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Using Prices, Automation, and Data to Shape Electricity Demand and Integrate Renewables into the Grid

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  • Wietelman, Derek

    (Resources for the Future)

  • Palmer, Karen

    (Resources for the Future)

  • Wichman, Casey

    (Resources for the Future)

Abstract

To realize the ambitious clean electricity goals of many states and the Biden administration, variable renewable energy sources will need to be effectively integrated into the electric grid. This report presents a summary of an online workshop convened by Resources for the Future (RFF) in December 2021. RFF convened a group of economists, industry officials, policymakers, data aggregators, and regulators to discuss the role that time-varying pricing, device automation, and high-frequency data can play in shaping electricity demand and aiding renewables integration effort. Existing regulatory, technological, and economic barriers have hindered progress in these efforts. These barriers include regulatory inertia, fears of retail bill volatility, and potentially less-effective rebates for reducing peak consumption. Recent research provides reason for optimism, however, as consumers appear to be cognizant of prices and willing to cede control of some types of electricity consumption to automated processes. Advances in machine learning may also help utilities effectively evaluate the consumption impact of different types of electricity rates. Moving forward, there are ample opportunities for researchers to partner with smart thermostat and other smart device companies, nonprofits, and data aggregators for insights on effective strategies to engage flexible demand from the vast amount of high-frequency consumption data made possible by smart meters.

Suggested Citation

  • Wietelman, Derek & Palmer, Karen & Wichman, Casey, 2022. "Using Prices, Automation, and Data to Shape Electricity Demand and Integrate Renewables into the Grid," RFF Reports 22-03, Resources for the Future.
  • Handle: RePEc:rff:report:rp-22-03
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    File URL: https://www.rff.org/documents/3346/Report_22-03.pdf
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