goldman1986

Energy and Buildings, 9 (1986) 89 - 98
89
Energy Conservation in Public Housing: A Case Study of
the San Francisco Housing Authority
CHARLES A. GOLDMAN and RONALD L. RITSCHARD
Applied Science Division, Lawrence Berkeley Laboratory, University of California, Berkeley, CA 94720 (U.S.A.)
(Received November 1984; accepted February 1985;revised April 1985)
SUMMARY
In 1982, the San Francisco Housing
Authority began trying to reduce rapidly
increasing energy expenses by installing attic
insulation, exterior door weather stripping,
low-flow shower-heads, and water-heater
blankets in the buildings that it manages.
The conservation measures were financed
by the local utility's zero-interest loan program (ZIP). We analyze utility billing data
for three years, including one post-retrofit
year, at five multifamily housing projects
(totalling 1822 units). Weather-normalized
annual natural gas consumption declined by
13% after the retrofit at the five projects;
net savings relative to a comparison group
were 8%. We determined that most o f the
energy savings resulted from reduced base
level usage. We found that the retrofit program was cost-effective, with a net present
value o f $399 000 or $220/unit. The Housing
Authority's careful efforts to control retrofit
costs, which averaged only $150/unit, contributed to the program's success.
INTRODUCTION
In the next decade, public housing officials
will have to pay increasing attention to
improving the energy efficiency of buildings
as rising energy costs create an ever-widening
gap between expenses and rental income.
A recent review of the topic concludes that
great potential exists for energy and cost
savings in public housing [1]. During the last
ten years, the U.S. Department of Housing
and Urban Development (HUD) and local
public housing authorities (PHAs) have initiated major retrofit programs. In 1980, HUD
awarded $23 million to 47 PHAs for modernizing oil heating systems and another
$5 million to 61 PHAs to install and test
innovative energy conservation and solar
measures. In addition, between 1975 and
1979, approximately 25% of HUD modernization funds were used for energy conservation.
Savings estimates for these programs have
been based almost exclusively on engineering
calculations; only a few evaluations of public
housing retrofit efforts have used metered
data [ 2 - 5 ] . Actual measured data give
credibility to predictions, help guide retrofit
investment decisions, and help identify issues
that deserve further analysis.
This report focuses on the San Francisco
Housing Authority, which cooperated with
the local utility, Pacific Gas & Electric Company (PG&E), to finance energy conservation
measures. The Housing Authority was deeply
concerned with energy expenses, which had
increased from $1.7 million in 1977 to
$4.3 million in 1983, although energy consumption actually decreased slightly during
this period. We analyze utility bills over a
three-year period at five housing projects,
including one year of post-retrofit data, in
order to estimate energy savings attributable
to the Housing Authority 's weatherization
program. These five projects represent roughly 25% of the dwelling units managed by the
Authority. The projects are occupied by
families and are master-metered; thus tenants
do not pay utility costs directly.
In this study, we discuss optimal approaches for selection, marketing, and financing of energy conservation retrofits in public
housing. Very little research has been done
in this area and San Francisco is one of the
first public housing authorities to fund
Elsevier Sequoia/Printed in The Netherlands
90
energy-efficiency improvements
using a
utility-sponsored conservation program. Innovative financial strategies are necessary in
order to overcome existing institutional
barriers and tight budgetary constraints.
This study also adds to research on multifamily buildings. A significant fraction of
the nation's public housing units are multifamily buildings. Until recently, the multifamily sector has received m u c h less attention
and study than have single-family residences.
R E T R O F I T AND BUILDING DESCRIPTION
F o u r of the five family housing projects
in this study are located on the east side of
San Francisco. Each site has many low-rise
buildings ( 2 - 3 story) with 8 - 20 apartment
units per building. Average floor area per
unit ranges from approximately 70 m 2 to
80 m 2 with an average of 3.6 occupants per
unit (see Table 1). Roughly 65% of the apartments are t w o - b e d r o o m units; one- and threeb e d r o o m units each account for approximately 15% of the total. During post-retrofit site
visits, we observed many apartments with
broken or boarded windows (perhaps 2% 4% of all windows). This observation suggests that, in any energy conservation effort,
additional funding for and attention to basic
maintenance must be considered in addition
to weatherization measures.
TABLE
Under the utility's conservation program,
an interest-free loan of up to $1000/unit
is available for the following conservation
measures: attic and duct insulation, low-flow
shower-heads, water-heater blankets, caulking,
and weather stripping. Loans may be used
for both material and labor costs and are
repayable over an eight-year period. Initially,
PG&E and Authority staff inspected a representative sample of apartment types managed
b y the Authority to determine which conservation measures were suitable. Those housing
projects with the highest estimated potential
savings were chosen first. Typically these
were t o w n h o u s e apartments with accessible
attics. Bid packages were prepared for each
project and bids were then requested from
weatherization contractors certified to participate in the zero-interest loan program (ZIP).
Attic insulation and exterior door weather
stripping were installed at each project. Two
sites with h o t water heaters in individual
dwelling units received insulating blankets
(Table 1). Retrofit costs ranged from $80
to $200 per unit, with an average of $150/
unit. In addition, inexpensive time clocks,
costing approximately $85/boiler, were installed on central boilers at three projects
in October 1982; this measure was not part
of the ZIP program. The time clocks regulate
the space heat water circulation pump, so
the p u m p would run for 14 hours rather than
24 hours a day. Housing Authority staff
1
Building description and retrofit measures
Project name
Alemany
Potrero Terrace
Sunnydale
Alice Griffith
Hayes Valleya
Total units
Occupied units b
Pre-retrofit
Post-retrofit
Avg. floor area (m 2)
Occupants/Unit c
Year built
Heating system type d
Retrofit measures e
158
469
767
258
170
152
150
81
4.0
1956
SH
IA, CW, W H
393
418
77
3.3
1942
CB
IA, CW, TC, S H
677
705
81
3.7
1942
SH
IA, CW, W H
193
236
78
4.8
1962
CB
IA, CW, T C
151
148
72
2.6
1963
CB
IA, CW, T C
aHayes Valley is located at three separate sites. W e have included results for only one site, Hayes B, which represents 170 of 328 units. Hayes C (140 units) was excluded due to anomalous utilitybillingdata.
bAverages were computed over the number of billing periods used in regression analysis.
cOccupant data are from 1982.
d S H = r o o m space heater; C B = central boilers that supply both space heat and domestic hot water.
eIA = attic insulation, C W = caulking/weather stripping, T C = time clock on boiler, S H = low-flow shower-head,
W H = water-heater jacket.
91
indicated that the timers would be disconnected if tenants at a project complained
about insufficient heat. The time clocks were
not in use on some boilers during our site
visits. The systems either had manual override
switches in effect or the on-and-off tripper
switches were missing from timer dials. We
have been unable to determine how long the
timers were in operation before they were
disconnected.
ANALYSIS
We use the Princeton Scorekeeping Method
(PRISM) to adjust for weather differences
during the pre- and post-retrofit periods
(described in the introductory paper to this
issue). The Housing Authority provided us
with monthly utility bills from January 1981
to April 1984. Daily average temperatures
were obtained from the San Francisco Airport
NOAA weather station, from which we computed heating degree-days to different reference temperatures. Normal year heating
degree-days were computed to different
reference temperatures using the 30-year
normal monthly outdoor average temperature and its standard deviation [6].
In this paper we also explore ways to adjust
for changing occupancy rates. Evaluations of
retrofit programs directed at single-family
homes generally exclude homes in which
occupancy has changed [7]. However, this
approach is not feasible in master-metered,
multifamily buildings. This is particularly
true in family housing projects where turnover is often high and occupancy rates vary
greatly over time. To adjust for occupancy
effects, we used monthly data on the number
of occupied units in each project as a rough
indicator of the number of units being heated.
It is worth noting that many more units were
occupied at Sunnydale, Potrero Terrace,
and Alice Griffith Projects after the retrofit
than in the pre-retrofit period [see Table 1].
We were concerned that decreases in gas consumption due to retrofitting would be masked
by increases in the number of occupied dwellings (and presumably the heating load). To
account for this effect, we divided gas use
during each billing period by the number of
occupied units in that period. We recognize
the limitations of this approach, which as-
sumes that no energy is being consumed in
vacant units. This assumption is probably
reasonable for appliance and hot water use,
particularly for the two projects with individual unit hot water heaters. However, in
the three projects with central heating plants,
unoccupied units were probably receiving
some direct heat (we found some vacant units
with manual radiator controller valves stuck
in the "open" position).
We used a comparison group to obtain a
rough estimate of the net impact of the conservation measures on energy consumption in
the five projects. The comparison group,
Group A, consists of two non-retrofitted
projects with characteristics similar to those
of the study group. These projects were
constructed during the same period (194050s), have central heating plants, and are
occupied by families. However, the Scorekeeping results seem to be not reliable (e.g.,
large standard errors in the reference temperatures; see Table 2). For these reasons,
changes in energy consumption in the comparison group and the corresponding adjustment in the treatment group's savings should
be viewed cautiously.
RESULTS
Actual energy consumption
Energy usage tracks seasonal weather
variations (as indicated by heating degreedays, HDD) fairly closely at the Sunnydale
Project (Fig. 1). Milder weather conditions
prevailed in the post-retrofit period than
during either of the pre-retrofit periods:
1402 HDD (base 18.3 °C) in the post-retrofit
period versus 1776 and 1737 HDD during
the 1981 - 82 and 1982- 83 pre-retrofit
periods respectively. In addition to weather,
another factor that could affect energy consumption is occupancy, which increased by
an average of 4% after the conservation
measures were installed.
Cooking energy use is metered separately
at two projects, Hayes Valley and Potrero
Terrace, and accounts for a surprisingly large
fraction (19%- 29%) of total gas consumption. Average gas consumption/unit for cooking is much higher at Potrero Terrace than
at Hayes Valley (1.2 vs. 0.5 kWth/unit).
In addition, cooking energy use is 30% - 50%
92
400
400
-
ZIP Retrofit units
!
350 ",,,
750- 360
. _
300
~
..........
; I( •
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o~
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r
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NI
/"
L~-- ~o o
\\ i ei li .o
,..m.,.,,
ol
'/
"~--
1981~
1982~
Quality of the PRISM results
/
1983
Fig. 1. Gas use/day, heating degree-days, and the
number of occupied units for each "monthly"
billing period at Sunnydale Project.
4.5
450
ZIPRetrofit
Boiler
\eTime Cloci
TOTALGASUSE
/r
: HEATIN.-OHW 4
400
•
A COOKING
.ok /
300
,.',
,.
3.5
P',
2.§ .~
\
8
1.B ~
150
100 a
d/
,
"
a
pA~
B0
0
1
06
~-
c . . . .
lg01~
,
. . . . .
1582
"1-
,
.....
gas ranges for heat, particularly in projects
like Potrero Terrace, where there are many
2- 3 bedroom units with only one radiator
per apartment.
In some instances, the time-trend plots
revealed questionable or anomalous data.
For example, energy usage was extremely
low at the Sunnydale Project in May 1982
(see Fig. 1). Some investigation revealed that
the project gas meter had been vandalized
and was operable during only part of May
1982; data from this billing period were
excluded from the regression analysis.
0
1083
Fig. 2. Cooking,
space heating/domestic hot water,
and total gas use for each "monthly" billing period
at Potrero Terrace Project.
higher in winter months compared to summer
averages at the two projects (Fig. 2). Residents probably cook at home more during
the winter and holiday season. Local housing
authority staff also believe that tenants use
The Normalized Annual Consumption
(NAC) and parameter estimates for each
project are summarized in Table 2. One of
the Hayes Valley sites (Hayes C) was eliminated from the final analysis because of
anomalies in the pre-retrofit billing data and
poor correlation between energy use and outdoor temperature. The model was run iteratively to include various time spans in the
pre- and post-retrofit periods in order to
optimize results (i.e., highest coefficient
of determination (R 2) and minimum standard
errors in reference temperature). Typically,
10- 15 billing months are included in the
final analysis. It is worth noting that higher
quality results were obtained at the two
projects with individual-unit space heaters
than the three centrally heated projects.
Occasionally, exclusion of a segment of the
billing history significantly reduced the
standard errors of the estimates, yet resulted
in only small changes (1%- 2%) in NAC.
The NAC indicator has a standard error of
1%- 2%. Not unexpectedly, this is much
smaller than the errors in the individual
parameters: base level, ~ (5%-10%), and
heating slope,/~ (10% - 30%).
R 2 values were greater than 0.83 at four
projects, with typical values above 0.9, except
for Alice Griffith Project. These values are
much lower than values reported elsewhere
in this issue for single-family houses in New
Jersey (median R 2 above 0.95), yet are comparable to values (mean of 0.79) reported
in 400 single-family, electric-heat homes
located in the Pacific Northwest [8 - 10].
The reference temperature increased (by
1 - 6 °C) at all five projects between the preand post-retrofit period. A substantial drop
93
TABLE 2
Scorekeeping results
Project name
Pre-retrofit (1/81 - 10/82)
eta
~b
Post-retrofit (1/83 - 4/84)
rc
NAC d
R 2
Ne
a
~
~
NAC
R 2
N
Hayes Valley B
2.50
176
(0.061) (66)
11.7
(1.6)
83.8
(1.4)
0.83 10
2.32
88
(0.122) (22)
18.3
(2.6)
88.1
(1.3)
0.90 10
Alemany
2.19
308
(0.073) (22)
14.8
(0.6)
91.4
(1.2)
0.98 11
1.75
220
(0.085) (22)
16.9
(0.9)
81.4
(1.2)
0.95 14
Sunnydale
2.60
330
(0.073) (44)
13.5
(0.7)
98.3
(1.3)
0.97 10
2.16
308
(0.110) (66)
14.7
(1.0)
89.1
(2.2)
0.86 14
PotreroTerrace
3.65
374
(0.110) (66)
14.8
(0.9)
142.1
(2.0)
0.94 11
2.77
264
(0.183) (44)
17.3
(1.4)
120.0 0.92 15
(2.0)
Alice Griffith
5.12
220
(0.098) (88)
13.6
(1.6)
173.1
(2.2)
0.73
3.37
154
(0.647) (22)
19.9
(5.2)
137.8 0.81 16
(2.1)
21.1
93.5
0.94 12
9
Co mpariso n gro u p
Valencia
North Beach
1.82
154
(4.65) (14)
(12.8) (3.5)
3.31
(0.41)
20.1
(14.0)
265
(31)
166.6
(2.8)
0.90 13
1.79
20.8
96.4
(0.46) (11)
177
(3.0)
(o.5)
3.91
(0.54)
18.4
(6.3)
149.7 0.69 13
(3.1)
172
(57)
0.99
9
Results are from billing data adjusted for occupancy rates. Numbers in parentheses indicate the standard errors of
the estimate. Multiplication of the standard error by 2.5 approximates the half-width of the 95% confidence interval.
a~ is the temperature-independent or base level usage (kWth/unit).
b~ is the heating slope (Wth/unit °C).
cT is the reference temperature (°C).
dNAC is Normalized Annual Consumption (GJth/year).
eN is number of billing months included in regression analysis.
in base level, ~, accompanied this increase
in reference temperature, T, in each of these
cases. This drop in base level, if due to a real
physical effect, could reasonably lead to a rise
in reference temperature because of the
concomitant drop in free heat. However, it
is difficult to separate real physical effects
from statistical effects when evaluating
changes over time in individual parameter
estimates.
Energy savings
Gas savings are calculated in two ways -changes in the NAC between the pre- and
post-retrofit periods, and changes relative
to a comparison group (i.e., net savings).
Table 3 summarizes individual project and
aggregate results. NAC at the five projects
decreased by an average of 14 GJth/unit
after retrofit. The weatherization program
achieved net energy savings of 8.5 GJth/unit,
an 8% reduction, if we consider changes in
consumption that occurred in the comparison
group. Energy savings varied widely, ranging
from 9 % of pre-retrofit consumption at
Alemany to 20% at the Alice Griffith site.
The level of savings was more strongly correlated with pre-retrofit usage levels than
with amount invested in retrofits. Those
projects with the largest savings, in relative
and absolute terms, also had the highest
energy usage per unit before implementation
of the program. The high consumption levels
at Alice Griffith are due in part to the project's higher occupant density as well as
improperly functioning heating system controls. W e observed room radiators with
manual controller valves stuck in the "open"
position and time clocks that were inoperable
on several boilers.
Energy use increased slightly at the Hayes
Valley project after the retrofit.These disappointing results are difficult to explain.
However, this project had the lowest initial
gas consumption and therefore the smallest
potential energy savings from the installed
retrofit measures. At three-story Hayes
94
TABLE 3
Summary of savings results for SFHA ZIP program
Project name
NAC a
Before
(GJth/unit-yr)
After
(GJth/unit-yr)
Savings
(GJth/unit-yr)
(%)
Hayes Valley
Alemany
Sunnydale
Potrero Terrace
Alice Griffith
83.8
91.4
98.3
142.1
173.1
88.1
81.4
89.1
120.0
137.8
--4.3
10.0
9.2
22.1
35.3
--5
11
9
16
20
Aggregate results c
112.0
97.8
14.2
12.7
Group A :
128.7
(Valencia, North Beach)
122.1
6.6
5.0
8.5
7.6
Cost of
retrofit
(19835)
Simple b
payback
(years)
82
160
203
93
165
*
3.3
4.5
0.9
1.0
154
2.1
Co m p a riso n gro u p
Net savings relative to
Group A d
3.5
aComputed for data adjusted for occupancy rates.
bSimple payback period is computed as cost divided by first year savings (gas savings multiplied by $5.10/MBtu).
CAggregate results are obtained by weighting gas usage/unit before and after by the total number of units in each
project.
dNet savings (S) are calculated as follows: S = NACpre*(NACcpost/NACcpre ) -- NACpost.
*Economic indicator cannot be calculated when there are negative savings.
Valley, only one-third of the units have direct
contact with an insulated attic. This contrasts
with the two-story townhouses at Alemany,
Sunnydale, and Alice Griffith, where every
apartment has an attic exposure. In addition,
energy consumption at Hayes Valley was
relatively insensitive to outdoor temperature
as indicated by the large uncertainties in T
(2.6 °C), and the relatively low heating slope,
~. Our site visits revealed one probable explanation for this phenomenon: the absence of
adequate heating system controls, such as
outdoor resets or cutout controls.
W h e n we do not adjust for occupancy
rates, we see a significant change in measured
energy savings at the three projects with large
changes in the number of occupied units
between the pre- and post-retrofit period
(see Table 1). For example, at the Alice
Griffith project, the most extreme case,
energy consumption decreased by 7.5 GJth/
unit after retrofit if we make no adjustment
for occupancy, versus 35 GJth/unit when
changes in the number of occupied units are
explicitly considered. N A C at the five projects
(unadjusted for occupancy rates) decreased
by an average of 8 GJth/unit, versus
14 GJth/unit (adjusted).
Base level a n d space h e a t use
PRISM also allows us to estimate annual
heating and base level consumption (although
these parameters are less well determined than
NAC) and thus to identify end uses with a
large conservation potential. After retrofit,
energy use declined markedly during the
summer months at all projects except Hayes
Valley. This trend is clear at the Alemany
project when pre- and post-retrofit energy
use are compared at zero heating degree-days
(Fig. 3). Base level use, c~, is estimated at
1.75 kWth/unit after installation of conservation measures, a 20% decrease from the preretrofit level. The high a estimate in three of
the projects (Fig. 4) suggests quite high
appliance and domestic hot water consumption. We alternatively estimated base level
gas use by taking utility bills from the
summer months (July - September) and
scaling consumption per day to a full year
(indicated by arrows in Fig. 4). This
technique yields base-level estimates that
agree closely (within 2 - 3%) with those derived by PRISM, and provides additional
evidence
that
temperature-independent
demand declined after the retrofits. Central
heating systems in San Francisco projects
95
4.0
N = 164 u n i t s /
3.5
~ 4
3.0
\
•
e-
" - Post
.o_
.RE-.E
ROF,T
2.5
A POST-RETROFIT
e
¢"
o
20
O.
E
)'/
~2
1.5
o
O
(D
"C
=
/~
=
NAC
R2
0
~
0
t
I
2
4
~
=
=
Pre
Post
14.8
2.19
308
91.4
0.978
16.9
1.75
220
81.4
0.955
8
10
t
6
J
~"
8
1.O > .
co
O5
OD
12(=C)
Heating degree-days per day (Base T -- 14.8"C)
Fig. 3. P l o t o f t o t a l gas use versus heating degree-
days, b o t h normalized b y the number of days in each
billing period, at Alemany Project. NAC is expressed
in GJth/year; units for (~ are kWth/unit; and ~, the
heating slope, is expressed in Wth/unit °C. Heating
degree<lays are calculated based on the pre-retrofit
reference temperature (14.8 °C). Lines represent the
best fit o f pre- and post-retrofit consumption data to
that HDD base.
60
[
C
•
PRE-RETROFIT
~
POST-RETROFIT
40
@
tG
O
¢g
O.
O~
"~
20
0
20
..~ 4o
~0
~
_o
81
m
m
B2j~~
8O
IO0
120
140
I
I
I
Alemany
Potrero
Sunnydale
Terrace
San Francisco Housing Authority Projects
Fig. 4. Pre- and post-retrofit estimates of the temperature-dependent (dominated by space heating) and
temperature-independent (base level) components of
total gas consumption at three projects. Base level
consumption is given by 365 × ~ and space heat use
is calculated b y multiplying the heating slope, ~, b y
heating degree-days in a " t y p i c a l " year, Ho(T ).
Arrows indicate scaled-up summer consumption.
are not shut off during the summer months,
unlike those in many Northeast and Midwest
public housing authorities. Thus, space heating probably accounts for a small fraction
of summer gas use, particularly in view of
San Francisco's typical summer weather
(e.g., mild temperature and coastal fog).
Temperature-dependent consumption (presumably dominated by space heating), as
estimated by PRISM, is a relatively small
fraction (20%-25%) of total gas use. It
increased slightly after retrofit, in contrast
to what we expected, although ~, the heating
slope, decreased at each project. Possible
decreases in space heat use are masked by
interactive effects among individual model
parameters, especially in view of the large
increase in r seen in four of the projects.
Fels et al. performed parametric tests on the
sensitivity of individual parameters and
NAC to changes in reference temperature on
single-family homes. They demonstrated that,
as the reference temperature, T, increases,
decreases and the space heat term increases,
leaving the much more stable NAC indicator
relatively unchanged [10]. This effect alone
can produce an increase in the estimated
space heat use, irrespective of the impact
of conservation measures. Note that the
change in base level is much larger than its
standard error, while the change in heating
use estimate is not (Fig. 4).
Two major conclusions emerge from this
analysis of individual parameter estimates:
(1) annual base-level usage decreased significantly, despite uncertainties in model estimates and interactive effects, and
(2) more detailed monitoring (e.g., indoor
temperature measurements and submetered
end-use data) is necessary before we can
establish a causal link between changes in
individual parameter estimates and associated
conservation actions.
Economic analysis
We use two indicators of cost-effectiveness
in the economic analysis: simple payback
period and net present value (NPV). Simple
payback period is the time required for the
undiscounted value of the energy savings,
at today's energy prices, to equal the original
investment. The net present value of an
investment is the difference between the
present value of benefits and costs. A worth-
96
while investment has a NPV greater than
zero. The NPV is determined as follows:
DISCUSSION
Bj--C
NPV
j.0
where n is 10 years, the expected lifetime of
the measures, when we estimate benefits,
and eight years, the loan repayment period,
in calculating costs; Bj is the annual (for year
j) economic benefit {19835), Cj is the annual
cost {19835) of the measures, and d is the
discount rate. In calculating net present
value, we assume that the real discount rate
is 7%, that incremental maintenance costs
are negligible, and that gas prices would
increase at a real rate of 1.8% (based on California Energy Commission forecasts) [11].
The aggregate simple payback period is
between 2 and 3.5 years, depending on
whether we use gross or net energy savings,
respectively {Table 3). In either case, the retrofit measures are worthwhile investments
according to this criteria. The aggregate NPV
results suggest that the ZIP program produces
a gross benefit of $445/unit, and a net benefit
of $220/unit at the five projects (see Table 4).
The net benefit/cost ratio is 2.9 (assuming
energy savings persist over the expected lifetime of the retrofit). The Housing Authority's
retrofit cost containment policy contributes
to the economic attractiveness of the weatherization effort. Retrofit costs, which averaged
$150/unit, were only one-fifth of original
utility estimates [12]. This low cost can be
explained, in part, by competition that the
bid process generated among private contractors; by utility cost estimates that were misleading because they were based on experience with individual homes rather than multifamily buildings; and apparent economies of
scale from retrofitting large tracts of similar
buildings.
TABLE 4
Economic analysis of ZIP program
Net present value ($)
NPV/unit ($)
Benefit/cost ratio
Retrofit
Savings
group
aggregate
savings
relative to
group a
806 000
445
4.8
399 000
220
2.9
comparison
aNet energy savings are calculated relative t o comparison group.
Through our work with the San Francisco
Housing Authority and survey of other local
authorities, we have gained some insight
into the process by which specific conservation measures are selected [12,1]. For the
most part, it appears that local authorities
use whatever programs or financial arrangement are readily available, without necessarily matching energy conservation efforts
to the most cost-effective strategies. For
example, under existing conservation programs, the San Francisco Authority is unable
to fund adequately several highly costeffective retrofit options, including lighting
conversions (incandescent to fluorescent)
and improved operations and maintenance
practices. Yet, the Authority had recently
allowed an energy management firm to install
a less predictably cost-effective measure, a
solar hot water heating system at each of
seven senior projects, in a "shared savings"
venture. This retrofit has an estimated
payback time greater than 10 years and its
economic viability is dependent largely on
utility rebates and existing energy and investment tax credits.
The Authority faces the institutional barrier of reduced maintenance budgets, at the
same time that it is attempting to improve
routine building maintenance practices. There
are several low-cost procedures that are likely
to yield highly cost-effective energy savings.
These practices include periodic checking and
adjustment of heating system controls, repair
of inoperable controller valves on apartment
unit radiators, and repair of broken windows
and boiler leaks. Faced with reduced operating budgets, most local authorities have turned
to HUD modernization funds to finance energy-efficiency investments.
Modernization
funds are used mostly for equipment replacement rather than retrofit; conservation potential and reduced life-cycle operating costs
are secondary criteria in the allocation of
funds. We believe that it is short-sighted public policy to neglect the energy and dollar savings potential of prudent maintenance and
energy management practices while encouraging capital-intensive equipment replacement
that improves energy efficiency only as a byproduct (and, in some cases, replaces equip-
97
ment whose main problem is inadequate
maintenance).
Given the limitations of existing programs,
optimal results in retrofitting low-income,
multifamily buildings can only be achieved
through conservation programs specifically
aimed at that sector. Key elements for program success include strong technical assistance (e.g., engineering expertise, detailed
site-specific building audit), sensitivity to
tenant comfort concerns and lifestyle patterns (e.g., to avoid problems like vandalism),
and program design that recognizes the severe
financial constraints faced by most building
owners, public or private.
CONCLUSION
Weather-normalized annual energy consumption declined in four out of five family
housing projects in San Francisco after the
implementation of various conservation measures. The energy savings were strongly correlated with pre-retrofit period consumption
levels: large energy users saved more. Reductions in base-level consumption account for
most of the savings. Our analysis indicates
that the Housing Authority's retrofit efforts
were cost-effective, with an average simple
payback time of 3.5 years when adjusted
for a comparison group, and a net benefit
of $400 000 over the estimated lifetime of
the retrofits.
We found PRISM a useful tool for determining energy savings due to conservation
measures in multifamily buildings. We believe
that it is important also to account explicitly
for changes in vacancy rates when analyzing
changes in consumption patterns. Our results
suggest that there are large uncertainties in
the estimate of base level and space heat
portions of total gas usage for muitifamily
buildings that are located in very mild climates. Yet, accurate end-use estimates are an
important first step in defining appropriate
retrofit strategies. We believe that end-use
estimates derived from model parameters
need to be validated by more detailed monitoring than is typically done by HUD and
local authorities. For example, in San Francisco, several central boilers should be instrumented in order to collect submetered data
on space heat and h o t water use. This small-
scale research monitoring effort, along with
technical audits that focus on heating system
retrofits, would be useful initial steps for the
Authority to take before embarking on expensive heating system capital improvements.
The San Francisco Housing Authority has
adopted an innovative approach in attempting
simultaneously to maintain its housing stock,
reduce energy consumption, and improve
tenant comfort levels. The first generation of
retrofits (mostly building shell improvements
and low~ost hot water measures) has been
completed at most projects and the Authority
is currently investigating new opportunities
(e.g., cogeneration, additional solar hot water
systems, and heating system retrofits). The
lessons learned here can help other public
housing authorities across the country that
face similar dilemmas: how to regain control
over spiraling operating expenses yet still
provide tenants with reasonable comfort and
amenities in a period of tight budgets.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge assistance from Ronald Atkielski at the San
Francisco Housing Authority. We thank
Richard Diamond, Ed Vine, and Margaret
Fels for their helpful comments on a draft of
this report. T h e work described in this report
was funded by the Assistant Secretary for
Conservation and Renewable Energy, Office
of Building Energy Research and Development, Buildings Systems Division of the U.S.
Department of Energy under Contract No.
DE-AC03-76SF00098.
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