7

- A

- i APPENDIX 7

- A. DEVELOPMENT OF HSPF IMPROVEMENT DEGRADATION

FACTOR

TABLE OF CONTENTS

7

- A.1 Introduction

................................ ................................ ................................ ............ 7

- A

- 1

7

- A.2 Development Methodology

................................ ................................ ................... 7

- A

- 1

LIST OF TABLES

Table 7A.1. Coefficients for %HSPF Decrease (used in equation 7A.1)

................................ 7

- A

- 2 Table 7A.2. Regional HSPF Improvement Degradation Factor

................................ .............. 7

- A

- 47

- A

- 1 A PPENDIX 7

- A

. DEVELOPMENT OF HSPF IMPROVEMENT DEGRADATION

FACTOR

7

- A.1 I ntroduction

Heat pump annual heating performance is affected by climate. There are two reasons for this. First, both the efficiency of compressor heating and the available output capacity of compressor heat are reduced wit h cooler outdoor temperatures and greater refrigerant lift. Second, because the heat pump rating is a rating of the total heating system, including electric backup heat, a greater fraction of the heat provided by the heat pump in cold climates occurs at

c older temperatures when the compressor

- heat capacity is low and where the remainder of the heat provided is electric resistance heat. Electric resistance heating has an effective COP of 1.0

-- lower than the compressor heating COP

-- so when the fraction of h eat that is electric resistance is increased; the average COP (and the corresponding seasonal HSPF for that climate) decreases.

DOE, in establishing the HSPF rating procedure, provided climate data for six climate regions (I

– VI) so manufacturers could develop regional HSPF ratings to inform consumers. However, manufacturers do not typically provide ratings at other than the standard rating condition established for Region IV in the DOE test procedure. a

7

- A.2 Development Methodology For the residential heat pump preliminary analysi s, DOE received comment that simply scaling the heating load with the rated HSPF would not address the climate dependence of heating performance. For the NOPR analysis, DOE developed a methodology to estimate the improvement in seasonal heating efficiency for a heat pump for a specific climate based on a nominal HSPF improvement . This methodology is described in this appendix.

For the residential analysis, DOE received comment that simply scaling the heating load with the rated HSPF would not address the climate dependence of heating performance. To address this, DOE developed a regional HPSF scaling factor which was incorporat ed in the residential energy analysis. This methodology was based on a published study of how heat pump seasonal heating performance is affected by climate

. 1

The simulation analysis showed that the 1% design temperature and rated nameplate

HSPF are suffici ent to achieve reasonable estimates of the climate dependent heating seasonal performance. The analysis showed that a significant decrease in nameplate HSPF (~50%) will occur in severe climates like Minneapolis, MN, but that in very mild climates like Mia mi, FL, the achieved heating seasonal performance exceeds the nominal HSPF. The analysis also suggested that there was a greater percentage discrepancy in climate

- specific seasonal heating performance and the nominal HPSF rating for higher nominal HPSF ra tings. The study This study used residential building simulations to calculate seasonal heating performance facto rs for residences in 15 U.S. climates for four HSPF ratings. The climates selected had from 149 (Miami, FL) to 7876 (Minneapolis, MN) heating degree days.

a Canada, with a cooler average climate, requires ratings for region V for compliance. However, data available for certified products seems to indicate that a region V rating allowed for compliance is simply 15% lower HSPF than the region IV HSPF rating u sed by the U.S.7

- A

- 2 developed a regression model to calculate the percentage degradation in climate

- specific HSPF as a function of the ASHRAE 1% heating design day temperature and the nominal HSPF rating. Two equations were provided, one to represent HSPF v alues <8.5 and one to represent HPSF values 8.5 or higher. These are shown in equation 7

- A.1 below

. b

%HSPF Decrease = a + b*Temp i + c*Temp 2 i + d*HSPF Eq. 7

- A .1

Where Temp i = 1% ASHRAE Heating Design Temperature for Climate i. in °F

HSPF = Nominal HSP F Rating and a, b, c, d are coefficients as shown in Table 7A

- 1

.

Table 7 A

. 1

. Coefficients for % HSPF D ecrease (used in equation 7A.1)

Coeff: HSPF < 8.5 HSPF => 8.5

a = 0.1392 0.1041

b =

- 0.008460

- 0.008862

c =

- 0.0001074

- 0.0001153

d = 0.02280 0.02817

In the analysis of residential heating energy with higher standards, the starting point is the RECS estimate of heating energy, not building load. Thus, for the same RECS observation in the same climate, it is not the intrinsic reduction in heating season al performance due to a colder climate that is important in the energy savings analysis. For example, if all HSPF ratings were simply reduced by 15 percent for a cold region, it would have no bearing in the energy savings

estimate for a higher HSPF. Rath er, it is the how that percentage reduction in a specific climate

differs as a function of nominal HSPF rating that is important.

The results of the simulation study for heat pu mps were also used to develop the Heating

Fuel Comparison Calculator spreadsh eet tool ( heatcalc.xls ) , available on the DOE/EIA website. 2

The heatcalc .xls tool provides estimated climate specific HSPF values for various locations in the U.S. based on a nominal HSPF rating. DOE modified the heatcalc.xls calculator to provide a

mapp ing between regional seasonal heating performance (climate specific HSPF) and nominal

rated HSPF values for each of 237 TMY2 locations using ASHRAE Heating Design Day data 3

DOE then developed HSPF improvement degradation factors (DF HSPF_clim_i ) for eac h nominal HSPF and for each climate location. The HSPF degradation factors are calculated for nominal HSPF improvements above 7.7 HSPF and are based on the ratio of relative improvement in climate specific HSPF (based on the corresponding climate specific HSPF value corresponding to a particular HSPF rating divided by a climate specific HSPF value corresponding to an HSPF of 7.7) divided by the ratio of the improvement in the nominal HSPF ratings. See Equation 7A

- 2 . Once the climate specific degradation factors have been calculated .

b The same study reports a similar analysis for SEER ratings, but notes that while the seasonal heating performance was strongly depending on climate, seasonal cooling performance was less affected. The analysis did not appear to

have take n into account multistage equipment or variable speed air handlers7

- A

- 3 for a range of HSPF values above the baseline, one can use the DF factor to estimate the improvement in climate specific HSPF from the improvement in nominal HSPF. This improvement in climate specific HSPF can, in turn, be use d to better estimate the reduction in heat pump heating energy for specific climates due to a change in nominal HSPF ratings.

** **  ** **  ** **  ** **  ** **  ** **  ** **  ** ** 

**=** 

### ÷

al no al no j

i c i c j

i c j HSPF HSPF HSPF

HSPF HSPF DF

min

_ 7

. 7 min

_

lim_

_ 7

. 7 lim_

_ lim_

_ _ Eq. 7

- A

. 2

Where

DF HSPF_ j_ clim_i =Degra dation Factor for specific HSPFj for specific climate i.

HSPF j_clim_i =Climate Specific HSPF in location i corresponding to a nominal HSPF j being

evaluated.

HSPF 7.7_clim_i = Climate Specific HSPF in location i corresponding to a nominal HSPF of 7.7.

HSPF j_nom = Nominal value of HSPF j being evaluated.

HSPF 7.7_nom = nominal HSPF of 7.7 (equal to 7.7)

The RECS observations do not correspond to particular locations. DOE developed aggregate regional degrad at ion factors for each of the 17 RECS geographic regions (13 censu s divisions with four large states

-- New York, California, Texas, Florida

-- broken out , plus those four states independently ) . To do this it used the climate specific HSPF ratings calculated for the 237 TMY2 locations and the fraction of U.S. population represented by those locations,

normalized for the total population weight for all of the states within a given RECS geographic regions (See Appendix 7

- C for calculation of population weights). This provided insight into the

climate

- specific HSPF variation at the geographic resolution provided by RECS

. DOE used the household weights assigned to each RECS observation with a heat pump to further develop regional HSPF degradation factors for the northern region, the hot

- humid region,

and the hot

- dry region. These regional degradation factors were then i ncorporated into the energy analysis of heat pump heating energy savings. Table 7A

- 2 show s the average degradation factors by region. B ecause the HSPF improvement degradation factors are simple ratios, it is possible to use these same factors to calculate the relative improvement in going from any pair of nominal HSPF ratings. It is also noted that the values shown in T able 7

- A

- 2 take into account

the relative number of RECS households with heat pumps in each of the 17 regions and are not purely the resul t of the differences in climates.7

- A

- 4 Table 7 A

. 2 . Regional HSPF Improvement Degradation Factor

HSPF Rating Regional HSPF Improvement Degradation Factor Rest of Country Hot

- Humid Hot

- Dry National

6.8 1.0286 1.0217 1.0188 1.0226

7.0 1.0223 1.0169 1.0146 1.0176

7.2 1.0159 1.0121 1.0104 1.0126

7.4 1.0095 1.0072 1.0063 1.0075

7.7 1.0000 1.0000 1.0000 1.0000

7.8 0.9968 0.9976 0.9979 0.9975

7.9 0.9936 0.9952 0.9958 0.9950

8.0 0.9905 0.9928 0.9937 0.9925

8.1 0.9873 0.9903 0.9917 0.9899

8.2 0.9841 0.9879 0.9896 0.9874

8.3 0.9809 0.9855 0.9875 0.9849

8.4 0.9777 0.9831 0.9854 0.9824

8.5 0.9622 0.9844 0.9945 0.9816

8.6 0.9583 0.9814 0.9920 0.9785

8.7 0.9543 0.9785 0.9894 0.9754

8.8 0.9504 0.9755 0.9868 0.9723

8.9 0.9465 0.9725 0.9842 0.9692

9.0 0.9425 0.9695 0.9817 0.9661

9.1 0.9386 0.9665 0.9791 0.9630

9.2 0.9347 0.9635 0.9765 0.9599

9.3 0.9307 0.9606 0.9739 0.9568

9.4 0.9268 0.9576 0.9714 0.9537

9.5 0.9229 0.9546 0.9688 0.9506

9.6 0.9190 0.9516 0.9662 0.9475

9.7 0.9150 0.9486 0.9636 0.9444

9.8 0.9111 0.9456 0.9611 0.9413

9.9 0.9072 0.9427 0.9585 0.9381

10.0 0.9032 0.9397 0.9559 0.9350

10.1 0.8993 0.9367 0.9533 0.9319

10.2 0.8954 0.9337 0.9508 0.92887

- A

- 5 REFERENCES

1

. Fairey, P., D.S. Parker, B. Wilcox and M. Lombardi, "Climate Impacts on Heating Seasonal Performance Factor (HSPF) and Seasonal Energy Efficiency Ratio (SEER) for

Air Source Heat Pum ps." ASHRAE Transactions, American Society of Heating, Refrigerating and Air Conditioning Engineers, Inc., Atlanta, GA, June 2004. (Also

available at http://www.fsec.ucf.edu/en/pub lications/html/FSEC

- PF

- 413

- 04/ )

2

. DOE/EIA 2009. Heating Fuel Comparison Calculator (Heatcalc.xls V. HEAT

- CALC

- Vsn

D_1

- 09.xls). < www.eia.doe.gov/neic/experts/heatcalc.xls > ( Accessed October 10, 2010 )

3

. ASHRAE 2009. 2009 ASHRAE Handbook of Fundamentals . American Society of Heating Refrigerating and Air Conditioning Engineers, Atlanta, GA.