BEFORE THE PUBLIC UTILITIES COMMISSION OF THE STATE OF COLORADO Proceeding No. 15A-______E ______________________________________________________________________________ IN THE MATTER OF THE APPLICATION OF BLACK HILLS/COLORADO ELECTRIC UTILITY COMPANY, LP FOR APPROVAL OF ITS ELECTRIC DEMAND SIDE MANAGEMENT (DSM) PLAN FOR PROGRAM YEARS 2016 – 2018 AND FOR APPROVAL OF UPDATES TO ITS ELECTRIC DSM COST ADJUSTMENT TARIFF. ______________________________________________________________________________
DIRECT TESTIMONY AND ATTACHMENTS OF
Colorado PUC E-Filings System
ANDREW W. COTTRELL ON BEHALF OF BLACK HILLS/COLORADO ELECTRIC UTILITY COMPANY, LP
May 29, 2015
ATTACHMENTS
Attachment AWC-1:
Black Hills/Colorado Electric Utility Company, LP Demand Side Management (DSM) Potential Study
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 1
I.
1
IDENTIFICATION OF WITNESS
2
Q.
PLEASE STATE YOUR NAME AND BUSINESS ADDRESS.
3
A.
My name is Andrew W. Cottrell. My business address is 317 George Street, Suite 305, New Brunswick, NJ 08901.
4 5
Q.
BY WHOM ARE YOU EMPLOYED AND IN WHAT CAPACITY?
6
A.
I am employed by Applied Energy Group, Inc. (“AEG”), a wholly-owned subsidiary of
7
Ameresco, Inc., as Principal Consultant in the Energy Analysis and Planning team. AEG
8
is a consultant retained by Black Hills/Colorado Electric Utility Company, LP (“Black
9
Hills” or the “Company”). In connection with this Proceeding, AEG was contracted by
10
Black Hills to conduct a DSM Potential Study to assess the electric energy efficiency
11
potential within the Black Hills service territory for the Company’s 2016-2018 Colorado
12
Electric Demand Side Management Plan (“2016-2018 DSM Plan”). AEG also assisted
13
the Company in development of the 2016-2018 DSM Plan.
14
Q.
PLEASE DESCRIBE YOUR EDUCATIONAL BACKGROUND AND BUSINESS BACKGROUND.
15 16
A.
My educational background and employment history are attached as Appendix A.
17
Q.
ON WHOSE BEHALF ARE YOU TESTIFYING?
18
A.
I am testifying on behalf of Black Hills.
19
Q.
HAVE YOU PREVIOUSLY TESTIFIED BEFORE THIS COMMISSION?
20
A.
No.
21
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 2
II.
1
PURPOSE OF TESTIMONY
2
Q.
WHAT IS THE PURPOSE OF YOUR TESTIMONY?
3
A.
The purpose of my direct testimony is to sponsor Black Hills’ Demand Side Management
4
(“DSM”) Potential Study (the “DSM Potential Study” or “Study”), which is attached to
5
my testimony as Attachment AWC-1, and to provide supplemental technical information
6
regarding development of the Company’s 2016-2018 DSM Plan. I explain how the Study
7
was designed, how the DSM Potential was estimated and how the Study informed the
8
2016-2018 DSM Plan. III.
9
DSM POTENTIAL STUDY PURPOSE AND DESIGN
10
Q.
WHAT IS THE PURPOSE OF THE DSM POTENTIAL STUDY?
11
A.
The DSM Potential Study provides a market potential assessment of electricity savings
12
for residential, commercial and industrial customers within the Black Hills service
13
territory. The Study provides estimates of potential reductions in annual electricity energy
14
use and peak demand from energy efficiency efforts carried out by electricity customers
15
within the Black Hills service territory. The Study provides energy efficiency savings
16
estimates for the three-year DSM Plan period, 2016-2018, in addition to estimates out
17
through 2025.
18
Q.
WHO PREPARED THE DSM POTENTIAL STUDY?
19
A.
AEG prepared the DSM Potential Study. The Study is an update of work performed by
20
AEG during 2011-2012 for the Company’s 2012-2015 DSM Plan. The scope of the Study
21
is similar to the potential study completed in support of the Company’s 2012-2015 DSM
22
Plan. However, AEG conducted the current study using its Load Management and
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 3
1
Analysis and Planning tool (“LoadMAPTM”), a rigorous end-use model that utilizes a
2
robust analytical framework that includes stock-accounting algorithms, equipment
3
saturations, vintage distributions, results from engineering simulations and other market
4
data.
5
Q.
HOW WAS THE DSM POTENTIAL STUDY DESIGNED?
6
A.
The study methodology was designed to be consistent with industry best practices,
7
including the National Action Plan for Energy Efficiency (“NAPEE”) guidelines. The
8
general concepts and steps to completing a potential study from the NAPEE guidelines
9
were closely followed and presented in Attachment AWC-1. Using data provided by
10
Black Hills, including primary data collected for the previous potential study, and
11
secondary sources that describe energy use by sector, segment, end use and technology,
12
the following four types of energy efficiency potential were estimated for all sectors and
13
end-uses: technical, economic, achievable high, and achievable low.
14
up approach, LoadMAPTM integrates various stages of data development to depict the
15
Black Hills market; defines measures, end uses, and segments; and develops a baseline
16
projection – all to generate the energy efficiency savings potentials previously described.
17
Q.
Through a bottom-
HOW ARE THE TECHNICAL, ECONOMIC, ACHIEVABLE HIGH AND
18
ACHIEVABLE LOW ENERGY EFFICIENCY POTENTIAL SCENARIOS
19
DEFINED?
20
A.
Technical potential encompasses all of the electric savings possible with the available
21
efficient technology, regardless of cost. Therefore, technical potential represents the
22
upper limit of DSM potential. Economic potential represents savings from cost effective
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 4
1
measures using the modified Total Resource Cost (“mTRC”) test.1 For this Study,
2
measures were considered cost effective if their benefits outweighed their costs when the
3
mTRC ratio was greater than 1.0. Achievable potential high reflects the application of
4
customer adoption rates to the cost effective measures. These savings were modeled with
5
ideal market conditions: optimal customer adoption levels, clear information channels,
6
and smooth measure delivery and program coordination. The achievable potential high is
7
the upper bound target for achievable savings. Achievable potential low sets the lower
8
bound for achievable energy efficiency savings and represents a closer approximation of
9
expected market conditions given participation, budget, and market constraints.
10
Q.
WHAT DATA WAS USED FOR THE STUDY?
11
A.
Customer data provided by Black Hills was segmented based on customer class –
12
Residential, Small Commercial and Large Commercial/Industrial – to develop market
13
profiles for LoadMAPTM. The market profile is a characterization, or “snap shot,” of
14
Black Hills’ electricity usage by sector and end-use for the 2013 base year. The market
15
profile includes a variety of characteristics, including: market size, equipment saturation,
16
unit energy consumption, annual energy intensity, annual usage and peak demand for
17
each sector, building segment and end use. Calendar year 2013 was used as the base year
18
for the Study because it was the most recent full year for which data was available at the
19
time AEG began to work on the DSM Potential Study in 2014.
1
The mTRC test is a widely-accepted methodology that has been used specifically in Colorado to assess costeffectiveness. The mTRC measures the net costs of an energy efficiency program as a resource option based on the total costs of the program, including both the participant and the utility costs. This test represents the combination of the effects of a program on both participating and non-participating customers.
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 5
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The primary data used to develop the market profile included utility sales data, the
2
Black Hills Residential Appliance Saturation Survey completed in connection with the
3
2012-2015 DSM Plan, and customer billing data provided by Black Hills. Secondary
4
sources were used to supplement the primary data, such as the U.S. Energy Information
5
Administration’s (“EIA”) Annual Energy Outlook (“AEO”), the Census Bureau’s
6
American Community Survey, and AEG-developed energy databases and analysis tools.
7
Each level of data development was vetted by AEG staff and compared with other
8
potential studies conducted by AEG in similar geographic areas and under comparable
9
market conditions to verify/validate information.
10
AEG developed an extensive list of measures characterized by efficiency levels,
11
savings, costs, lifetime, market on/off year, and annual energy use for each building
12
segment and sector. The measure list was specifically tailored to reflect the technology
13
and end uses applicable to the Black Hills service territory. Data to compile the measure
14
list was taken from a variety of sources. AEG maintains a detailed internal Database of
15
Energy Efficiency Measures (“DEEM”) containing detailed measure characterizations
16
based on a multitude of sources including regional and state technical reference manuals,
17
the California Database for Energy Efficient Resources (“DEER”), as well as national
18
sources such as the EIA and the U.S. Department of Energy (“DOE”). AEG also used its
19
Building Energy Simulation Tool (“BEST”), a derivative of the DOE 2.2 building
20
simulation model, to ensure that weather sensitive measure characterizations were
21
calibrated to reflect local conditions within the Black Hills service territory.
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 6
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In addition to the market profiles and measure characterizations, AEG developed
2
a series of customer data points to model baseline market conditions within the Black
3
Hills service territory. Baseline customer purchasing decisions were developed using a
4
number of sources including Energy Information Administration’s Annual Energy
5
Outlook (“AEO”), ENERGY STAR™ appliance shipment data, prior participation in
6
Black Hills’ DSM programs, as well as feedback from Black Hills’ staff. Equipment
7
purchase shares were adjusted to reflect baseline shifts caused by changing federal
8
appliance standards over the time horizon of the Study. Growth in market size and
9
equipment saturation was developed based on Black Hills sales forecasts and AEO data,
10
as well as Black Hills’ and AEG’s knowledge and experience within the service territory.
11
Overall, AEG examined a variety of primary and secondary sources to develop a
12
comprehensive set of data that reflects current market conditions for Black Hills in order
13
to perform the potential assessment.
14
Q.
HOW WAS DSM POTENTIAL ESTIMATED?
15
A.
As a starting point, AEG developed a baseline energy consumption/usage projection for
16
each Black Hills sector, building segment and end use using LoadMAPTM. The 2013 to
17
2025 baseline projections represent annual electricity consumption and peak demand
18
without any new utility programs and incorporate the impacts of federal energy codes and
19
standards that are expected to come into effect during the Study timeframe. This
20
important step establishes the foundation for Company energy efficiency savings
21
potentials. The baseline projection is not the Company’s forecast, but is a modeling
22
output that reflects market growth based on data obtained by AEG, including electricity
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 7
1
price forecasts, customer growth, building code and equipment standards, trends in fuel
2
shares and saturation, and naturally occurring efficiency improvements.
3
LoadMAPTM analyzed each measure in a building segment based on the attributes
4
defined in the market characterization. LoadMAPTM used stock accounting algorithms to
5
replace older, less efficient equipment at the end of its useful life with new equipment
6
based on vintage distributions. LoadMAPTM isolated new construction from existing
7
equipment and buildings and treated purchase decisions for new and existing equipment
8
and buildings separately. All measures were screened for cost effectiveness using the
9
mTRC test with Black Hills specific inputs, including avoided costs, line losses, discount
10
rates, program delivery and administrative costs. The economic screening showed each
11
measure’s cost effectiveness relative to its baseline condition and was conducted for all
12
measures applicable to each building segment and vintage.
13
Potential savings were estimated for the years 2016 through 2025. LoadMAPTM
14
calculated technical potential savings by adopting the most efficient measure option
15
available for a given building segment, end use, and vintage regardless of market barriers
16
or cost effectiveness. By contrast, economic potential savings took cost-effectiveness into
17
account by only adopting the most efficient measures that passed the mTRC test. Next,
18
market adoption rates were applied to economic potential to calculate the achievable
19
potential savings scenarios. Market adoption rates were based on factors developed by
20
the Northwest Power and Conservation Council and modified to be consistent with Black
21
Hills’ market conditions, energy efficiency program implementation efforts, budgetary
22
constraints, and strategic goals.
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 8
IV.
1
DSM POTENTIAL STUDY RESULTS AND 2016-2018 DSM PLAN INTEGRATION
2 3
Q.
WHAT DO THE DSM POTENTIAL STUDY RESULTS INDICATE?
4
A.
Although changes in federal energy codes and standards continue to narrow the gap
5
between the baseline and efficient alternatives, the overall results of the DSM Potential
6
Study indicate there is still considerable achievable energy efficiency potential across all
7
sectors in the Company’s service territory for a wide variety of end uses.
8
Q.
WHERE IS THE MOST DSM POTENTIAL AVAILABLE?
9
A.
The majority of DSM Potential is available in the commercial and industrial sector.
10
Approximately two-thirds of the overall potential is available in the commercial and
11
industrial sector, with the residential sector accounting for approximately one-third of the
12
overall potential.
13
Q.
INDUSTRIAL POTENTIAL?
14 15
WHAT MEASURES AND END USES MADE UP THE COMMERCIAL AND
A.
In the near term, lighting makes up a large portion of sector savings potential; accounting
16
for over fifty percent of the commercial and industrial savings.
This percentage
17
decreases over time as the impact of federal lighting standards are fully realized (savings
18
decrease to approximately forty percent of sector potential). Cooling has the second
19
highest potential with approximately fifteen percent of sector savings potential. These
20
savings remain fairly consistent through the entire Study period. Heating, ventilation,
21
water heating, and miscellaneous (which includes industrial motors) make up the
22
remainder of the sector savings potential.
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 9
1
Q.
POTENTIAL?
2 3
WHAT MEASURES AND END USES MADE UP THE RESIDENTIAL
A.
In the near term, lighting makes up a large portion of sector savings potential; accounting
4
for over sixty percent of the residential savings. This percentage decreases over time as
5
the impact of federal lighting standards are fully realized (savings decrease to less than
6
half of sector potential).
7
approximately ten percent of the residential potential in the near term. Over the long
8
term, cooling savings potential increases, water heating potential decreases, and
9
appliance savings potential increases. These shifts in the proportion of potential by end
10
use are consistent with the federal baseline standards that will impact the energy
11
efficiency market.
12
Q.
HOW DID THE DSM POTENTIAL STUDY INFORM THE 2016 – 2018 DSM PLAN?
13 14
Cooling, appliances, and water heating each account for
A.
The DSM Potential Study results were used to inform the 2016-2018 DSM Plan program
15
design process. Achievable high and achievable low potentials set upper and lower
16
bounds of savings that informed program designs.
17
determined in the DSM Potential Study with individual programs designed to at least
18
meet achievable low potential in each sector. The measures and end uses that drove
19
savings in the DSM Potential Study provided specific areas to focus the program design.
20
The DSM Potential Study laid key groundwork to further understand the Black Hills
21
service territory and the potential savings available to Black Hills.
22
Total sector potentials were
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 10
V.
1
ROLE IN 2016-2018 DSM PLAN DEVELOPMENT
2
Q.
WHAT WAS AEG’S ROLE IN DEVELOPING THE 2016-2018 DSM PLAN?
3
A.
AEG evaluated measures for inclusion in the portfolio, bundled measures into deliverable
4
programs, developed measure incentives, developed program participation and budgets,
5
and performed cost-effectiveness analyses.
6
Q.
PROGRAMS?
7 8
HOW WERE MEASURES EVALUTED FOR INCLUSION AND BUNDLED INTO
A.
AEG began by creating a comprehensive “global” measure list that included all measures
9
currently offered in Black Hills’ existing DSM programs, measures offered by similar
10
utilities by geography and size, measures identified in the DSM Potential Study, and
11
other measures that could be applicable to the Black Hills service territory. Technical
12
assumptions for each measure were developed including measure life, energy savings,
13
peak demand savings, net-to-gross ratios, and measure incremental costs. Technical
14
assumptions were developed uniquely for each measure utilizing a variety of
15
methodologies for each individual assumption. Measure lives and incremental costs were
16
taken from technical reference manuals, determined through evaluations, or pulled from
17
assumptions used for a similar utility. Energy and peak demand savings were calculated
18
using engineering algorithms and deemed savings from technical reference manuals,
19
determined through evaluations, or pulled from savings used for a similar utility. The
20
most recently available Black Hills evaluation studies were utilized for net-to-gross
21
ratios. Each measure was initially screened for cost-effectiveness on a measure-level
22
basis and low performing measures (those with an mTRC ratio below 1.0) were removed
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 11
1
from consideration for the portfolio. Measures were then bundled together into programs
2
based on end use and the desired delivery mechanism of the program. For example,
3
residential lighting measures (CFLs, LEDs, Specialty LEDs, etc.) were bundled because
4
they are all lighting products and they are proposed to be delivered through a point of
5
purchase rebate to the customer. Some measures may be included in multiple programs
6
due to different delivery mechanisms. For example, CFLs are included in the Residential
7
Lighting program as a point-of-purchase rebate, the Home Energy Evaluation program as
8
a direct install measure free to the customer, and in the Low Income program as a direct
9
install measure free to the customer.
10
Q.
HOW WERE INCENTIVES DEVELOPED?
11
A.
Incentives were developed using multi-variable criteria including the measure’s
12
incremental cost, the program delivery mechanism, target market, and comparable
13
incentives that are available in the marketplace.
14
programs, incentives are generally calculated at approximately fifty percent of the
15
measure’s incremental cost. For direct install programs, incentives are equal to the total
16
cost of the measure being installed. Specialty programs have unique incentive structures
17
that differ from standard incentive mechanisms. The Small Business Direct Lighting
18
track of the Commercial Lighting program offers up to a seventy percent rebate of the
19
entire cost of the project. This is justified because the small business sector is a very
20
difficult market to reach for participation in DSM programs due to a variety of factors,
21
including lack of access to capital, lack of customer education, and other market factors.
22
For standard prescriptive rebate
Proceeding No. 15A-_____E Black Hills 2016-2018 DSM Plan Direct Testimony of Andrew W. Cottrell May 29, 2015, Page 12
1
Q.
HOW DID AEG DEVELOP PROGRAM PARTICIPATION AND BUDGETS?
2
A.
An overall budget target consistent with past program spending, with the addition of
3
funds from new programs, was used as the foundation for building individual program
4
and budgets.
5
bottom-up approach where individual measure participation was determined and budgets
6
were an eventual derivative of program participation. Participation was then adjusted to
7
levels that would be cost-effective and within the bounds of the overall budget target.
Program-level participation and budgets were developed utilizing the
8
Q.
HOW WAS COST-EFFECTIVENESS DETERMINED?
9
A.
Cost-effectiveness analysis was determined utilizing AEG’s BenCost model.
The
10
BenCost model is an input-output Microsoft Excel-based linear program model that
11
calculates all five standard cost-effectiveness tests (mTRC, Societal Test, Utility Cost
12
Test, Participant Cost Test, and Ratepayer Impact Measure). The modeling details and
13
results, including model inputs and outputs, are described in Mr. Daunis’ direct testimony
14
and in Appendix A to the 2016-2018 DSM Plan.
15
Q.
DOES THIS CONCLUDE YOUR TESTIMONY?
16
A.
Yes.
Appendix A STATEMENT OF QUALIFICATIONS ANDREW W. COTTRELL My name is Andrew W. Cottrell. My business address is 317 George Street, Suite 305, New Brunswick, New Jersey, 08901. My current title is Principal Consultant for Applied Energy Group, Inc. My educational background consists of a Bachelor’s of Arts degree in Engineering with a minor in Government & Law from Lafayette College in Easton, Pennsylvania in 2004. I also obtained a Master’s of Public Policy from the Edward J. Bloustein School of Planning and Public Policy at Rutgers University in New Brunswick, New Jersey in 2006. I have performed professional internships with the Sustainable Development Fund in Philadelphia, PA and was a Graduate Assistant for the Center for Energy, Economic, and Environmental Policy in New Brunswick, NJ. In my employment history prior to joining Applied Energy Group, I worked for four years as the Research Project Coordinator at the Center for Energy, Economic, and Environmental Policy (CEEEP) at Rutgers University; performing wholesale electricity market modeling, designing cost-benefit analysis models, and evaluating energy efficiency programs. While working at CEEEP I also performed independent consulting with Independent Electricity Consultants in Ridgewood, NJ. Beginning in July of 2010, I worked as a Senior Analyst in Applied Energy Group’s Utility Consulting practice, supporting utility clients in the Northeast and Midwest. My duties included the following: energy efficiency/demand response cost-effectiveness analysis and modeling, DSM implementation plan filings, baseline and market analysis studies, energy efficiency potential studies, tracking of new technologies and DSM industry developments, and performing energy efficiency process and impact evaluations. In 2011-2012, I lead the analysis for the Black Hills/Colorado Electric Utility Company, LP (Black Hills) Baseline Study and Potential Study. I also designed the 2012-2015 Black Hills Energy Efficiency Plan during that engagement. In September of 2012, I was promoted to Principal Consultant, where I became the project manager for key clients. I continue to perform the work described above as well as manage a team of Analysts and Support Staff in the Utility Consulting practice’s Energy Analysis and Planning team.