Hemsath, T. L., & Alagheband Bandhosseini, K. (2015). Sensitivity analysis evaluating basic building geometry’s effect on energy use. Renewable Energy, 76, 526-538. doi:10.1016/j.renene.2014.11.044
Griego, D., Krarti, M., & Hernandez-Guerrero, A. (2015). Energy efficiency optimization of new and existing office buildings in Guanajuato, Mexico. Sustainable Cities and Society, 17, 132-140. doi:10.1016/j.scs.2015.04.008
Lin, H.-W., & Hong, T. (2013). On variations of space-heating energy use in office buildings. Applied Energy, 111, 515-528. doi:10.1016/j.apenergy.2013.05.040
[+]
Hemsath, T. L., & Alagheband Bandhosseini, K. (2015). Sensitivity analysis evaluating basic building geometry’s effect on energy use. Renewable Energy, 76, 526-538. doi:10.1016/j.renene.2014.11.044
Griego, D., Krarti, M., & Hernandez-Guerrero, A. (2015). Energy efficiency optimization of new and existing office buildings in Guanajuato, Mexico. Sustainable Cities and Society, 17, 132-140. doi:10.1016/j.scs.2015.04.008
Lin, H.-W., & Hong, T. (2013). On variations of space-heating energy use in office buildings. Applied Energy, 111, 515-528. doi:10.1016/j.apenergy.2013.05.040
Pikas, E., Thalfeldt, M., & Kurnitski, J. (2014). Cost optimal and nearly zero energy building solutions for office buildings. Energy and Buildings, 74, 30-42. doi:10.1016/j.enbuild.2014.01.039
Terés-Zubiaga, J., Campos-Celador, A., González-Pino, I., & Escudero-Revilla, C. (2015). Energy and economic assessment of the envelope retrofitting in residential buildings in Northern Spain. Energy and Buildings, 86, 194-202. doi:10.1016/j.enbuild.2014.10.018
Lee, J., Kim, J., Song, D., Kim, J., & Jang, C. (2017). Impact of external insulation and internal thermal density upon energy consumption of buildings in a temperate climate with four distinct seasons. Renewable and Sustainable Energy Reviews, 75, 1081-1088. doi:10.1016/j.rser.2016.11.087
Anderson, J. E., Wulfhorst, G., & Lang, W. (2015). Energy analysis of the built environment—A review and outlook. Renewable and Sustainable Energy Reviews, 44, 149-158. doi:10.1016/j.rser.2014.12.027
Abdelaziz, E. A., Saidur, R., & Mekhilef, S. (2011). A review on energy saving strategies in industrial sector. Renewable and Sustainable Energy Reviews, 15(1), 150-168. doi:10.1016/j.rser.2010.09.003
Nejat, P., Jomehzadeh, F., Taheri, M. M., Gohari, M., & Abd. Majid, M. Z. (2015). A global review of energy consumption, CO 2 emissions and policy in the residential sector (with an overview of the top ten CO 2 emitting countries). Renewable and Sustainable Energy Reviews, 43, 843-862. doi:10.1016/j.rser.2014.11.066
Balaras, C. A., Droutsa, K., Dascalaki, E., & Kontoyiannidis, S. (2005). Heating energy consumption and resulting environmental impact of European apartment buildings. Energy and Buildings, 37(5), 429-442. doi:10.1016/j.enbuild.2004.08.003
Pérez-Lombard, L., Ortiz, J., & Pout, C. (2008). A review on buildings energy consumption information. Energy and Buildings, 40(3), 394-398. doi:10.1016/j.enbuild.2007.03.007
Galvin, R. (2010). Thermal upgrades of existing homes in Germany: The building code, subsidies, and economic efficiency. Energy and Buildings, 42(6), 834-844. doi:10.1016/j.enbuild.2009.12.004
Reducing US Greenhouse Gas Emissions: How Much at What Cost?: US Greenhouse Gas Abatement Mapping Initiative https://www.mckinsey.com/business-functions/sustainability/our-insights/reducing-us-greenhouse-gas-emissions
Chappells †, H., & Shove ‡, E. (2005). Debating the future of comfort: environmental sustainability, energy consumption and the indoor environment. Building Research & Information, 33(1), 32-40. doi:10.1080/0961321042000322762
Geva, A., Saaroni, H., & Morris, J. (2013). Measurements and simulations of thermal comfort: a synagogue in Tel Aviv, Israel. Journal of Building Performance Simulation, 7(3), 233-250. doi:10.1080/19401493.2013.819530
Nguyen, A. T., & Reiter, S. (2013). Passive designs and strategies for low-cost housing using simulation-based optimization and different thermal comfort criteria. Journal of Building Performance Simulation, 7(1), 68-81. doi:10.1080/19401493.2013.770067
Rey Martínez, F. J., Chicote, M. A., Peñalver, A. V., Gónzalez, A. T., & Gómez, E. V. (2015). Indoor air quality and thermal comfort evaluation in a Spanish modern low-energy office with thermally activated building systems. Science and Technology for the Built Environment, 21(8), 1091-1099. doi:10.1080/23744731.2015.1056655
Wardiningsih, W., & Troynikov, O. (2017). Force attenuation capacity and thermophysiological wear comfort of vertically lapped nonwoven fabric. The Journal of The Textile Institute, 109(8), 1035-1043. doi:10.1080/00405000.2017.1398624
Oropeza-Perez, I., Petzold-Rodriguez, A. H., & Bonilla-Lopez, C. (2017). Adaptive thermal comfort in the main Mexican climate conditions with and without passive cooling. Energy and Buildings, 145, 251-258. doi:10.1016/j.enbuild.2017.04.031
Matzarakis, A., Mayer, H., & Iziomon, M. G. (1999). Applications of a universal thermal index: physiological equivalent temperature. International Journal of Biometeorology, 43(2), 76-84. doi:10.1007/s004840050119
Peeters, L., Dear, R. de, Hensen, J., & D’haeseleer, W. (2009). Thermal comfort in residential buildings: Comfort values and scales for building energy simulation. Applied Energy, 86(5), 772-780. doi:10.1016/j.apenergy.2008.07.011
Ahmed, K., Akhondzada, A., Kurnitski, J., & Olesen, B. (2017). Occupancy schedules for energy simulation in new prEN16798-1 and ISO/FDIS 17772-1 standards. Sustainable Cities and Society, 35, 134-144. doi:10.1016/j.scs.2017.07.010
Antoniadou, P., & Papadopoulos, A. M. (2017). Occupants’ thermal comfort: State of the art and the prospects of personalized assessment in office buildings. Energy and Buildings, 153, 136-149. doi:10.1016/j.enbuild.2017.08.001
Oropeza-Perez, I., & Østergaard, P. A. (2014). Potential of natural ventilation in temperate countries – A case study of Denmark. Applied Energy, 114, 520-530. doi:10.1016/j.apenergy.2013.10.008
Zhang, L., Zhang, L., & Wang, Y. (2016). Shape optimization of free-form buildings based on solar radiation gain and space efficiency using a multi-objective genetic algorithm in the severe cold zones of China. Solar Energy, 132, 38-50. doi:10.1016/j.solener.2016.02.053
Lei, J., Yang, J., & Yang, E.-H. (2016). Energy performance of building envelopes integrated with phase change materials for cooling load reduction in tropical Singapore. Applied Energy, 162, 207-217. doi:10.1016/j.apenergy.2015.10.031
Chen, C.-W., Lee, C.-W., & Lin, Y.-W. (2014). Air Conditioning — Optimizing Performance by Reducing Energy Consumption. Energy & Environment, 25(5), 1019-1024. doi:10.1260/0958-305x.25.5.1019
Sivak, M. (2009). Potential energy demand for cooling in the 50 largest metropolitan areas of the world: Implications for developing countries. Energy Policy, 37(4), 1382-1384. doi:10.1016/j.enpol.2008.11.031
Attia, S., Hensen, J. L. M., Beltrán, L., & De Herde, A. (2012). Selection criteria for building performance simulation tools: contrasting architects’ and engineers’ needs. Journal of Building Performance Simulation, 5(3), 155-169. doi:10.1080/19401493.2010.549573
Crawley, D. B., Lawrie, L. K., Winkelmann, F. C., Buhl, W. F., Huang, Y. J., Pedersen, C. O., … Glazer, J. (2001). EnergyPlus: creating a new-generation building energy simulation program. Energy and Buildings, 33(4), 319-331. doi:10.1016/s0378-7788(00)00114-6
Newsham, G. R. (1997). Clothing as a thermal comfort moderator and the effect on energy consumption. Energy and Buildings, 26(3), 283-291. doi:10.1016/s0378-7788(97)00009-1
Schiavon, S., & Lee, K. H. (2013). Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures. Building and Environment, 59, 250-260. doi:10.1016/j.buildenv.2012.08.024
Lee, Y. S., & Malkawi, A. M. (2014). Simulating multiple occupant behaviors in buildings: An agent-based modeling approach. Energy and Buildings, 69, 407-416. doi:10.1016/j.enbuild.2013.11.020
Kang, D. H., Mo, P. H., Choi, D. H., Song, S. Y., Yeo, M. S., & Kim, K. W. (2010). Effect of MRT variation on the energy consumption in a PMV-controlled office. Building and Environment, 45(9), 1914-1922. doi:10.1016/j.buildenv.2010.02.020
Luo, M., Cao, B., Zhou, X., Li, M., Zhang, J., Ouyang, Q., & Zhu, Y. (2014). Can personal control influence human thermal comfort? A field study in residential buildings in China in winter. Energy and Buildings, 72, 411-418. doi:10.1016/j.enbuild.2013.12.057
Manu, S., Shukla, Y., Rawal, R., Thomas, L. E., & de Dear, R. (2016). Field studies of thermal comfort across multiple climate zones for the subcontinent: India Model for Adaptive Comfort (IMAC). Building and Environment, 98, 55-70. doi:10.1016/j.buildenv.2015.12.019
Hwang, R.-L., & Shu, S.-Y. (2011). Building envelope regulations on thermal comfort in glass facade buildings and energy-saving potential for PMV-based comfort control. Building and Environment, 46(4), 824-834. doi:10.1016/j.buildenv.2010.10.009
Ioannou, A., & Itard, L. C. M. (2015). Energy performance and comfort in residential buildings: Sensitivity for building parameters and occupancy. Energy and Buildings, 92, 216-233. doi:10.1016/j.enbuild.2015.01.055
Hong, T., Taylor-Lange, S. C., D’Oca, S., Yan, D., & Corgnati, S. P. (2016). Advances in research and applications of energy-related occupant behavior in buildings. Energy and Buildings, 116, 694-702. doi:10.1016/j.enbuild.2015.11.052
Yan, D., O’Brien, W., Hong, T., Feng, X., Burak Gunay, H., Tahmasebi, F., & Mahdavi, A. (2015). Occupant behavior modeling for building performance simulation: Current state and future challenges. Energy and Buildings, 107, 264-278. doi:10.1016/j.enbuild.2015.08.032
Putra, H. C., Andrews, C. J., & Senick, J. A. (2017). An agent-based model of building occupant behavior during load shedding. Building Simulation, 10(6), 845-859. doi:10.1007/s12273-017-0384-x
Thomas, A., Menassa, C. C., & Kamat, V. R. (2017). Lightweight and adaptive building simulation (LABS) framework for integrated building energy and thermal comfort analysis. Building Simulation, 10(6), 1023-1044. doi:10.1007/s12273-017-0409-5
Lindner, A. J. M., Park, S., & Mitterhofer, M. (2017). Determination of requirements on occupant behavior models for the use in building performance simulations. Building Simulation, 10(6), 861-874. doi:10.1007/s12273-017-0394-8
Cedeno Laurent, J. G., Samuelson, H. W., & Chen, Y. (2017). The impact of window opening and other occupant behavior on simulated energy performance in residence halls. Building Simulation, 10(6), 963-976. doi:10.1007/s12273-017-0399-3
Kuznik, F., Virgone, J., & Johannes, K. (2010). Development and validation of a new TRNSYS type for the simulation of external building walls containing PCM. Energy and Buildings, 42(7), 1004-1009. doi:10.1016/j.enbuild.2010.01.012
Salvalai, G., Pfafferott, J., & Sesana, M. M. (2013). Assessing energy and thermal comfort of different low-energy cooling concepts for non-residential buildings. Energy Conversion and Management, 76, 332-341. doi:10.1016/j.enconman.2013.07.064
Lebon, M., Fellouah, H., Galanis, N., Limane, A., & Guerfala, N. (2016). Numerical analysis and field measurements of the airflow patterns and thermal comfort in an indoor swimming pool: a case study. Energy Efficiency, 10(3), 527-548. doi:10.1007/s12053-016-9469-0
Calleja Rodríguez, G., Carrillo Andrés, A., Domínguez Muñoz, F., Cejudo López, J. M., & Zhang, Y. (2013). Uncertainties and sensitivity analysis in building energy simulation using macroparameters. Energy and Buildings, 67, 79-87. doi:10.1016/j.enbuild.2013.08.009
Basinska, M., Koczyk, H., & Szczechowiak, E. (2015). Sensitivity analysis in determining the optimum energy for residential buildings in Polish conditions. Energy and Buildings, 107, 307-318. doi:10.1016/j.enbuild.2015.08.029
Tian, W. (2013). A review of sensitivity analysis methods in building energy analysis. Renewable and Sustainable Energy Reviews, 20, 411-419. doi:10.1016/j.rser.2012.12.014
Lomas, K. J., & Eppel, H. (1992). Sensitivity analysis techniques for building thermal simulation programs. Energy and Buildings, 19(1), 21-44. doi:10.1016/0378-7788(92)90033-d
Breesch, H., & Janssens, A. (2010). Performance evaluation of passive cooling in office buildings based on uncertainty and sensitivity analysis. Solar Energy, 84(8), 1453-1467. doi:10.1016/j.solener.2010.05.008
Peel, M. C., Finlayson, B. L., & McMahon, T. A. (2007). Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences Discussions, 4(2), 439-473. doi:10.5194/hessd-4-439-2007
Balvís, E., Sampedro, Ó., Zaragoza, S., Paredes, A., & Michinel, H. (2016). A simple model for automatic analysis and diagnosis of environmental thermal comfort in energy efficient buildings. Applied Energy, 177, 60-70. doi:10.1016/j.apenergy.2016.04.117
Meteonorm: Irradiation Data for Every Place on Earth. Bern2014: Switzerlan https://meteonorm.com
Fanger, P. O. (1986). Thermal environment — Human requirements. The Environmentalist, 6(4), 275-278. doi:10.1007/bf02238059
Hasan, M. H., Alsaleem, F., & Rafaie, M. (2016). Sensitivity study for the PMV thermal comfort model and the use of wearable devices biometric data for metabolic rate estimation. Building and Environment, 110, 173-183. doi:10.1016/j.buildenv.2016.10.007
Ascione, F., Bianco, N., De Stasio, C., Mauro, G. M., & Vanoli, G. P. (2016). Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality. Applied Energy, 174, 37-68. doi:10.1016/j.apenergy.2016.04.078
Méndez Echenagucia, T., Capozzoli, A., Cascone, Y., & Sassone, M. (2015). The early design stage of a building envelope: Multi-objective search through heating, cooling and lighting energy performance analysis. Applied Energy, 154, 577-591. doi:10.1016/j.apenergy.2015.04.090
Lam, J. C., & Hui, S. C. M. (1996). Sensitivity analysis of energy performance of office buildings. Building and Environment, 31(1), 27-39. doi:10.1016/0360-1323(95)00031-3
Havenith, G., Holmér, I., & Parsons, K. (2002). Personal factors in thermal comfort assessment: clothing properties and metabolic heat production. Energy and Buildings, 34(6), 581-591. doi:10.1016/s0378-7788(02)00008-7
Nikolopoulou, M., Baker, N., & Steemers, K. (2001). Thermal comfort in outdoor urban spaces: understanding the human parameter. Solar Energy, 70(3), 227-235. doi:10.1016/s0038-092x(00)00093-1
Humphreys, M. A., & Fergus Nicol, J. (2002). The validity of ISO-PMV for predicting comfort votes in every-day thermal environments. Energy and Buildings, 34(6), 667-684. doi:10.1016/s0378-7788(02)00018-x
Coakley, D., Raftery, P., & Keane, M. (2014). A review of methods to match building energy simulation models to measured data. Renewable and Sustainable Energy Reviews, 37, 123-141. doi:10.1016/j.rser.2014.05.007
[-]