Investments in energy efficiency and distributed generation reduce electric utility retail sales. Since electric utilities have historically collected a large portion of revenues from volumetric energy rates, such reductions in sales can impact the utility’s ability to sufficiently recover non-production costs.
Regulatory mechanisms that “decouple” utility revenues from sales are intended to help make the utility indifferent to energy efficiency and distributed generation by ensuring the utility is able to collect an allowed level of revenue each year regardless of its sales. However, noticeable and consistent surcharges over time may create the perception of an incorrectly designed or implemented decoupling mechanism.
We are pleased to announce the release of a technical brief, entitled The Distribution of U.S. Electric Utility Revenue Decoupling Rate Impacts from 2005 to 2017, exploring annual retail rate adjustments from electric utility revenue decoupling. To determine the size of retail rate adjustments associated with decoupling mechanisms and whether they have a tendency towards bill surcharges or credits, we analyzed a large dataset of historical annual decoupling rate adjustments for 21 electric utilities in 11 states between 2005 and 2017.
We found that decoupling mechanisms adjusted rates, both up and down, between rate cases, and the majority of those adjustments (54 percent) were small (within a range of -1 to 1 percent).
However, we also found that 64 percent of the rate adjustment observations in our sample showed a positive rate adjustment. Importantly, once a surcharge was applied, there was an 86 percent chance that there would be a surcharge in the next year as well.
Two possible conclusions may be drawn about revenue decoupling mechanisms. First, they are working as intended to collect additional revenue from customers in order to counteract the impacts of energy efficiency and distributed generation on retail sales. Second, the revenue decoupling mechanisms themselves, or underlying forecasting practices, may be poorly designed or incorrectly implemented. While our analysis did not seek to understand the root causes for such results, some possible factors include the accuracy of revenue requirement forecasts, emerging structural changes in customer use and production of energy, misaligned financial motivation, and other factors that influence sales (e.g., economic recession).
The technical brief is available at: https://emp.lbl.gov/
We appreciate the support of U.S. Department of Energy’s Grid Modernization Initiative through funding from both the Electricity Resilience Division in the Office of Electricity and the Solar Energy Technologies Office in the Office of Energy Efficiency and Renewable Energy in making this work possible.