CPUC RPS Calculator Work

The purpose of this post is to summarize Black & Veatch’s recent and ongoing work on the RPS Calculator for the CPUC.

Black &Veatch has worked in partnership with the team at E3 to develop an energy and economic model to evaluate multiple scenarios for reaching a 50 percent Renewable Portfolio Standard for California.

California utilities are well on their way to achieving the 33 percent RPS target that was first established by state laws in 2002.  See the table below showing an overview of renewable energy procurement status in California.

Renewable Procurement Status Percentages
Actual RPS Procurement Percentages in 2013 Percentage of RPS Procurement Currently Under Contract for 2020
PG&E  23.8 %  31.3%
SCE 21.6% 23.5%
SDG&E 23.6% 38.8%

The RPS calculator is an economic model, with a geospatial component, developed under contract with the CPUC.  The model has been used to track and monitor progress towards the state’s renewable energy goals, and to evaluate the feasibility of achieving a higher level – a 50 percent RPS target.  The model was developed and significant scenario analysis completed, before the 50 percent target was signed into law.

Black & Veatch’s scope of work has consisted of many different analyses, including developing a geospatial dataset to quantify and characterize the renewable energy resource potential in California, and throughout the WECC.

The renewable energy resource potential dataset consists of about 2,000 entries, each row representing a renewable energy resource, with the following characteristics identified for each resource:

  • Technology (solar, wind, bioenergy, hydro, geothermal, energy storage)
  • Location (point or polygon)
  • Vintage (existing, contracted “under development”, or future “proxy” project)
  • Product content category (1, 2, 3 see content category definitions here)
  • Size (MW)
  • Electrical Resource Area (Super CREZ – expanded competitive renewable energy zone)
    • This is a rough estimate of transmission infrastructure for each area
  • Annual energy (MWh)
  • Capital cost ($)
  • Interconnection cost ($)
  • O&M cost ($/yr)
  • PPA price (if available – $/MWh)

Once complete, this dataset has been modified, by changing the criteria for resource inclusion, to represent different scenarios. Scenarios are differentiated by the following key variables:

  • Geography: In-state renewable energy procurement only, vs. WECC-wide renewable energy procurement
  • Land use: broadest definition of “developable land” vs. more restrictive definitions of “developable land”
  • Transmission upgrade costs: all renewable resources required to achieve “Fully Deliverable Capacity” status, vs. some resources procured with “Energy Only” status
    • Need for specific transmission upgrades reviewed in more detail (West of Devers for example – see map)
  • Electric load growth: high vs. low future load growth scenarios
  • Others (see User’s Guide for more detail)

The purpose of the RPS calculator scenario analysis is to address the following questions:

  • Is it technically feasible for the state of California to meet a 50 percent renewable energy target by 2030?
  • How close are we now?  How much more renewable energy do we need (renewable net short)?
  • Is it possible to estimate the costs and benefits of different scenarios for reaching the 50 percent renewable energy target?
  • Can we evaluate how significant the cost impacts will be, to ratepayers overall?
  • By evaluating a range of scenarios, can we identify the key drivers for cost impacts, thereby anticipating and minimizing the cost impacts to ratepayers?
  • What is the optimal portfolio of resources to minimize cost impacts, and maximize environmental benefit?

While the economic portfolio selection algorithm was designed by partner firm E3, there is a significant amount of pre-processing which is done by Black & Veatch.. Analyses completed by Black & Veatch include the following:

  • Identification of geospatial resource “zones,” based on multiple selection criteria:
    • Resource availability: geospatial screening for wind speeds, solar irradiance, bioenergy feedstock availability, geothermal resource potential
    • Technical constraints: geospatial screening for land characteristics (slope, access to infrastructure)
    • Land use and planning designations (geospatial screening for RETI category 1, category 2, and other designations for example DRECP categories, San Joaquin Valley Least Conflict Solar study categories)
  • Estimation of location-specific capital costs for a variety of technologies, including changes over time from present day to 2030
  • Estimation of location-specific annual energy production profiles for each resource
  • Estimation of location-specific  interconnection costs based on project technology, size, and access to infrastructure
  • High level guidance on strategic directions of model development and public/stakeholder engagement

RPS calculator materials, including the Excel model, the user’s guide, Energy division staff papers and ALJ rulings, can be found online here.

See slide deck from latest public workshop here.  Slides 11-37 highlight the most recent land use updates.

GIS data can be viewed on Databasin here.  (To be updated with version 6.2 materials soon.)

A future project (recently announced CEC grant award) will focus on a smaller region, performing a more detailed evaluation of land use impacts for a specific local government, yet-to-be-disclosed.  Potential focus areas under consideration include the following: LA County, City of Lancaster, City of Palmdale, Santa Barbara County, EBMUD.  CEC is particularly interested in selecting an area that has experienced tension surrounding the land-use implications of converting protected agricultural lands to different land use designations for solar development.  The kickoff for this future project is currently scheduled for July 2016.

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