BEFORE THE PUBLIC UTILITIES COMMISSION OF THE STATE OF … · 2016-04-30 · For its 2021 and 2024 analysis, SCE used only the fundamental, non-blended prices from the PLEXOS model

BEFORE THE PUBLIC UTILITIES COMMISSION OF THE

STATE OF CALIFORNIA

Order Instituting Rulemaking to Assess Peak Electricity Usage Patterns and Consider Appropriate Time Periods for Future Time-of-Use Rates and Energy Resource Contract Payments.

R.15-12-012

(Filed December 17, 2015)

SOUTHERN CALIFORNIA EDISON COMPANY’S (U 338-E) RESPONSE TO

ADMINISTRATIVE LAW JUDGE’S MARCH 17, 2016 RULING REQUIRING

ADDITIONAL TOU PERIOD FORECAST ANALYSIS

JANET S. COMBS R. OLIVIA SAMAD

Attorneys for SOUTHERN CALIFORNIA EDISON COMPANY

2244 Walnut Grove Avenue Post Office Box 800 Rosemead, California 91770 Telephone: (626) 302-3477 Facsimile: (626) 302-7740 E-mail: [email protected]

Dated: April 29, 2016

1


STATE OF CALIFORNIA


R.15-12-012


SOUTHERN CALIFORNIA EDISON COMPANY’S (U 338-E) RESPONSE TO

ADMINISTRATIVE LAW JUDGE’S MARCH 17, 2016 RULING REQUIRING

ADDITIONAL TOU PERIOD FORECAST ANALYSIS

I.

INTRODUCTION

Pursuant to the Rules of Practice and Procedure of the California Public Utilities

Commission (“CPUC” or “Commission”), and in compliance with Administrative Law Judge

(“ALJ”) McKinney’s Ruling Notifying Parties of Schedule Changes and Required Supplemental

Information Filings, issued March 17, 2016 (“Ruling”), Southern California Edison Company

(SCE) responds to the ALJ’s request in Sections 1b and 1c of the Ruling for additional Time of

Use (“TOU”) period forecast analysis.

In response to Section 1b of the Ruling, SCE has attached the generation marginal energy

costs and generation marginal capacity costs that SCE originally proposed in its 2015 General

Rate Case (“GRC”) Phase 2 Application,1 which included forecast costs for the years 2015-2017.

Although the final marginal energy and capacity cost values adopted by the Commission in

1 CPUC Proceeding No. A.14-06-014.

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D.16-03-030 differed as a result of a settlement between SCE and many parties,2 SCE is

presenting the originally filed values because they are derived from a set of complete cost studies

that can be openly shared in this forum. SCE’s presentation is not intended to revisit or disturb

the settled values adopted as reasonable by the Commission; the information is formatted to

permit interested parties to replace the stated values with those from the settlement agreements

should they choose. The assumptions and methodologies proposed by SCE in A.14-06-014 are

consistent with the proposals presented in prior GRC Phase 2 applications. Additional detail on

general assumptions and the methodology used in A.14-06-014 are provided in Section II below.

As suggested in the Ruling, the vintage of the data provided in the most recent ratesetting

proceeding may not be the most relevant or useful for this proceeding. SCE agrees; the marginal

generation costs should be updated to reflect the current view of the 2021 and 2024 time-frame

being examined in the 2016 Long Term Procurement Plan and the California Independent

System Operator’s (“CAISO’s”) updated net load analysis.3 It is critical to expand the analysis

to include a broad time horizon so the forward-looking TOU periods are set to send the

appropriate price signals, especially in light of the changing conditions that will result from the

increased renewable portfolio standard introduced by Senate Bill (“SB”) 350. Accordingly, SCE

has updated the marginal generation cost studies, as proposed in A.14-06-014, to reflect

forecasted 2021 and 2024 load and costs.

2 See A.14-06-014, Motion of SCE and Settling Parties for Adoption of Marginal Cost and Revenue Allocation Settlement Agreement, filed August 14, 2015. The Settling Parties are SCE; The Utility Reform Network (“TURN”); the Office of Ratepayer Advocates (“ORA”); California Farm Bureau Federation (“CFBF”); Agricultural Energy Consumers Association (“AECA”); Southern California Fluid Milk Handlers (“SCFMH”); Federal Executive Agencies (“FEA”); California Manufacturers & Technology Association (“CMTA”); California Large Energy Consumers Association (“CLECA”); Energy Producers and Users Coalition (“EPUC”); Energy Users Forum (“EUF”); California City-County Street Light Association (“CAL-SLA”); Solar Energy Industries Association (“SEIA”); and the Direct Access Customer Coalition (“DACC”). The Marginal Cost and Revenue Allocation Settlement Agreement appended to the motion was adopted by the Commission in its entirety in D.16-04-030.

3 Pursuant to Section 1c of the Ruling, the updated CAISO net load analysis will be filed in this proceeding in June 2016.

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In addition to the marginal generation cost analysis requested in Section 1b, the Ruling

also invites parties to identify other factors and forecasts for possible consideration in the TOU

period analyses and to propose steps for developing the new data sources and studies. SCE

recommends that the hourly marginal costs of flexible (also known as “ramp”) generation

capacity also be considered in this proceeding, and has included the proposed ramp methodology

and forecasted 2021 and 2024 cost data in Section III, below. If deemed in scope, SCE supports

various parties’ suggestion to examine the role of distribution costs in TOU period analysis in a

later phase of this proceeding.4 Regardless of the timeline in this proceeding, SCE will include

an analysis of distribution cost time-differentiation in its September 1, 2016 Rate Design

Window (“RDW”) Application.

SCE is including three separate excel sheets with toggling functionality to allow parties

to examine the following scenarios:

1. 2015 GRC Marginal Generation Costs as Filed

a. No toggling functionality, response to Section 1b

2. 2021 Marginal Generation Costs

a. Toggle “LOLE only” and “Flat RPS Adder” for response to 1b, which is an

update of existing methodologies to reflect 2021 costs and forecasts

b. Toggle “LOLE + Flex” and “No RPS Adder” for response to 1c

3. 2024 Marginal Generation Costs

a. Toggle “LOLE only” and “Flat RPS Adder” for response to 1b, which is an

update of existing methodologies to reflect 2021 costs and forecasts

b. Toggle “LOLE + Flex” and “No RPS Adder” for response to 1c

4 See Tr. PHC-2 63:2 – 66:13 for discussion on examining the role of distribution costs in a later phase of this proceeding.

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II.

IOU MARGINAL GENERATION COST STUDIES; RESPONSE TO SECTION 1B OF

THE RULING

A. Vintage of Data

As stated above, SCE’s 2015 GRC Phase 2 Application utilized 2015-17 forecasts to

develop its marginal generation costs. As described in SCE’s testimony in that proceeding,5 SCE

blended results from the PLEXOS®6 production simulation model and market based quotes to

develop its 2015-17 hourly marginal energy price forecast. SCE utilized 2017 load forecast data

from the 2012 Integrated Energy Policy Report (“IEPR”) to develop its Loss of Load

Expectation (“LOLE”) estimates.

For its 2021 and 2024 analysis, SCE used only the fundamental, non-blended prices from

the PLEXOS model to develop its marginal energy costs, and used 2021 and 2024 load forecast

data from the 2014 IEPR to develop its LOLE estimates.

B. Marginal Energy Costs

Marginal Energy Costs are defined as the sum of the hourly wholesale market clearing

price ($/MWh) and the marginal cost premium of Renewable Portfolio Standard (“RPS”)

compliance for the incremental MWh of energy served.

1. Wholesale Market Clearing Price for Energy

SCE develops a wholesale marginal energy price forecast using the PLEXOS

production simulation model. The PLEXOS model used in the price forecast is a California-only

nodal model. It models the detailed transmission topology for California based on the Congestion

5 See A.14-06-014, SCE-02. 6 PLEXOS® Integrated Energy Model is simulation software for energy market analysis was

developed by and is available for license from Energy Exemplar LLC. Additional information is available at http://www.energyexemplar.com/ [as of April 29, 2016].

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Revenue Rights (“CRR”) Full Network Model (“FNM”) published by the CAISO, including

major intertie imports. The model contains the following inputs:

Gross load projections, which include the effects of on-site load impacts due to

Distributed Energy Resources (“DERs”), including demand response, energy

efficiency and Distributed Generation (“DG”) such as rooftop solar;

Gas price forecasts for each “hub”;

Greenhouse Gas (“GHG”) compliance cost forecasts;

Transmission line and interface limitations based on the transmission capability of

the interties and the CAISO Full Network Model;

RPS trajectory for all Load Serving Entities (“LSEs”) within the Western

Electricity Coordinating Council (“WECC”);

Generation profiles for RPS-eligible wind and solar resources;

The costs in the forecast energy price are those for incremental fuel, variable

operation and maintenance (“O&M”), emissions costs, startup costs, and no load fuel costs. The

energy price includes the costs related to congestion and losses.

The PLEXOS model is a mixed integer programming (“MIP”) model that

produces a marginal market clearing price for each hour by determining the least-cost means of

matching generation to meet forecasted demand and ancillary services with respect to

transmission constraints. Because renewable generation is modeled as “must-take” generation,

the forecasted demand used in the model is net of the renewable generation expected in the

forecasted time period (“Net Load”), and the day-ahead marginal price forecast reflects the level

of demand that dispatchable units will be expected to support.

2. Marginal Cost premium of RPS-Eligible resources

In its 2015 GRC Phase 2 application, SCE introduced the need for an adder to the

marginal energy price forecast to account for the marginal cost of complying with the state’s

RPS requirements (“RPS Adder”). SCE proposed that the marginal cost of the RPS Adder be

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quantified using the methodology adopted in D.11-12-018 and Resolution E-4475, multiplied by

the expected compliance target in that year, then added equally to the marginal energy price

forecast in each hour. Intervening parties in A.14-06-014 had significantly different opinions

regarding RPS costs, with some parties recommending their exclusion altogether. Ultimately,

parties settled upon an RPS Adder and a general shaping methodology. Because SCE’s response

to Section 1b of the Ruling focuses strictly on the generation marginal cost methodologies

proposed in its 2015 GRC Phase 2 Application, the Section 1b responses reflect the fixed RPS

Adder methodology that SCE originally proposed. However, because parties had differing views

on the RPS Adder’s inclusion and shape, SCE has provided a “toggle” option for the 2021 and

2024 scenarios to remove this flat RPS cost adder from the marginal energy costs.

C. Marginal Generation Capacity Costs

1. Proxy Resource and Valuation

SCE bases the marginal generation capacity cost (“MGCC”) on the deferral value

of a combustion turbine (“CT”) proxy resource, net of any energy rents obtained from the

market. The proxy is the estimated long-run7 cost (in $/kW) for a new SCE-owned generation

unit in the Southern California region, including all permitting, financing, development costs and

inflation during the construction period. The annualized cost ($/kW-yr) is then calculated using

the real economic carrying charge (“RECC”) methodology, to which fixed O&M costs and

property taxes are added to get total annualized costs. This annualized cost value is then reduced

by an estimate of forecasted “energy rents,”8 to determine the annualized “capacity” cost of the

resource.

7 SCE has traditionally used the long-run value of the proxy resource for purposes of determining generation capacity marginal costs. However, California is expected to be long on System capacity for the foreseeable future.

8 Energy rents are defined as operating profits that capture the instances when market prices are above its variable operating costs (which principally consist of fuel, emission costs, and variable O&M).

Continued on the next page

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In its capacity valuation analyses, SCE typically selects the resource with the

lowest annualized capacity cost as its proxy resource. In A.14-06-014, as well as the 2021 and

2024 scenarios developed in response to Sections 1b and 1c of the Ruling, the proxy resource

determined to have the lowest annualized capacity cost was a simple-cycle CT.9

2. Loss of Load Expectation

There is always some likelihood, however small, that the electricity system will

be unable to serve demand due to insufficient availability of generation relative to the electricity

demanded by customers. The risk of a generation shortage can be reduced by having more

generation available than forecast peak demand (i.e., a reserve margin), but this additional

generation imposes costs on customers. Determining the optimum supply and demand balance

requires the study of expected system operations using a probabilistic risk assessment approach.

Analysis of a system’s LOLE is one appropriate risk assessment approach—it is a measure of

system reliability that indicates the ability (or inability) to deliver energy to the load. An LOLE

analysis can provide insight into the planning reserve margin required for each LSE in a region.10

The LOLE metric provides a method for allocating annualized capacity value

across hours in proportion to when the loss of load is likely to occur.11 If the LOLE is greatest in

the summer period primarily due to load conditions, particularly during the on-peak period, then

most of the value SCE attributes to capacity will be assigned to that period. Similarly, if the

probability for loss-of-load is nearly zero during winter off-peak periods, SCE will assign very

Continued from the previous page

Energy rents are also knows as energy-related capital costs (“ERCC”). See A.14-06-014, SCE-02, p. 22, line 11 – p. 23, line 1.

9 In its 2015 GRC Phase 2 proceeding, SCE identified a simple cycle Frame 7 unit as the marginal generation capacity resource, while the future period assumptions identify a LMS 100 unit as the marginal generation capacity resource.

10 In D.04-10-035, the Commission directed LSEs under its jurisdiction to plan based upon meeting a 15 to 17 percent RA requirement. This implicitly reflects a balancing of customer risks and costs.

11 The purpose of SCE’s LOLE analysis is not to forecast the precise timing of future low-reserve margin events, nor is it to forecast the absolute magnitude of any single loss-of-load event. Rather, it is intended to be a relative distribution of risk used to allocate capacity value across hours.

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little capacity value to that period. LOLE makes it possible to evaluate the relative reliability

contribution of different resources across a range of TOU periods.

To develop the hourly marginal generation capacity cost allocation, SCE uses 30

historic weather years to create 30 possible peak and energy scenarios with an expected peak and

energy equal to its model year load forecast. Daily wind and solar generation forecasts are then

randomized against load, by month, to generate approximately 3,600 possible Net Load forecasts

for each day in the model year. These daily forecasts are then sampled and compared to a

distribution of non-intermittent resource availability, adjusted for expected maintenance and

forced outages, to determine the LOLE in each hour. This approach provides a reasonable

estimate of the relative risk of being unable to serve some portion of system load in any given

period.

III.

ADDITIONAL ANALYSES TO BE CONSIDERED

In Section 1c, the Ruling requests “Other Ideas on Additional Data and Analyses” for

“possible consideration in TOU period analyses.” SCE describes two such elements below –

flexible generation capacity and a proposed allocation methodology for peak load-related

distribution costs. The 2021 and 2024 scenario models included with this filing provide parties

with the ability to see the impact of including flexible generation in the marginal generation cost

analysis.

A. Marginal Generation Flexible Capacity Costs

As intermittent renewable energy resource penetration has expanded throughout

California, multiple parties have identified the need to enhance the Resource Adequacy (“RA”)

program to include physical attributes for “flexible capacity,” to sustain or increase output during

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the greatest upward three-hour net load ramp in each month.12 In recognition of this growing

need, the Commission formally adopted a policy framework for incorporating flexible capacity

needs as a part of the local capacity requirements for LSEs in 2013, and began including flexible

capacity requirements in the 2015 RA Program. As the electric system evolves and California

progresses towards its 50 percent RPS requirement, the need for flexible capacity will increase

and require the utilities to assess the cost directly associated with the procurement of flexible

capacity. As such, SCE recommends that flexible capacity be recognized as a cost driver

relevant for TOU period determination and utility rate setting, and proposes that a marginal cost

methodology consistent with the framework adopted in the CPUC’s RA program be established.

1. CAISO Flexible Resource Adequacy Criteria Must Offer Obligation and the

Introduction of Effective Flexible Capacity

In recognition of the issues described above, an interim solution was developed

by the CAISO to guarantee enough flexible generation in the CAISO markets. The proceeding,

called Flexible Resource Adequacy Criteria Must Offer Obligation (“FRAC-MOO”), established

the interim definition of flexibility that has been developed into a market product. Although the

FRAC-MOO proposal has yet to be accepted as the final solution for California’s flexibility

issues, the CPUC is looking to establish a durable flexible product in Track 2 of the RA

Proceeding.13

There are two parts (supply and demand) to the flexible shortfall calculation in

FRAC-MOO: (1) calculation of the effective flexible capacity (“EFC”) (supply), and (2)

definition of the flexible capacity need (demand). Generation resources’ ability to qualify as

“flexible capacity” is defined by its EFC. EFC is similar to the concept of Net Qualifying

12 As discussed in Section III.A.1, below, this definition of flexible capacity has been adopted as an interim definition, and is being further examined in Phase 2 of the RA proceeding.

13 See R.14-10-010, Assigned Commissioner and Administrative Law Judge’s Phase 2 Scoping Memo and Ruling, December 23, 2015, pp. 3-5.

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Capacity (“NQC”) in the RA program, and is defined as the amount of a generator’s capacity

that can be used to meet a three-hour upward net load ramp on the system. Additional detail on

determining EFC can be found on the CAISO FRAC-MOO website.14

Flexible capacity needs are defined as the quantity of resources needed by the CAISO to

manage grid reliability during the greatest three-hour continuous ramp in each month. Once the

overall monthly flexible need is determined, it is further refined into three categories, as defined

by the CAISO FRAC-MOO proposal: Base Ramp-- the largest morning upward ramp; Peak

Ramp—the overall flexible need less the Base Ramp; and the Super-Peak Ramp—can be up to 5

percent of the maximum upward three hour net load ramp of the month.15 These categories can

then be evaluated to determine if and when there is a system shortfall of EFC. While the

identification of system need for EFC is not within the scope of this proceeding, SCE believes

that a methodology, similar to the LOLE, of identifying the most likely hours of flexible capacity

need is the way to allocate the costs associated with flexible capacity.

2. Proxy Resource and Valuation

As described in Section II.C., above, the marginal costs of generation capacity are

based on the deferral costs of a proxy resource. Because the simple-cycle CT selected as the

proxy resource to meet peak capacity needs can also be used as capacity to meet flexible capacity

needs due to its short start times and ramp rates, SCE believes that it is an appropriate proxy for

both marginal peak capacity and marginal flexible capacity costs. A majority of CT’s count their

full capacity for both NQC and EFC.16

14 The CAISO FRAC-MOO website is available at https://www.caiso.com/informed/Pages/StakeholderProcesses/FlexibleResourceAdequacyCriteria-MustOfferObligations.aspx [as of April 29, 2016].

15 CAISO definitions of generator characteristics necessary to meet each of these ramping categories can be found on its FRAC-MOO website, supra. Additionally, the latest list of CAISO generator categories and EFC values can be found on the CAISO’s website, available at https://www.caiso.com/Pages/documentsbygroup.aspx?GroupID=9A94E71F-5542-49E8-BFBF-B9E00A2EC11B [as of April 29, 2016].

16 See CAISO’s latest list of generator categories and EFC values, supra.

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Typically the MGCC is allocated solely to the hours of likely shortfall identified

by the LOLE model. However, by including flexibility into the allocation model, the overall

MGCC must now be allocated to hours of likely “peak” shortfall, as identified by the LOLE

model, as well as to hours of likely “flexibility” shortfall.17 To determine the appropriate

allocation between the two functions, SCE modeled the statewide 2021 and 2024 net loads18 to

forecast future NQC and EFC needs, and determined the annual maximum peak requirement and

the annual maximum ramp requirement for each year. The ratio of the maximum ramp

requirement relative to the maximum peak requirement determined the percentage of MGCC

allocated to the flexibility function, and the remaining percentage of MGCC was allocated to the

peak function. Functional MGCCs were then allocated to each hour based on its respective

allocation methodology (LOLE and the methodology described below in Section III.A.3) to

determine the final marginal cost allocation of the MGCC.

3. Allocation of Flexible Capacity Costs in Each Hour

SCE utilized the following deterministic approach to determine the allocation of

flexible capacity to each hour:

1. Each daily max three hour upward ramp is grouped according to the hour in

which the ramp ends, resulting in a model in which the maximum three hour

upward ramp is represented by a value, based on the amplitude of the ramp, in

a single hour19

2. Each value is then normalized by the sum of all of the daily maximum three

hour upward ramps

17 Although SCE has developed a proxy methodology for allocating the marginal costs between peak capacity and flexible capacity, SCE continues to support bundling flexible capacity with generic capacity for procurement transactions.

18 Net loads were modeled using IEPR targets applied to Transmission Expansion Planning Policy Committee (“TEPCC”).

19 The end of the ramp is the targeted hour in which flex need is allocated, as it informs the period during which load should be reduced to lessen the three hour ramp.

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This deterministic approach is acceptable because it identifies the hours in which

the largest ramp need potentially occurs, and assigns more weight to the hours with larger needs.

As this process is refined, a more probabilistic approach, similar to the LOLE, may be developed

for allocation purposes.

B. Time Differentiation of Distribution Costs

To maintain service reliability and meet demand needs of our customers, SCE expands,

upgrades, and reinforces all levels of its electric system, including transmission, sub-

transmission, and distribution assets. SCE uses electricity facility peak loading data and load

growth forecasts to evaluate whether existing facilities will exceed their loading thresholds (also

known as a planning load limit) under normal and abnormal20 conditions, and plans

infrastructure projects to mitigate existing and expected violations. This planning process is

described in further detail in SCE’s GRC Phase 1 applications.

In its 2015 GRC Phase 2, SCE performed an “Effective Demand Factor” (“EDF”)

analysis, used to estimate each rate group’s (coincident) contribution to typical distribution

circuit peaks, to allocate distribution costs amongst rate groups.21 This methodology has been

employed for revenue allocation purposes over the last several GRC cycles and SCE’s current

rate designs recover these allocated distribution costs through non-time differentiated demand

charges.22 With the completed deployment of smart meters and associated TOU rate

requirements (mandatory for non-residential customers and default for residential coming in

2019), it is now possible to assess the TOU allocation of distribution costs to customers beyond

the revenue allocation phase and into the rate designs.

20 Abnormal conditions include, for example, planned facility outages for maintenance, unplanned facility outages due to equipment failures, and facilities removed from service as a result of a fault on the system.

21 See A.14-06-014, SCE-02, Appendix B. 22 Distribution costs are recovered through non time-differentiated energy charges from those rate

groups without demand charges.

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Per D.16-03-030, SCE has committed to review the time-differentiation of distribution

costs in its 2016 RDW filing and is currently exploring the degree to which time differentiation

of distribution charges may be warranted. SCE notes this analysis is “in-flight” and the

discussion below represents a “work-in-progress” that is in the process of further refinement.

Two additional modifications to the discussion below include: 1) a determination of the fixed

versus variable (peak load driven) distribution cost components; and 2) an assessment of the

degree to which the significant influx of distributed generation will affect the load shapes of the

distribution grid. As in the current generation system discussion, the distribution system peak

analysis will also need to be forward-looking and SCE is making these types of adjustments as

part of its 2016 RDW filing.

The differentiation between fixed and variable distribution costs is critical when

considering the time differentiation of distribution costs, because only the peak load-driven

variable distribution costs should be used to inform the definition of the TOU periods. Because

the methods to differentiate fixed and variable distribution costs are outside of the scope of this

proceeding, SCE has included only a methodology, the Peak Load Risk Allocation Factor that

can be used to allocate the variable distribution costs to each hour.

Once the fixed and variable distribution cost have been differentiated, SCE

proposes that the following methodology can allocate the variable distribution costs to each hour.

While this is still a work in progress, it can help to inform the relative cost allocation of

distribution costs over the 8760 hours in a year.

In its analysis, SCE has tried to replicate the parameters that drive capacity

planning decisions for substations and distribution circuits to determine how distribution costs

should be allocated throughout the year. Because upgrades to substations and distribution

circuits are triggered by different criteria, SCE has evaluated B-Substation, or substations that

step-down voltage from the sub-transmission levels (66 kV and 115 kV), data separately from

primary distribution circuit (typically 4 kV, 12 kV, and 16 kV) data.

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SCE’s load growth plan is driven in part by an analysis of historical temperatures

in each geographical area. The planning process includes an analysis of the sensitivity between

the load patterns and temperature measured at each substation and circuit. This temperature

sensitivity is then used to normalize the recorded load to a criteria projected load for a given

substation or circuit. Any substation and primary distribution circuit with a temperature

normalized criteria projected load that exceeds 90 percent and 73 percent, respectively, of its

planning load limit (“PLL”) will trigger a review process to determine whether additional

capacity is required.

SCE has used this criteria to identify the hours in which individual substations

and distribution circuits experience loads that exceed their threshold PLLs. To conduct this

analysis, SCE analyzes the historical hourly recorded data by substation and circuit, adjusts it by

the appropriate temperature sensitivity, and compares the temperature normalized load to the

established threshold level. Hours in which the temperature normalized load exceeds the

threshold are flagged as “Peak Load Risk” hours. All other load points are set to zero. The peak

load values, by hour, across all substations and/or circuits, are then summed to develop a

dispersion of peak load values for the entire system over the 8,760 hours of the year.

The Peak Load Risk Factor in each hour, a method of capturing the relative

distribution of risk, is then calculated as the ratio of the aggregated peak load in a specific hour

to the sum of all the aggregated peaks loads experienced in the year. Although this method of

identifying distribution peak load risk is a deterministic approach, it is similar to the probabilistic

LOLE approach, as it identifies the hours of highest “risk” of exceeding the threshold PLL.

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Respectfully submitted, JANET S. COMBS R. OLIVIA SAMAD

/s/ R. Olivia Samad By: R. Olivia Samad



April 29, 2016

Appendix A

A-1

As a reference, SCE hereby attaches the output of the 2024 marginal generation cost analysis

(with flexible capacity and without an RPS adder)—the analysis that SCE believes is most relevant for

consideration in TOU period determination. The total marginal generation costs, marginal generation

capacity costs, and marginal energy costs matrices attached below provide a visual representation, or a

“heat map,” of the hours of highest (top 10th percentile shown in red) and lowest (bottom 10th percentile

shown in green) costs.

Columns:��HoursRows:��Months

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Average

1 0.049� 0.048� 0.047� 0.048� 0.048� 0.049� 0.053 0.064 0.048 0.046 0.045 0.044 0.041 0.043 0.044� 0.046� 0.069 0.150 0.098 0.067 0.060 0.056 0.052 0.050 0.057��2 0.044� 0.043� 0.043� 0.042� 0.043� 0.044� 0.047 0.045 0.042 0.041 0.041 0.040 0.040 0.040 0.041� 0.041� 0.046 0.129 0.114 0.065 0.055 0.051 0.046 0.044 0.051��3 0.047� 0.046� 0.046� 0.046� 0.046� 0.047� 0.048 0.044 0.043 0.041 0.041 0.038 0.037 0.040 0.041� 0.043� 0.044 0.199 0.078 0.065 0.061 0.060 0.053 0.048 0.054��4 0.047� 0.047� 0.047� 0.046� 0.047� 0.047� 0.046 0.043 0.043 0.042 0.042 0.041 0.039 0.041 0.043� 0.044� 0.046 0.193 0.069 0.064 0.069 0.060 0.053 0.048 0.054��5 0.047� 0.047� 0.046� 0.046� 0.047� 0.047� 0.043 0.044 0.044 0.044 0.044 0.044 0.043 0.044 0.045� 0.046� 0.048 0.169 0.075 0.061 0.068 0.065 0.056 0.049 0.055��6 0.043� 0.043� 0.043� 0.042� 0.043� 0.042� 0.038 0.039 0.040 0.043 0.040 0.040 0.040 0.041 0.042� 0.044� 0.046 0.133 0.382 0.111 0.071 0.060 0.051 0.045 0.065��7 0.048� 0.047� 0.047� 0.047� 0.047� 0.047� 0.042 0.044 0.046 0.047 0.049 0.050 0.052 0.053 0.057� 0.058� 0.059 0.191 0.096 0.073 0.070 0.065 0.061 0.053 0.060��8 0.049� 0.048� 0.048� 0.047� 0.048� 0.048� 0.046 0.046 0.047 0.048 0.048 0.049 0.050 0.052 0.055� 0.057� 0.095 0.265 0.489 0.111 0.082 0.065 0.062 0.053 0.084��9 0.045� 0.044� 0.044� 0.044� 0.044� 0.044� 0.044 0.043 0.043 0.044 0.044 0.044 0.045 0.046 0.049� 0.055� 0.185 2.275 0.993 0.279 0.090 0.059 0.053 0.047 0.196��

10 0.049� 0.049� 0.049� 0.048� 0.049� 0.049� 0.053 0.048 0.047 0.047 0.047 0.047 0.047 0.048 0.049� 0.049� 0.123 0.167 0.067 0.073 0.065 0.060 0.054 0.050 0.060��11 0.044� 0.043� 0.043� 0.042� 0.043� 0.044� 0.046 0.044 0.042 0.042 0.042 0.041 0.041 0.042 0.042� 0.043� 0.128 0.151 0.062 0.059 0.054 0.050 0.046 0.044 0.053��12 0.048� 0.048� 0.047� 0.047� 0.048� 0.048� 0.053 0.054 0.048 0.048 0.047 0.047 0.046 0.046 0.047� 0.048� 0.057 0.241 0.077 0.069 0.063 0.061 0.056 0.050 0.060��

Hourly�Average 0.047� 0.046� 0.046� 0.046� 0.046� 0.046� 0.047 0.047 0.045 0.044 0.044 0.044 0.044 0.045 0.046� 0.048� 0.079 0.355 0.217 0.091 0.067 0.059 0.054 0.048


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Average

1 0.051� 0.050� 0.049� 0.049� 0.049� 0.050� 0.051 0.069 0.046 0.042 0.043 0.038 0.037 0.034 0.036� 0.044� 0.051 0.168 0.088 0.066 0.060 0.056 0.053 0.051 0.056��2 0.046� 0.045� 0.045� 0.045� 0.045� 0.046� 0.046 0.045 0.040 0.034 0.039 0.038 0.033 0.037 0.038� 0.039� 0.051 0.073 0.147 0.063 0.055 0.051 0.050 0.047 0.050��3 0.049� 0.049� 0.049� 0.048� 0.048� 0.048� 0.048 0.043 0.034 0.028 0.029 0.028 0.014 0.020 0.034� 0.042� 0.057 0.177 0.073 0.062 0.062 0.064 0.060 0.051 0.051��4 0.038� 0.037� 0.037� 0.037� 0.037� 0.037� 0.034 0.024 0.031 0.028 0.025 0.028 0.017 0.016 0.016� 0.043� 0.033 0.137 0.039 0.042 0.051 0.050 0.046 0.039 0.038��5 0.042� 0.042� 0.042� 0.042� 0.042� 0.042� 0.027 0.030 0.030 0.033 0.032 0.032 0.032 0.030 0.020� 0.036� 0.049 0.132 0.059 0.049 0.052 0.053 0.051 0.045 0.044��6 0.047� 0.047� 0.047� 0.047� 0.047� 0.046� 0.034 0.023 0.035 0.040 0.040 0.040 0.040 0.041 0.043� 0.044� 0.058 0.138 0.079 0.060 0.061 0.065 0.059 0.049 0.051��7 0.043� 0.043� 0.043� 0.042� 0.042� 0.041� 0.035 0.031 0.037 0.038 0.040 0.041 0.042 0.042 0.043� 0.044� 0.045 0.168 0.077 0.062 0.060 0.057 0.052 0.045 0.050��8 0.044� 0.043� 0.043� 0.043� 0.043� 0.043� 0.039 0.036 0.038 0.039 0.040 0.041 0.041 0.042 0.043� 0.092� 0.071 0.104 0.115 0.061 0.066 0.064 0.058 0.046 0.054��9 0.049� 0.048� 0.048� 0.048� 0.048� 0.048� 0.046 0.039 0.040 0.041 0.042 0.044 0.045 0.046 0.047� 0.049� 0.051 0.511 0.151 0.082 0.068 0.062 0.059 0.050 0.073��

10 0.044� 0.044� 0.044� 0.044� 0.044� 0.044� 0.045 0.037 0.037 0.038 0.039 0.039 0.040 0.041 0.042� 0.044� 0.117 0.129 0.058 0.066 0.057 0.051 0.047 0.045 0.052��11 0.056� 0.055� 0.055� 0.055� 0.055� 0.055� 0.056 0.053 0.045 0.048 0.048 0.045 0.043 0.047 0.049� 0.053� 0.145 0.194 0.081 0.077 0.067 0.063 0.059 0.056 0.065��12 0.051� 0.051� 0.050� 0.050� 0.050� 0.050� 0.051 0.050 0.046 0.040 0.044 0.043 0.043 0.043 0.044� 0.047� 0.053 0.244 0.067 0.067 0.061 0.060 0.055 0.051 0.059��

Hourly�Average 0.047� 0.046� 0.046� 0.046� 0.046� 0.046� 0.043 0.040 0.038 0.038 0.038 0.038 0.035 0.037 0.038� 0.048� 0.065 0.181 0.086 0.063 0.060 0.058 0.054 0.048

Weekdays

Weekends�and�Holidays

Total�Marginal�Generation�Costs2024�Forecast��With�Flex�Capacity�and�Without�RPS�Adder


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Average

1 �� 0.008 �� 0.017 0.072 0.025 �� 0.005��2 �� 0.003 0.071 0.047 �� 0.005��3 �� 0.145 0.018 �� 0.007��4 �� 0.142 0.010 �� 0.006��5 �� 0.002 0.119 0.013 �� 0.006��6 �� 0.002 �� 0.000� 0.000� 0.002 0.086 0.323 0.047 0.009 0.000 �� 0.020��7 �� 0.000� 0.000� 0.000 0.129 0.011 0.003 0.002 0.000 �� 0.006��8 �� 0.000� 0.037 0.190 0.395 0.040 0.011 0.000 �� 0.028��9 �� 0.000� 0.006� 0.132 2.172 0.931 0.211 0.028 0.001 �� 0.145��

10 �� 0.003 �� 0.000� 0.000� 0.065 0.091 0.002 0.000 0.000 0.000 �� 0.007��11 �� 0.075 0.065 �� 0.006��12 �� 0.160 0.007 �� 0.007��

Hourly�Average �� 0.000 0.001 �� 0.000 �� 0.000� 0.001� 0.028 0.287 0.148 0.025 0.004 0.000 ��


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Average

1 �� 0.018 �� 0.095 0.018 �� 0.005��2 �� 0.008 0.022 0.088 �� 0.005��3 �� 0.012 0.127 0.018 �� 0.007��4 �� 0.012� �� 0.099 �� 0.005��5 �� 0.010 0.090 0.012 �� 0.005��6 �� 0.000� 0.000� 0.012 0.091 0.023 0.000 0.000 0.000 �� 0.005��7 �� 0.000� 0.000� 0.000 0.119 0.014 0.003 0.003 0.000 �� 0.006��8 �� 0.048� 0.027 0.048 0.045 0.002 0.002 0.000 �� 0.007��9 �� 0.000� 0.000� 0.001 0.430 0.082 0.007 0.002 0.000 �� 0.022��

10 �� 0.000� 0.000� 0.070 0.067 0.000 0.000 0.000 0.000 �� 0.006��11 �� 0.084 0.101 �� 0.008��12 �� 0.167 �� 0.007��

Hourly�Average �� 0.001 �� 0.000� 0.005� 0.019 0.121 0.025 0.001 0.000 0.000 ��

Marginal�Generation�Capacity�Costs2024�Forecast��With�Flex�Capacity�and�Without�RPS�Adder

Weekdays



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Average

1 0.049� 0.048� 0.047� 0.048� 0.048� 0.049� 0.053 0.056 0.048 0.046 0.045 0.044 0.041 0.043 0.044� 0.046� 0.052 0.078 0.073 0.067 0.060 0.056 0.052 0.050 0.052��2 0.044� 0.043� 0.043� 0.042� 0.043� 0.044� 0.047 0.045 0.042 0.041 0.041 0.040 0.040 0.040 0.041� 0.041� 0.044 0.058 0.067 0.065 0.055 0.051 0.046 0.044 0.046��3 0.047� 0.046� 0.046� 0.046� 0.046� 0.047� 0.048 0.044 0.043 0.041 0.041 0.038 0.037 0.040 0.041� 0.043� 0.044 0.053 0.060 0.065 0.061 0.060 0.053 0.048 0.047��4 0.047� 0.047� 0.047� 0.046� 0.047� 0.047� 0.046 0.043 0.043 0.042 0.042 0.041 0.039 0.041 0.043� 0.044� 0.046 0.052 0.059 0.064 0.069 0.060 0.053 0.048 0.048��5 0.047� 0.047� 0.046� 0.046� 0.047� 0.047� 0.043 0.044 0.044 0.044 0.044 0.044 0.043 0.044 0.045� 0.046� 0.047 0.050 0.062 0.061 0.068 0.065 0.056 0.049 0.049��6 0.043� 0.043� 0.043� 0.042� 0.043� 0.042� 0.038 0.039 0.040 0.040 0.040 0.040 0.040 0.041 0.042� 0.043� 0.044 0.047 0.059 0.064 0.063 0.060 0.051 0.045 0.045��7 0.048� 0.047� 0.047� 0.047� 0.047� 0.047� 0.042 0.044 0.046 0.047 0.049 0.050 0.052 0.053 0.057� 0.058� 0.059 0.062 0.086 0.070 0.068 0.064 0.061 0.053 0.054��8 0.049� 0.048� 0.048� 0.047� 0.048� 0.048� 0.046 0.046 0.047 0.048 0.048 0.049 0.050 0.052 0.055� 0.056� 0.058 0.075 0.094 0.071 0.072 0.065 0.062 0.053 0.056��9 0.045� 0.044� 0.044� 0.044� 0.044� 0.044� 0.044 0.043 0.043 0.044 0.044 0.044 0.045 0.046 0.048� 0.049� 0.054 0.102 0.062 0.068 0.062 0.058 0.053 0.047 0.051��

10 0.049� 0.049� 0.049� 0.048� 0.049� 0.049� 0.050 0.048 0.047 0.047 0.047 0.047 0.047 0.048 0.049� 0.049� 0.058 0.075 0.065 0.073 0.065 0.060 0.054 0.050 0.053��11 0.044� 0.043� 0.043� 0.042� 0.043� 0.044� 0.046 0.044 0.042 0.042 0.042 0.041 0.041 0.042 0.042� 0.043� 0.053 0.086 0.062 0.059 0.054 0.050 0.046 0.044 0.047��12 0.048� 0.048� 0.047� 0.047� 0.048� 0.048� 0.053 0.054 0.048 0.048 0.047 0.047 0.046 0.046 0.047� 0.048� 0.057 0.082 0.071 0.069 0.063 0.061 0.056 0.050 0.053��

Hourly�Average 0.047� 0.046� 0.046� 0.046� 0.046� 0.046� 0.046 0.046 0.045 0.044 0.044 0.044 0.044 0.045 0.046� 0.047� 0.051 0.068 0.068 0.066 0.063 0.059 0.054 0.048 0.050��


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Average

1 0.051� 0.050� 0.049� 0.049� 0.049� 0.050� 0.051 0.051 0.046 0.042 0.043 0.038 0.037 0.034 0.036� 0.044� 0.051 0.073 0.070 0.066 0.060 0.056 0.053 0.051 0.050��2 0.046� 0.045� 0.045� 0.045� 0.045� 0.046� 0.046 0.045 0.040 0.034 0.039 0.038 0.033 0.037 0.038� 0.039� 0.043 0.051 0.059 0.063 0.055 0.051 0.050 0.047 0.045��3 0.049� 0.049� 0.049� 0.048� 0.048� 0.048� 0.048 0.043 0.034 0.028 0.029 0.028 0.014 0.020 0.034� 0.042� 0.044 0.051 0.055 0.062 0.062 0.064 0.060 0.051 0.044��4 0.038� 0.037� 0.037� 0.037� 0.037� 0.037� 0.034 0.024 0.031 0.028 0.025 0.028 0.017 0.016 0.016� 0.032� 0.033 0.038 0.039 0.042 0.051 0.050 0.046 0.039 0.034��5 0.042� 0.042� 0.042� 0.042� 0.042� 0.042� 0.027 0.030 0.030 0.033 0.032 0.032 0.032 0.030 0.020� 0.036� 0.039 0.042 0.047 0.049 0.052 0.053 0.051 0.045 0.039��6 0.047� 0.047� 0.047� 0.047� 0.047� 0.046� 0.034 0.023 0.035 0.040 0.040 0.040 0.040 0.041 0.043� 0.044� 0.046 0.048 0.056 0.060 0.061 0.065 0.059 0.049 0.046��7 0.043� 0.043� 0.043� 0.042� 0.042� 0.041� 0.035 0.031 0.037 0.038 0.040 0.041 0.042 0.042 0.043� 0.044� 0.045 0.049 0.063 0.058 0.057 0.056 0.052 0.045 0.045��8 0.044� 0.043� 0.043� 0.043� 0.043� 0.043� 0.039 0.036 0.038 0.039 0.040 0.041 0.041 0.042 0.043� 0.044� 0.044 0.057 0.069 0.058 0.064 0.064 0.058 0.046 0.047��9 0.049� 0.048� 0.048� 0.048� 0.048� 0.048� 0.046 0.039 0.040 0.041 0.042 0.044 0.045 0.046 0.047� 0.049� 0.051 0.081 0.069 0.075 0.066 0.062 0.059 0.050 0.052��

10 0.044� 0.044� 0.044� 0.044� 0.044� 0.044� 0.045 0.037 0.037 0.038 0.039 0.039 0.040 0.041 0.042� 0.044� 0.047 0.062 0.058 0.066 0.057 0.051 0.047 0.045 0.046��11 0.056� 0.055� 0.055� 0.055� 0.055� 0.055� 0.056 0.053 0.045 0.048 0.048 0.045 0.043 0.047 0.049� 0.053� 0.061 0.093 0.081 0.077 0.067 0.063 0.059 0.056 0.057��12 0.051� 0.051� 0.050� 0.050� 0.050� 0.050� 0.051 0.050 0.046 0.040 0.044 0.043 0.043 0.043 0.044� 0.047� 0.053 0.076 0.067 0.067 0.061 0.060 0.055 0.051 0.052��

Hourly�Average 0.047� 0.046� 0.046� 0.046� 0.046� 0.046� 0.043 0.038 0.038 0.038 0.038 0.038 0.035 0.037 0.038� 0.043� 0.046 0.060 0.061 0.062 0.059 0.058 0.054 0.048 0.046��

Marginal�Energy�Costs2024�Forecast��With�Flex�Capacity�and�Without�RPS�Adder

Weekdays


Appendix B


STATE OF CALIFORNIA


R.15-12-012


NOTICE OF AVAILABILITY OF SOUTHERN CALIFORNIA EDISON (U 338-E)

POSTING OF MARGINAL GENERATION COST SUPPLEMENTAL INFORMATION

JANET S. COMBS R. OLIVIA SAMAD



Dated: April 29, 2016

B-1


STATE OF CALIFORNIA


R.15-12-012


NOTICE OF AVAILABILITY OF SOUTHERN CALIFORNIA EDISON (U 338-E)

POSTING OF MARGINAL GENERATION COST SUPPLEMENTAL INFORMATION

Southern California Edison Company (“SCE”) hereby provides notice to the service list

in Proceeding R.15-12-012 that the following files are available for viewing and downloading on

SCE’s website:

1. Microsoft Excel® file providing marginal generation energy costs and generation

marginal capacity costs as filed in SCE’s 2015 General Rate Case (“GRC”) Phase

2 Application,1 including forecast costs for the years 2015-2017, in response to

Section 1b of Administrative Law Judge (“ALJ”) McKinney’s Ruling Notifying

Parties of Schedule Changes and Required Supplemental Information Filings,

issued March 17, 2016 (“Ruling”);

2. Excel file providing updated marginal generation cost studies to reflect forecasted

2021 load and costs, with toggling functionality, in response to Sections 1b and 1c

of the Ruling; and

1 CPUC Proceeding A.14-06-014.

3. Excel file providing updated marginal generation cost studies to reflect forecasted

2024 load and costs, with toggling functionality, in response to Sections 1b and 1c

of the Ruling.

These files will be available via the following URL as of the date of service of this

Notice, April 29, 2016:

http://www3.sce.com/law/cpucproceedings.nsf/vwSearchProceedings?SearchView&Query=R.15

-12-012&SearchMax=1000&Key1=1&Key2=25

The files are presented in Microsoft Excel (.xlsx) format and can be viewed online,

printed, or saved to your hard drive. If you experience technical difficulties accessing the

documents on SCE’s website, please contact Lisa Tobias, SCE’s CPUC regulatory paralegal, at

(626) 302-3812 or [email protected].

If you are unable to access the documents via SCE’s website, copies of them can be

provided via secure transfer upon request to SCE Legal Administration, who can be reached at

[email protected].

Respectfully submitted, JANET S. COMBS R. OLIVIA SAMAD

/s/ R. Olivia Samad By: R. Olivia Samad



April 29, 2016


STATE OF CALIFORNIA


R.15-12-012 (Filed December 17, 2015)

CERTIFICATE OF SERVICE

I hereby certify that, pursuant to the Commission’s Rules of Practice and Procedure, I have this day served a true copy of SOUTHERN CALIFORNIA EDISON COMPANY'S (U 338-E) RESPONSE TO ADMINISTRATIVE LAW JUDGE’S MARCH 17, 2016 RULING REQUIRING ADDITIONAL TOU PERIOD FORECAST ANALYSIS on all parties identified on the attached service list(s) R.15-12-012. Service was effected by one or more means indicated below:

Transmitting the copies via e-mail to all parties who have provided an e-mail address.

Placing the copies in sealed envelopes and causing such envelopes to be delivered by hand or by overnight courier to the offices of the Assigned ALJ(s) or other addressee(s).

ALJ Jeanne McKinney CPUC 505 Van Ness Ave. San Francisco, CA 94102

Executed this 29th day of April, 2016, at Rosemead, California.

/s/Gina Leisure Gina Leisure

SOUTHERN CALIFORNIA EDISON COMPANY 2244 Walnut Grove Avenue

Post Office Box 800 Rosemead, California 91770

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DONALD KELLY JAMIE L MAULDIN EXE DIR ADAMS BROADWELL JOSEPH & CARDOZO UTILITY CONSUMERS ACTION NETWORK EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 FOR: COALITION OF CALIFORNIA UTILITY FOR: UCAN EMPLOYEE JOHN W. LESLIE, ESQ. DANIEL W. DOUGLASS PARTNER ATTORNEY DENTONS US LLP DOUGLASS & LIDDELL EMAIL ONLY 4766 PARK GRANADA, SUITE 209 EMAIL ONLY, CA 00000-0000 CALABASAS, CA 91302 FOR: SHELL ENERGY NORTH AMERICA (US), FOR: NEST LABS, INC. L.P. OLIVA SAMAD DONALD C. LIDDELLL SENIOR ATTORNEY ATTORNEY SOUTHERN CALIFORNIA EDISON COMPANY DOUGLAS & LIDDELL 2244 WALNUT GROVE AVENUE / PO BOX 800 2928 2ND AVE. ROSEMEAD, CA 91770 SAN DIEGO, CA 92103 FOR: SOUTHERN CALIFORNIA EDISON COMPANY FOR: CALIFORNIA ENERGY STORAGE ALLIANCE (SCE) OLIVIA SAMAD IS REP JOHN A. PACHECO KATHERINE RAMSEY ATTORNEY CLEAN COALITION SAN DIEGO GAS & ELECTRIC COMPANY 16 PALM CT 8330 CENTURY PARK CT., CP32 MENLO PARK, CA 94025 SAN DIEGO, CA 92123 FOR: CLEAN COALITION FOR: SAN DIEGO GAS & ELECTRIC COMPANY MATTHEW FREEDMAN NORA SHERIFF STAFF ATTORNEY COUNSEL THE UTILITY REFORM NETWORK ALCANTAR & KAHL LLP 785 MARKET STREET, 14TH FL 345 CALIFORNIA ST., STE. 2450 SAN FRANCISCO, CA 94103 SAN FRANCISCO, CA 94104

Page 1 of 6CPUC - Service Lists - R1512012

4/29/2016https://ia.cpuc.ca.gov/servicelists/R1512012_83439.htm

FOR: TURN FOR: CALIFORNIA LARGE ENERGY CONSUMERS ASSOCIATION LARISSA KOEHLER JEANNE B. ARMSTRONG ATTORNEY ATTORNEY ENVIRONMENTAL DEFENSE FUND GOODIN MACBRIDE SQUERI & DAY LLP 123 MISSION STREET, 28TH FLOOR 505 SANSOME STREET, SUITE 900 SAN FRANCISCO, CA 94105 SAN FRANCISCO, CA 94111 FOR: ENVIRONMENTAL DEFENSE FUND FOR: SOLAR ENERGY INDUSTRIES ASSOCIATION SEAN P. BEATTY GAIL L. SLOCUM WEST REGION GEN. COUNSEL ATTORNEY AT LAW NRG ENERGY, INC, PACIFIC GAS AND ELECTRIC COMPANY 100 CALIFORNIA STREET, SUITE 650 77 BEALE STREET, B30A / PO BOX 7442 SAN FRANCISCO, CA 94111 SAN FRANCISCO, CA 94120-7442 FOR: NRG ENERGY, INC. FOR: PACIFIC GAS AND ELECTRIC COMPANY CHRIS S. KING JOSEPH F. WIEDMAN EMETER, A SIEMENS BUSINESS ATTORNEY 4000 E. THIRD AVE., 4TH FLOOR KEYES FOX & WIEDMAN LLP FOSTER CITY, CA 94404 436 - 14TH STREET, SUITE 1305 FOR: ON BEHALF OF EMETER, A SIEMENS OAKLAND, CA 94612 BUSINESS FOR: THE ENERGY FREEDOM COALITION OF AMERICA, LLC (EFCA) MELISSA W. KASNITZ GREGG MORRIS CENTER FOR ACCESSIBLE TECHNOLOGY DIR. 3075 ADELINE STREET, STE. 220 THE GREEN POWER INSTITUTE BERKELEY, CA 94703 2039 SHATTUCK AVE., SUTE. 402 FOR: CENTER FOR ACCESSIBLE TECHNOLOGY BERKELEY, CA 94704 FOR: THE GREEN POWER INSTITUTE JORDAN PINJUV MATTHEW SWINDLE GEN. COUNSEL CEO & FOUNDER CALIFORNIA INDEPENDENT SYSTEM OPERATOR NLINE ENERGY, INC. 250 OUTCROPPING WAY 5170 GOLDEN FOOTHILL PARKWAY FOLSOM, CA 95630 EL DORADO HILLS, CA 95762 FOR: CALIFORNIA ISO FOR: NLINE ENERGY, INC. BRAD HEAVNER ROBERT LIEBERT POLICY DIR. ELLISON, SCHNEIDER & HARRIS LLP CALIFORNIA SOLAR ENERGY INDUSTRIES 2600 CAPITOL AVE., STE. 400 1107 9TH ST., NO.820 SACRAMENTO, CA 95816 SACRAMENTO, CA 95814 FOR: CALIFORNIA MANUFACTURERS & FOR: CALIFORNIA SOLAR ENERGY INDUSTRIES TECHNOLOGY ASSN. ASSOCIATION KAREN N. MILLS ASSOCIATE COUNSEL CALIFORNIA FARM BUREAU FEDERATION 2300 RIVER PLAZA DRIVE SACRAMENTO, CA 95833 FOR: CALIFORNIA FARM BUREAU FEDERATION

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0 WAHL BARBARA R. BARKOVICH DEP. DIR. - POLICY & ELECTRICITY MARKETS CONSULTANT SOLARCITY CORPORATION BARKOVICH & YAP, INC. EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 FOR: CALIFORNIA LARGE ENERGY CONSUMERS ASSOCIATION DAVID MARCUS KA YING CHEU EMAIL ONLY PACIFIC GAS AND ELECTRIC COMPANY EMAIL ONLY, CA 00000 EMAIL ONLY EMAIL ONLY, CA 00000 KAREN SHEA KATY MORSONY PACIFIC GAS AND ELECTRIC COMPANY ALCANTAR & KAHL



EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 MARC D. JOSEPH MERRIAN BORGESON ADAMS BROADWELL JOSEPH & CARDOZO NATURAL RESOURCES DEFENSE COUNCIL EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 NELLIE TONG NORA SHERIFF SENIOR CONSULTANT ATTORNEY DNV KEMA ENERGY & SUSTAINABILITY ALCANTAR & KAHL EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 RACHEL GOLD SEPHRA A. NINOW POLICY DIRECTOR REGULATORY AFFAIRS MGR. LARGE-SCALE SOLAR ASSOCIATION CENTER FOR SUSTAINABLE ENERGY EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 SIERRA MARTINEZ SUSAN GLICK LEGAL DIR - CALIF. ENERGY PROJECT SENIOR MGR., PUBLIC POLICY NATURAL RESOURCES DEFENSE COUNCIL SUNRUN, INC. EMAIL ONLY EMAIL ONLY EMAIL ONLY, CA 00000 EMAIL ONLY, CA 00000 MRW & ASSOCIATES, LLC DOUGLAS DAVIE EMAIL ONLY VICE PRESIDENT EMAIL ONLY, CA 00000 WELLHEAD ELECTRIC COMPANY, INC. EMAIL ONLY EMAIL ONLY, CA 00000-0000 KAREN TERRANOVA BRANDON SMITHWOOD ALCANTAR & KAHL SOLAR ENERGY INDUSTRIES ASSOCIATION EMAIL ONLY 600 14TH STREET, NW, SUITE 400 EMAIL ONLY, CA 00000-0000 WASHINGTON, DC 20005 KELLY CRANDALL DANIEL RAMIREZ KEYES, FOX & WIEDMAN, LLP ANALYST 1580 LINCOLN STEET, SUITE 880 ENERGY STRATEGIES, LLC DENVER, CO 80203 215 SOUTH STATE STREET, STE 200 SALT LAKE CITY, UT 84111 LON W. HOUSE DAVID P. LOWREY WATER AND ENERGY CONSULTING DIRECTOR, REGULATORY STRATEGY 10645 N. ORACLE RD., STE. 121-216 COMVERGE, INC. ORO VALLEY, AZ 85737 8105 CALMOSA AVENUE WHITTIER, CA 90602 DANIEL DOUGLASS ANDRE RAMIREZ ATTORNEY SOUTHERN CALIFORNIA EDISON COMPANY DOUGLASS & LIDDELL 2244 WALNUT GROVE AVE. 4766 PARK GRANADA, SUITE 209 ROSEMEAD, CA 91770 CALABASAS, CA 91302 FOR: ALLIANCE FOR RETAIL ENERGY MARKETS / DIRECT ACCESS CUSTOMER COALITION / WESTERN POWER TRADING FORUM CASE ADMINISTRATION FADIA KHOURY SOUTHERN CALIFORNIA EDISON COMPANY SOUTHERN CALIFORNIA EDISON COMPANY 2244 WALNUT GROVE AVE. / PO BOX 800 2244 WALNUT GROVE AVENUE ROSEMEAD, CA 91770 ROSEMEAD, CA 91770 FOR: OLIVIA SAMAD IS REP AT SCE OLIVIA SAMAD DAVID CROYLE SR. ATTORNEY EXECUTIVE DIRECTOR SOUTHERN CALIFORNIA EDISON COMPANY UTILITY CONSUMERS' ACTION NETWORK 2244 WALNUT GROVE AVENUE 3405 KENYON STREET, STE. 401 ROSEMEAD, CA 91770 SAN DIEGO, CA 92110 FOR: UCAN MARCIE A. MILNER PARINA P. PARIKH VP - REG AFFAIRS REGULATORY CASE MGR. SHELL ENERGY NORTH AMERICA (US), L.P. SAN DIEGO GAS & ELECTRIC COMPANY



4445 EASTGATE MALL, STE. 100 8330 CENTURY PARK COURT, CP 32F SAN DIEGO, CA 92121 SAN DIEGO, CA 92123 FOR: SHELL ENERGY NORTH AMERICA (US), L.P. CENTRAL FILES CYNTHIA FANG SAN DIEGO GAS AND ELECTRIC COMPANY SAN DIEGO GAS & ELECTRIC COMPANY 8330 CENTURY PARK COURT-CP31E 8330 CENTURY PARK COURT, CP32E SAN DIEGO, CA 92123-1530 SAN DIEGO, CA 92123-1530 DANA GOLAN WILLIAM FULLER SAN DIEGO GAS & ELECTRIC COMPANY CALIF. REGULATORY AFFAIRS 8330 CENTURY PARK CT., CP421 SAN DIEGO GAS & ELECTRIC COMPANY SAN DIEGO, CA 92123-1530 8330 CENTURY PARK COURT, 32CH SAN DIEGO, CA 92123-1548 JASON M. ACKERMAN JEANNETTE OLKO BEST BEST & KRIEGER, LLP CITY OF MORENO VALLEY 3390 UNIVERSITY AVENUE, 5TH FLOOR 14177 FREDERICK STREET RIVERSIDE, CA 92501 MORENO VALLEY, CA 92552 BRIAN KORPICS ANTHONY HARRISON STAFF ATTY & POLICY MGR. MGR. - REGULATORY AFFAIRS THE CLEAN COALITION STEM, INC. 16 PALM CT. 100 ROLLINS RD. MENLO PARK, CA 94025 MILLBRAE, CA 94030 SUE MARA ERIC BORDEN CONSULTANT ENERGY POLICY ANALYST RTO ADVISORS, LLC THE UTILITY REFORM NETWORK 164 SPRINGDALE WAY 785 MARKET STREET, STE. 1400 REDWOOD CITY, CA 94062 SAN FRANCISCO, CA 94103 ALISON SEEL CASE ADMINISTRATION ASSOCIATE ATTORNEY PACIFIC GAS AND ELECTRIC COMPANY SIERRA CLUB 77 BEALE STREET 85 SECOND STREET, 2ND FLOOR SAN FRANCISCO, CA 94105 SAN FRANCISCO, CA 94105 JAMES FINE, PH.D SHERIDAN PAUKER SR. ECONOMIST REGULATORY COUNSEL ENVIRONMENTAL DEFENSE FUND WILSON SONSINI GOODRICH & ROSATI 123 MISSION ST., 28TH FL. ONE MARKET PLAZE, SPEAR TOWER, STE. 3300 SAN FRANCISCO, CA 94105 SAN FRANCISCO, CA 94105 ELIAH GILFENBAUM MARC KOLB DEPUTY DIR SOLARCITY SOLARCITY 444 DE HARO STREET, SUITE 100 444 DE HARO STREET SAN FRANCISCO, CA 94107 SAN FRANCISCO, CA 94107 CRAGG ANNA MURVEIT ATTORNEY CALIFORNIA EMVIRONMENTAL ASSOCIATES GOODIN, MACBRIDE, SQUERI & DAY, LLP 423 WASHINGTON ST. 4TH FL. 505 SANSOME ST., STE. 900 SAN FRANCISCO, CA 94111 SAN FRANCISCO, CA 94111 BRIAN THEAKER DIANE FELLMAN DIR - REGULATORY AFFAIRS VP - REGULATORY & GOVERNMENT AFFAIRS NRG ENERGY, INC. NRG WEST REGION 100 CALIFORNIA , STE. 650 100 CALIFORNIA ST., STE. 650 SAN FRANCISCO, CA 94111-4505 SAN FRANCISCO, CA 94111-4505 CALIFORNIA ENERGY MARKETS CHARLES R. MIDDLEKAUFF 425 DIVISADERO ST. SUITE 303 PACIFIC GAS AND ELECTRIC COMPANY SAN FRANCISCO, CA 94117 77 BEALE STREET, B30A, PO BOX 7442 SAN FRANCISCO, CA 94120 MEGAN M. MYERS ANDREW YIP LAW OFFICES OF SARA STECK MYERS MGR - BUS. DEVELOPMENT (RBNA/PJ-BGT) 122 - 28TH AVENUE ROBERT BOSCH LLC SAN FRANCISCO, CA 94121 4009 MIRANDA AVENUE, STE. 200 PALO ALTO, CA 94304 RICK COUNIHAN BONNIE DATTA



NEST LABS, INC. SIEMENS USA 3400 HILLVIEW AVENUE 4000 E. THIRD AVENUE PALO ALTO, CA 94304 FOSTER CITY, CA 94404 MICHAEL ROCHMAN MATTHEW BARMACK MANAGING DIR. DIR. - MARKET & REGULATORY ANALYSIS SCHOOL PROJECT UTILITY RATE REDUCTION CALPINE CORPORATION 1850 GATEWAY BLVD., STE. 235 4160 DUBLIN BLVD., SUITE 100 CONCORD, CA 94520 DUBLIN, CA 94568 FOR: SPURR YAP CATHERINE DAVID J. MILLER ATTORNEY AT LAW GEN. ATTORNEY BARKOVICH & YAP, INC. AT&T SERVICES, INC. PO BOX 11031 2150 WEBSTER STREET, 8TH FL. OAKLAND, CA 94611 OAKLAND, CA 94612 MICHELLE CHOO THOMAS SELHORST AT&T SERVICES, INC. SENIOR PARALEGAL 2150 WEBSTER STREET, 8TH FL AT&T CALIFORNIA, INC. OAKLAND, CA 94612 2150 WEBSTER STREET, 8TH FLOOR OAKLAND, CA 94612 NANCY RADER TOM BEACH EXECUTIVE DIR. PRINCIPAL CALIFORNIA WIND ENERGY ASSOCIATION CROSSBORDER ENERGY 2560 NINTH STREET, STE. 213A 2560 NINTH STREET, SUITE 213A BERKELEY, CA 94710 BERKELEY, CA 94710 PHILLIP MULLER JOHN NIMMONS PRESIDENT COUNSEL SCD ENERGY SOLUTIONS JOHN NIMMONS & ASSOCIATES, INC. 436 NOVA ALBION WAY 175 ELINOR AVE., STE. G SAN RAFAEL, CA 94903 MILL VALLEY, CA 94941 C.SUSIE BERLIN DELPHINE HOU LAW OFFICES OF SUSIE BERLIN CALIF. INDEPENDENT SYSTEMS OPERATOR 1346 THE ALAMEDA, SUITE 7 NO.141 250 OUTCROPPING WAY SAN JOSE, CA 95126 FOLSOM, CA 95630 JOHN GOODIN CAROLYN KEHREIN CALIFORNIA ISO ENERGY MANAGEMENT SERVICES 250 OUTCROPPING WAY ENERGY USERS FORUM FOLSOM, CA 95630-8773 2602 CELEBRATION WAY WOODLAND, CA 95776 DAN GRIFFITHS JOSHUA NELSON ATTORNEY ASSOCIATE BRAUN BLAISING MCLAUGHLIN & SMITH, P.C. BEST BEST & KRIEGER LLP 915 L STREET, SUITE 1480 500 CAPITOL MALL, STE. 1700 SACRAMENTO, CA 95814 SACRAMENTO, CA 95814 JUSTIN WYNNE KEVIN WOODRUFF ATTORNEY WOODRUFF EXPERT SERVICES BRAUN BLAISING MCLAUGHLIN & SMITH, P.C. 1127 - 11TH STREET, SUITE 514 915 L STREET, SUITE 1480 SACRAMENTO, CA 95814 SACRAMENTO, CA 95814 FOR: TURN MATTHEW KLOPFENSTEIN REBECCA FRANKLIN ATTORNEY REGULATORY ADVOCATE GONZALEZ, QUINTANA & HUNTER, LLC ASSOCIATION OF CALIF. WATER AGENCIES 915 L STREET, STE. 1480 910 K STREET, STE. 100 SACRAMENTO, CA 95814 SACRAMENTO, CA 95814 FOR: NLINE INC. RICK WALTMAN SCOTT BLAISING ATTORNEY AT LAW BRAUN BLAISING MCLAUGHLIN & SMITH P.C. BRAUN BLAISING MCLAUGHLIN & SMITH, P.C. 915 L STREET, SUITE 1480 915 L STREET, SUITE 1480 SACRAMENTO, CA 95814 SACRAMENTO, CA 95814 STEVEN KELLY ANDREW B. BROWN POLICY DIRECTOR ATTORNEY AT LAW INDEPENDENT ENERGY PRODUCERS ASSCIATION ELLISON SCHNEIDER & HARRIS LLP



1215 K STREET, STE. 900 2600 CAPITOL AVENUE, SUITE 400 SACRAMENTO, CA 95814 SACRAMENTO, CA 95816-5905 MIKE CADE INDUSTRY SPECIALIST ALCANTAR & KAHL 121 SW SALMON STREET, SUITE 1100 PORTLAND, OR 97204

State Service

SCOTT MURTISHAW AARON LU CPUC - EXEC DIV CALIF PUBLIC UTILITIES COMMISSION EMAIL ONLY ELECTRICITY PRICING AND CUSTOMER PROGRAM EMAIL ONLY, CA 00000 AREA 4-A 505 VAN NESS AVENUE SAN FRANCISCO, CA 94102-3214 BENJAMIN GUTIERREZ CODY NAYLOR CALIF PUBLIC UTILITIES COMMISSION CALIF PUBLIC UTILITIES COMMISSION ELECTRICITY PRICING AND CUSTOMER PROGRAM EXECUTIVE DIRECTOR AREA AREA 505 VAN NESS AVENUE 505 VAN NESS AVENUE SAN FRANCISCO, CA 94102-3214 SAN FRANCISCO, CA 94102-3214 GREGORY HEIDEN JEANNE MCKINNEY CALIF PUBLIC UTILITIES COMMISSION CALIF PUBLIC UTILITIES COMMISSION LEGAL DIVISION DIVISION OF ADMINISTRATIVE LAW JUDGES ROOM 4300 ROOM 5011 505 VAN NESS AVENUE 505 VAN NESS AVENUE SAN FRANCISCO, CA 94102-3214 SAN FRANCISCO, CA 94102-3214 LEE-WHEI TAN NATHAN CHAU CALIF PUBLIC UTILITIES COMMISSION CALIF PUBLIC UTILITIES COMMISSION ELECTRICITY PRICING AND CUSTOMER PROGRAM ELECTRICITY PRICING AND CUSTOMER PROGRAM ROOM 4102 AREA 505 VAN NESS AVENUE 505 VAN NESS AVENUE SAN FRANCISCO, CA 94102-3214 SAN FRANCISCO, CA 94102-3214 ROBERT LEVIN SEAN A. SIMON CALIF PUBLIC UTILITIES COMMISSION CALIF PUBLIC UTILITIES COMMISSION ENERGY DIVISION COMMISSIONER RANDOLPH ROOM 4102 AREA 4-A 505 VAN NESS AVENUE 505 VAN NESS AVENUE SAN FRANCISCO, CA 94102-3214 SAN FRANCISCO, CA 94102-3214 WHITNEY RICHARDSON LYNN MARSHALL CALIF PUBLIC UTILITIES COMMISSION CONSULTANT DEMAND RESPONSE, CUSTOMER GENERATION, AN CALIFORNIA ENERGY COMMISSION AREA 4-A 1516 9TH STREET, MS-20 505 VAN NESS AVENUE SACRAMENTO, CA 95814 SAN FRANCISCO, CA 94102-3214

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BEFORE THE PUBLIC UTILITIES COMMISSION OF THE STATE OF … · 2016-04-30 · For its 2021 and 2024 analysis, SCE used only the fundamental, non-blended prices from the PLEXOS model