Distributed Generation Projections for High DG Case October 10, 2014 Arne Olson, Partner Nick Schlag, Sr. Consultant.

Distributed Generation Projections for High DG Case

October 10, 2014

Arne Olson, Partner

Nick Schlag, Sr. Consultant

2

Background

In a number of past efforts, E3 has worked with LBNL and WECC to establish input assumptions regarding distributed generation in study cycles:

• In 2011-12, E3 worked with LBNL and WECC to develop estimates of DG potential for the SPSC’s 2022 and 2032 High DG/DSM cases

• In 2014, E3 & LBNL developed an approach to project “market-driven” distributed generation in the WECC, which was used to inform the 2024 Common Case

WECC has requested projections of distributed generation consistent with High DG futures for the Western Interconnection to use in the SPSC’s 2024 and 2034 High DG/DSM cases

To develop these projections, E3 has used logic from both prior efforts to assess future DG installations

3

Defining “Distributed Generation”

“Distributed” generation means different things to different people:

• Behind-the-meter, e.g., customer-owned resource

• Small utility or IPP owned resource that is connected at the distribution system and serves load downstream

• Small resource that is connected at the distribution system and does not serve load downstream

• Small resource that is connected to the sub-transmission system (i.e., low-voltage transmission) near load

• Small resource that is located remote from load

• Large resource that is located in load pocket and helps defer or avoid transmission investments

This analysis focuses on small scale solar PV installations that individual retail customers would install to avoid purchasing electricity from an electric utility

• Does not include “wholesale DG” that a utility might procure to meet state DG targets

4

Approaches to Developing High DG Assumptions

2022/2032 High DG Case assumptions developed in two steps:

• Estimate interconnection potential for each state

• Make state-specific adjustments to interconnection potential to reflect differences in economic drivers of DG

2024/2034 High DG Case assumptions derived by modeling customer decisions under a scenario favorable to distributed generation adoption

• Use E3’s Market Driven DG Model to develop projections of adoption

• Rely on estimates of interconnection potential as an upper bound

MODELING MARKET-DRIVEN DG

6

Channels for Distributed Solar PV Adoption

Background

In prior transmission planning study cycles, WECC has incorporated distributed solar PV assumptions consistent with state policy goals

This framework ignores the potential for market-driven DG

• With low PV costs, this could become a large amount of capacity

E3 and LBNL have developed a framework to incorporate market-driven DG into transmission planning studies

Program Goals(e.g. California Solar Initiative)

RPS Set-Asides(e.g. 30% DG set-aside in Arizona)

Market-Driven Adoption

Policy-driven DG, modeled in past WECC studies

New to WECC studies

7

E3’s Market Driven DG Model

To provide inputs for WECC’s transmission planning studies, E3 has developed a model of DG deployment throughout the WECC footprint between present day and 2040

• Joint funding from WECC and LBNL through DOE’s ARRA grants

Input assumptions capture geographic variations in PV cost-effectiveness and state policy

• State-specific PV costs

• State-specific net metering policy

• Capacity factors at a BA level

• Utility-specific retail rates (and incentives where applicable)

The model also captures the changing cost-effectiveness of PV:

• Continued declines in PV capital costs

• Expiration of incentives & tax credits (e.g. ITC in 2017)

• Escalation of retail rates

• Expected changes to state net metering policies (e.g. California AB 327)

8

2024 Common Case Recommendations

The Market-Driven DG Model used to develop preliminary recommendations for customer-sited solar for the 2024 Common Case

2024Market Peak Market

Driven DG Load Driven DGState (MW) (MW) (% of Peak)

Arizona 1,751 23,227 7.5%California 5,742 68,908 8.3%Colorado 742 11,789 6.3%Idaho 51 5,664 0.9%Montana 35 2,483 1.4%New Mexico 170 5,139 3.3%Nevada 241 9,951 2.4%Oregon 191 10,392 1.8%Utah 106 5,537 1.9%Washington 90 20,950 0.4%Wyoming 47 3,464 1.4%

Total 9,166 167,505 5.5%

For the 2024 Common Case, TAS adjusted the recommended

values (shown at left) downward by 20%

HIGH DG CASE RECOMMENDATIONS

10

Key Drivers of Market Driven DG Model

The main drivers of the modeled customer adoption of solar PV are:

1. Solar PV capital cost

2. Customer bill savings

3. Federal investment tax credit

4. State-specific incentive programs

5. State net energy metering caps

6. Utility system interconnection potential

Changing the assumptions for each of these parameters provides the basis for exploring alternative projections

Affect customer decision to invest in solar PV

Limit total penetration on a utility’s system

11

High DG projections are developed by relaxing existing NEM caps and assuming achievement of aspirational solar PV cost reductions

Overview of Assumptions

Assumption Reference Case High DG Case

Net Metering CapsCurrent Policy• Current NEM caps remain in

place• California cap lifted after 2016

NEM Caps Removed• All NEM caps lifted• Limits associated with

interconnection potential enforced

Solar PV Cost TrendsModerate Reductions• Cost trajectory derived by E3

for TEPPC planning studies

Aspirational Reductions• Sunshot goals achieved by

2020

12

Treatment of NEM Caps

In the Reference Case, each state’s NEM cap was enforced according to current policy

High DG case assumes current NEM caps are removed, allowing installations of DG in each utility’s service territory up to its ‘Interconnection Potential’

State Current NEM Cap

Arizona n/a

California

Limits under current NEM rate design established by AB327 (approximately 5% of non-coincident peak); beyond 2017, alternative rate designs will be considered with no associated cap

Colorado n/a

Idaho n/a

New Mexico n/a

Nevada 3% of utility peak

Oregon 0.5% of peak for munis, coops, & PUDs; no cap for IOUs

Utah 0.1% of peak for munis; 20% of peak for IOUs

Washington 0.5% of peak

Wyoming n/a

13

6,638

11,668

15,336

0

5,000

10,000

15,000

20,000

Rule 21 30% Rule Max w/oCurtailment

Incr

emen

tal P

V Po

tenti

al (M

W)

Residential Rooftop Commercial Rooftop

Ground Mounted

Interconnection Potential Background

To estimate interconnection potential across the WECC, E3 leveraged results from a 2012 analysis, Technical Potential for Local Distributed Photovoltaics in California

Study produced estimates of the amount of “local” distributed PV (LDPV) potential under different interconnection standards in California:

1. Rule 21 (Current Policy): sum of rated capacity of interconnections on a feeder may not exceed 15% of the feeder’s peak load

2. 30% Rule: same as (1), but with constraint relaxed to 30%

3. Max w/o Curtailment: the maximum capacity that can be installed on a feeder for which all generation will serve load on that feeder (e.g. no required backflow or curtailment)

In 2012 study cycle, E3 generalized these results to the WECC BAs; the same method is used to determine limits in this study cycle

• 30% Rule for 2024 High DG projections

• Max w/o Curtailment for 2034 High DG projections

14

Capital Cost Trajectories

Reference case cost reduction trajectory derived through application of learning curve approach

• 20% learning rate on modules; 15% on BOS

• IEA medium-term renewable energy outlook

• Adopted by TEPPC

Aspirational case cost reduction trajectory assumes achievement of Sunshot goals by 2020

• $1.50/W residential

• $1.25/W commercial

$4.11$3.23

$2.83

$1.50 $1.50$0

$2

$4

$6

$8

2010 2014 2018 2022 2026 2030 2034

Residential Costs (2013 $/W-dc)

Reference

Aspirational

$3.54$2.80 $2.45

$1.25 $1.25$0

$2

$4

$6

$8

2010 2014 2018 2022 2026 2030 2034

Commercial Costs (2013 $/W-dc)

Reference

Aspirational

15

Other Key Assumptions

No changes in retail rate design

• Surplus NEM generation is compensated at full retail rate

• EXCEPTION: in California, after 2017, exports are assumed to be compensated at avoided cost (see Slide 30)

Retail rates escalate at 0.5% per year in real terms

Federal ITC sunsets in 2017

• Credit reduces to 10% of capital costs thereafter

Current state incentive programs sunset after current NEM cap is exceeded

• e.g. Washington & Oregon (see Slide 31)

16

High DG Case projections

2024 Projections

Reference Case projections

0

5,000

10,000

15,000

20,000

25,000

2012 2014 2016 2018 2020 2022 2024

Inst

alle

d Ca

paci

ty (M

W)

WECC-US2012 - 2024

2024Market Peak Market

Driven DG Load Driven DGState (MW) (MW) (% of Peak)

Arizona 3,533 23,227 15.2%California 12,305 68,908 17.9%Colorado 2,301 11,789 19.5%Idaho 351 5,664 6.2%Montana 249 2,483 10.0%New Mexico 613 5,139 11.9%Nevada 1,023 9,951 10.3%Oregon 812 10,392 7.8%Utah 574 5,537 10.4%Washington 639 20,950 3.1%Wyoming 248 3,464 7.2%

Total 22,648 167,505 13.5%

0

5,000

10,000

15,000

20,000

25,000

2012 2014 2016 2018 2020 2022 2024

Inst

alle

d Ca

paci

ty (M

W)

WECC-US2012 - 2024

2024Market Peak Market

Driven DG Load Driven DGState (MW) (MW) (% of Peak)

Arizona 1,751 23,227 7.5%California 5,742 68,908 8.3%Colorado 742 11,789 6.3%Idaho 51 5,664 0.9%Montana 35 2,483 1.4%New Mexico 170 5,139 3.3%Nevada 241 9,951 2.4%Oregon 191 10,392 1.8%Utah 106 5,537 1.9%Washington 90 20,950 0.4%Wyoming 47 3,464 1.4%

Total 9,166 167,505 5.5%

Incremental Additions

Incremental Additions

17

Comparison to 2022 High DG Recommendations

2022 and 2024 High DG projections have similar quantities of distributed generation capacity, but show a regional shift

• Relative increases in California, Colorado

• Slight decreases in states in the Pacific Northwest

2022 2024High DG High DG Change

State (MW) (MW) (MW)Arizona 3,650 3,533 (117) California 11,670 12,305 635 Colorado 1,410 2,301 891 Idaho 550 351 (199) Montana 160 249 89 New Mexico 600 613 13 Nevada 1,090 1,023 (67) Oregon 1,240 812 (428) Utah 690 574 (116) Washington 1,090 639 (451) Wyoming 510 248 (262)

Total 22,660 22,648 (12)

Notable decreases from 2022

Notable increases from 2022

18

2034Market Peak Market

Driven DG Load Driven DGState (MW) (MW) (% of Peak)

Arizona 4,495 27,833 16.1%California 17,852 78,325 22.8%Colorado 3,426 12,749 26.9%Idaho 493 6,312 7.8%Montana 345 2,763 12.5%New Mexico 773 5,954 13.0%Nevada 1,274 11,489 11.1%Oregon 1,067 11,794 9.0%Utah 739 5,481 13.5%Washington 852 23,560 3.6%Wyoming 333 3,955 8.4%

Total 31,650 190,215 16.6%

2034Market Peak Market

Driven DG Load Driven DGState (MW) (MW) (% of Peak)

Arizona 2,314 27,833 8.3%California 6,816 78,325 8.7%Colorado 1,133 12,749 8.9%Idaho 93 6,312 1.5%Montana 65 2,763 2.3%New Mexico 251 5,954 4.2%Nevada 307 11,489 2.7%Oregon 234 11,794 2.0%Utah 181 5,481 3.3%Washington 95 23,560 0.4%Wyoming 82 3,955 2.1%

Total 11,570 190,215 6.1%0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034

Inst

alle

d Ca

paci

ty (M

W)

WECC-US2012 - 2034

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034

Inst

alle

d Ca

paci

ty (M

W)

WECC-US2012 - 2034

High DG Case projections

2034 Projections

Reference Case projections

DETAILED PROJECTIONS BY LOAD AREA

20

2024 High DG Projections

Total capacity: 22,648 MW

Load Area

Distributed PV Capacity

(MW)Peak Load

(MW)Capacity

(% of Peak)AESO - 16,370 0.0%APS 1,548 8,512 18.2%AVA 129 2,571 5.0%BCHA - 11,603 0.0%BPA 394 12,023 3.3%CFE - 2,753 0.0%CHPD 18 803 2.3%DOPD 13 500 2.6%EPE 70 2,346 3.0%FAR EAST 34 420 8.2%GCPD 14 1,029 1.4%IID 74 1,198 6.2%LDWP 1,032 5,826 17.7%MAGIC VLY 75 884 8.5%NEVP 747 4,937 15.1%NWMT 207 2,324 8.9%PACE_ID 49 878 5.5%PACE_UT 576 5,642 10.2%PACE_WY 141 1,829 7.7%PACW 263 4,387 6.0%

Load Area

Distributed PV Capacity

(MW)Peak Load

(MW)Capacity

(% of Peak)PG&E_BAY 2,234 12,792 17.5%PG&E_VLY 2,813 12,517 22.5%PGN 441 4,828 9.1%PNM 490 3,472 14.1%PSC 1,645 7,235 22.7%PSE 204 5,222 3.9%SCE 4,534 23,779 19.1%SCL 57 2,709 2.1%SDGE 933 4,520 20.6%SMUD 495 3,206 15.4%SPP 322 3,603 8.9%SRP 1,240 8,484 14.6%TEP 434 4,151 10.5%TIDC 117 603 19.5%TPWR 19 1,137 1.7%TREAS VLY 153 1,924 7.9%WACM 821 5,529 14.8%WALC 294 2,460 12.0%WAUW 19 152 12.2%

21

2034 High DG Projections

Total capacity: 31,650 MW

Load Area

Distributed PV Capacity

(MW)Peak Load

(MW)Capacity

(% of Peak)AESO - 22,683 0.0%APS 1,990 9,715 20.5%AVA 177 2,920 6.1%BCHA - 12,948 0.0%BPA 553 13,930 4.0%CFE - 3,513 0.0%CHPD 27 990 2.7%DOPD 18 638 2.8%EPE 87 2,891 3.0%FAR EAST 49 500 9.7%GCPD 20 1,199 1.6%IID 91 1,449 6.3%LDWP 1,327 6,550 20.3%MAGIC VLY 103 889 11.6%NEVP 925 5,548 16.7%NWMT 282 2,541 11.1%PACE_ID 67 988 6.8%PACE_UT 740 5,523 13.4%PACE_WY 181 1,891 9.5%PACW 347 4,633 7.5%

Load Area

Distributed PV Capacity

(MW)Peak Load

(MW)Capacity

(% of Peak)PG&E_BAY 3,237 14,225 22.8%PG&E_VLY 4,247 14,478 29.3%PGN 571 5,644 10.1%PNM 607 3,679 16.5%PSC 1,965 7,105 27.7%PSE 262 5,602 4.7%SCE 6,605 26,716 24.7%SCL 75 2,852 2.6%SDGE 1,437 5,331 27.0%SMUD 620 3,480 17.8%SPP 422 4,487 9.4%SRP 1,509 10,321 14.6%TEP 513 4,693 10.9%TIDC 174 710 24.5%TPWR 26 1,252 2.1%TREAS VLY 206 2,171 9.5%WACM 1,108 7,136 15.5%WALC 470 3,910 12.0%WAUW 26 172 15.4%

Thank You!Energy and Environmental Economics, Inc. (E3)

101 Montgomery Street, Suite 1600

San Francisco, CA 94104

Tel 415-391-5100

Web http://www.ethree.com

MARKET-DRIVEN DG: METHODOLOGY AND ASSUMPTIONS

24

General Model Logic

E3’s Market-Driven DG model combines a customer decision model with policy targets and NEM caps to provide a comprehensive assessment of behind-the-meter solar PV in the Western Interconnect

Modeling steps:

1. Assess potential size of distributed solar PV market based on economics

2. Adjust forecast upward to meet any policy targets

3. Limit total installations based on state net metering caps

25

Step 1: Market-Driven Adoption

1. Determine payback period

Payback

-$4,000

-$3,000

-$2,000

-$1,000

$0

$1,000

$2,000

$3,000

$4,000

0 5 10 15

Cum

ulati

ve N

et C

ost (

$)

Years Since Installation

2. Determine max market share

3. Fit logistic curve

t-1t

0%

1%

2%

3%

4%

5%

6%

7%

8%

0 5 10 15 20 25

Mar

ket P

enet

ratio

n (%

)

Years

4. Apply to technical potential

7%

0%

20%

40%

60%

80%

100%

0 5 10 15 20 25 30 35

Max

imum

Mar

ket S

hare

(%)

Payback Period

Technical potenial MW

x Market penetration at t %

= Installed capacity at t MW

26

Calculating the Payback Period

The payback period is the first year in which a customer who choose to install solar PV will have a net positive cash flow

To determine the payback period, E3 considers:

• System capital costs: costs of purchasing & installing a PV system

• Operating & maintenance costs: costs of year-to-year maintenance, including inverter replacement

• Federal tax credits: investment tax credit (30% until 2017; 10% thereafter)

• State & local incentives: up-front & performance-based incentives, vary by utility & state

• Bill savings: reductions monthly energy bills, vary by utility

• Green premium: a non-financial value that a customer derives from having invested in solar PV (assumed to be 1 cent/kWh)

27

Solar PV Capital Costs by Installation Vintage

Installed PV cost assumptions based on draft recommendations for PV capital costs developed by E3

• Presented to TAS on December 19

Future cost reductions primarily reflect lower balance-of-systems costs

Historical

$4.8

$3.6$4.0

$3.0

$0

$1

$2

$3

$4

$5

$6

$7

$8

$9

$10

2010 2012 2014 2016 2018 2020 2022 2024

Inst

alle

d Co

st (2

014

$/W

-dc)

Residential

Commercial

28

Solar PV Costs by State

System average costs are adjusted for each state to capture regional variations in costs

• Regional adjustments based on LBNL’s Tracking the Sun VI

$5.1$4.8

$4.6$4.3 $4.3

$3.7$3.5

$4.2$4.0 $3.9

$3.6 $3.6

$3.1$2.9

$4.8 $4.6 $4.6 $4.6 $4.5

$3.9 $3.8 $3.8 $3.8 $3.7

$0

$1

$2

$3

$4

$5

$6

CA NM WA OR MT ID UT WY NV AZ CO TX

2013

Inst

alle

d Co

sts

(201

4 $/

W-d

c)

Residential

Commercial

Where Tracking the Sun VI did not report PV costs, costs were interpolated based on the Army Corps of Engineer’s Construction Works Cost Index

29

All WECC states currently allow net metering, under which a customer is compensated for PV output based on its retail rate

• This is the primary economic benefit to a customer who chooses to install distributed PV

Market adoption model includes utility-specific rate information for 30 large utilities in the West (a subset are shown below)

• For other smaller utilities, a state-specific average retail rate is used

$0.00

$0.05

$0.10

$0.15

$0.20

$0.25

$0.30

$0.35

2013

Res

iden

tial R

etai

l Rat

e ($

/kW

h)

Avoided Energy Cost

California: IOUs’ high tiered rates provide strong incentive to

customers

Northwest: Low-cost hydropower keeps

rates lowSouthwest Rocky Mountains

General trend in retail rates

30

Changes to Avoided Energy Cost over Time

E3 assumes that utilities continue to compensate customers at their full retail rate throughout the analysis horizon with one exception

• Real escalation of 0.5% per year is assumed

California’s AB 327 directs the CPUC to implement a standard NEM tariff beginning in July 2017

As this tariff has not yet been defined, E3 has chosen to model it in the following manner:

• All generation consumed on-site is compensated at the customer’s retail rate

• 50% for residential systems, 70% for commercial systems (based on CPUC NEM study)

• All generation exported to the grid is compensated at the utility’s long-run avoided cost (based on a CCGT)

31

State-Specific Incentives

Payback period is also heavily influenced by state incentive programs

E3’s model captures the impact of two large incentive programs:

• Renewable Energy Cost Recovery Program (WA)

• Performance-based incentive capped at $5,000 per year

• Program ends in 2020

• Residential Energy Tax Credit (OR)

• Incentive of $2.1/W-dc, capped at $6,000

• Program ends in 2018

Note: incentives linked to specific policy targets (e.g. set-asides, program goals) are not modeled explicitly and are instead accounted for by adjusting market-driven forecast upward to meet policy goals

32

Sample Payback Period Results, 2013 Residential Systems

Payback periods vary widely across the WECC geography as a function of:

• System costs

• Incentives

• Retail rates

• Capacity factors

Utility StateCost

($/W-ac)ITC (%)

Incentive ($/W-ac)

Incentive ($/kWh)

Retail Rate ($/kWh)

Capacity Factor (%)

Payback(yrs)

Arizona Public Service Co AZ 5.06$ 30% -$ -$ 0.13$ 22% 12

Pacific Gas & Electric Co CA 6.02$ 30% -$ -$ 0.31$ 20% 7

Public Service Co of Colorado CO 4.39$ 30% -$ -$ 0.12$ 20% 13

Idaho Power Co ID 5.39$ 30% -$ -$ 0.09$ 19% 20

NorthWestern Energy LLC - (MT) MT 5.43$ 30% -$ -$ 0.11$ 17% 19

Public Service Co of NM NM 5.66$ 30% -$ -$ 0.13$ 23% 13

Nevada Power Co NV 5.06$ 30% -$ -$ 0.12$ 22% 13

Portland General Electric Co OR 5.46$ 30% 1.25$ -$ 0.10$ 15% 17

PacifiCorp UT 5.39$ 30% -$ -$ 0.11$ 19% 17

Puget Sound Energy Inc WA 5.60$ 30% -$ 0.15$ 0.10$ 14% 11

33

Modeling Solar PV Adoption

NREL’s Solar Deployment System (SolarDS) model provides one of the more transparent forecasts of PV adoption:

• “…a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of photovoltaics (PV) on residential and commercial rooftops in the continental United States through 2030”

Much of the logic used in the Adoption Module has been adapted from SolarDS:

• Maximum market share as a function of payback period

• Logistic curves for adoption

Documentation for SolarDS model: http://www.nrel.gov/docs/fy10osti/45832.pdf(Figures taken from this document)

34

Assumed Payback Curves

Payback curves are based on functional forms documented in SolarDS model

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 5 10 15 20 25 30

Max

imum

Mar

ket S

hare

(% o

f tec

hnic

al

pote

ntial

)

Payback Period

Res Existing

Res New

Com Existing

Com New

Utility StatePayback

(yrs)

Maximum Market

Share (%)

Arizona Public Service Co AZ 12 2.7%

Pacific Gas & Electric Co CA 7 12.2%

Public Service Co of Colorado CO 13 2.0%

Idaho Power Co ID 20 0.2%

NorthWestern Energy LLC - (MT) MT 19 0.3%

Public Service Co of NM NM 13 2.0%

Nevada Power Co NV 13 2.0%

Portland General Electric Co OR 15 1.1%

PacifiCorp UT 17 0.6%

Puget Sound Energy Inc WA 11 3.7%

35

Assumed Technical Potential

E3 calculates technical potential by specifying:

1. The percentage of total customers that could feasibly install solar PV (50% for residential and commercial)

2. The representative system size for a typical install (4 kW for residential; 50 kW for commercial)

Resulting assumed technical potential aligns well with NREL’s assessment of rooftop PV technical potential on a state level:

Total technical potential is approximately 150 GW in 20100

10

20

30

40

50

60

70

80

AZ CA CO ID MT NM NV OR UT WA WY

Rooft

op P

V Te

chni

cal P

oten

tial

(GW

)

E3 Assumed Technical Potential

NREL Modeled Technical Potential

Source: U.S. Renewable Energy

Technical Potentials: A GIS-

Based Analysis (NREL)

36

Step 2: Policy Adjustments

A large number of states have enacted policies to encourage the deployment of distributed solar PV

In cases where the market-based adoption forecast falls short of state policy targets, upward adjustments are made to reflect achievement of current policy

• Assumes utilities will fund programs to reach targets

State Policy

Arizona RPS DG Set-Aside (4.5% of IOU/coop retail sales by 2025)

California California Solar Initiative (2,300 MW for IOUs; 700 MW for publics)

Colorado RPS DG set-aside (3% of IOU 2020 retail sales; 1% of public utility 2020 retail sales)

New Mexico RPS DG set-aside (0.6% of 2020 retail sales)

Nevada Nevada Solar Incentives Program (36 MW among NVE and SPP)

Oregon Energy Trust (124 MW among PGE and PacifiCorp)Solar Volumetric Incentive and Payments Program (27.5 MW among PGE, PacifiCorp, and IPC)

37

Policy Adjustments

For each utility, initial market-driven DG forecast is adjusted upward in each year it is short of policy targets

Illustrative example shown for APS

0

100

200

300

400

500

600

700

800

900

2010 2012 2014 2016 2018 2020 2022 2024

Inst

alle

d Ca

paci

ty (M

W)

Market-Driven DG Policy Target

38

Step 3: Adjust for Net Metering Policy

Common Case projections assume all current NEM caps remain in place

• Arizona, Colorado, Montana, New Mexico, Wyoming: no cap

• Oregon & Washington: 0.5% of utility peak

• Idaho: 0.1% of utility peak

• Nevada: 3% of utility peak

• California: 5% of noncoincident peak (currently)

Common Case projections assume these caps remain in place throughout the analysis

• Exception: California’s AB 327 lifts the existing NEM cap beginning in 2017 with the implementation of a standard NEM tariff

39

NEM Adjustments

For each utility whose installed capacity would be constrained by a NEM cap, installation forecast is adjusted downward to the limit

Illustrative example shown for Puget Sound

0

50

100

150

200

250

300

2010 2012 2014 2016 2018 2020 2022 2024

Inst

alle

d Ca

paci

ty (M

W)

Market-Driven DG Policy Target