NewEnergyNews: ORIGINAL REPORTING: Achieving A Distributed Energy System Could Require A Self-Driving Grid/

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YESTERDAY

THINGS-TO-THINK-ABOUT WEDNESDAY, August 23:

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    WEEKEND VIDEOS, July 15-16:

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    Founding Editor Herman K. Trabish

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    Wednesday, February 19, 2020

    ORIGINAL REPORTING: Achieving A Distributed Energy System Could Require A Self-Driving Grid

    As utilities scramble to manage explosive DER growth, is power grid autonomy a solution? The U.S. electric grid could face hundreds of millions of distributed resource deployments in the near future. But optimizing these data points may exceed human ability.

    Herman K. Trabish, Sept. 11, 2019 (Utility Dive)

    Editor’s note: Real artificial intelligence and autonomy are still a long way off but there are some autonomous functions that can help with today’s challenges to managing an increasingly complex distribution system.

    Within a decade, there may be more distributed energy resources (DER) coming onto distribution systems than any utility control room can manage. An autonomous energy grid (AEG) could optimize those high levels of DER for the benefit of power system and DER owners, research under development by the National Renewable Energy Laboratory (NREL) shows. But if this groundbreaking system autonomy proves elusive, utilities could face voltage and frequency fluctuations, potential supply-demand imbalances or even outages, according to distribution system experts.

    NREL’s concept “is about controlling hundreds of millions of different kinds of devices in real time on a second-by-second basis," DOE Power Systems Engineering Center Director Benjamin Kroposki told Utility Dive. A successful AEG concept would require greater technical precision than autonomous driving and the Internet, the two most comparable examples in terms of data management, data analyst specialists and utility system authorities told Utility Dive. But the expected massive growth of DER makes NREL's ambition necessary, according to Kroposki.

    Residential solar installations are expected to grow approximately 8% annually through 2050. Behind-the-meter storage deployments are anticipated to hit almost 1.9 GW by 2024. Current forecasts project around 18.7 million EVs on U.S. roads in 2030. It is not unreasonable to imagine electricity customers a decade from now having up to five devices at a time — a rooftop solar system, a home battery, a smart thermostat, a smart water heater and an EV charger, said Kroposki. By that math, the 4 million customers in the San Francisco Bay area could leave PG&E with 20 million devices to manage.

    Utilities will also see rising penetrations of bulk system wind and solar generation that will create supply-demand imbalances that traditional control centers will not be able to manage simply by ramping supply up or down, he said. Instead, it will require managing demand, which could be done through DER technologies. But the sheer volume of DER could exceed a utility's ability to optimize. A comparable challenge is managing the Internet's hundreds of millions of data points, but the power system is under higher pressure to maintain precise moment-by-moment supply-demand balance and avoid any delays, he added.

    The basic element of NREL's theoretical AEG architecture is the optimization and control of a "cell," which can be a home or building energy management system and their controllable devices. Kroposki describes the AEG as "distributed cells with a hierarchical, scalable, reconfigurable and self-organizing control structure on top of them."

    The next level up may be the distribution circuit, and the level above that might be a substation, Kroposki said. "Each level's cells have parameters and constraints, like voltage, currents or system pricing, that they use to self-optimize and maximize self-optimizing at each level." Pilots are testing optimization algorithms… click here for more

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