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Frontiers of Agricultural Science and Engineering

ISSN 2095-7505

ISSN 2095-977X(Online)

CN 10-1204/S

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Front. Agr. Sci. Eng.    2020, Vol. 7 Issue (4) : 478-489    https://doi.org/10.15302/J-FASE-2019289
RESEARCH ARTICLE
An optimized solar-air degree-day method to evaluate energy demand for poultry buildings in different climate zones
Yang WANG1, Baoming LI1,2,3()
1. Department of Agricultural Structure and Bioenvironmental Engineering, College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
2. Laboratory of Agricultural Engineering in Structure and Environment, Ministry of Agriculture and Rural Affairs, Beijing 100083, China
3. Beijing Engineering Research Center for Animal Healthy Environment, Beijing 100083, China
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Abstract

The degree-day method is widely used to determine energy consumption but cannot be directly applied to poultry buildings without improvements in its accuracy. This study was designed to optimize the degree-day calculation and proposes a solar-air degree-day method, which can be used to calculate the cooling and heating degree-days and the annual cooling and heating loads under different climate conditions for poultry buildings. In this paper, the solar-air degree-day method was proposed, which considers the effects of solar radiation with different wall orientations and surface colors. Five Chinese cities, Harbin, Beijing, Chongqing, Kunming and Guangzhou, were selected to represent different climate zones to determine the solar-air degree-days. The heating and cooling energy requirements for different climates were compared by DeST (Designer’s Simulation Toolkit) simulation and the solar-air degree-day method. Approaches to decrease energy consumption were developed. The results showed that the maximum relative error was less than 10%, and the new method was not significantly different from the DeST simulation (P>0.05). The accuracy of calculating energy requirements was improved by the solar-air degree-day method in the different climate zones. Orientation and surface color effects on energy consumption need to be considered, and external walls of different orientations should have different surface colors.
Keywords base temperature      energy consumption      solar radiation      orientation      surface color     
Corresponding Author(s): Baoming LI   
Just Accepted Date: 20 September 2019   Online First Date: 14 November 2019    Issue Date: 06 November 2020
 Cite this article:   
Yang WANG,Baoming LI. An optimized solar-air degree-day method to evaluate energy demand for poultry buildings in different climate zones[J]. Front. Agr. Sci. Eng. , 2020, 7(4): 478-489.
 URL:  
https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2019289
https://academic.hep.com.cn/fase/EN/Y2020/V7/I4/478
Type Severe cold Cold Hot summer and cold winter Temperate Hot summer and warm winter
ηc 2.65 2.70 2.75 2.65 2.75
ηh 3.25 3.35 3.40 3.30 3.45
Tab.1  Parameters of the energy efficiency ratio for the cooling and heating system
Animals Optimum temperature/°C Base temperature for cooling tic/°C Base temperature for heating/°C
Laying hens (127–432 d) 18–24 24 18
Tab.2  Optimum production temperature and base temperature for poultry[17]
Building envelope Area/m2 Building envelope components Heat transfer coefficient/(W·m−2·K−1)
Roof 1173 200 mm polyurethane foam 0.29
Wall 752 150 mm polyurethane foam 0.39
Door 4.0 single-deck wooden 4.76
Windows 11.5 polystyrene of the metal frame 6.67
Fan 24.0 galvanized and stainless steel 10.0
Floor 1152 concrete 0.47
Tab.3  Geometric and structure characteristics of the building considered[16,19]
City Degree-days/(°C·d) S SE-SW E-W NE-NW N H
Harbin SCDD* 198 249 245 164 99 290
SHDD* 4404 4230 4242 4544 4868 4109
Beijing SCDD* 516 629 658 524 382 759
SHDD* 2084 1898 1855 2069 2340 1994
Chongqing SCDD* 666 886 1014 877 650 1194
SHDD* 722 529 437 536 738 328
Kunming SCDD* 2 44 119 65 8 226
SHDD* 862 632 507 581 783 393
Guangzhou SCDD* 912 1248 1530 1433 1151 1770
SHDD* 236 131 74 91 157 42
Tab.4  SHDD* and SCDD* in laying house (°C·d) at a base temperature of 24°C (cooling) and 18°C (heating)
Fig.1  Comparison of cooling (a) and heating (b) energy demand calculated by the degree-day method, solar-air degree-day method and DeST simulation for five cities in different climate zones of China. Within a city, bars with the same letters are not significantly different (P<0.05).
Period City Degree-day method Solar-air degree-day method
kW·h·m−2 % kW·h·m−2 %
Cooling demand Harbin 0.55 34.8 -0.08 5.22
Beijing 0.45 10.7 -0.05 1.15
Chongqing 0.90 14.3 0.04 0.69
Kunming 0.18 31.0 -0.06 9.59
Guangzhou 1.40 14.9 0.26 2.71
Heating demand Harbin -4.20 10.8 -0.43 1.12
Beijing -2.91 17.9 1.28 7.85
Chongqing -0.90 18.6 -0.07 1.46
Kunming -0.81 15.7 0.30 5.86
Guangzhou -0.44 33.0 -0.13 9.63
Tab.5  Absolute (ΔE) and relative (ΔδE) errors compared with DeST simulation based on five cities in different climate zones of China
Fig.2  Effect of external surface color and orientation on temperature difference between the solar-air temperature and the outside air temperature in five cities in different climate zones of China. (a) Light color; (b) mid color; (c) deep color. S, south; SE, south-east; SW, south-west; E, east; W, west; NE, north-east; NW, north-west; N, north; H, horizontal.
Fig.3  Effect of base temperatures on solar-air cooling (a) and heating (b) degree-days for five cities in different climate zones of China.
City Degree-days/(°C·d) External surface color S SE-SW E-W NE-NW N H
Harbin SCDD* Light 95 112 111 83 61 56
Mid 198 249 245 164 99 290
Deep 349 457 449 276 149 748
SHDD* Light 4889 4794 4800 4965 5138 5179
Mid 4404 4230 4242 4544 4868 4109
Deep 3953 3714 3731 4150 4612 3210
Beijing SCDD* Light 343 391 402 347 282 275
Mid 516 629 658 524 382 759
Deep 720 933 987 736 489 1473
SHDD* Light 2422 2321 2297 2413 2560 2578
Mid 2084 1898 1855 2069 2340 1994
Deep 1769 1519 1461 1748 2133 1030
Chongqing SCDD* Light 499 594 648 590 492 478
Mid 666 886 1014 877 650 1194
Deep 851 1228 1451 1212 825 2171
SHDD* Light 905 796 740 800 914 931
Mid 722 529 437 536 738 328
Deep 556 309 200 317 579 20
Kunming SCDD* Light 0 1 5 2 0 0
Mid 2 44 119 65 8 226
Deep 19 202 426 280 52 1106
SHDD* Light 1031 893 816 862 985 1027
Mid 862 632 507 581 783 393
Deep 714 412 261 352 610 64
Guangzhou SCDD* Light 747 896 1019 976 854 764
Mid 912 1248 1530 1433 1151 1770
Deep 1093 1636 2098 1937 1478 3033
SHDD* Light 309 243 198 212 261 301
Mid 236 131 74 91 157 42
Deep 174 58 17 28 82 0
Tab.6  SHDD* and SCDD* in laying house at a base temperature of 24°C (cooling) and 18°C (heating)
Fig.4  Cooling (a) and heating (b) energy demand for six wall orientations of laying houses in five cities in different climate zones of China. S, south; SE, south-east; SW, south-west; E, east; W, west; NE, north-east; NW, north-west; N, north; H, horizontal.
Fig.5  Cooling (a) and heating (b) energy demand for laying houses with three surface color materials in five cities in different climate zones of China.
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