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RPS Model Methodology. Arne Olson, Partner Doug Allen, Consultant. Contents. Updates to Previous 33% Implementation Analysis Resource Potential, Cost, and Performance Portfolio Selection Methodology. Updates to Previous 33% Implementation Analysis.
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RPS Model Methodology Arne Olson, Partner Doug Allen, Consultant
Contents • Updates to Previous 33% Implementation Analysis • Resource Potential, Cost, and Performance • Portfolio Selection Methodology
33% RPS Implementation Analysis was focused on informing state RPS policy Key tasks: Develop “plausible scenarios” for achieving 33% by 2020 Estimate the net ratepayer costs associated with each plausible scenario Highlight key obstacles to reaching the 33% goal, including the need for new transmission and the integration costs of new resources The current analysis is focused on informing state RPS planning Key tasks: Develop “plausible scenarios” for achieving 33% by 2020 Estimate year-by-year resource build-outs under each alternative scenario Feed information into LTPP proceeding to inform the Commission’s decisions regarding fossil procurement Current Analysis Compared to 2009 Implementation Analysis
Weaknesses of Previous 33% Implementation Study • New transmission is assumed for most projects • No way to determine which projects could get built without new lines • Renewable projects are selected in aggregated “bundles” and could not be selected individually • Crude methodology for addressing potential out-of-state REC resources (“Out-of-State Early”, “Out-of-State Late”) • Did not look at operational impacts of renewables at such high levels of penetration • Integration costs for intermittent resources based on a rule of thumb • Lack of transparency in handling of short-listed CPUC projects • Project viability ratings not very scientific
Key Improvements in Portfolio Development Methodology • Improved handling of transmission requirements for new renewable resources • Allows some resource to be delivered over existing transmission or with minor upgrades • Allows individual selection of Non-CREZ resources • Incorporation of unbundled REC resources • Can now model out-of-state REC-only resources as well as out-of-state CREZs • Incorporation of “Discounted Core” of commercial projects • Projects in advanced stage of permitting and development
Other Updates to Analysis • Improved detail on Commercial projects in CPUC ED Database • CREZ assignments • 2009 solicitations • Confidential projects either aggregated or excluded to improve transparency • New Aspen environmental scores • Updated resource list based on RETI Phase 2B analysis • Updated RPS Net Short based on: • 2009 IEPR Load Forecast • New load decrements for EE and CHP calculated by CPUC • Existing renewable resources from 2008 Net System Power Report
General Approach • Determine renewable resource gap (GWh) in 2020 • Compile database of resources available to meet RPS target • Rank available resources based on cost, commercial interest, environmental sensitivity and timeline • Select resources to fill renewable resource gap
Determining Demand for Renewables • Demand for renewables in California is based on 2020 RPS target, equal to 33% of eligible retail sales • 2020 retail sales based on CEC 2009 IEPR load forecast • Excludes retail sales by small LSEs (<200 GWh/yr) • Estimate quantity of renewable resources online in base year • Used renewable resource “claims” from CEC 2008 Net System Power Report • Added new resources online in 2009 based on ED Database • RPS resource gap is the difference between the 2020 target and the 2009 renewables claims
Sources of New Resources to Fill Resource Gap • Commercial Projects • ED Database of IOU projects • POU procurement plan data obtained from CARB • Additional “Theoretical” Projects • RETI pre-identified and proxy projects for California • WREZ projects for the rest of the WECC • Original Renewable DG resource potential estimates • Developed as part of 2010 LTPP
Updated ED Database • Analysis incorporates the latest ED Database, including 2009 IOU solicitations • Contracted projects are included individually • Shortlisted projects are aggregated by resource type and zone in cases where there are at least three such projects to preserve confidentiality (otherwise they are left out) • Distribution of projects among zones has changed since previous analysis
Treatment of Commercial Projects • Commercial projects are divided into two categories: • Discounted Core: Project has obtained or has made significant progress towards obtaining a permit • Non-Discounted Core: Project has made limited progress towards obtaining a permit • Discounted Core projects are given first priority in the resource selection sorts, reflecting their high probability of development • Non-Discounted Core projects are given priority over generic resources but are not guaranteed development • POU planned resources treated as Non-Discounted core
POU Resources • E3 has included POU resource procurement plans in the development of the resource portfolios based on CEC data • POU resources are included as Non-Discounted Core commercial resources
RETI Phase 2B Database • The updated RETI Phase 2B Database contains site-specific information for renewable resource potential, cost, and performance in California • Out-of-state resources from the WREZ Transmission Model have been incorporated with the RETI data • WREZ estimates of potential represent high-quality remote renewable resources that would require significant transmission upgrades to reach load centers
Out of State Renewable Resource Data from E3 Models • E3 maintains a database of renewable resource cost and performance data in the West • Wind and solar data based on NREL GIS modeling • Geothermal and hydro data from EIA • Biomass aggregated from various sources • Additional resource data for BC and Alberta • Used to supplement WREZ data for out-of-state resources (Montana, Colorado, BC, Alberta)
Estimates of Statewide DG Potential • As part of the 2010 LTPP, E3 and Black & Veatch collaborated to develop original estimates of the statewide potential of solar PV • The RPS model integrates these estimates, allowing it to evaluate the viability of the development of these resources
Resource Cost and Performance • E3 used site-specific data on resource cost and performance where available (RETI and WREZ projects) • Generic assumptions were developed for resources without specific information based on averages of the RETI data (shown below)
Transmission and Geographic Classification of Resources • Each resource is assigned one of three classifications • CREZ: resources located within one of the 48 Competitive Renewable Energy Zones (either in California or in other states) • Non-CREZ: resources in California or directly across the border that are not located within a CREZ and can be delivered with minor transmission upgrades • Out-of-State REC: out-of-state resources that would deliver energy to the local market
Transmission Bundles • Resources in CREZs are aggregated into transmission bundles in the following order: • Existing transmission bundle • Minor upgrade bundle • New transmission bundle • Discounted core projects given first priority to fill each transmission bundle • Non-core Commercial projects given next priority to fill the New Transmission bundle • Any remaining transmission capacity in the bundle is allocated to the lowest-scoring generic projects • Up to 3000 MW of new transmission allowed for each CREZ
Out-of-State REC Resources • Out-of-State RECs previously included in two “zones” (“Out-of-State Early” and “Out-of-State Late”) • New model can select REC resources individually • Assume physical limitations on wind integration for each region • REC resources priced at long-run “Green Premium” or Cost minus Value • REC resources optimized for access to transmission, not for resource quality – RECs are allowed for average quality resources, not best sites • Pricing based on long-run cost, not REC market price forecast (analogous to in-state resources) • No pricing distinction between different types of RECs (bundled vs. unbundled, with or without delivery requirement)
Unbundled Out-of-State REC-Only Transaction • Pure REC transaction with no energy purchase requirement and no delivery requirement • Developer sells energy at Mid-C • California LSE purchases REC from developer at LCOE minus Mid-C price • Separately, California LSE arranges for energy transaction from CAISO market to load • California LSE never owns energy • No incremental imports to California Mid-C Market Leg 1: Developer to Mid-C Leg 2: CAISO to load
Out-of-State REC with Delivery Requirement • REC transaction with energy purchase requirement and delivery requirement • California LSE purchases energy and REC from developer at LCOE of wind facility and sells energy at Mid-C • Separately, California LSE arranges for energy transaction from CAISO market to load • California LSE rebundles REC with transaction from Mid-C to CAISO that would have occurred anyway! • No incremental imports to California Mid-C Market Leg 1: CA utility to Mid-C Leg 3: Mid-C to CAISO Leg 2: CAISO to load
Pricing of Out-of-State REC vs. In-State Resource • In-State Resource priced at LCOE, ratepayer impact is cost relative to market value or “Green Premium” • Out-of-State REC priced directly at “Green Premium” • Energy and capacity values vary by market (higher in California) • Pricing is the same for all flavors of RECs Example of In-State vs. REC-only Pricing
Initially, wind displaces gas resources More wind reduces market prices and raises integration costs Value decreases significantly as wind displaces baseload Physical Limits on Out-of-State REC Supply There is a practical limit to how much intermittent energy each zone can easily accept Market Value of Wind Energy $/MWh MW of Intermittent Renewables
Initially, wind displaces gas resources More wind reduces market prices and raises integration costs Value decreases significantly as wind displaces baseload Physical Limits on Out-of-State REC Supply There is a practical limit to how much intermittent energy each zone can easily accept Market Value of Wind Energy $/MWh E3 limited the REC supply based on a simplified representation MW of Intermittent Renewables
Limits on Wind Penetration Total limit on wind in region Wind available to California 1,700 MW 850 MW 2,211 MW 808 MW • Ability to easily absorb wind is limited to load served with flexible generation • E3 estimated hourly flexible generation in each zone: • Load – Nuclear – Coal – Base Hydro + Export Transmission Capacity • Wind limit is min value • Other regions also have RPS requirements – assume CA can soak up 50% of each region’s limit 738 MW 404 MW 6,461 MW 2,257 MW 1,231 MW 461 MW 229 MW 47 MW 0 MW 0 MW 3,665 MW 1,371 MW 13,745 MW 3,968 MW 1,939 MW 2,135 MW 947 MW
Resource Selection Methodology • Calculate project score for each resource • Allocate lowest-scoring out-of-state theoretical projects to other states until all non-CA WECC RPS targets for 2020 are satisfied • Rank remaining CREZ projects and select to fill transmission bundles • Calculate aggregate score for each transmission bundle • Rank transmission bundles against individual non-CREZ and REC resources • Select resources and bundles to meet 33% RPS target in 2020
Detailed Portolio Development Potential CREZ Resources Potential Non-CREZ and REC Resources Resources Selected for Local Use Resource Sort for Local Use Resources Remaining After Local Sort Resources Remaining After Local Sort Resource Sort for Existing Tx Resource Sort for CA Use as RECs Resources Remaining After Existing Tx Sort Resources on Existing Transmission Resource Sort for New Tx Non-CREZ and REC Resource Rankings New Transmission Bundles Resource Sort for CA Use Towards RPS Resources Selected for CA RPS Portfolio
Project Scoring Methodology • Each project is scored on a 0-100 scale based on four metrics (0 is better): • Net Cost • Environmental Score • Commercial Interest Score • Timing Score • Final score for each project is a weighted average of the four individual metrics • Weights are user-defined and vary by scenario
Net Cost Score • Cost score is based on a modified version of the RETI Ranking Cost • Includes integration and T&D avoided costs • Scores are converted to 0 – 100 scale, bounded by the model’s lowest and highest net cost resources Modified RETI Ranking Cost +Levelized cost of energy + Interconnection (gen-tie) costs + Deemed integration costs + Levelized, per-MWh incremental transmission costs – T&D avoided costs – Energy value – Capacity value = Final project ranking cost
Environmental Score • Handicaps resources in areas where environmental issues might hinder development • Considers a variety of factors: • Disturbed lands • Right-of-Way • Significant species • Air quality • Others • Scores for each resource in each CREZ on 0-100 scale
Commercial and Timing Scores • Commercial Score: Scale of 0-100 reflecting contracting activity of California utilities • Commercial projects receive a score of 0, while generic projects receive a score of 100 • POU-planned projects considered “Commercial” and receive score of 0 • Timing Score: Gives better score to resources that can be developed on a relatively short time scale • Online date < 2010 gets 0, > 2021 gets 100 • For ED database projects, online dates filed with the applications • For other resources, dates based on size and type of project
Selection of RPS Portfolio • Each transmission bundle is assigned an aggregate score based on an average of the constituent resources and compared against individual non-CREZ and RECs resources • Discounted Core Projects are selected first unless in New Transmission bundle • After Discounted Core, resources & bundles with the lowest score are selected to fill the 2020 RPS gap