Written by: Joaquin Acuna
Image credit: smartDataTM Enterprises https://dkk4qeqny48s0.cloudfront.net/wp-content/uploads/2023/05/EV.jpg
In recent years, a significant contribution to reducing greenhouse gas emissions from the transport industry has been an uptrend in the use of electrical vehicles (EVs), which produce no tailpipe emissions and have a much higher energy efficiency than gas-powered alternatives. A significant concern in the widespread use of EVs, however, is the stress placed on the electrical grid when charging the vehicles, as well as the fact that often the electricity used to charge them is produced by burning fossil fuels.
In the past few years, companies have found an unlikely ally to address these concerns: artificial intelligence. With smart charging, by utilizing AI-powered algorithms that optimize different aspects of charging EVs, stress on the grid is avoided by charging at low-demand times. Even more importantly, users can choose to charge their vehicles when intermittent renewable energies such as solar and wind power are abundant, therefore reducing their carbon footprint. At a large scale—for example companies charging a fleet of vehicles—and for consumers with time-of-use plans, which charge more for energy at peak demand times, utilizing this technology can also significantly reduce energy costs.
The next time you hear someone ask, isn’t charging your electric vehicle burning fossil fuels anyway, so it’s the same as a gas-powered car? First, tell them it’s not (electric vehicles are more energy efficient), but then share with them the good news that by utilizing AI, you can now make sure your vehicle is charged when renewable energies are abundant—plus, you’re also helping not place stress on the energy grid at peak times!
Sources: https://www.epa.gov/greenvehicles/electric-vehicle-myths
https://www.iea.org/reports/global-ev-outlook-2024/trends-in-electric-cars
https://www.bluwave-ai.com/about