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

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1.2 Background and literature review 24 requirements of IEATask 28 (2003). Simulations of the buildings for cold climate data in Stockholm were carried out with computer code DEROB-LTH (2005). This dynamic simulation tool was built based on a ray tracing model. The results of the calculation revealed that the space-heating demand can be reduced by up to 83 % for single-family houses and by up to 85 % for apartment buildings. The authors’ conclusion was that we should take into consideration the following design features: tightness of the building envelope, air ventilation balancing and heat recovery systems in order to obtain demand space-heating requirements equaling less than 15 – 25 kWh/m 2 . Experimental investigations of three Danish single-family houses constructed according to the new building energy requirements introduced in Denmark in 2006, were carried out by Tommerup and co-authors (Tommerup, et al., 2007). This project assumed a complex measure of energy consumption for space heating, domestic hot water and electricity consumption, solar radiation, outdoor and indoor temperatures and temperatures in HVAC systems. Findings of the experiment indicated that the energy consumption of all investigated houses can be classified as ‘‘low-energy house class 2’’. It means that energy consumption is 75 % of the required maximum value. Furthermore, applying existing lowenergy products in analyzed buildings can reduce consumption of electricity by about 40 %. The authors hope that the results of the current project will be a good basis for the development of energy-saving buildings in the future. Turkish Standard Number 825 (TS 825) introduces four different degree-day (DD) regions namely: Izmir (DD: 1450), Bursa (DD: 2203), Eskis-ehir (DD: 3215) and Erzurum (DD: 4856). For these provinces Sisman and co-workers (Sisman, et al., 2007) determined an optimum insulation thickness for a lifetime of N years. Optimization calculations assumed exterior air temperature, length of the heating period, operating time of the system, economical lifetime and properties of the insulation material. The optimum value of insulation thickness, which is the result of the current analysis, is equal to 0.033 m for Izmir, 0.047 m for Bursa, 0.061 m for Eskis-ehir and 0.08 m for Erzurum. Bakos (Bakos, 2000) analyzed the thermal insulation in residential and tertiary sector, which was built before the enactment of the Greek Thermal Insulation Code. Various insulation protection approaches for buildings situated in Kavala (Northern Greece) were investigated. The economical analysis took into account the costs of insulation material, labour and insurance. Bakos concluded that the correct combination of insulation materials can make substantial energy savings. The analysis of heat transfer through composite roofs consisting of different positions of insulation materials was realized by Ozel and Pihtili (2007). They applied numerical models based on an implicit finite difference scheme and MATLAB environment in their simulations. Twelve different roof constructions were investigated for both winter and summer periods. Ozel and Pihtili (Ozel, et al., 2007) states that “the best load leveling was achieved in the case where three pieces of insulation of equal thickness were placed one at the outdoor surface of the roof, the second piece of insulation was placed in the middle of the roof and the third piece of insulation was placed on the indoor surface of the roof”.
1.2 Background and literature review 25 Fig. 1.3 presents the best location of insulation inside a roof. glass wool concrete block glass wool concrete block glass wool Fig. 1.3: Configuration of insulation selected by Ozel and Pihtili (2007) as the best solution. Dombayci and co-workers (Dombayci, et al., 2006) investigated the optimization of external wall insulation thickness for Denizli (southwestern Turkey) weather conditions. The effects of the energy source types (coal, natural gas, LPG, fuel oil, electricity) on energy savings and the use of different insulation materials (expanded polystyrene, rock wool) were analyzed. The difference between the buildings’ heating costs, with and without the insulation of external walls, was used in a life-cycle cost analysis (LCCA). Results of the calculations revealed that the life cycle savings are $ 14.09 per square metre of wall surface area and a very short payback period of 1.43 years for the optimum insulation-thickness. These results were obtained with coal as the energy source and expanded polystyrene as the insulating material. Khaled (Khaled, 2003) comprised two types of roof insulation (polystyrene and fiberglass) for warm and cold climate conditions. Energy analysis was carried out for a 108 m 2 house in two USA locations: College Station (Texas) and Minneapolis (Minnesota). The RENCON simulation program (Degelman, et al., 1991) was used to determine annual heating and cooling energy consumption. Six different insulation resistance levels of the roof (R5, R10, R15, R20, R25, R30) were examined. In Khaled’s opinion, the most costeffective thermal resistance for polystyrene is R5 and for fiberglass is R10. Besides this, the author remarked that the payback time of using insulation in a cold climate is shorter than that of a warm climate and that the best solution for thermal insulation design is the use of a life-cycle cost analysis rather than the construction budget limitation. The problem concerning the best insulation level of the envelope of new residential buildings in 6 Italian climatic zones was studied by Lollini (Lollini, et al., 2006). Economical analysis was based on two main parameters of investment efficiency: the net present value (NPV) and the payback rate (PBR). The methodology used in this project included the following factors: calculation of the optimal insulation thickness, analyses of market and cost, energy calculation of the reference buildings, calculation for different
Page 1 and 2: ANALYSIS OF THE INFLUENCES OF SOLAR
Page 3 and 4: than the inner air temperature. It
Page 5 and 6: 4.1 SUMMARY .......................
Page 7 and 8: Subscripts σ - Stefan-Boltzmann co
Page 9 and 10: 1.1 Introduction 9 Another problem,
Page 11 and 12: 1.2 Background and literature revie
Page 23: 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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3.3 Estimation of thermal energy ga
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3.3 Estimation of thermal energy ga
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3.4 Testing of a building indoor en
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36 34 32 30 28 26 24 22 20 18 36 34
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3,00 2,50 2,00 1,50 1,00 0,50 0,00
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3.5 Optimization of a solar domesti
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4.1 Summary 99 4 Summary and conclu
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4.2 Comments and conclusions 101 So
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4.3 Future research 103 of the annu
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References 105 Beausoleil-Morrison,
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References 107 Hendron, R., et al.
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References 109 Rees, S. and Haves,
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References 111 Yohanis, Y.G., et al
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Appendix 1 113 Fig. A1.1 VASATI 2.0
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Appendix 2 123 !-Generator IDFEdito
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Appendix 2 125 0.035, !- Conductivi
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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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