Artificial Intelligence and the Decarbonization Challenge

Abstract

To help “operators estimate available capacity on the system and plan for future needs,” the European DSO uses AI to analyze data on voltage, load, and grid topology. The DSO was able to employ available and incoming distributed energy resource assets more effectively thanks to AI Similar to this, a German transmission system operator employed AI to produce more accurate grid loss forecasts. AI could be used into both new and existing advanced distribution management systems in the United States (ADMS). The ADMS conducts tasks including “fault location, peak demand management, support for microgrids and electric vehicles,” and is “the software platform that enables the full range of distribution administration and optimization.” Finally, by optimizing end uses, AI can make significant progress in lowering the demand for electricity usage. For instance, Google declared in 2015 that machine intelligence from DeepMind had helped it cut the energy needed to cool its data centers by 40%. Given that the DeepMind project has been contracted to assist in reducing waste in the UK's National Grid, further savings appear possible. More recently, in 2019, Hewlett Packard and the National Renewable Energy Laboratories collaborated to assess how AI may improve the efficiency of their data center operations. Energy efficiency is frequently referred to as the unsung hero of decarbonization because it affects numerous industries and has some of the greatest effects at the lowest prices. Increasing efficiency in many industries can also aid in lowering electricity consumption.