Unified RA and IRP Modeling Datasets   

This page lists unified modeling input datasets and scenarios used by Energy Division to model the electric and gas system.  The datasets are fundamental inputs to Energy Division modeling and other analytical work products.

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.  The detailed setup and data development for the SERVM model is 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.

Regional Breakdown of WECC for modeling purposes

For modeling purposes, the BAAs of WECC are aggregated and grouped into 24 total regions, 8 inside California and 16 external to California. A list of those regions is below.  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 (due to the need to understand potential congestion between these regions): PG&E Valley, PG&E Bay, SCE, and SDG&E. Multiple modeling inputs correspond to a particular region.

SERVM Region

Description

California Regions

IID

Imperial Irrigation District

LADWP

Los Angeles Department of Water and Power, Burbank, Glendale

PGE_Bay

Pacific Gas & Electric (Greater Bay Area)

PGE_Valley

Pacific Gas & Electric (Valley)

SCE

Southern California Edison, Valley Electric Association

SDGE

San Diego Gas & Electric

SMUD

Balancing Authority of Northern California

TID

Turlock Irrigation District

Non-California Regions

AZPS

Arizona Public Service Co

BCHA_AESO

British Columbia Hydro Authority, Alberta Electric System Operator

BPAT

Bonneville Power Adminstration, Avista Corporation, Chelan County PUD, Douglas County PUD, Grant County PUD, Puget Sound Energy, Seattle City Light, Tacoma Power

CFE

Comision Federal de Electricidad

IPCO

Idaho Power Co

NEVP

Nevada Power Co, Sierra Pacific Power

NWMT_WAUW

Northwestern Energy, WAPA Upper Wyoming

PACE

Pacificorp East

PACW

Pacificorp West

PNM_EPE

Public Service Co of New Mexico, El Paso Electric Co

PortlandGE

Portland General Electric Co

PSCO

Public Service Co of Colorado

SRP

Salt River Project

TEPC

Tuscon Electric Power Co

WACM

WAPA Colorado Missouri

WALC

WAPA Lower Colorado

 

Hourly Electricity Consumption Shapes  

Each shape file below contains hourly load in MW for a particular study (target) year. Columns correspond to each of 24 regions modeled in SERVM. Rows correspond to hours of the year for 35 weather years, i.e. 35 different versions of the study year, each version based on weather from one of the historical years 1980 through 2014. Each of the 35 versions of a particular study year are scaled and stretched to match that study year’s annual peak and energy consumption levels as forecasted by the California Energy Commission (CEC)'s adopted Integrated Energy Policy Report (IEPR).
Each year uses the 1990 calendar, meaning the first day of the year is a Monday, and all holidays and weekends correspond to 1990 dates. These hourly shapes were generated using a weather normalization process described in the Unified RA and IRP Inputs and Assumptions document referenced above.

Load profiles based on the 2017 IEPR demand forecast:

·         Annual Peak and Total Consumption values used in SERVM (5-1-2018)

·         Load Shapes for 2019 Study Year (5-1-2018)

·         Load Shapes for 2022 Study Year (5-1-2018)

·         Load Shapes for 2026 Study Year (5-1-2018)

·         Load Shapes for 2030 Study Year (5-1-2018)

 50% RPS Default and 42 MMT Core portfolios from 2017-18 IRP Reference System Plan

 The files below are workbooks that map the aggregated resource types in the IRP’s RESOLVE model to available unit-level information for porting to full production cost models. Unit-level information is generally available for CAISO area baseline resources and coarse geographic information is associated with new (generic) resources and non-CAISO area resources.

 The file below is a workbook that maps resources in the RESOLVE model with the 2017 IEPR demand forecast, to available unit-level information for porting to full production cost models. New (generic) resources are based on a rerun of the RESOLVE 42 MMT case using the 2017 IEPR. This workbook includes additional analysis mapping and comparing the assumed units in the RESOLVE model to the assumed units in the SERVM model and describes differences.
• Coming soon: [RESOLVE 42 MMT with 2017 IEPR compared to SERVM units]

Transmission-level Busbar Information for use in the 2018-19 TPP

The allocation of new renewables included in the RESOLVE model's 50% RPS Default Core case and 42 MMT Core case to busbar are provided by the CEC's siting department.  That information is linked here: CEC Proof-of-Concept to Allocate Selected Renewables to Specific Locations.

For the purpose of mapping to busbar, the locations of energy storage procured to date are provided here: Combined IOU Storage Procurement 2017 Update Public

Guidance on allocating other resource types to busbar is provided in the most recent version of the Unified RA and IRP Inputs and Assumptions document found under the “IRP Modeling and Analytics” section of the Energy Resource Modeling Projects page.

Intermittent Generation Profiles

Each link file below contains hourly electricity production in MW for the intermittent generators assumed to be operating in the target study year, by region in the SERVM model.  Generators that are not online in any given study year will have 0 production in each hour.

Each row represents one generator and generators are grouped together by region.  Each tab represents one historical weather year from 1980 through 2014 normalized to the average of all years.  [Note: these are very large files and the range of historical weather years are separated into two files to manage file size.]

Coming soon:

  • Intermittent generation profiles for 2019 Study Year (5-xx-2018)
  • Intermittent generation profiles for 2022 Study Year (5-xx-2018)
  • Intermittent generation profiles for 2026 Study Year (5-xx-2018)
  • Intermittent generation profiles for 2030 Study Year (5-xx-2018)  

 Other WECC-wide datasets

The files linked below include other important assumptions and inputs typically needed for modeling the WECC area with hourly detail in a production cost modeling environment.

 

 

   


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