Drift is a young company founded in 2014 that aims to be similar disruptive like Uber was to the taxi business. Drift employs Machine Learning and Artificial Intelligence as well as High Frequency Trading to compete with the traditional utilities.
Drift operates a peer-to-peer marketplace that lets residential, business, and commercial customers buy power directly from local solar, wind, hydroelectric, and large commercial buildings. The company promises customers savings of 10 percent or more compared to traditional utilities. Customers also have the option of picking from low-emission sources or cheaper power options, depending on their priorities.
Drift uses Artificial intelligence and Machine learning to determine how much energy will be needed the next day. . They build a daily 24-hour supply-demand curve based on the sources in their network. The company uses everything from internet search terms, local events, business hours, age of infrastructure, building types, social media, etc. as data sources that can reveal correlations with how power is going to be used in the next day or hour. Drift’s computers then use those correlations to construct 24-hour curves on both the supply and demand side. As the firm grows and gets more data it will be able to predict further out.
Energy costs are determined, in part, by energy forecasts. Forecasts are influenced by ever-changing factors, from weather to the relative costs of different energy sources. Drift has developed sophisticated algorithms and complex models, statistics, and code to create more accurate forecasts. This increased accuracy means the Drift clients aren’t paying for inaccurately overpriced energy.
It will be interesting to see the degree to which customers embrace Drift’s approach to buying electricity. The ultimate test will be whether the company can deliver considerable energy cost savings. If it can, Drift could be the next disruptive technology to influence rapidly changing power markets