June 25, 2019
The company revealed that addressing climate change will require adding renewable energy wherever possible, and making decisions that have an impact beyond our walls.
Google (NASDAQ: GOOGL) announced that it is the first organisation of its magnitude to achieve 100% renewable energy two years running.
“Our first priority is to use as little energy as possible, operating our offices and facilities sustainably, with a strong focus on our data centres,” said Neha Palmer, Director, Operations, Energy and Location Strategy, Google.
“Thanks to advances in artificial intelligence and chip design, our data centres are seven times more energy efficient today than they were five years ago.
“Our latest Environmental Report shows that computing using centralized cloud services is up to 85 percent more efficient than using on-premises servers, which is good news for our users and the planet.”
Google added that its main strategy involves entering into long-term contracts, called Power Purchase Agreements (PPAs), to buy electricity from wind or solar farms built near our facilities.
In 2018, Google’s energy purchasing kept pace with its demand because of its PPA-driven projects—including three wind farms in Scandinavia, dozens of massive wind turbines in Oklahoma, and more than 120,000 solar panels in the Netherlands, the company revealed.
Also last year, Google had announced its intention to power its operations entirely with carbon-free energy 365 days a year.
To bridge the gap between intermittent renewable resources and the constant demands of the digital economy, Google revealed that it will have to test new business models, deploy new technologies, and advocate for new policies.
In the Netherlands, Google joined several companies to buy energy as a consortium.
“We hope our approach to cross-company energy purchasing will serve as a useful model for smaller companies interested in banding together to realize the cost savings that come with large renewable energy deals,” added Palmer.
“We’ve also started using machine learning to make wind production in the central U.S. more predictable and valuable, improving the business case for deploying more of it.”