Crowley, McLeod, and Wang File Report on Methods for the Design of Custom Incentive Regulation Framework in Ontario
Categories: Performance-Based Ratemaking, Rate Design
October 14, 2025 - Nicholas Crowley, Dan McLeod, and Sherry Wang
CA Energy Consulting authored a report on behalf of the Ontario Energy Board (OEB) to evaluate a Custom Incentive Regulation (Custom IR) proposal filed by Hydro Ottawa Limited under Docket EB-2024-0115. The CA Energy Consulting report advanced a partial productivity factor to adjust Hydro Ottawa’s operation, maintenance, and administrative expenses (OM&A) and offered corrections to the proposed cost benchmarking analysis.
In Ontario, electricity distribution utilities have the option to propose a customized incentive regulation plan in lieu of adopting the OEB’s standard price cap framework. The largest distributors in the province tend to file Custom IR proposals that set capital-related revenue according to a five-year forecast while constraining OM&A-related revenues to an I-X cap. This bifurcated approach aligns with recent performance-based regulation trends in British Columbia and Massachusetts. CA Energy Consulting noted in its report that an OM&A-only revenue cap should be calibrated according to industry OM&A productivity growth, rather than Total Factor Productivity (TFP) growth. TFP growth includes capital inputs, and is therefore appropriate for calibrating a total revenue cap (or price cap), but would bias the X factor in an OM&A-only revenue cap.
Our report also reviewed Hydro Ottawa’s proposed adjustments to the results of the OEB’s electricity distribution sector cost benchmarking model. To set stretch factors for each electricity distributor, the OEB relies on an econometric cost benchmarking model that controls for certain cost drivers like system capacity and circuit miles. The model determines an estimate of each Ontario distributor’s cost by applying the utility’s actual outputs each year to coefficients estimated from a regression model. Our analysis demonstrated that no single distributor can adjust its current year data to calculate a current year estimated total cost for itself without creating a bias in the model’s estimated cost. Instead, data corrections would need to be applied for all distributors and the regression coefficients would need to be re-estimated using this updated data.
Other considerations in the report included adjustments to the proposed growth factor and comments on the company’s proposed variance accounts.
The report can be downloaded here.