analysis of the influences of solar radiation and façade glazing ...

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3.3 Estimation of thermal energy gain and loss through building fenestration 78 optimal value of the window-to-wall ratio for the entire building was equal to over 22 %. But the area of the south-facing windows was enlarged to 58 % of the façade size. The lowest value of WWR, only equal to about 4 %, characterizes the north façade of the building under consideration. Window Opening Area - design value (m 2 ) Window Opening Area - optimal value (m 2 ) Difference between design and optimal value (m 2 ) Difference between design and optimal value (%) Optimal value of the Window-to-Wall Ratio (%) Table 3.9: Optimal value of Window-to-Wall Ratio. Total North 315 to 45 deg East 45 to 135 deg South 135 to 225 deg West 225 to 315 deg 768.42 148.11 155.67 205.26 259.37 410.70 17.78 53.77 260.38 78.77 357.72 130.33 101.9 -55.12 180.6 46.55 88.00 65.46 -26.85 69.63 22.15 3.96 11.23 58.07 16.45 It is crucial to note that the optimal value of WWR can significantly provide a reduction in energy consumption. As we see in Table 3.10, it is possible to decrease the space heating energy requirements by over 30 %. Design value Optimal value Difference between design and optimal value Difference between design and optimal value (%) Table 3.10: Heating energy consumption. District Heating (kWh) Energy Per Total Building Area (kWh/m 2 ) Energy Per Conditioned Building Area (kWh/m 2 ) 29138.56 21.23 21.98 19963.75 17.32 17.93 9174.81 3.910 4.050 31.49 18.42 18.43 It is important to underline that the results of the optimization procedure, shown above, cannot be applied to other multi-family buildings because the optimal value of WWR mainly depends upon the apartment arrangement, the thermal and optical performance of windows and the building shape. However, the proposed optimization procedure is universal and can be used for single-family as well as multi-family buildings.
3.4 Testing of a building indoor environment during the warm period 79 3.4 Testing of a building indoor environment during the warm period The simulation was carried out to audit the thermal environment in the apartments during the warm period. Calculations were performed with the following assumptions: • the cooling system is turned off, • mechanical intensive night ventilation with outside air and at a variable flow rate was realized. Reduction of gains from solar radiation during the summer was performed by: • protection shields made by movable glass parts printed with various patterns, which were positioned on a movable rails construction on the level of the building facade in front of the balconies, • alternatively an internal or external window shade with high reflect parameters. The zone’s thermal environment was defined by using: Predicted Mean Vote (PMV), Predicted Percentage of Dissatisfied (PPD) and operative temperature θO given by: ( A) MR θO = Aθa , i + 1− θ , (3.5) where: A = hr / (hc + hr) hr – surface heat transfer coefficient by radiation, hc – surface heat transfer coefficient by convection, θa,i – the air temperature inside the zone-i, θMR – the mean radiant temperature. The calculation of the mean radiant temperature was done by equation (3.6). n 4 ∑ i= 1 θ = F θ , MR where: 4 o−i i, r n – the number of surfaces inside the zone-i, Fo-i – the view factor of the human body, – the radiant temperature of the isothermal surface. θi,r (3.6)
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ANALYSIS OF THE INFLUENCES OF SOLAR
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than the inner air temperature. It
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4.1 SUMMARY .......................
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Subscripts σ - Stefan-Boltzmann co
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1.1 Introduction 9 Another problem,
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1.2 Background and literature revie
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Page 27 and 28: 1.2 Background and literature revie
Page 41 and 42: 2.1 Building energy simulation soft
Page 47 and 48: 2.2 Experimental research methods 4
Page 53 and 54: 3.1 Building description 53 Fig. 3.
Page 55 and 56: 3.1 Building description 55 All int
Page 57 and 58: 3.1 Building description 57 Case B5
Page 59 and 60: 3.1 Building description 59 Of cour
Page 61 and 62: 3.1 Building description 61 Outside
Page 63 and 64: 3.1 Building description 63 In orde
Page 69 and 70: 3.2 Selection of the optimal glazin
Page 71 and 72: 3.3 Estimation of thermal energy ga
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Page 83 and 84: 3,00 2,50 2,00 1,50 1,00 0,50 0,00
Page 85 and 86: 3.4 Testing of a building indoor en
Page 91 and 92: 3.5 Optimization of a solar domesti
Page 99 and 100: 4.1 Summary 99 4 Summary and conclu
Page 101 and 102: 4.2 Comments and conclusions 101 So
Page 103 and 104: 4.3 Future research 103 of the annu
Page 105 and 106: References 105 Beausoleil-Morrison,
Page 107 and 108: References 107 Hendron, R., et al.
Page 109 and 110: References 109 Rees, S. and Haves,
Page 111 and 112: References 111 Yohanis, Y.G., et al
Page 113 and 114: Appendix 1 113 Fig. A1.1 VASATI 2.0
Page 123 and 124: Appendix 2 123 !-Generator IDFEdito
Page 125 and 126: Appendix 2 125 0.035, !- Conductivi
Page 127 and 128: Appendix 2 127 , !- Zone Inside Con
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Appendix 2 129 Discrete; !- Numeric
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Appendix 2 131 Fraction, !- Schedul
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Appendix 2 133 Air Conditioner:Wind
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Appendix 2 135 , !- Sensible Heat F
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Appendix 2 137 281, !- Lighting Lev
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Appendix 2 139 OG2 InfilTRATION, !-
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Appendix 2 141 OG3, !- Zone Name 16
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Appendix 2 143 0.004, !- Zone Heati
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Appendix 2 145 Zone15WindACAirInlet
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Appendix 2 147 0, !- Maximum Flow R
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Appendix 2 149 Zone16WindACOAMixer,
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Appendix 2 151 Zone 9 Outlet Node;
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Appendix 2 153 Stand Alone ERV 16,
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Appendix 2 155 ZoneHVAC:WindowAirCo
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Appendix 2 157 ZoneHVAC:Baseboard:C
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Appendix 2 159 Zone Control Type Sc
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Appendix 2 161 WindACPLFFPLR, !- Pa
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Appendix 2 163 Stand Alone ERV Supp
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Appendix 2 165 0.03001, !- Maximum
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Appendix 2 167 0.81, !- Sensible Ef
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Appendix 2 169 !- == ALL OBJECTS IN
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