Achieving net zero starts at the source.
While utilities have long been able to track these curves along the grid, the curve itself offers little information in understanding the cause. As a result, utilities’ ability to deliver the right amount of energy—both immediately and in the future—is less of an exact science and more of an educated guess. As more electric vehicles connect to the grid and more solar energy is generated, balancing supply and demand at the utility level becomes even more complex.
From my experience, legacy approaches to grid management like these will not be enough to tackle larger-scale, longer-scale initiatives. Instead, utilities want to know more details: Who is charging an EV? When are appliances running and how are they performing? Are there inefficiencies that could be fixed? How much solar energy is being generated and stored?
Using AI, utilities can build “energy profiles” for each household in its territory that categorize energy consumption by a set of characteristics, including appliance type and times of use. With these profiles, utilities can identify, isolate and target customers for load-shifting programs based on real-time insights.
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