@misc{35564,
  author = {Brian F Gerke and Marius Stübs and Samanvitha Murthy and Aditya Khandekar and Peter Cappers and Richard E Brown and Mary Ann Piette},
  title = {Potential bill impacts of dynamic electricity pricing on California utility customers},
  abstract = {<div dir="ltr"><span>The rapid growth of renewable generation is creating challenges for the California grid in the form of the “duck curve,” with increasingly steep ramping required for conventional generation resources in the morning and evening, and growing curtailment of solar resources in midday periods. Time-varying electricity tariffs have received considerable attention as a tool to address these challenges, with a renewed recent focus on the potential for dynamic tariffs that vary to reflect conditions on the grid in near-real time. Consideration of dynamic tariffs may raise concerns about the financial impact on utility customers, especially for those who have limited flexibility to modify their electricity consumption in response. Specific areas of concern include electricity bills, bill volatility, and equity implications related to cost shifting among customer groups. In this paper we leverage smart meter data for more than 400,000 California utility customers, spanning residential, commercial, industrial, and agricultural customers, to assess potential customer bill impacts arising from a multi-component dynamic tariff . Specifically, we compute impacts on customer bills and bill volatility under the assumption of fully inelastic demand, i.e., where customers do not change their consumption patterns in response to the tariff.&nbsp;We also assess various approaches designing subscription load shapes that customers can pre-purchase as a hedge that may provide a measure of protection against large negative impacts, while still incentivizing the modification of loads on the margin. We compare and contrast the relative impacts on different customer classes and discuss benefits and pitfalls of different dynamic tariff structures and subscription&nbsp;load shapes.&nbsp;</span></div><div class="yj6qo ajU">&nbsp;</div>},
  year = {2024},
  month = {01/2024},
  publisher = {Lawrence Berkeley National Laboratory},
  url = {https://escholarship.org/uc/item/2wj199mq},
  doi = {https://doi.org/10.20357/B7WK65},
  language = {eng},
}