Draft Rate Scenario
Model Methodology
DAWG Forecasting Subgroup
Sept. 11, 2014
Lynn Marshall
Supply Analysis Office
Assessments Division
Lynn.marshall@energy.ca.gov / 916-654-4767
California Energy Commission
www.energy.ca.gov
Why we are here
•
•
•
•
CEC staff is developing a model for developing retail electric rate
scenarios
First application will be to support 2015 IEPR demand/supply analysis
cycle
Have not had internal tool where we could understand what’s in the
rate or driving the rate.
DAWG comments requested on
o
o
o
o
Proposed model structure
Methodology incorporating price effects
Interactions with other proceedings?
Data sources we should use?
California Energy Commission
www.energy.ca.gov
Background on Ratemaking
• Revenue Requirement = Rate Base*Rate of Return + Operating &
program costs + depreciation expense +utility incentives + taxes
• Rate Base = Capital Stock– Accumulated Depreciation+ working
cash +inventory
• Operating costs include generation, transmission, distribution
o
o
ERRA Procurement and program costs are “passed through”
GRC costs are embedded and not trued up.
Rate of Return set by CPUC – varies with economic conditions
Class Average Rate = Class Cost Allocation Share* Revenue
Requirement / Sales
Cost allocation shares based on marginal cost of serving the class for
various elements of cost of service (energy, capacity, distribution,
customer service, transmission)
• Marginal cost varies by TOU period
California Energy Commission
www.energy.ca.gov
High Level Perspective on
IOU Revenue Requirements
Example using PG&E 2015 Annual Electric True-Up and GRC Decision Tables
Component
Distribution O&M
Distribution Return and Deprec.
Generation O&M
Generation Return and Deprec.
Electric Procurement/ERRA
Total FERC Jurisdictional
Everything Else
Total
Billion $
Percent
2,215
1,932
951
1,110
5,433
1,433
814
13,889
Average
$/kwh
16% 0.0255
14% 0.0223
7% 0.0127
8% 0.0148
39% 0.0723
10% 0.0165
6% 0.0094
100% 0.1734
Source: PG&E Advice 4484-E and 2014 CPUC General Rate Case D.1408032
Decision Tables Revision 2, Appendix C.
California Energy Commission
www.energy.ca.gov
Staff criteria: what do we want in a model?
•
•
•
The ability to assess interactive effects of energy usage, operating
costs, cost allocation, rate design, and revenue requirements.
The ability to model California market characteristics, policies, plans
and scenarios (LTTP, RPS, TPP, AB 32, RA)
Transparency:
o
o
•
•
Model individual components of rates to allow easier evaluation.
POU v. IOU; bundled v. ESP rates .
Flexibility to adapt to evolving rate or market design and allow
stochastic analyses
Leverage analysis from, and interface efficiently with, other state and
CEC tools and processes including the LTPP, RPS calculator, TPP,
Cost of Generation model, PLEXOS, and NamGas.
•
•
Generation by technology type
Some costs and rates by TOU/LOLP time periods
California Energy Commission
www.energy.ca.gov
CEC Demand Forecast Modeling Interactions
o
o
o
o
Support and be consistent with the state demand forecast
development. Needed output:
 annual average rates by sector and utility forecast area, so
need to translate from classes to sectors.
 IOU rates need to be compiled with public utility rates.
 support distributed resource and transportation demand
analysis.
Incorporate future analysis on load shape trends.
Account for effects of TOU rates.
Model common econ/demo and other scenario assumptions
California Energy Commission
www.energy.ca.gov
Modeling Approach
•
•
•
•
•
Dynamic, simultaneous equation simulation
o Annual time step, with TOU detail for some elements.
Structural equations define sales, capital additions, operating costs and
other elements of revenue requirement
solved using the SAS Proc Model procedure.
o Allows estimation, simulation, and forecasting of nonlinear
simultaneous equation models.
o Variance structure from internal or externally estimated variables
can be incorporated for stochastic analysis.
Treat major long run investments (LTPP, TPP) as fixed per planning
decisions, and load-related short run operational costs (such as energy
purchases, portions of distribution operations) as endogenous
Post process to translate to real, sector rates, NEM 2.0, and iterate with
self gen model
California Energy Commission
www.energy.ca.gov
High Level Equation Summary
California Energy Commission
www.energy.ca.gov
Incorporating CEC Econometric models
• Demand Office estimates econometric models for residential,
commercial, industrial, resource, and TCU as a function of
average annual rates and economic and demographic drivers.
• Incorporate parameter estimates, including price elasticity, and
calibrate to recorded utility distribution area usage.
• Econometric models are estimated statewide by sector; need to
adapt to utility area and class; account for direct access
• How to capture residential TOU rate effects on sales and
usage?
California Energy Commission
www.energy.ca.gov
Residential Usage and TOU Rates
Apply constant elasticity of substitution (CES) approach (as in statewide pricing
pilot)
• Disaggregate the annual forecast to summer and winter
• Decompose seasonal usage into TOU periods and apply substitution elasticity
The substitution equation models the ratio of peak to off-peak quantities as a
function of the ratio of peak to off-peak prices and other factors.
The seasonal energy usage modeled as a function of average price and other
factors.
• But assumptions and effects depend heavily on program design and
effectiveness. External analysis on TOU design could be incorporated
Other considerations
• Fixed charges could lower marginal rates
• Marginal cost-based revenue allocations could change with
o
o
Load shapes
Hourly Market prices, technology mix
California Energy Commission
www.energy.ca.gov
Residential Usage and TOU Rates
California Energy Commission
www.energy.ca.gov
ERRA Procurement Costs
Existing contracts: Use CEC Plexos output to estimate output trends of conventional
resources by resource or resource type; reconcile with utilty-level historic data
and IEPR supply forms
Current Renewable: Combine RPS procurement report data on forecasted energy
production and costs by generation technology with LTPP RPS scenarios to fill
net short.
Forecasting :
• Estimate new authorizations – LTPP scenarios; COG costs
• Forecast future renewables costs using CEC cost of generation model
• Residual market and capacity purchases: Use standard GRC/Avoided Costs
methodologies for pricing market energy and capacity purchases; CEC COG,
NamGas, Plexos inputs
• Track “New Gen/Local Gen” costs for cost allocation to direct access
• Fuel costs: CEC NamGas forecast
• GHG costs: CEC GHG forecast
o indirect cost impact on market prices
o Direct costs from natural gas generation, CHP, imports
California Energy Commission
www.energy.ca.gov
ERRA Procurement Costs
California Energy Commission
www.energy.ca.gov
Distribution Costs
Major drivers of distribution capital and operation costs:
• Customer growth - housing starts, floorspace
• Design demand – noncoincident peak
• Interconnections
• Ongoing reliability upgrades & maintenance –forecast in line with
historic trends
But… Expanded Distributed Energy Resources? (DER)
Forthcoming work to develop distribution cost scenarios:
• CEC pilot study on cost-effective strategies for integrating DER
• CEC tech support to develop base scenario assumptions and methods
• CPUC proceeding on IOU Distribution Resource Plan Proposals in
2015
• Other resources or suggestions for modeling?
California Energy Commission
www.energy.ca.gov
FERC Transmission
Major projects known well in advance from CAISO TPP
• Renewables integration
• Reliability additions are ongoing
• CAISO publishes TAC area charge forecast model with forecast of
projects in current transmission plan and total revenue requirements
• The model makes some simplified escalation assumptions
Low voltage planned and in progress IOU transmission projects are
reported in each PTO’s five year forecast on FERC Form 730.
CEC will undertake further analysis on capital additions, costs and
scenario assumptions as part of tech support work.
California Energy Commission
www.energy.ca.gov
Generation GRC
Generation O&M
• Utility Owned Resources (SCE peakers, PG&E Hydro, solar)
• Energy production based on common scenarios and CEC
Plexos output (shape)
• Estimate costs based on forecasted profile and cost trends.
Generation Capital Expenditures
• Assume no new IOU-owned generation unless specifically
authorized
• Upgrades, maintenance on existing resources continue in line
with historic trends
California Energy Commission
www.energy.ca.gov
Next Steps
• Further comments and suggestions requested to Lynn
• Demand Forecast “input” workshop in February with preliminary
results.
• 2015 IEPR scenarios will incorporate current econometric
analysis, common scenario assumptions, CPUC decisions, data
from utility supply and demand forms for 2015 IEPR
• Draft rate scenarios in April 2015
California Energy Commission
www.energy.ca.gov