A Risk-Based Framework for Retail Electricity Rate Forecasting
Author URLs
Document Type
Article
Publication Date
9-14-2026
Subject: LCSH
Energy consumption--Forecasting
Disciplines
Electrical and Computer Engineering
Abstract
The expanding scale of utility capital investment, combined with increasing volatility in market-based pricing mechanisms, presents material challenges for retail electricity rate forecasting. This white paper examines retail electricity rate forecasting through the revenue-requirement framework and the Rate Forecast Volatility and Governance Index (RFVGI).
The white paper presents an integrated scoring framework for quantifying retail rate forecast volatility. The RFVGI evaluates the principal technical, market, regulatory, and load-related factors affecting retail electricity rate forecasts, aggregating four standardized dimensions into a composite index applicable across both cost-of-service and market-based pricing mechanisms. The quantitative assessment incorporates capital program execution risk, commodity and weather exposure, cost-recovery and regulatory mechanism design, and load-forecast uncertainty and volumetric risk as the primary scoring dimensions.
The analysis applies these four RFVGI dimensions across five case studies. The results indicate that identical composite index values can arise from fundamentally distinct underlying risk architectures, isolating the principal driver of volatility specific to each case. The analysis further establishes the significance of regulatory treatment, cost-recovery mechanism design, and rate-base recovery in determining the allocation of forecast error and financial risk between shareholders and ratepayers. In addition, this document evaluates probabilistic load forecasting, securitization, and capacity-market risk assessment as complementary methodologies for retail rate forecasting and regulatory analysis.
Repository Citation
Mohammadi, Fazel; Aghajani, Zahra; and Saif, Mehrdad, "A Risk-Based Framework for Retail Electricity Rate Forecasting" (2026). Electrical & Computer Engineering and Computer Science Faculty Publications. 141.
https://digitalcommons.newhaven.edu/electricalcomputerengineering-facpubs/141
Publisher Citation
GridERP Inc., “A Risk-Based Framework for Retail Electricity Rate Forecasting,” September 2026.
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