The coronavirus (COVID-19) could alter who needs reliable energy — and when — and place new importance on residential microgrids.
While it’s too soon to gauge energy trends after society emerges from isolation, short-term indicators may offer clues.
For one, we’re seeing what it means when a significant portion of the US population makes home their workplace.
Before COVID-19, about 5 million people, or 3.6% of the workforce, worked from home, according to Global Workplace Analytics’ analysis of 2018 American Community Service (ACS) data.
Now with as many as 56% of workers operating from home, skeptical employers are forced to test the approach. Kate Lister, president of the analytics firm, believes many will see the advantages and continue the practice.
How many will keep working from home after COVID-19?
“Our prediction is that the longer people are required to work at home, the greater the adoption we will see when the dust settles. We believe, based on historical trends, that those who were working remotely before the pandemic, will increase their frequency after they are allowed to return to their offices,” Lister said.
She estimates that work-at-home employees could grow from 3.6% to 25-30% of the workforce within the next two years.
This could shift the energy landscape meaningfully, given that Lister estimates a home-based worker adds 3,000 kWh per year to household electricity use, a significant uptick. The average annual consumption for a US household is about 11,000 kWh.
Innowatts, which provides AMI-enabled predictive analytics for the power industry, offers some additional insight.
The company’s data science team noted a 6-8% daily increase in residential demand due to COVID-19 isolation practices and a 25% drop in energy use by commercial buildings.
“The full impact of these shifts is yet to be determined,” wrote Siddhartha Sachdeva, founder & CEO at Innowatts on LinkedIn. “It’s a scenario new to all of us…”
Reports from grid operators also suggest that the large influx of home workers are reconfiguring electric demand patterns.