Distributed Generation
Projections for High DG Case
October 10, 2014
Arne Olson, Partner
Nick Schlag, Sr. Consultant
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
2
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
3
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
4
MODELING MARKETDRIVEN DG
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
Channels for Distributed Solar PV Adoption
Program Goals
(e.g. California Solar Initiative)
RPS Set-Asides
Policy-driven DG,
modeled in past
WECC studies
(e.g. 30% DG set-aside in Arizona)
Market-Driven
Adoption
New to WECC
studies
6
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 costeffectiveness 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)
7
2024 Common Case
Recommendations
The Market-Driven DG Model used to develop preliminary
recommendations for customer-sited solar for the 2024
Common Case
Market
Driven DG
State
(MW)
Arizona
1,751
California
5,742
Colorado
742
Idaho
51
Montana
35
New Mexico
170
Nevada
241
Oregon
191
Utah
106
Washington
90
Wyoming
47
Total
9,166
2024
Peak
Market
Load
Driven DG
(MW) (% of Peak)
23,227
7.5%
68,908
8.3%
11,789
6.3%
5,664
0.9%
2,483
1.4%
5,139
3.3%
9,951
2.4%
10,392
1.8%
5,537
1.9%
20,950
0.4%
3,464
1.4%
167,505
5.5%
For the 2024 Common
Case, TAS adjusted
the recommended
values (shown at left)
downward by 20%
8
HIGH DG CASE
RECOMMENDATIONS
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
Affect customer decision
to invest in solar PV
Limit total penetration
on a utility’s system
Changing the assumptions for each of these parameters
provides the basis for exploring alternative projections
10
Overview of Assumptions
High DG projections are developed by relaxing
existing NEM caps and assuming achievement of
aspirational solar PV cost reductions
Assumption
Reference Case
Current Policy
Net Metering Caps
•
•
Solar PV Cost Trends
Current NEM caps remain in
place
California cap lifted after 2016
Moderate Reductions
•
Cost trajectory derived by E3
for TEPPC planning studies
High DG Case
NEM Caps Removed
•
•
All NEM caps lifted
Limits associated with
interconnection potential
enforced
Aspirational Reductions
•
Sunshot goals achieved by
2020
11
Treatment of NEM Caps
In the Reference Case, each state’s NEM cap was enforced
according to current policy
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
High DG case assumes current NEM caps are removed, allowing
installations of DG in each utility’s service territory up to its
‘Interconnection Potential’
12
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
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
20,000
Incremental PV Potential (MW)
Study produced estimates of the amount of
“local” distributed PV (LDPV) potential
under different interconnection standards in
California:
15,336
15,000
11,668
10,000
6,638
5,000
0
Rule 21
•
30% Rule for 2024 High DG projections
Residential Rooftop
•
Max w/o Curtailment for 2034 High DG
projections
Ground Mounted
30% Rule
Max w/o
Curtailment
Commercial Rooftop
13
Capital Cost Trajectories
Reference case cost
reduction trajectory
derived through
application of learning
curve approach
Residential Costs (2013 $/W-dc)
$8
$4.11
$2
•
IEA medium-term
renewable energy outlook
$0
2010
Aspirational case cost
reduction trajectory
assumes achievement of
Sunshot goals by 2020
$3.23
$4
20% learning rate on
modules; 15% on BOS
Adopted by TEPPC
Aspirational
$6
•
•
Reference
$2.83
$1.50
2014
2018
2022
$1.50
2026
2030
2034
Commercial Costs (2013 $/W-dc)
$8
Reference
Aspirational
$6
$4
•
$1.50/W residential
$2
•
$1.25/W commercial
$0
2010
$3.54
$2.80
$2.45
$1.25
2014
2018
2022
$1.25
2026
2030
2034
14
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)
15
2024 Projections
Reference Case projections
WECC-US
2012 - 2024
20,000
15,000
10,000
Incremental
Additions
5,000
Installed Capacity (MW)
25,000
0
2012
2014
2016
2018
2020
2022
2024
Market
Driven DG
State
(MW)
Arizona
1,751
California
5,742
Colorado
742
Idaho
51
Montana
35
New Mexico
170
Nevada
241
Oregon
191
Utah
106
Washington
90
Wyoming
47
Total
9,166
2024
Peak
Market
Load
Driven DG
(MW) (% of Peak)
23,227
7.5%
68,908
8.3%
11,789
6.3%
5,664
0.9%
2,483
1.4%
5,139
3.3%
9,951
2.4%
10,392
1.8%
5,537
1.9%
20,950
0.4%
3,464
1.4%
167,505
5.5%
Market
Driven DG
State
(MW)
Arizona
3,533
California
12,305
Colorado
2,301
Idaho
351
Montana
249
New Mexico
613
Nevada
1,023
Oregon
812
Utah
574
Washington
639
Wyoming
248
Total
22,648
2024
Peak
Market
Load
Driven DG
(MW) (% of Peak)
23,227
15.2%
68,908
17.9%
11,789
19.5%
5,664
6.2%
2,483
10.0%
5,139
11.9%
9,951
10.3%
10,392
7.8%
5,537
10.4%
20,950
3.1%
3,464
7.2%
167,505
13.5%
High DG Case projections
WECC-US
2012 - 2024
20,000
15,000
Incremental
Additions
10,000
5,000
0
2012
2014
2016
2018
2020
2022
2024
Installed Capacity (MW)
25,000
16
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
State
Arizona
California
Colorado
Idaho
Montana
New Mexico
Nevada
Oregon
Utah
Washington
Wyoming
Total
2022
High DG
(MW)
3,650
11,670
1,410
550
160
600
1,090
1,240
690
1,090
510
22,660
2024
High DG
(MW)
3,533
12,305
2,301
351
249
613
1,023
812
574
639
248
22,648
Change
(MW)
(117)
635
891
(199)
89
13
(67)
(428)
(116)
(451)
(262)
(12)
Notable
increases
from 2022
Notable
decreases
from 2022
17
2034 Projections
Reference Case projections
WECC-US
2012 - 2034
30,000
25,000
20,000
15,000
10,000
5,000
Installed Capacity (MW)
35,000
0
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034
Market
Driven DG
State
(MW)
Arizona
2,314
California
6,816
Colorado
1,133
Idaho
93
Montana
65
New Mexico
251
Nevada
307
Oregon
234
Utah
181
Washington
95
Wyoming
82
Total
11,570
2034
Peak
Market
Load
Driven DG
(MW) (% of Peak)
27,833
8.3%
78,325
8.7%
12,749
8.9%
6,312
1.5%
2,763
2.3%
5,954
4.2%
11,489
2.7%
11,794
2.0%
5,481
3.3%
23,560
0.4%
3,955
2.1%
190,215
6.1%
Market
Driven DG
State
(MW)
Arizona
4,495
California
17,852
Colorado
3,426
Idaho
493
Montana
345
New Mexico
773
Nevada
1,274
Oregon
1,067
Utah
739
Washington
852
Wyoming
333
Total
31,650
2034
Peak
Market
Load
Driven DG
(MW) (% of Peak)
27,833
16.1%
78,325
22.8%
12,749
26.9%
6,312
7.8%
2,763
12.5%
5,954
13.0%
11,489
11.1%
11,794
9.0%
5,481
13.5%
23,560
3.6%
3,955
8.4%
190,215
16.6%
High DG Case projections
WECC-US
2012 - 2034
30,000
25,000
20,000
15,000
10,000
5,000
0
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034
Installed Capacity (MW)
35,000
18
DETAILED PROJECTIONS
BY LOAD AREA
2024 High DG Projections
Total capacity: 22,648 MW
Load Area
AESO
APS
AVA
BCHA
BPA
CFE
CHPD
DOPD
EPE
FAR EAST
GCPD
IID
LDWP
MAGIC VLY
NEVP
NWMT
PACE_ID
PACE_UT
PACE_WY
PACW
Distributed PV
Capacity
(MW)
1,548
129
394
18
13
70
34
14
74
1,032
75
747
207
49
576
141
263
Peak Load
(MW)
16,370
8,512
2,571
11,603
12,023
2,753
803
500
2,346
420
1,029
1,198
5,826
884
4,937
2,324
878
5,642
1,829
4,387
Capacity
(% of Peak)
0.0%
18.2%
5.0%
0.0%
3.3%
0.0%
2.3%
2.6%
3.0%
8.2%
1.4%
6.2%
17.7%
8.5%
15.1%
8.9%
5.5%
10.2%
7.7%
6.0%
Load Area
PG&E_BAY
PG&E_VLY
PGN
PNM
PSC
PSE
SCE
SCL
SDGE
SMUD
SPP
SRP
TEP
TIDC
TPWR
TREAS VLY
WACM
WALC
WAUW
Distributed PV
Capacity
(MW)
2,234
2,813
441
490
1,645
204
4,534
57
933
495
322
1,240
434
117
19
153
821
294
19
Peak Load
(MW)
12,792
12,517
4,828
3,472
7,235
5,222
23,779
2,709
4,520
3,206
3,603
8,484
4,151
603
1,137
1,924
5,529
2,460
152
Capacity
(% of Peak)
17.5%
22.5%
9.1%
14.1%
22.7%
3.9%
19.1%
2.1%
20.6%
15.4%
8.9%
14.6%
10.5%
19.5%
1.7%
7.9%
14.8%
12.0%
12.2%
20
2034 High DG Projections
Total capacity: 31,650 MW
Load Area
AESO
APS
AVA
BCHA
BPA
CFE
CHPD
DOPD
EPE
FAR EAST
GCPD
IID
LDWP
MAGIC VLY
NEVP
NWMT
PACE_ID
PACE_UT
PACE_WY
PACW
Distributed PV
Capacity
(MW)
1,990
177
553
27
18
87
49
20
91
1,327
103
925
282
67
740
181
347
Peak Load
(MW)
22,683
9,715
2,920
12,948
13,930
3,513
990
638
2,891
500
1,199
1,449
6,550
889
5,548
2,541
988
5,523
1,891
4,633
Capacity
(% of Peak)
0.0%
20.5%
6.1%
0.0%
4.0%
0.0%
2.7%
2.8%
3.0%
9.7%
1.6%
6.3%
20.3%
11.6%
16.7%
11.1%
6.8%
13.4%
9.5%
7.5%
Load Area
PG&E_BAY
PG&E_VLY
PGN
PNM
PSC
PSE
SCE
SCL
SDGE
SMUD
SPP
SRP
TEP
TIDC
TPWR
TREAS VLY
WACM
WALC
WAUW
Distributed PV
Capacity
(MW)
3,237
4,247
571
607
1,965
262
6,605
75
1,437
620
422
1,509
513
174
26
206
1,108
470
26
Peak Load
(MW)
14,225
14,478
5,644
3,679
7,105
5,602
26,716
2,852
5,331
3,480
4,487
10,321
4,693
710
1,252
2,171
7,136
3,910
172
Capacity
(% of Peak)
22.8%
29.3%
10.1%
16.5%
27.7%
4.7%
24.7%
2.6%
27.0%
17.8%
9.4%
14.6%
10.9%
24.5%
2.1%
9.5%
15.5%
12.0%
15.4%
21
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
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 behindthe-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
24
Step 1: Market-Driven Adoption
Cumulative Net Cost ($)
$4,000
$3,000
$2,000
Payback
$1,000
$0
-$1,000
0
5
10
15
-$2,000
-$3,000
100%
80%
60%
40%
20%
7%
0%
0
-$4,000
Years Since Installation
5
10
15
20
Technical potenial
7%
6%
5%
t
t-1
3%
30
35
4. Apply to technical potential
8%
4%
25
Payback Period
3. Fit logistic curve
Market Penetration (%)
Maximum Market Share (%)
2. Determine max market share
1. Determine payback period
MW
x Market penetration at t
%
= Installed capacity at t
MW
2%
1%
0%
0
5
10
15
20
25
Years
25
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)
26
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 balanceof-systems costs
$10
$9
Installed Cost (2014 $/W-dc)
Residential
Historical
Commercial
$8
$7
$6
$4.8
$5
$4.0
$4
$3.6
$3.0
$3
$2
$1
$0
2010
2012
2014
2016
2018
2020
2022
2024
27
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
2013 Installed Costs (2014 $/W-dc)
$6
Residential
$5.1
$4.8
$5
$4.2
$4
Commercial
$4.8
$4.0
$4.6
$3.9
$4.6
$3.9
$4.6
$3.8
$4.6
$3.8
$4.5
$3.8
$4.3
$3.7
$4.3
$3.6
$3.6
$3.7
$3.5
$3.1
$3
$2.9
$2
$1
$0
CA
NM
WA
OR
MT
ID
UT
WY
NV
AZ
CO
TX
Where Tracking the Sun VI did not report PV costs, costs were interpolated based on
the Army Corps of Engineer’s Construction Works Cost Index
28
Avoided Energy Cost
All WECC states currently allow net metering, under which a customer is
compensated for PV output based on its retail rate
•
This is the primary economic benefit to a customer who chooses to install distributed PV
Market adoption model includes utility-specific rate information for 30
large utilities in the West (a subset are shown below)
2013 Residential Retail Rate ($/kWh)
•
For other smaller utilities, a state-specific average retail rate is used
California: IOUs’ high
tiered rates provide
strong incentive to
customers
$0.35
$0.30
Southwest
Rocky Mountains
Northwest: Low-cost
hydropower keeps
rates low
General trend in retail rates
$0.25
$0.20
$0.15
$0.10
$0.05
$0.00
29
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)
30
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 $6,000
• Program ends in 2018
Note: incentives linked to specific policy targets (e.g. setasides, program goals) are not modeled explicitly and are
instead accounted for by adjusting market-driven forecast
upward to meet policy goals
31
Sample Payback Period Results,
2013 Residential Systems
Payback periods vary widely across the WECC
geography as a function of:
• System costs
• Retail rates
• Incentives
• Capacity factors
Cost
($/W-ac)
ITC
(%)
Incentive
($/W-ac)
Incentive
($/kWh)
Retail Rate
($/kWh)
Capacity
Factor (%)
Payback
(yrs)
Utility
State
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
32
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)
33
Assumed Payback Curves
Payback curves are based on functional forms
documented in SolarDS model
Maximum Market Share (% of technical
potential)
100%
Res Existing
90%
Res New
80%
Maximum
Market
Share (%)
Payback
(yrs)
Com Existing
Utility
State
Com New
Arizona Public Service Co
AZ
12
2.7%
60%
Pacific Gas & Electric Co
CA
7
12.2%
50%
Public Service Co of Colorado
CO
13
2.0%
40%
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%
70%
30%
20%
10%
0%
0
5
10
15
Payback Period
20
25
30
34
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)
Rooftop PV Technical Potential
(GW)
Resulting assumed technical potential aligns well with NREL’s
assessment of rooftop PV technical potential on a state level:
80
E3 Assumed Technical Potential
70
NREL Modeled Technical Potential
Source: U.S.
Renewable Energy
Technical
Potentials: A GISBased Analysis
(NREL)
60
50
40
30
20
10
0
AZ
CA
CO
ID
MT
NM
NV
OR
UT
WA
WY
Total technical potential is approximately 150 GW in 2010
35
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)
36
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
900
Market-Driven DG
Policy Target
Installed Capacity (MW)
800
700
600
500
400
300
200
100
0
2010
2012
2014
2016
2018
2020
2022
2024
37
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
38
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
Installed Capacity (MW)
300
Market-Driven DG
Policy Target
250
200
150
100
50
0
2010
2012
2014
2016
2018
2020
2022
2024
39