NRRI paper touts AI forecasting as means to weather COVID-19 energy management demands
Forecasting through artificial Intelligence could be key to managing the ongoing COVID-19 pandemic’s effects on energy consumption, according to a new research paper published by the National Regulatory Research Institute (NRRI).
The coronavirus pandemic has impacted many areas of life, and energy management has been no expectation. Both commercial and residential segments of the economy have seen energy consumption shift, but in “How AI Forecasting Can Help Utility Regulators Weather the COVID-19 Storm,” author Siddhartha Sachdeva — founder and CEO of Innowatts — noted that machine learning-enabled predictive intelligence could be used to protect utilities from financial and operational disruption.
“Smart meters and other smart-grid infrastructure generate vast amounts of data, but unlocking insights from these huge and interconnected data sets can be challenging,” Sachdeva wrote. “That is where ML-enabled predictive intelligence shines. By using breakthrough machine learning tools to identify patterns in large data sets, it’s becoming far easier to identify actionable signals amidst the noise.”
Such technologies could also lower costs for scrambling consumers and offer regulators additional means to protect them while also assisting the larger energy sector. Efforts such as load clustering analysis, load disaggregation, and usage trends showcased AI’s ability to signal demand patterns and create effective strategies for better energy management.
“Machine learning-enabled artificial intelligence is an exciting new tool for understanding energy usage to adjust to the changing energy landscape,” NRRI Director Carl Pechman said.
