Topic:"Energy Efficiency Resource Assessment Model" in M12350

e also significantly lower than unit revenues in each calendar year. This is because the unit revenues are reflective of total costs of service of the four DATE FILED: June 27, 2025 Page 12 of 20 functional areas of generation, transmissio...

AI summary The text discusses the relationship between marginal generation costs and unit revenues, noting that marginal costs typically do not exceed unit revenues due to the inclusion of fixed costs. However, in 2022, marginal costs surged above average system fuel costs due to geopolitical events. The average system marginal cost increased by 14.7% from 2023 to 2024, primarily due to changes in the generation mix and increased load.

Lionel Lerner Energy Forecasting and Resource Assessments Division CALIFORNIA ENERGY COMMISSION July 17, 1996

AI summary Lionel Lerner from the Energy Forecasting and Resource Assessments Division of the California Energy Commission provided a document dated July 17, 1996, which may be relevant to energy forecasting and resource assessments.

pectively (Dahl, 1986; Dahl and Sterner, 1991). 4 The estimates of the price elasticity of demand for electricity are comparable to those for gasoline, though possibly slightly higher in the long run. Table 1 is less clear as· to whether t...

AI summary The text discusses price elasticity of electricity demand, noting that residential consumers are more sensitive to price changes in the short run, while commercial users may be more sensitive in the long run. Staff estimates from an energy demand forecasting model show elasticities below -.3, likely representing short-run values. California consumers may be less sensitive compared to the general U.S. population.

DATE REFILED: August 15, 2025 Page 6 of 20 NS Power utilized price elasticity of -0.15 applied in its SAE load forecast model from the 2024 Load Forecast Report (M11689) for the Domestic, Small General, and General rate classes. For all ot...

AI summary NS Power uses price elasticity estimates from its 2024 Load Forecast Report and a California Energy Commission report to model inefficient usage in different rate classes. A formula is provided to calculate estimated inefficient usage based on price elasticity, unit revenue, and marginal costs. The elasticity value of -0.15 was found reasonable for modeling impacts of price on energy sales. In 2024, no inefficiency occurred as unit revenue was above marginal cost.

pectively (Dahl, 1986; Dahl and Sterner, 1991). 4 The estimates of the price elasticity of demand for electricity are comparable to those for gasoline, though possibly slightly higher in the long run. Table 1 is less clear as· to whether t...

AI summary The text discusses the price elasticity of electricity demand, comparing residential, commercial, and industrial users. It notes that residential consumers are more sensitive to price changes in the short run, while commercial users may be more sensitive in the long run. Staff estimates from the energy demand forecasting model show elasticities below -.3, likely representing short-run effects.