Thermal Monitoring and Indoor Temperature Predictions in a Passive Solar Building in an Arid Environment

Selecting sunspaces-attaching passive solar house and contrast house which have the same layout and enclosure structure, with the software of DEST to build model and simulation, obtained a heating period interior hourly temperature of the two houses. Arranging, calculating the white, day average indoor temperature of solar house and contrast house. The results show that sunspaces-attaching passive solar house can improve the indoor temperature 3°C, energy saving rate is 37% in this area.

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Estimation of Indoor Temperature for a Direct-Gain Passive Solar Building

Journal of Energy Engineering ◽

10.1061/(asce)ey.1943-7897.0000104 ◽

2014 ◽

Vol 140 (1) ◽

pp. 04013007 ◽

Cited By ~ 3

Author(s):

Jasmina M. Radosavljevic ◽

Miroslav R. Lambic ◽

Emina R. Mihajlovic ◽

Amelija V. Djordjevic

Keyword(s):

Indoor Temperature ◽

Passive Solar

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Estimation of Indoor Temperature for a Passive Solar Residential Building with an Attached Sunspace during the Heating Period

Environmental Progress & Sustainable Energy ◽

10.1002/ep.13127 ◽

2018 ◽

Vol 38 (4) ◽

pp. 13127 ◽

Cited By ~ 1

Author(s):

Ana V. Vukadinović ◽

Jasmina M. Radosavljević ◽

Amelija V. Djordjević ◽

Dejan M. Bonić

Keyword(s):

Residential Building ◽

Heating Period ◽

Indoor Temperature ◽

Passive Solar

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A Pedestrian Approach to Indoor Temperature Distribution Prediction of a Passive Solar Energy Efficient House

Journal of Renewable Energy ◽

10.1155/2015/128496 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9

Author(s):

Golden Makaka

Keyword(s):

Prediction Model ◽

Thermal Behaviour ◽

Indoor Environment ◽

Statistical Prediction ◽

Design Stage ◽

Indoor Temperature ◽

Comfort Levels ◽

Simulation Results ◽

Passive Solar ◽

Statistical Prediction Model

With the increase in energy consumption by buildings in keeping the indoor environment within the comfort levels and the ever increase of energy price there is need to design buildings that require minimal energy to keep the indoor environment within the comfort levels. There is need to predict the indoor temperature during the design stage. In this paper a statistical indoor temperature prediction model was developed. A passive solar house was constructed; thermal behaviour was simulated using ECOTECT and DOE computer software. The thermal behaviour of the house was monitored for a year. The indoor temperature was observed to be in the comfort level for 85% of the total time monitored. The simulation results were compared with the measured results and those from the prediction model. The statistical prediction model was found to agree (95%) with the measured results. Simulation results were observed to agree (96%) with the statistical prediction model. Modeled indoor temperature was most sensitive to the outdoor temperatures variations. The daily mean peak ones were found to be more pronounced in summer (5%) than in winter (4%). The developed model can be used to predict the instantaneous indoor temperature for a specific house design.

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