California Energy Commission Draft Rate Scenario Model Methodology DAWG Forecasting Subgroup Sept. 11, 2014 Lynn Marshall Supply Analysis

California Energy Commissionwww.energy.ca.gov

Draft Rate Scenario Model Methodology

DAWG Forecasting Subgroup

Sept. 11, 2014

Lynn MarshallSupply Analysis OfficeAssessments Division

[email protected] / 916-654-4767

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 Proposed model structureo Methodology incorporating price effectso Interactions with other proceedings? o Data sources we should use?


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, distributiono ERRA Procurement and program costs are “passed through”o 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


High Level Perspective on IOU Revenue Requirements

Example using PG&E 2015 Annual Electric True-Up and GRC Decision Tables


Component Billion $ PercentAverage $/kwh

Distribution O&M 2,215 16% 0.0255Distribution Return and Deprec. 1,932 14% 0.0223Generation O&M 951 7% 0.0127Generation Return and Deprec. 1,110 8% 0.0148Electric Procurement/ERRA 5,433 39% 0.0723Total FERC Jurisdictional 1,433 10% 0.0165Everything Else 814 6% 0.0094Total 13,889 100% 0.1734

Source: PG&E Advice 4484-E and 2014 CPUC General Rate Case D.1408032 Decision Tables Revision 2, Appendix C.

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 Model individual components of rates to allow easier evaluation. o 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


CEC Demand Forecast Modeling Interactions

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.o Incorporate future analysis on load shape trends. o Account for effects of TOU rates.o Model common econ/demo and other scenario assumptions


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

High Level Equation Summary


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?

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 Load shapeso Hourly Market prices, technology mix


Residential Usage and TOU Rates


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 priceso Direct costs from natural gas generation, CHP, imports


ERRA Procurement Costs


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?


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.


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


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


Documents

California Energy Commission Draft Rate Scenario Model Methodology DAWG Forecasting Subgroup Sept. 11, 2014 Lynn Marshall Supply Analysis