Memorandum
To:
2003 Distributed Energy Market Study Subscribers
From:
Nick Lenssen, Shawn McNulty
Email:
nlenssen@primen.com
smcnulty@primen.com
Date:
November 17, 2003
Phone:
303.545.0100, x336
608.663.9616
Subject: Main Quantitative Findings
As part of the Primen Distributed Energy Market Study 2003 (DEMS03),
“Converting Distributed Energy Prospects Into Customers,” we fielded a short
quantitative survey to more than 800 commercial, industrial, and institutional energy
users. This memo presents the main findings from that quantitative survey, results of
which are also being woven into our forthcoming report summarizing the findings from
the 100 in-depth, qualitative interviews that make up the core of the DEMS03 project.
Sample surveyed
The sample for the DEMS03 survey queried 806 energy users in April and May of
2003. Four hundred completes were among users with an average demand of 300 kW
- 10 MW, with the remaining 406 completes among mass-market users with an
average demand of between 10 kW and 299 kW. (See Table 1.) The results in this
summary were weighted to reflect their true representation in the population of U.S.
businesses. Businesses with fewer than five employees and those that had their
energy bills included in their rent were excluded from the sample, as were agricultural,
construction, and mining businesses.
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
Page 1
Table 1. Survey Sample Plan and Completes
Targeted
completes
Actual
completes
Mass market (10 kW to 299 kW)
400
406
Large (300 kW to 10 MW)
400
400
Manufacturing
100
130
Schools, colleges, & universities
100
115
Restaurants
100
100
Other (all other sectors except agriculture,
mining, & construction)
500
461
Total
800
806
How receptive to baseload DE are energy users?
Overall, 13% of the business establishments we surveyed this year say their
likelihood of acquiring baseload DE in the next two years is greater than 50%. In
keeping with last year’s practice, we classify this group as “receptive” to baseload DE
— meaning that they would seriously entertain an offer if approached by a DE supplier.
Within this 13%, however, are two distinct categories of prospects: strong and soft.
Strong prospects, which totaled 2% of respondents, say they are >50% likely to
acquire baseload DE in the next two years and are actively evaluating their options.
Soft prospects, which totaled 11% of respondents, also say they are >50% likely to
acquire baseload DE in the next two years, but they have not begun to actively
investigate their options. (See Figure 1.)
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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Figure 1. Relative number of prospects for acquiring DE within the next two years
Soft
Prospects
11%
Strong
Prospects
2%
Nonprospects
87%
How has receptivity to baseload DE changed in the past year?
Although the prospects percentage is the same as we found in the 2002 DE Market
Study, they come from a much broader group of industries and customer sizes than
last year’s study, which only covered users above the 300 kW level. When we
compare this year’s data with the 2002 data (looking only at those sectors and
customer sizes that were included in both years) we find a marginally significant
increase in strong prospects, from 2% to 5% — meaning that receptivity to baseload
DE has increased slightly in the past year. (See Figure 2.)
Figure 2. User receptivity to baseload DE shows signs of rebounding
Strong Prospects
Soft Prospects
25%
20%
15%
10%
5%
0%
2001
2002
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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2003
Who are the most receptive customers?
Receptivity by size
The greatest receptivity is found in larger users, with 4.1% of them being strong
prospects. Among mass market users in the 10-299 kW size range, only 1.8% are
strong prospects.
Receptivity by region
Among all prospects, the greatest receptivity is found in the high spark spread
states, though the lowest interest is in medium spark spread states, not low spark
spread states. (See Figure 3.) Among strong prospects, the higher interest in high
spark spread states is an indication that energy cost pressure is the primary driver for
baseload DE projects.
Figure 3. Relative number of prospects by region
Soft prospects
Strong propects
High Spark Spread
Medium Spark
Spread
Low Spark Spread
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
The perceived benefit of baseload DE
Respondents identify three main benefits of DE: save money on energy, more
reliable power, and greater predictability of energy prices. (See Figure 4.) Even
among soft prospects, who identified other benefits, these three areas dominated as
the rationale for pursing DE projects.
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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Figure 4. Perceived benefits of baseload DE
Strong prospects
Soft prospects
Save money on energy
Greater predicatibility of energy prices
More reliable power
Improved power quality
Capture waste heat for use
Use waste products as fuel
Environmental benefits
More secure power source
0%
20%
40%
60%
80%
100%
DE technology preferences
Strong prospects have a high preference for gas engines as their technology of
choice, with diesel engines and gas turbines far behind. (See Figure 5.) Only 1% of
strong prospects said that microturbines are their preferred technology, and none
mentioned fuel cells. Among soft prospects, however, 17% indicated that fuel cells
would be their preferred technology, only slightly below the 20% who preferred gas
engines.
Figure 5. Technology preferences among prospects
Soft Prospects
Strong Prospects
35%
30%
25%
20%
15%
10%
5%
0%
Diesel
Gas engines
Gas turbines Microturbines
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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Fuel cells
Leasing vs. Purchase Preference
Prospects are roughly evenly split in rating their likelihood to buy or to lease baseload
DE equipment, with leasing being slightly more likely. This subtle shift from last year’s
preference for buying might be an indication that capital budgets have become even
tighter at many companies.
Purchase
Lease
Very Likely
10
9
8
7
6
5
4
3
2
Not at all
Likely
1
Non-Prospects
Soft Prospects
Strong Prospects
Payback Requirements
Strong prospects have far more realistic payback requirements for baseload DE than
soft prospects. In fact, 86% of strong prospects are willing to accept a payback of four
years or more on a DE project. For soft prospects, 37% find a four-year or longer
payback acceptable. (See Figure 7.)
Figure 7. Minimum acceptable payback for purchase among DE prospects
100%
1
2
3
4
6
80%
60%
40%
20%
0%
Soft Prospects
Strong Prospects
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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year or less
years
years
to 5 years
or more years
The finding extends to leasing DE: strong prospects have less stringent savings
requirements than soft prospects. For strong prospects, 56% would find a savings of
10% or less acceptable, roughly double the level of soft prospects. (See Figure 8.)
Figure 8. Minimum acceptable savings for DE leasing among prospects
100%
80%
60%
More than 20%
11% to 20%
6% to 10%
5% or less
40%
20%
0%
Soft Prospects
Strong Prospects
Standby Generation Saturation
The market for standby generation is far larger than baseload applications. Primen’s
survey finds that 37% of large business establishments already have standby
generation capabilities, while a surprising 23% of mass market businesses also do.
(See Figure 9.)
Figure 9. Standby generation saturation among prospects and non-prospects
Mass Market
(10 kW to 299
kW)
Large (300 kW
to 10 MW)
0%
10%
20%
30%
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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40%
Targeted Marketing Efforts to Identify DE Prospects
Because the overall incidence of DE prospects remains low, the challenge is to identify
characteristics among energy users that might point to a higher likelihood to purchase
DE systems, so that targeted marketing efforts can be effective. In the below material,
Primen looks at various indicators that provide a portrait of the prototypical DE
prospect.
Interest in DE systems is substantially higher among those energy users that are also
good prospects for participation in demand response programs. In fact, energy users
already participating in demand response programs also represent fertile ground for
utilities that are seeking potential DE customers (Figure 10).
Figure 10. DE prospects and demand response (DR) program interest
Total sample
DE prospects: 13%
Non-prospects: 87%
100%
Demand response interest segments
In DR or load program
Good DR prospects
Fair DR prospects
Poor DR prospects
DE prospects: 22%
Non-prospects: 78%
19%
DE prospects: 23%
Non-prospects: 77%
17%
DE prospects:
6%
Non-prospects: 94%
30%
DE prospects:
8%
Non-prospects: 92%
34%
Good
prospects
Poor
prospects
The higher the energy portion of operating costs, the more likely a company is to be a
DE prospect. About 45% of the total prospects (strong and soft prospects combined)
have energy costs that exceed 5% of operating costs, and 30% of this group have
energy costs of 20% or more or operating costs (Figure 11). Of the 2% that are strong
prospects, almost half have energy expenses of 20% or more of total operating costs.
Due to sample size, this percentage is not statistically valid. However, it may be an
indicator.
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
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Figure 11. DE prospects by energy portion of total costs
Total sample
Prospects:
13%
Non-prospects: 87%
100%
Energy % of total operating costs
Prospects:
30%
Non-prospects: 70%
12%
Prospects:
15%
Non-prospects: 85%
38%
Prospects:
6%
Non-prospects: 93%
38%
Prospects:
9%
Non-prospects: 91%
12%
5% to 19%
Less than 5%
Don’t know or data
missing
20% or more
Good
prospects
Poor
prospects
The bubble charts in Figures 12 and 13 show the characteristics of companies that
can be used to target prospective buyers of DE systems. The analytic technique used
to create these charts is also valuable for exploring the reasons businesses are
prospects for DE. Once the reasons for interest in DE are identified, they can be used
as part of the message for marketing these systems. Alternatively, utilities that would
prefer to discourage independent generation in certain customer classes can orient
their marketing toward that end.
The finding of greatest interest in Figure 12 is that businesses most likely to be DE
prospects must believe both that electricity costs will increase substantially in the next
year and that their facility will experience an increase in power outages. If they believe
that costs will rise but that their level of outages will remain steady or drop, their
interest in distributed energy is lower than average.
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
Page 9
Figure 12. DE prospects and their beliefs about energy
Total sample
Prospects:
13%
Non-prospects: 87%
100%
Electricity costs will increase dramatically in next 12 months
Neutral or agree
Somewhat disagree
Prospects:
18%
Non-prospects: 82%
64%
Prospects:
1%
Non-prospects: 99%
19%
Strongly disagree
Prospects:
5%
Non-prospects: 95%
17%
Facility will experience more power outages
Prospects:
32%
Non-prospects: 68%
27%
Neutral or agree
Prospects:
4%
Non-prospects: 96%
13%
Prospects:
10%
Non-prospects: 90%
24%
Somewhat disagree
Strongly disagree
Good
prospects
Poor
prospects
Satisfaction with utility services shows a similar pattern (Figure 13). Businesses must
have poor satisfaction both with their utility’s emergency response performance and
with their power quality before they become prime candidates for distributed energy.
Moreover, when satisfaction with both of these performance factors is low, interest in
distributed energy more than triples from the 13% level to 39%.
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
Page 10
Figure 13. DE prospects and utility performance satisfaction
Total sample
Prospects:
13%
Non-prospects: 87%
100%
Satisfaction with emergency response (1-10)
Not satisfied (6 or Less)
Somewhat satisfied (7-9)
Very satisfied (10)
Prospects:
25%
Non-prospects: 75%
18%
Prospects:
13%
Non-prospects: 87%
51%
Prospects:
5%
Non-prospects: 95%
31%
Satisfaction with power Quality (1-10)
Prospects:
39%
Non-prospects: 61%
11%
6 or less
Prospects:
1%
Non-prospects: 99%
7%
7 or more
Good
prospects
2003 Distributed Energy Market Study – Quantitative Survey Main Findings
Page 11
Poor
prospects