This page lists unified modeling input datasets and scenarios used by Energy Division to model the electric and gas system, typically in support of the Resource Adequacy (RA) and Integrated Resource Plan (IRP) proceedings.  In 2019, Energy Division conducted a comprehensive data update to what was posted for 2018.  Energy Division expects to post periodic updates every one or two calendar years, depending on the needs of CPUC proceedings.

Modeling Input Datasets 

The production cost model used by Energy Division is the SERVM model developed by Astrape Consulting. The fundamental inputs and datasets are described and available for download below, and supersedes the generalized descriptions of the setup and data development for the SERVM model that were described in the most recent version of the Unified RA and IRP Inputs and Assumptions - Guidance for Production Cost Modeling and Network Reliability Studies document found under the "IRP Modeling and Analytics" section of the Energy Resource Modeling Projects page.

Representation of the WECC-wide Transmission System by Regions

For modeling purposes, the Balancing Authority Areas (BAAs) of WECC are aggregated and grouped into 24 total regions, 8 inside California and 16 external to California. The regions are mapped to actual BAAs in this workbook: Master Region Lookup.  This workbook also includes region mapping for the RESOLVE model used in the IRP proceeding. 

For areas outside the CAISO footprint, a region in the SERVM model generally represents a Balancing Authority Area (or a large portion of a BAA) within the Western Interconnect (referred to as the "WECC" area for short). In contrast, the CAISO footprint is modeled as four regions (to model potential congestion between these regions): PG&E Valley, PG&E Bay, SCE, and SDG&E.

The modeled transmission capability and hurdle rates (with and without carbon adders) between each region are tabulated in this workbook:

Transmission Flow Limits and Hurdle Rates in SERVM (Revised 11-6-19)

The carbon adder refers to the low carbon price forecast from the CEC's 2019 IEPR Preliminary GHG Allowance Price Projections and converted to 2016 $ per MWh.

Simultaneous flow limits for specific transmission interfaces were developed from the annually updated WECC Path Rating Catalog.

Hydro Resources in SERVM

1998 to 2017 Hydro Inputs (Revised 10-4-19)  

Hourly Electricity Consumption Profiles used by SERVM

Normalized Consumption Profiles by Region in SERVM (updated 2-21-20)

The normalized consumption profiles are grouped by which day of week is January 1.  Depending on which year is being studied in SERVM, e.g. 2030 starts on Tuesday, the appropriate normalized consumption profile group should be used to maintain day of week alignment with demand-side modifier profiles (which are directly derived from the CEC's IEPR demand forecast hourly data).

Within SERVM, the selected normalized consumption profiles are scaled/stretched to match the forecasted peak and annual consumption by region, provided in the following file.

CEC 2018 IEPR Electric Demand Forecast Components Used by SERVM  

Peak and Annual Consumption by Region in SERVM summarizes the 2018 annual IEPR peak demand and total energy forecast that is used to develop consumption profiles in SERVM.  This format is easier to trace back to source IEPR demand forecast data than the Hourly Profile data provided above.

Peak and Annual Consumption by Region in SERVM

Hourly Electricity Demand Modifier Profiles used by SERVM

The Demand-side Modifier Profiles in SERVM (updated 2-21-20) (normalized to SERVM's allowed range of hourly values for "R" Unit Type) is paired with the Annual IEPR Demand Modifier Forecasts (specifies annual "capmax").  For each demand-side modifier resource, SERVM uses the "capmax" to scale the corresponding normalized demand-side modifier profile such that the annual energy of the resultant profile is consistent with the corresponding load modifier in the CEC 2018 IEPR demand forecast. 

CEC 2019 IEPR Electric Demand Forecast Components Used by SERVM

Annual Summary of IEPR component used in SERVM summarizes annually each element of the 2019 IEPR demand forecast that is used to develop consumption and demand modifier profiles in SERVM

Peak and Annual Consumption by Region in SERVM Peak electric demand and total energy forecasts from 2019 IEPR Update. 

Baseline Generator Unit List

Baseline Generator Unit List for SERVM and RESOLVE used in TPP studies (updated 2-8-21)

Baseline Generator Unit List for SERVM and RESOLVE used in TPP studies (updated 2-9-21)

Baseline Generator Unit List used in 2021 PSP modeling and TPP Modeling (updated 9-20-21)

Data Field Definitions All Units  

These lists itemize all baseline generator units in the SERVM and RESOLVE models. The data field definitions files explain each field.

Baseline resources are those generating units assumed to be fixed as a capacity expansion model (RESOLVE) input, whereas candidate resources are selected by the capacity expansion simulation and are incremental to the baseline.  Baseline resources are all existing and online resources, plus LSE-owned or contracted resources that are still under development and not yet online. Projects without approved contracts are not considered part of the baseline.  Specific mandated resource procurement is also considered baseline, e.g. achievement of the AB 2514 storage target.  Only announced or policy-driven (e.g. State Water Board Once-Through-Cooling policy compliance) retirements are accounted for.

Baseline Generic Battery Storage Details

Only existing online baseline battery storage has nameplate MW values captured in the Baseline Generator Unit List above.  Generic baseline storage is itemized in the list but no nameplate MW values are provided because these units are not online yet.  For details including the assumed annual nameplate MW of baseline generic battery storage, see the Baseline Battery Storage Dataset page.

Conventional Unit Technology Operating Parameters for RESOLVE   

Technology Operating Parameters for RESOLVE (Revised 11-6-19)

The Technology Operating Parameters for RESOLVE file above identifies for each conventional thermal resource type, operational parameters that are used by the model to determine dispatch, including heat rate, ramp rate, start times, etc.  These parameters are weighted class averages derived from confidential individual unit operating parameters that SERVM uses.

Total Demand Response Unit List for Reference System Portfolio Proposed Decision  

Demand Response resources in SERVM (updated 2-21-20)

This file captures supply-side demand response programs (assumed to participate in the CAISO market and/or dispatched to meet system needs).  "Load-modifying demand response" programs are separately counted as a component of the electric demand forecast.  Both baselines and total demand response resources are included in this file.  Total means inclusive of the demand response selected by the RESOLVE model for the Reference System Portfolio published on 2-21-20.  Use the Unit Modifier column in the Monthly tab to filter on baseline or total.

Total Resources Unit List for Reference System Portfolio Proposed Decision, including separation into Baseline and New

SERVM Total Unit List for RSP Proposed Decision with baseline and new resources identified(updated 3-3-20)  

This file itemizes all units modeled in SERVM for the Reference System Portfolio in the Proposed Decision published on 02-21-2020.  It includes baseline plus RESOLVE-selected units.  The file contains three tabs, one for each study year examined in SERVM, 2022, 2026, and 2030.  The region the unit serves load to, the unit name, the unit category, and the installed capacity are provided in the file.  The "Cover" tab of this file provides further explanation of the content and includes an explanation of how to separate baseline resources from new (RESOLVE-selected) resources.

CAISO REC Contract Assumptions Used by RESOLVE

CAISO REC contracts supplemental list

Most renewables generating units or projects located in the CAISO area serve CAISO load and their RECs accrue to an entity within CAISO.  However, there are some projects where the unit is located and balanced within CAISO, but the RECs accrue to an entity outside CAISO.  Likewise, there are some projects that are located and balanced outside CAISO but the RECs accrue to an entity within CAISO.  Tracking this information is needed to correctly represent RPS and GHG emissions compliance within the CAISO and is primarily used by RESOLVE to model RPS compliance within California.  The CAISO REC contracts supplemental list workbook linked above provides the necessary information.

Intermittent Generation Profiles Used by SERVM  

Solar SERVM Hourly Profiles Revised 8-23-19

Wind SERVM Hourly Profiles Revised 8-23-19

SERVM Wind Hourly Profiles Revised 7-24-20

Weather Name Lookup Location Revised 8-23-19

Each zip file above contains hourly electricity production in MW for intermittent generators (wind and solar) modeled by SERVM. The data has these attributes:

  • MW outputs are normalized to a generator with a maximum output of 100 MW.
  • The field "Weather Name" identifies a weather year, a location (i.e. weather station), and a technology type (e.g. fixed-tilt solar or tracking solar).  The weather stations included cover most solar and wind resource potential in the WECC area.
  • Each row represents one hour of MW output in a year corresponding to weather from each year of 1998 through 2017. There are 20 x 8760 rows per "Weather Name". In leap years, the last day of the year is truncated so all years are 8760 hours in length.
  • Ignore the field "Randomize Profiles" - it is a required field by SERVM but not used in Energy Division's implementation.

Fuel and Carbon Prices

Burner-Tip Fuel Price Curves used in SERVM and RESOLVE are modeled using 2016 dollars.  Prices are derived from the CEC's April 2019 NAMGas model found at the CEC's Natural Gas Burner Tip Prices webpage.

Carbon allowance prices used in modeling are derived from the CEC's 2019 IEPR Preliminary GHG Allowance Price Projections.

Energy Division uses Dollar deflators for adjusting price data in nominal dollars into real dollars.  All modeling uses 2016 dollars.