Company: SCE-PL
Filing Date: 2025-10-28
Form Type: SF-1/A
Source: 0001193125-25-253849
Chunk: 68

Company: SOUTHERN CALIFORNIA EDISON Co
Filing Date: 2025-10-28
Form: SF-1/A
Chunk 68
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1,203,042 |     |           | 1,186,318 |     |           | 1,310,287 |
| Residential Domestic (FERA)                 |     |           |    25,003 |     |           |    29,922 |     |           |    25,979 |     |           |    31,400 |     |           |    31,385 |
|                                             |     | 5,167,816 |           |     | 5,192,954 |           |     | 5,226,508 |           |     | 5,263,625 |           |     | 5,271,437 |           |

| (1) | Amounts may not recalculate due to rounding. |

Forecasting Electricity Consumption SCE forecasts retail electricity sales and also the components of retail sales – bundled customer sales, sales to customers supplied by Community Choice Aggregators (CCAs), and sales to customers supplied by Electricity Service Providers/Direct Access (ESP/DA). Sales to customers supplied by CCAs and sales to customers supplied by ESP/DA are referred to as “ Generation Departing Load”, meaning retail customers that have departed from SCE bundled service but still take transmission and distribution service from SCE. SCE develops retail electricity sales forecasts at least once a year. SCE most recently updated its retail sales forecast in December 2024 to reflect updated macroeconomic and demographic trends, electrification progress, and expected future policy impacts. This forecast included updated outlooks for distributed energy resources like solar photovoltaic, transportation electrification, data centers, and building electrification. To forecast retail electricity sales, SCE develops econometric models for the residential, commercial, industrial, government, and agricultural market segments sales. These forecasts will be used to calculate the fixed recovery charges for any given period, in order to determine the revenue required to meet the expected sinking fund schedules for the bonds. For the residential sector, electricity consumption is forecasted by geographic region, accounting for the different climate zones in SCE’s services area. The models incorporate weather variables like surface air temperature and economic indicators such as regional output to predict consumption. For non-residentialsectors, SCE also uses econometric models that relate electricity usage to economic, demographic, and other factors. These include employment in specific sectors (e.g., government, manufacturing, agriculture), economic activity, and climate indicators like the Palmer Drought Severity Index that measure relative dryness based on temperature and precipitation data. SCE’s electricity sales forecast models are