With the recent development of IoT, smart meter technology, and advanced weather forecasts by machine learning, we have the ability to analyze usage and load patterns and estimate future needs to help balance the electricity grid.
In most of the industrialized world the backbone of the power grids is over 50 years old.
“The more solar there is in any given mix of ‘fuels’ used to generate electricity, the harder it is to cope with the sudden arrival of a cloud,” writes Dr. Gretchen Bakke in her bestseller book: “The Grid.” She argues that “the grid is the weakest link. It isn’t made for modern power.”
One important recent addition to the grid, however, makes all the difference and provides invaluable data in real time, down to the individual user: the smart meter.
Now, the combination of data obtained in real time and historical usage from smart meters, paired with edge serves, cloud computing, and Machine Learning, can offer new insights and forecast, if not predict, what the demand will be in specific areas of grid, down to a city block.
FULL STORY: HOME Smart Meters and AI take on Electrical Grid Load Forecasting
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City of Costa Mesa
Licking County
Barrett Planning Group LLC
HUD's Office of Policy Development and Research
Mpact Transit + Community
HUD's Office of Policy Development and Research
Tufts University, Department of Urban and Environmental Policy & Planning
City of Universal City TX
ULI Northwest Arkansas
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