Here you can find publications from the jEPlus team and papers/reports/websites used or referenced the jEPlus and jEPlus+EA tools. You are much welcome to send us your publications if the tools have benefited your study.
Here is a list of postgraduate theses and dissertations that can be found online:
Pajek, L. (2022) Energy efficiency of single-family bioclimatic buildings in relation to climate change. University of Ljubljana. Available at: https://repozitorij.uni-lj.si/IzpisGradiva.php?id=136717&lang=slv
Botti, A. (2019) The Development of an Early Stage Design Tool to Assess the Risk of Overheating for UK Residential Buildings. University of Surrey. doi: 10.15126/thesis.00850959.
Nelson, J. (2019) Evaluation of the Passive Cooling Potential of Mass Inherent in Medium to Large Commercial Buildings, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2240095551?accountid=14511.
Miao, L. L. (2019) Net Zero Energy Potential and Parametric Analysis for Multiunit Residential Buildings in Toronto, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2323168859?accountid=14511.
Baniassadi, A. (2019) Vulnerability of U.S. Residential Building Stock to Heat: Status Quo, Trends, Mitigation Strategies, and the Role of Energy Efficiency, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2309942211?accountid=14511.
Alothaimeen, I. (2018) Multi-Objective Optimization for LEED: New Construction Using Genetic Algorithms, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2189752285?accountid=14511.
Duran, Ö. (2018) Evaluation of retrofitting strategies for post-war office buildings. Loughborough University. Available at: https://repository.lboro.ac.uk/articles/thesis/Evaluation_of_retrofitting_strategies_for_post-war_office_buildings/9456431.
Hendricken, L. (2018) Regional Energy Simulation Methods: Identifying, Evaluating, and Comparing Methods to Support the Generation of Virtual Building Stocks at the Sub-national Level, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2153854033?accountid=14511.
Schwartz, Y. (2018) An Integrated Thermal Simulation & Generative Design Decision Support Framework for the Refurbishment or Replacement of Buildings: A Life Cycle Performance Optimisation Approach. UCL (University College London). Available at: https://discovery.ucl.ac.uk/id/eprint/10064687 (Accessed: 31 January 2020).
Lim, H. (2017) Prediction of Urban-Scale Building Energy Performance with a Stochastic-Deterministic-Coupled Approach, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1904921523?accountid=14511.
Kamal, R. (2017) Optimization and Performance Study of Select Heating Ventilation and Air Conditioning Technologies for Commercial Buildings, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1889540271?accountid=14511.
Lozinsky, C. (2017) Improving the Characterization of Infiltration and Natural Ventilation Parameters in Whole-Building Energy Models of Multi-Unit Residential Buildings, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1992172731?accountid=14511.
Zhang, L. (2017) Occupant-aware Energy Management: Energy Saving and Comfort Outcomes Achievable Through Application of Cooling Setpoint Adjustments, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2112752927?accountid=14511.
Bingham, R. D. (2017) Optimization of Residential Buildings and Renewable Energy Integration in Small Island Developing States: The Bahamas as a Case Study, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2014467700?accountid=14511.
Garcia, A. O. (2016) EFFECTS OF ARCHITECTURAL DESIGN VARIABLES ON ENERGY AND ENVIRONMENTAL PERFORMANCE OF OFFICE BUILDINGS. Universitat Rovira i Virgili. Available at: https://www.tdx.cat/handle/10803/395212 (Accessed: 30 January 2020).
Rosado, P. J. (2016) Evaluating Cool Impervious Surfaces: Application to an Energy-Efficient Residential Roof and to City Pavements, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1847567942?accountid=14511.
Bae, N. R. (2016) Influence of Uncertainty in User Behaviors on the Simulation-Based Building Energy Optimization Process and Robust Decision-Making, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1874468446?accountid=14511.
Rahmani Asl, M. (2015) A building information model (BIM) based framework for performance optimization, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1739209354?accountid=14511.
Sun, S. (2015) Energy Efficient Buildings: A Method of Probabilistic Risk Assessment Using Building Energy Simulation, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/2066832910?accountid=14511.
Poudel, N. (2014) Towards the development of performance based guidelines for using Phase Change Materials in lightweight buildings, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1552714918?accountid=14511.
Tresidder, E. (2014) Accelerated optimisation methods for low-carbon building design. De Montfort University. Available at: http://hdl.handle.net/2086/10512 (Accessed: 31 January 2020).
Wang, J. (2014) Integrating Acclimated Kinetic Envelopes into sustainable building design, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1650238889?accountid=14511.
DeLarm-Neri, R. (2013) Energy Modeling of Low-Cost Houses in Colder Climates of South Africa. M.Sc Thesis. Appalachian State University. Available at: http://libres.uncg.edu/ir/asu/listing.aspx?id=10129.
Daily, D. R. (2013) TRADE-OFF BASED DESIGN AND IMPLEMENTATION OF ENERGY EFFICIENCY RETROFITS IN RESIDENTIAL HOMES, University of Maryland. Available at: https://search.proquest.com/docview/1560894132?accountid=14511.
Karaguzel, O. T. (2013) Simulation-Based Parametric Analysis of Building Systems Integrative Solar Photovoltaics, ProQuest Dissertations and Theses. Available at: https://search.proquest.com/docview/1460261840?accountid=14511.
Porritt, S. M. (2012) Adapting UK dwellings for heat waves. De Montfort University. Available at: https://dora.dmu.ac.uk/handle/2086/6327 (Accessed: 31 January 2020).
Dingwall, A. (2012) Testing the impact of using cumulative data with genetic algorithms for the analysis of building energy performance and material cost. M.Sc Thesis. Georgia Institute of Technology. Available at: http://hdl.handle.net/1853/45952.
Moret, S. (2012) Energy efficiency in lighting: daylight harvesting optimization and wireless sensor networks. M.Sc Thesis. University of Padova. Available at: http://tesi.cab.unipd.it/40510.
Korolija, I. (2011) Heating, Ventilating and Air-conditioning System Energy Demand Coupling with Building Loads for Office Buildings. Ph.D. Thesis. De Montfort University. Available at: http://hdl.handle.net/2086/5501 (Accessed: 31 January 2020).
Here is a list of papers where jEPlus and jEPlus+EA are cited to have been used in the research.
Pajek, L. and Košir, M. (2021) ‘Strategy for achieving long-term energy efficiency of European single-family buildings through passive climate adaptation’, Applied Energy, 297, 117116, doi: 10.1016/j.apenergy.2021.117116
Pajek, L. and Košir, M. (2021) ‘Exploring Climate-Change Impacts on Energy Efficiency and Overheating Vulnerability of Bioclimatic Residential Buildings under Central European Climate’, Sustainability, 13(12), 6791, doi: 10.3390/su13126791
Martínez, S. et al. (2020) ‘Model calibration and exergoeconomic optimization with NSGA-II applied to a residential cogeneration’, Applied Thermal Engineering. Elsevier Ltd, 169. doi: 10.1016/j.applthermaleng.2020.114916.
de Gastines, M. and Pattini, A. E. (2020) ‘Window energy efficiency in Argentina - Determining factors and energy savings strategies’, Journal of Cleaner Production, 247, p. 119104. doi: 10.1016/j.jclepro.2019.119104.
Guo, R. et al. (2020) ‘Optimization of cool roof and night ventilation in office buildings: A case study in Xiamen, China’, Renewable Energy. Elsevier Ltd, 147, pp. 2279–2294. doi: 10.1016/j.renene.2019.10.032.
Aghamolaei, R. and Ghaani, M. (2020) ‘Balancing the impacts of energy efficiency strategies on comfort quality of interior places: Application of optimization algorithms in domestic housing’, Journal of Building Engineering, p. 101174. doi: 10.1016/j.jobe.2020.101174.
Qin, H. and Pan, W. (2020) ‘Energy use of subtropical high-rise public residential buildings and impacts of energy saving measures’, Journal of Cleaner Production, p. 120041. doi: 10.1016/j.jclepro.2020.120041.
Fernández Bandera, C. et al. (2020) ‘Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass’, Sustainability, 12(2), p. 553. doi: 10.3390/su12020553.
Xu, K. et al. (2020) ‘Estimation of degraded grassland aboveground biomass using machine learning methods from terrestrial laser scanning data’, Ecological Indicators. Elsevier B.V., 108. doi: 10.1016/j.ecolind.2019.105747.
Zeferina, V. et al. (2019) ‘Sensitivity analysis of peak and annual space cooling load at simplified office dynamic building model’, E3S Web of Conferences. Edited by S. . Tanabe et al., 111, p. 04038. doi: 10.1051/e3sconf/201911104038.
Li, B., Wild, P. and Rowe, A. (2019) ‘Performance of a heat recovery ventilator coupled with an air-to-air heat pump for residential suites in Canadian cities’, Journal of Building Engineering. Elsevier Ltd, 21, pp. 343–354. doi: 10.1016/j.jobe.2018.10.025.
Guo, R. et al. (2019) ‘Influence of design parameters on the night ventilation performance in office buildings based on sensitivity analysis’, Sustainable Cities and Society. Elsevier Ltd, 50. doi: 10.1016/j.scs.2019.101661.
Gokarakonda, S., van Treeck, C. and Rawal, R. (2019) ‘Influence of building design and control parameters on the potential of mixed-mode buildings in India’, Building and Environment. Elsevier Ltd, 148, pp. 157–172. doi: 10.1016/j.buildenv.2018.10.043.
Zuhaib, S., Hajdukiewicz, M. and Goggins, J. (2019) ‘Application of a staged automated calibration methodology to a partially-retrofitted university building energy model’, Journal of Building Engineering. Elsevier Ltd, 26. doi: 10.1016/j.jobe.2019.100866.
Di Giuseppe, E. (2019) ‘A parametric building design tool for assessing energy savings and life cycle costs’, Proceedings of the Institution of Civil Engineers - Engineering Sustainability, 172(6), pp. 283–292. doi: 10.1680/jensu.17.00062.
Mantesi, E. et al. (2019) ‘Empirical and computational evidence for thermal mass assessment: The example of insulating concrete formwork’, Energy and Buildings. Elsevier Ltd, 188–189, pp. 314–332. doi: 10.1016/j.enbuild.2019.02.021.
Lan, L., Wood, K. L. and Yuen, C. (2019) ‘Sustainable design of residential net-zero energy buildings: A multi-phase and multi-objective optimization approach’, in Proceedings of the ASME Design Engineering Technical Conference. American Society of Mechanical Engineers (ASME). doi: 10.1115/DETC2019-97171.
Liu, J. et al. (2019) ‘Energy storage and management system design optimization for a photovoltaic integrated low-energy building’, Energy. Elsevier BV, p. 116424. doi: 10.1016/j.energy.2019.116424.
Stevanović, S., Stevanović, D. and Dehmer, M. (2019) ‘On optimal and near-optimal shapes of external shading of windows in apartment buildings’, PLOS ONE. Edited by L. Wang, 14(2), p. e0212710. doi: 10.1371/journal.pone.0212710.
Lee, P. et al. (2019) ‘Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics’, Facilities. Emerald Group Publishing Ltd., 37(11–12), pp. 860–878. doi: 10.1108/F-05-2017-0051.
Krstić, D. et al. (2019) ‘Effect of external solar shading usage on energy consumption and thermal comfort in the student dormitory in Niš’, E3S Web of Conferences. Edited by S. . Tanabe et al., 111, p. 03050. doi: 10.1051/e3sconf/201911103050.
Lan, L., Wood, K. L. and Yuen, C. (2019) ‘A holistic design approach for residential net-zero energy buildings: A case study in Singapore’, Sustainable Cities and Society. Elsevier Ltd, 50. doi: 10.1016/j.scs.2019.101672.
Rosado, P. J. and Levinson, R. (2019) ‘Potential benefits of cool walls on residential and commercial buildings across California and the United States: Conserving energy, saving money, and reducing emission of greenhouse gases and air pollutants’, Energy and Buildings. Elsevier Ltd, 199, pp. 588–607. doi: 10.1016/j.enbuild.2019.02.028.
Zeferina, V. et al. (2019) ‘Sensitivity analysis of a simplified office building’, Journal of Physics: Conference Series, 1343, p. 012129. doi: 10.1088/1742-6596/1343/1/012129.
Hendricken, L., Wen, J. and L.Gurian, P. (2019) ‘Development of a new reduced order model for predicting the energy savings of multi-ECM permutations’, Energy and Buildings. Elsevier Ltd, 182, pp. 287–299. doi: 10.1016/j.enbuild.2018.10.028.
Guo, R. et al. (2019) ‘Optimal Night Mechanical Ventilation control strategy in office buildings’, in IOP Conference Series: Materials Science and Engineering. Institute of Physics Publishing. doi: 10.1088/1757-899X/609/3/032013.
Naderi, Ehsan et al. (2019) ‘Multi-objective simulation-based optimization of controlled blind specifications to reduce energy consumption, and thermal and visual discomfort: Case studies in Iran’, Building and Environment. Pergamon, p. 106570. doi: 10.1016/J.BUILDENV.2019.106570.
Harputlugil, G. U. et al. (2019) ‘A novel approach for renovation of current social housing stock based on energy consumption in Turkey: significance of occupant behaviour’, Architectural Science Review, 62(4), pp. 323–337. doi: 10.1080/00038628.2019.1615862.
Kamal, R. et al. (2019) ‘Strategic control and cost optimization of thermal energy storage in buildings using EnergyPlus’, Applied Energy. Elsevier Ltd, 246, pp. 77–90. doi: 10.1016/j.apenergy.2019.04.017.
Zuhaib, S. and Goggins, J. (2019) ‘Assessing evidence-based single-step and staged deep retrofit towards nearly zero-energy buildings (nZEB) using multi-objective optimisation’, Energy Efficiency. Springer Netherlands. doi: 10.1007/s12053-019-09812-z.
Fernández Bandera, C. et al. (2018) ‘Exergy As a Measure of Sustainable Retrofitting of Buildings’, Energies, 11(11), p. 3139. doi: 10.3390/en11113139.
Triana, M. A., Lamberts, R. and Sassi, P. (2018) ‘Should we consider climate change for Brazilian social housing? Assessment of energy efficiency adaptation measures’, Energy and Buildings. Elsevier Ltd, 158, pp. 1379–1392. doi: 10.1016/j.enbuild.2017.11.003.
Ramos Ruiz, G., Lucas Segarra, E. and Fernández Bandera, C. (2018) ‘Model Predictive Control Optimization via Genetic Algorithm Using a Detailed Building Energy Model’, Energies, 12(1), p. 34. doi: 10.3390/en12010034.
Allesina, G. et al. (2018) ‘A calibration methodology for building dynamic models based on data collected through survey and billings’, Energy and Buildings. Elsevier Ltd, 158, pp. 406–416. doi: 10.1016/j.enbuild.2017.09.089.
Gou, S. et al. (2018) ‘Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand’, Energy and Buildings. Elsevier Ltd, 169, pp. 484–506. doi: 10.1016/j.enbuild.2017.09.095.
Kneifel, J. et al. (2018) ‘An exploration of the relationship between improvements in energy efficiency and life-cycle energy and carbon emissions using the BIRDS low-energy residential database’, Energy and Buildings. Elsevier Ltd, 160, pp. 19–33. doi: 10.1016/j.enbuild.2017.11.030.
Azarnejad, A. and Mahdavi, A. (2018) ‘Implications of façades’ visual reflectance for buildings’ thermal performance’, Journal of Building Physics, 42(2), pp. 125–141. doi: 10.1177/1744259117731287.
Sghiouri, H. et al. (2018) ‘Shading devices optimization to enhance thermal comfort and energy performance of a residential building in Morocco’, Journal of Building Engineering. Elsevier Ltd, 18, pp. 292–302. doi: 10.1016/j.jobe.2018.03.018.
Jang, H. and Kang, J. (2018) ‘An energy model of high-rise apartment buildings integrating variation in energy consumption between individual units’, Energy and Buildings. Elsevier Ltd, 158, pp. 656–667. doi: 10.1016/j.enbuild.2017.10.047.
Lim, H. and Zhai, Z. (John) (2018) ‘Influences of energy data on Bayesian calibration of building energy model’, Applied Energy. Elsevier Ltd, 231, pp. 686–698. doi: 10.1016/j.apenergy.2018.09.156.
Lee, P., Lam, P. T. I. and Lee, W. L. (2018) ‘Performance risks of lighting retrofit in Energy Performance Contracting projects’, Energy for Sustainable Development. Elsevier B.V., 45, pp. 219–229. doi: 10.1016/j.esd.2018.07.004.
Lee, J. et al. (2018) ‘Thermal performance evaluation of low-income buildings based on indoor temperature performance’, Applied Energy. Elsevier Ltd, 221, pp. 425–436. doi: 10.1016/j.apenergy.2018.03.083.
Luddeni, G. et al. (2018) ‘An analysis methodology for large-scale deep energy retrofits of existing building stocks: Case study of the Italian office building’, Sustainable Cities and Society. Elsevier Ltd, 41, pp. 296–311. doi: 10.1016/j.scs.2018.05.038.
Stevanović, S. and Stevanović, D. (2018) ‘Optimisation of curvilinear external shading of windows in cellular offices’, PLOS ONE. Edited by L. Wang, 13(9), p. e0203575. doi: 10.1371/journal.pone.0203575.Torres-Rivas, A. et al. (2018) ‘Multi-objective optimisation of bio-based thermal insulation materials in building envelopes considering condensation risk’, Applied Energy. Elsevier Ltd, 224, pp. 602–614. doi: 10.1016/j.apenergy.2018.04.079.
Khayatian, F. et al. (2018) ‘Hybrid Probabilistic-Possibilistic Treatment of Uncertainty in Building Energy Models: A Case Study of Sizing Peak Cooling Loads’, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. American Society of Mechanical Engineers (ASME), 4(4). doi: 10.1115/1.4039784.
Tagliabue, L. C. et al. (2018) ‘Techno-economical analysis based on a parametric computational evaluation for decision process on envelope technologies and configurations evaluation for decision process of envelope technologies and configurations’, Energy and Buildings. Elsevier Ltd, 158, pp. 736–749. doi: 10.1016/j.enbuild.2017.10.004.
Bingham, R., Agelin-Chaab, M. and Rosen, M. A. (2017) ‘Multi-objective optimization of a residential building envelope in the Bahamas’, in 2017 5th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2017. Institute of Electrical and Electronics Engineers Inc., pp. 294–301. doi: 10.1109/SEGE.2017.8052815.
Pang, X., Piette, M. A. and Zhou, N. (2017) ‘Characterizing variations in variable air volume system controls’, Energy and Buildings. Elsevier Ltd, 135, pp. 166–175. doi: 10.1016/j.enbuild.2016.11.031.
Giannakis, G; Kontes, G; Korolija, I; Rovas, D. (2017) ‘Simulation-time reduction techniques for a retrofit planning tool’, in 15th International Conference of IBPSA. San Francisco, USA. doi: 10.26868/25222708.2017.554.
Yun, G. Y. and Song, K. (2017) ‘Development of an automatic calibration method of a VRF energy model for the design of energy efficient buildings’, Energy and Buildings. Elsevier Ltd, 135, pp. 156–165. doi: 10.1016/j.enbuild.2016.11.060.
Pinotti, R. et al. (2017) ‘Optimised parametric model of a modular multifunctional climate adaptive façade for shopping centres retrofitting’, in Journal of Facade Design and Engineering. TU Delft, pp. 23–36. doi: 10.7480/jfde.2017.1.1421.
Chen, X., Yang, H. and Wang, T. (2017) ‘Developing a robust assessment system for the passive design approach in the green building rating scheme of Hong Kong’, Journal of Cleaner Production. Elsevier Ltd, 153, pp. 176–194. doi: 10.1016/j.jclepro.2017.03.191.
Djemame, K. et al. (2017) ‘Energy efficiency support through intra-layer cloud stack adaptation’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, pp. 129–143. doi: 10.1007/978-3-319-61920-0_10.
García Kerdan, I. et al. (2017) ‘The role of an exergy-based building stock model for exploration of future decarbonisation scenarios and policy making’, Energy Policy. Elsevier Ltd, 105, pp. 467–483. doi: 10.1016/j.enpol.2017.03.020.
Jankovic, L. (2017) Designing zero carbon buildings using dynamic simulation methods: Second edition, Designing Zero Carbon Buildings Using Dynamic Simulation Methods: Second Edition. Taylor and Francis Inc. doi: 10.4324/9781315620909.
Fernández Bandera, C. and Ramos Ruiz, G. (2017) ‘Towards a New Generation of Building Envelope Calibration’, Energies, 10(12), p. 2102. doi: 10.3390/en10122102.
Pellegrino, A. et al. (2017) ‘Impact of daylighting on total energy use in offices of varying architectural features in Italy: Results from a parametric study’, Building and Environment. Elsevier Ltd, 113, pp. 151–162. doi: 10.1016/j.buildenv.2016.09.012.
Bingham, R. D. and Bingham, D. (2017) Optimization of Residential Buildings and Renewable Energy Integration in Small Island Developing States: The Bahamas as a Case Study. University of Ontario Institute of Technology. Available at: https://ir.library.dc-uoit.ca/handle/10155/847 (Accessed: 30 January 2020).
Zhang, B. et al. (2017) ‘Invariant probabilistic sensitivity analysis for building energy models’, Journal of Building Performance Simulation, 10(4), pp. 392–405. doi: 10.1080/19401493.2016.1265590.
Hosseini, M., Lee, B. and Vakilinia, S. (2017) ‘Energy performance of cool roofs under the impact of actual weather data’, Energy and Buildings. Elsevier Ltd, 145, pp. 284–292. doi: 10.1016/j.enbuild.2017.04.006.
Giuseppe, E. Di, Massi, A. and D’Orazio, M. (2017) ‘Impacts of Uncertainties in Life Cycle Cost Analysis of Buildings Energy Efficiency Measures: Application to a Case Study’, in Energy Procedia. Elsevier Ltd, pp. 442–451. doi: 10.1016/j.egypro.2017.03.206.
Ramos Ruiz, G. and Fernández Bandera, C. (2017) ‘Analysis of uncertainty indices used for building envelope calibration’, Applied Energy. Elsevier Ltd, 185, pp. 82–94. doi: 10.1016/j.apenergy.2016.10.054.
García Kerdan, I. et al. (2017) ‘ExRET-Opt: An automated exergy/exergoeconomic simulation framework for building energy retrofit analysis and design optimisation’, Applied Energy. Elsevier Ltd, 192, pp. 33–58. doi: 10.1016/j.apenergy.2017.02.006.
Lee, J. et al. (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. Elsevier Ltd, pp. 1081–1088. doi: 10.1016/j.rser.2016.11.087.
Bodach, S., Lang, W. and Auer, T. (2016) ‘Design guidelines for energy-efficient hotels in Nepal’, International Journal of Sustainable Built Environment. Elsevier B.V., 5(2), pp. 411–434. doi: 10.1016/j.ijsbe.2016.05.008.
Jang, H. and Kang, J. (2016) ‘A stochastic model of integrating occupant behaviour into energy simulation with respect to actual energy consumption in high-rise apartment buildings’, Energy and Buildings. Elsevier Ltd, 121, pp. 205–216. doi: 10.1016/j.enbuild.2016.03.037.
Fennell, P., Ruyssevelt, P. and Smith, A. (2016) ‘Energy Performance Contracting - Is it time to check the small print?’, In: Proceedings of the 4th European Conference on Behaviour and Energy Efficiency (BEHAVE 2016). European Conference on Behaviour and Energy Efficiency: Coimbra, Portugal. (2016). European Conference on Behaviour and Energy Efficiency. Available at: https://discovery.ucl.ac.uk/id/eprint/1542172/ (Accessed: 31 January 2020).
Delgarm, N., Sajadi, B. and Delgarm, S. (2016) ‘Multi-objective optimization of building energy performance and indoor thermal comfort: A new method using artificial bee colony (ABC)’, Energy and Buildings. Elsevier Ltd, 131, pp. 42–53. doi: 10.1016/j.enbuild.2016.09.003.
Skarning, G. C. J., Hviid, C. A. and Svendsen, S. (2016) ‘Roadmap for improving roof and façade windows in nearly zero-energy houses in Europe’, Energy and Buildings. Elsevier Ltd, 116, pp. 602–613. doi: 10.1016/j.enbuild.2016.01.038.
Kim, C. et al. (2016) ‘Optimized operation method for an active chilled beam with VAV system’, Science and Technology for the Built Environment, 22(4), pp. 372–378. doi: 10.1080/23744731.2016.1158044.
Ji, Y. et al. (2016) ‘Design summer year weather – outdoor warmth ranking metrics and their numerical verification’, Building Services Engineering Research and Technology, 37(6), pp. 639–663. doi: 10.1177/0143624416648179.
Khattak, S. H. et al. (2016) ‘An exergy based approach to resource accounting for factories’, Journal of Cleaner Production. Elsevier Ltd, 121, pp. 99–108. doi: 10.1016/j.jclepro.2015.12.029.
Stevanović, S. (2016) ‘Parametric study of a cost-optimal, energy efficient office building in Serbia’, Energy. Elsevier Ltd, 117, pp. 492–505. doi: 10.1016/j.energy.2016.06.048.
Ramos Ruiz, G. et al. (2016) ‘Genetic algorithm for building envelope calibration’, Applied Energy. Elsevier Ltd, 168, pp. 691–705. doi: 10.1016/j.apenergy.2016.01.075.
Schwartz, Y., Raslan, R. and Mumovic, D. (2016) ‘Implementing multi objective genetic algorithm for life cycle carbon footprint and life cycle cost minimisation: A building refurbishment case study’, Energy. Elsevier Ltd, 97, pp. 58–68. doi: 10.1016/j.energy.2015.11.056.
Delgarm, N. et al. (2016) ‘Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)’, Applied Energy. Elsevier Ltd, 170, pp. 293–303. doi: 10.1016/j.apenergy.2016.02.141.
Tokarik, M. S. and Richman, R. C. (2016) ‘Life cycle cost optimization of passive energy efficiency improvements in a Toronto house’, Energy and Buildings. Elsevier Ltd, 118, pp. 160–169. doi: 10.1016/j.enbuild.2016.02.015.
Sun, S. et al. (2016) ‘A method of probabilistic risk assessment for energy performance and cost using building energy simulation’, Energy and Buildings. Elsevier Ltd, 110, pp. 1–12. doi: 10.1016/j.enbuild.2015.09.070.
Gilan, S. S., Goyal, N. and Dilkina, B. (2016) ‘Active learning in multi-objective evolutionary algorithms for sustainable building design’, in GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference, pp. 589–596. doi: 10.1145/2908812.2908947.
Cipriano, J. et al. (2016) ‘Development of a dynamic model for natural ventilated photovoltaic components and of a data driven approach to validate and identify the model parameters’, Solar Energy. Elsevier Ltd, 129, pp. 310–331. doi: 10.1016/j.solener.2016.01.039.
Papasifaki, A., Garcia Kerdan, I. and Ucci, M. (2016) ‘Multi Objective Optimisation analysis of non-domestic building retrofit strategies in the UK, under climate change uncertainty: A Passivhaus case study approach’, in In: Proceedings of 6th Masters Conference: People and Buildings. Network for Comfort and Energy Use in Buildings: London, UK. (2016). Network for Comfort and Energy Use in Buildings. Available at: https://discovery.ucl.ac.uk/id/eprint/1544896/ (Accessed: 31 January 2020).
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