Authors
Department of Mechanical engineering, Jamia Millia Islamia (Central University), New Delhi, India
Abstract
This study used a simulate based approach for calculating building energy consumption using monitoring data. This calibration was carried out on a building situated in Gurgaon, Delhi. Software used for dynamic simulation was E-Quest 3.65. The objective function was set to minimize the difference between calculated data and simulated data. The evaluation of the model accuracy, the mean bias error (MBE) and the Coefficient of Variation (Cv RMSE) were calculated. Through this paper show the real behavior of people in a building simulation, there may be differences up to 30% [1]. This paper shows the possibility of energy, money and time saving. The schedule of simulated building is same as per actual building.
Keywords
- María Eguaras-Martínez, Marina Vidaurre-Arbizu, César Martín-Gómez 2014, Simulation and evaluation of Building Information Modeling in a real pilot site, Applied Energy science direct 114 : 475–484.
- Government of India Power Sector Jan-2017 Ministry of Power Central Electricity Authority New Delhi.
- Valentina monetti, E. Davin, E. febrizo, P. Andre, M. Fillipi, 2015, Calibration of Building Energy Simulation Models Based on Optimization: A Case Study, Energy Procedia: 2971-2976
- Clevenger C, Haymaker J., 2006, characterstic occupant behavior in abuildig : towards stochastic model, The impact of the building occupant on energy modeling simulations. In: Joint international conference on computing and decision making in civil and building engineering. Montreal, Canada;.
- Crawley D, Lawrie B, Winkelmann LK, Buhl FC, Huang WF, Pedersen YJ, et al. J. 2001, Energy Plus: creating a new-generation building energy simulation program.Energy Buildings;33(4):319–31.
- Crawley DB, Hand JW, Kummert M, Griffith BT. 2008, Contrasting the capabilities of building energy performance simulation programs. Building Environment;43(4):661–73
- J. Yang, H. Fu, M. Qin. 2015, Evaluation of Different Thermal Models in Energy Plus for Calculating Moisture Effects on Building Energy Consumption in Different Climate Conditions. Procedia Engineering, 121: 1635-1641
- R. Singh,I.J. Lazarus,V.V.N. Kishore. 2015, Effect of internal woven roller shade and glazing on the energy and daylighting performances of an office building in the cold climate of Shillong, Applied Energy, 159:317-333.
- A.Pedrini, F. S. Westphal, R. Lamberts. 2001, A methodology for building energy modelling and calibration in warm climates. Office of Building Technology, S.a.C.P.B., Tools Directory. U.S. Department of Energy,.
- É. Mata, A. Sasic, F. Johnsson, 2010, Retrofitting measures for energy savings in theSwedish residential building stock—assessing methodology, Proceedings ofthe Thermal Performance of the Exterior Envelopes of Whole Buildings XIInternational Conference. Florida. USA.December 5–9.
- PORTUGAL, 2006, Regulamento das Características de Comportamento Térmico dos Edifícios (RCCTE), PORTUGAL, Lisboa, Portugal.
- BRASIL, Portaria n. 18, 16 de janeiro de 2012. Requisitos Técnicos da Qualidade para o Nível de Eficiência Energética de Edificac¸ ões Residenciais, BRASIL, Rio de Janeiro, RJ, 2012.
- A.B.C. Board, 2008, About the Australian Building Codes Board Available from. Handbook , ashrae.org.
- M.J. Sorgato, A.P. Melo∗, R. Lamberts, The effect of window opening ventilation control on residential building energy consumption, Lamberts Laboratory for Energy Efficiency in Buildings, Federal University of Santa Catarina, Brazila.
- Balance between energy conservation and environmental impact: Life-cycle energy analysis and life-cycle environmental impactanalysis.
- K.Lam, Z. jhao, B. E. Ydstie, J. Wirick, M. Qi, 2014, AN ENERGYPLUS WHOLE BUILDING ENERGY MODEL CALIBRATION METHOD FOR OFFICE BUILDINGS USING OCCUPANT BEHAVIOR, ASHRAE/IBPSA-USA Building Simulation Conference, 160-167.
- W. Wang, H. Rivard, R. Zmeureanu, 2005, An object-oriented framework for simulation-based green building design optimization with genetic algorithms, Advanced Engineering Informatics 19: 5–23
- J.Ma, X. Li, Y. Zhu. 2015, An hourly simulation method for outdoor thermal environment evaluation. Building simulation, 8: 113–122.
- T. Honga, S. C. Taylor-Langea, S. D’Ocab, D. Yanc, S.P. Corgnatib. 2016. Advances in research and applications of energy-related occupant behavior in buildings. Energy and Buildings, 116: 694 – 702.
- L. Aeleneia, H.Gonçalvesa. 2014, From solar building design to Net Zero Energy Buildings: performance insights of an office building. Energy Procedia,48: 1236 – 1243.
- H. Altana,b, J. Mohelnikovac, P. Hofman. 2015. Thermal and Daylight Evaluation of Building Zones. Energy Procedia 78: 2784 – 2789.88
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