The Future of Energy Innovation Is In Smart Algorithms

A new type of energy-focused startup has emerged recently focused on innovation around smart algorithms. These companies are using information analytics — in much the same way that the web giants like Amazon (s AMZN), Google (s GOOG) and Netflix (s NFLX) do — to mine information and use it to help reduce energy consumption in buildings. Call them Energy 2.0 or the next-generation of energy data innovators, these companies and tools could help provide a low cost way to deliver energy efficiency.
For example, as I describe in an article at GigaOM Pro today (sub. req’d), five-year-old Efficiency 2.0 has developed algorithms around an energy reduction recommendation service that it sells to utilities. Its service uses publicly available data, like real estate info and income data, to make highly personalized and targeted energy efficiency recommendations to utility customers. Efficiency 2.0’s CEO Thomas Scaramellino thinks of his service as the of energy.
EcoFactor, a smart thermostat software maker, also uses publicly available info, like weather data and real estate data, to shave off energy use via connected thermostats. Zensi, a startup recently bought by Belkin, uses algorithms similar to facial recognition software, to listen to the voltage noise of appliances in a home.
Regen Energy, a Toronto-based startup, has developed a wireless node that uses algorithms based on “swarm logic” — in which each individual makes a decision based on the actions of the group — to reduce energy consumption of HVAC systems in commercial buildings. The idea is if energy-consuming devices in buildings were made to act like a swarm of bees, a school of fish or a flock of birds, it could significantly cut energy consumption.
The potential business opportunity is massive, and when utilities invest billions of dollars into smart grid infrastructure over the next 5 years they will be overwhelmed with the amount of energy information that is unleashed. These energy info innovators will be crucial to helping utilities make sense of the data, and help them reach their energy efficiency targets. To read my entire analysis go check out my article on GigaOM Pro, and come to Green:Net today to learn more about the intersection of algorithms and energy.
Read the full article here.
Image courtesy of woodleywonderworks photostream.