, according to the Intergovernmental Panel on Climate Change (IPCC).

Myst, whose founders come from Google and Nest among others, already works with a dozen energy companies in North America and Europe, including Fortum, Enel Green Power and East Bay Community Energy. The company has competition in Urbint, a startup developing AI-powered solutions for infrastructure and security of supply; Innowatts, which provides US utilities with an automated toolkit for energy monitoring and management; and Autogrid, which works with over 50 customers in 10 countries to deliver AI-powered insights into power consumption.

But the solution from the San Francisco-based company Myst was obviously robust enough to attract investors like Valo Ventures, which led the A-round. Gradient Ventures from Google also took part.


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