meta data for this page
Research Publications where jEPlus Tools Were Used
Here you can find publications that used jEPlus and jEPlus+EA tools. You are welcome to send us your publications if the tools have benefited your study.
Last updated: 1 Feb 2023
Aghamolaei, R. and Ghaani, M. R. M. R. (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, 29, p. 101174. doi: https://doi.org/10.1016/j.jobe.2020.101174.
Alajmi, A., Abou-Ziyan, H. and Al-Mutairi, H. H. (2022) ‘Reassessment of fenestration characteristics for residential buildings in hot climates: energy and economic analysis’, Frontiers in Energy. Higher Education Press Limited Company, 16(4), pp. 629–650. doi: 10.1007/S11708-021-0799-Z/METRICS.
Alkaabi, N. et al. (2020) ‘A data-driven modeling and analysis approach to test the resilience of green buildings to uncertainty in operation patterns’, Energy Science and Engineering, 8(12). doi: 10.1002/ese3.808.
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.
Alsharif, R. et al. (2022) ‘Machine learning-based analysis of occupant-centric aspects: Critical elements in the energy consumption of residential buildings’, Journal of Building Engineering, 46, p. 103846. doi: https://doi.org/10.1016/j.jobe.2021.103846.
Azar, E. et al. (2021) ‘Drivers of energy consumption in Kuwaiti buildings: Insights from a hybrid statistical and building performance simulation approach’, Energy Policy, 150, p. 112154. doi: https://doi.org/10.1016/j.enpol.2021.112154.
Azarnejad, A. and Mahdavi, A. (2018) ‘Implications of façades’ visual reflectance for buildings’ thermal performance’, Journal of Building Physics. SAGE Publications Ltd, 42(2), pp. 125–141. Available at: http://journals.sagepub.com/doi/10.1177/1744259117731287 (Accessed: 24 January 2020).
Baba, F. M., Ge, H., Zmeureanu, R., et al. (2022) ‘Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study’, Building and Environment, 207, p. 108518. doi: https://doi.org/10.1016/j.buildenv.2021.108518.
Baba, F. M., Ge, H., Wang, L. (Leon), et al. (2022) ‘Do high energy-efficient buildings increase overheating risk in cold climates? Causes and mitigation measures required under recent and future climates’, Building and Environment, 219, p. 109230. doi: https://doi.org/10.1016/j.buildenv.2022.109230.
Baghoolizadeh, M., Rostamzadeh-Renani, M., et al. (2022) ‘A prediction model for CO2 concentration and multi-objective optimization of CO2 concentration and annual electricity consumption cost in residential buildings using ANN and GA’, Journal of Cleaner Production, 379, p. 134753. doi: https://doi.org/10.1016/j.jclepro.2022.134753.
Baghoolizadeh, M., Nadooshan, A. A., et al. (2022) ‘The effect of photovoltaic shading with ideal tilt angle on the energy cost optimization of a building model in European cities’, Energy for Sustainable Development, 71, pp. 505–516. doi: https://doi.org/10.1016/j.esd.2022.10.016.
Baghoolizadeh, M. et al. (2023) ‘Multi-objective optimization of Venetian blinds in office buildings to reduce electricity consumption and improve visual and thermal comfort by NSGA-II’, Energy and Buildings, 278, p. 112639. doi: https://doi.org/10.1016/j.enbuild.2022.112639.
Bandera, C. F. 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.
Banoczy, E. (2015) ‘Development of simulation-based methodology for Energy Performance Certification of Buildings’, in 2015 5th International Youth Conference on Energy (IYCE). Pisa, Italy: IEEE, pp. 27–30. doi: 10.1109/IYCE.2015.7180733.
Bánóczy, E., Szemes, P. T. and Korondi, P. (2014) ‘Simulation of building renovation’s return in Energy plus’, Environmental Engineering and Management Journal, 13(11), pp. 2743–2748.
Bao, Y., Lee, W. L. and Jia, J. (2021) ‘Probabilistic assessment of overcooling risk for a novel extra-low temperature dedicated outdoor air system for Hong Kong office buildings’, Building Simulation. Tsinghua University, 14(3), pp. 633–648. Available at: https://link.springer.com/10.1007/s12273-020-0684-4 (Accessed: 31 January 2023).
Basurra, S. and Jankovic, L. (2015) ‘Bringing building simulation to a wider audience - A web based simulation and optimisation system’, in 14th International Conference of IBPSA - Building Simulation 2015, BS 2015, Conference Proceedings, pp. 1962–1969.
Becq, A. and Chèze, D. (2021) ‘Influence of mixing valve dynamics and recirculation loop connection to solar tank on large hot water system performances’, Solar Energy, 218, pp. 211–225. doi: https://doi.org/10.1016/j.solener.2021.02.012.
Belleri, A. et al. (2013) ‘A Sensitivity Analysis of Natural Ventilation Design Parameters for Non Residential Buildings’, in BS 2013 - 13th Int. IBPSA Conference. Chambery, France, pp. 3300–3307. Available at: https://www.researchgate.net/publication/256396401_A_sensitivity_analysis_of_natural_ventilation_design_parameters_for_non_residential_buildings.
Belleri, A. and Lollini, R. (2012) ‘Uncertainties in airflow network modelling to support natural ventilation early stage design’, in 33rd AIVC - 2nd Tightvent conference: Optimising Ventilative Cooling and Airtightness for [Nearly] Zero-Energy Buildings, IAQ and Comfort. Copenhagen, Denmark.
Belleri, A., Lollini, R. and Dutton, S. M. (2014) ‘Natural ventilation design: An analysis of predicted and measured performance’, Building and Environment. Elsevier Ltd, 81, pp. 123–138. doi: 10.1016/j.buildenv.2014.06.009.
Bengoetxea, A. et al. (2020) ‘Control strategy optimization of a Stirling based residential hybrid system through multi-objective optimization’, Energy Conversion and Management, 208, p. 112549. doi: https://doi.org/10.1016/j.enconman.2020.112549.
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.
Boafo, F. E., Kim, J.-T. and Kim, J.-H. (2017) ‘Evaluating the impact of green roof evapotranspiration on annual building energy performance’, International Journal of Green Energy. Taylor & Francis, 14(5), pp. 479–489. doi: 10.1080/15435075.2016.1278375.
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.
Bordbari, M. J., Rastegar, M. and Seifi, A. R. (2020) ‘Probabilistic Energy Efficiency Analysis in Buildings Using Statistical Methods’, Iranian Journal of Science and Technology - Transactions of Electrical Engineering. Springer, 44(3), pp. 1133–1145. doi: 10.1007/S40998-019-00288-2/TABLES/9.
Botti, A. et al. (2022) ‘Developing a meta-model for early-stage overheating risk assessment for new apartments in London’, Energy and Buildings, 254, p. 111586. doi: https://doi.org/10.1016/j.enbuild.2021.111586.
Bull, J. et al. (2014) ‘Life cycle cost and carbon footprint of energy efficient refurbishments to 20th century UK school buildings’, International Journal of Sustainable Built Environment. Elsevier B.V., 3(1), pp. 1–17. doi: 10.1016/j.ijsbe.2014.07.002.
Bull, J., Kimpian, J. and Mumovic, D. (2013) ‘Parametric models for predicting life cycle energy, cost, and carbon implications of refurbishment in schools and offices’, in CIBSE Technical Symposium 2013. Liverpool, UK.
Calama-González, C. M. et al. (2021) ‘Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring’, Applied Energy, 282, p. 116118. doi: https://doi.org/10.1016/j.apenergy.2020.116118.
Calama-González, C. M. et al. (2022) ‘Optimal retrofit solutions considering thermal comfort and intervention costs for the Mediterranean social housing stock’, Energy and Buildings, 259, p. 111915. doi: https://doi.org/10.1016/j.enbuild.2022.111915.
Calama-González, C. M., León-Rodríguez, Á. L. and Suárez, R. (2022) ‘Climate change mitigation: thermal comfort improvement in Mediterranean social dwellings through dynamic test cells modelling’, International Journal of Energy and Environmental Engineering. Springer Science and Business Media Deutschland GmbH, pp. 1–14. doi: 10.1007/S40095-022-00498-1/FIGURES/11.
Calama-González, C. M., Suárez, R. and León-Rodríguez, Á. L. (2022) ‘Thermal comfort prediction of the existing housing stock in southern Spain through calibrated and validated parameterized simulation models’, Energy and Buildings, 254, p. 111562. doi: https://doi.org/10.1016/j.enbuild.2021.111562.
Carlucci, S. et al. (2021) ‘On the impact of stochastic modeling of occupant behavior on the energy use of office buildings’, Energy and Buildings, 246, p. 111049. doi: https://doi.org/10.1016/j.enbuild.2021.111049.
Carlucci, S., Pagliano, L. and Sangalli, A. (2014) ‘Statistical analysis of the ranking capability of long-term thermal discomfort indices and their adoption in optimization processes to support building design’, Building and Environment, 75, pp. 114–131. doi: 10.1016/j.buildenv.2013.12.017.
Carreras, J. et al. (2015) ‘Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact’, Energy and Buildings. Elsevier Ltd, 88, pp. 335–346. doi: 10.1016/j.enbuild.2014.12.007.
Carreras, J. et al. (2016) ‘Eco-costs evaluation for the optimal design of buildings with lower environmental impact’, Energy and Buildings. Elsevier Ltd, 119, pp. 189–199. doi: 10.1016/j.enbuild.2016.03.034.
Chen, R. and Tsay, Y.-S. (2022) ‘Carbon emission and thermal comfort prediction model for an office building considering the contribution rate of design parameters’, Energy Reports, 8, pp. 8093–8107. doi: https://doi.org/10.1016/j.egyr.2022.06.012.
Chen, R., Tsay, Y.-S. and Ni, S. (2022) ‘An integrated framework for multi-objective optimization of building performance: Carbon emissions, thermal comfort, and global cost’, Journal of Cleaner Production, 359, p. 131978. doi: https://doi.org/10.1016/j.jclepro.2022.131978.
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.
Cipriano, J. et al. (2015) ‘Evaluation of a multi-stage guided search approach for the calibration of building energy simulation models’, Energy and Buildings. Elsevier Ltd, 87, pp. 370–385. doi: 10.1016/j.enbuild.2014.08.052.
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.
Coakley, D., Raftery, P. and Molloy, P. (2012) ‘Calibration of whole building energy simulation models: Detailed case study of a naturally ventilated building using hourly measured data’, in BSO12 - Building Simulation and Optimization Conference. Loughborough, UK.
Costa-Carrapiço, I. et al. (2022) ‘Hygrothermal calibration and validation of vernacular dwellings: A genetic algorithm-based optimisation methodology’, Journal of Building Engineering, 55, p. 104717. doi: https://doi.org/10.1016/j.jobe.2022.104717.
Cruz, A. S. and Cunha, E. G. da (2022) ‘The impact of climate change on the thermal-energy performance of the SCIP and ICF wall systems for social housing in Brazil’, Indoor and Built Environment. SAGE Publications Ltd, 31(3), pp. 838–852. doi: 10.1177/1420326×211038047/ASSET/IMAGES/10.1177_1420326X211038047-IMG2.PNG.
Delač, B. et al. (2022) ‘Integrated optimization of the building envelope and the HVAC system in nZEB refurbishment’, Applied Thermal Engineering, 211, p. 118442. doi: https://doi.org/10.1016/j.applthermaleng.2022.118442.
Delgarm, Navid et al. (2016) ‘A novel approach for the simulation-based optimization of the buildings energy consumption using NSGA-II: Case study in Iran’, Energy and Buildings. Elsevier Ltd, 127, pp. 552–560. doi: 10.1016/j.enbuild.2016.05.052.
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.
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.
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. Available at: https://link.springer.com/chapter/10.1007/978-3-319-61920-0_10 (Accessed: 24 January 2020).
Du, Y., Zhou, Z. and Zhao, J. (2022) ‘Multi-regional building energy efficiency intelligent regulation strategy based on multi-objective optimization and model predictive control’, Journal of Cleaner Production, 349, p. 131264. doi: https://doi.org/10.1016/j.jclepro.2022.131264.
Duran, Ö., Taylor, S. C. and Lomas, K. J. (2015) ‘Evaluation of refurbishment strategies for Post-War office buildings’, in 14th International Conference of IBPSA - Building Simulation 2015, BS 2015, Conference Proceedings, pp. 138–145.
Duran, Özlem, Taylor, S. and Lomas, K. (2015) ‘The Impact of Refurbishment on Thermal Comfort in Post-war Office Buildings’, Energy Procedia, 78, pp. 877–882. doi: 10.1016/j.egypro.2015.11.011.
Faramarzi, A. et al. (2020) ‘Marine Predators Algorithm: A nature-inspired metaheuristic’, Expert Systems with Applications, 152, p. 113377. doi: https://doi.org/10.1016/j.eswa.2020.113377.
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).
Fernández Bandera, C. et al. (2018) ‘Exergy As a Measure of Sustainable Retrofitting of Buildings’, Energies, 11(11), p. 3139. doi: 10.3390/en11113139.
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.
Gallardo, A. and Berardi, U. (2021) ‘Design and control of radiant ceiling panels incorporating phase change materials for cooling applications’, Applied Energy, 304, p. 117736. doi: https://doi.org/10.1016/j.apenergy.2021.117736.
Gao, B. et al. (2023) ‘Multi-objective optimization of energy-saving measures and operation parameters for a newly retrofitted building in future climate conditions: A case study of an office building in Chengdu’, Energy Reports, 9, pp. 2269–2285. doi: https://doi.org/10.1016/j.egyr.2023.01.049.
García Kerdan, I. et al. (2017a) ‘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.
García Kerdan, I. et al. (2017b) ‘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.
de Gastines, M. and Pattini, A. E. A. E. A. E. (2020) ‘Window energy efficiency in Argentina - Determining factors and energy savings strategies’, Journal of Cleaner Production, 247, p. 119104. doi: https://doi.org/10.1016/j.jclepro.2019.119104.
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.
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.
Gilan, S. S. S. S. and Dilkina, B. (2015) Sustainable Building Design: A Challenge at the Intersection of Machine Learning and Design Optimization, AAAI Workshop - Technical Report. Available at: http://www.aaai.org/ocs/index.php/WS/AAAIW15/paper/view/10203/10183.
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.
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.
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.
Gomes, R. et al. (2021) ‘Retrofit measures evaluation considering thermal comfort using building energy simulation: two Lisbon households’, Advances in Building Energy Research. Taylor & Francis, 15(3), pp. 291–314. doi: 10.1080/17512549.2018.1520646.
Goncalves, V., Ogunjimi, Y. and Heo, Y. (2021) ‘Scrutinizing modeling and analysis methods for evaluating overheating risks in passive houses’, Energy and Buildings, 234, p. 110701. doi: https://doi.org/10.1016/j.enbuild.2020.110701.
González, V. G. and Bandera, C. F. (2022) ‘A building energy models calibration methodology based on inverse modelling approach’, Building Simulation. Tsinghua University, 15(11), pp. 1883–1898. doi: 10.1007/S12273-022-0900-5/METRICS.
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.
Green, A. et al. (2020) ‘Above-roof air temperature effects on HVAC and cool roof performance: Experiments and development of a predictive model’, Energy and Buildings, 222, p. 110071. doi: https://doi.org/10.1016/j.enbuild.2020.110071.
Guo, R. et al. (2019a) ‘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.
Guo, R. et al. (2019b) ‘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.
Guo, R., Gao, Y., 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: https://doi.org/10.1016/j.renene.2019.10.032.
Guo, R., Heiselberg, P., et al. (2020) ‘Optimization of night ventilation performance in office buildings in a cold climate’, Energy and Buildings, 225, p. 110319. doi: https://doi.org/10.1016/j.enbuild.2020.110319.
Gutiérrez González, V., Ramos Ruiz, G. and Fernández Bandera, C. (2020) ‘Empirical and Comparative Validation for a Building Energy Model Calibration Methodology’, Sensors, 20(17), p. 5003. doi: 10.3390/s20175003.
Gutiérrez González, V., Ramos Ruiz, G. and Fernández Bandera, C. (2022) ‘Ground characterization of building energy models’, Energy and Buildings, 254, p. 111565. doi: https://doi.org/10.1016/j.enbuild.2021.111565.
Hamdy, M. and Sirén, K. (2016) ‘A multi-aid optimization scheme for large-scale investigation of cost-optimality and energy performance of buildings’, Journal of Building Performance Simulation, 9(4), pp. 411–430. doi: 10.1080/19401493.2015.1069398.
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. Taylor & Francis, 62(4), pp. 323–337. doi: 10.1080/00038628.2019.1615862.
He, M. et al. (2014) ‘Dynamic modelling of a large scale retrofit programme for the housing stock in the North East of England’, in Urban Sustainability and Resilience (USAR) Conference Series. London, UK: Urban Sustainability and Resilience (USAR) Conference Series. Available at: https://dspace.lboro.ac.uk/dspace-jspui/handle/2134/16519 (Accessed: 18 September 2015).
He, M., Lee, T., et al. (2015) ‘Coupling a stochastic occupancy model to energyplus to predict hourly thermal demand of a neighbourhood’, in 14th International Conference of IBPSA - Building Simulation 2015, BS 2015, Conference Proceedings, pp. 2101–2108. Available at: https://repository.lboro.ac.uk/articles/Coupling_a_stochastic_occupancy_model_to_EnergyPlus_to_predict_hourly_thermal_demand_of_a_neighbourhood/9437543.
He, M., Brownlee, A., Wright, J., et al. (2015) ‘Multi-dwelling refurbishment optimization: Problem decomposition, solution and trade-off analysis’, in 14th International Conference of IBPSA - Building Simulation 2015, BS 2015, Conference Proceedings, pp. 2066–2072. Available at: https://www.researchgate.net/publication/314155784_Multi-dwelling_refurbishment_optimization_problem_decomposition_solution_and_trade-o_analysis.
He, M., Brownlee, A., Lee, T., et al. (2015) ‘Multi-objective optimization for a large scale retrofit program for the housing stock in the North East of England’, in Energy Procedia, pp. 854–859. doi: 10.1016/j.egypro.2015.11.007.
Hendricken, L., Taylor, R. and Casey, P. (2013) ‘Pareto efficient retrofit package selection for multi-family buildings in the Philadelphia Metropolitan Region’, in Future Build 2013. Bath, UK.
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.
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.
Hoyt, T., Arens, E. and Zhang, H. (2015) ‘Extending air temperature setpoints: Simulated energy savings and design considerations for new and retrofit buildings’, Building and Environment. Elsevier Ltd, 88, pp. 89–96. doi: 10.1016/j.buildenv.2014.09.010.
Husi, G. (2014) ‘The latest research results of the Intelligent buildings group in the DEnzero project’, in 2014 IEEE/SICE International Symposium on System Integration. Tokyo, Japan: IEEE, pp. 240–244. doi: 10.1109/SII.2014.7028044.
Huws, H. and Jankovic, L. (2014) ‘A METHOD FOR ZERO CARBON DESIGN USING MULTI-OBJECTIVE OPTIMISATION’, in Proceedings of the 1st International Conference on Zero Carbon Buildings Today and in the Future. Birmingham, UK: Birmingham City University.
Ioannou, A. and Itard, L. C. M. C. M. (2015) ‘Energy Performance and comfort in residential buildings: Sensitivity for building parameters and occupancy’, Energy and Buildings. Elsevier Ltd, 92, pp. 216–233. doi: 10.1016/j.enbuild.2015.01.055.
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.
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.
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.
Kahsay, M. T., Bitsuamlak, G. T. and Tariku, F. (2021) ‘Thermal zoning and window optimization framework for high-rise buildings’, Applied Energy, 292, p. 116894. doi: https://doi.org/10.1016/j.apenergy.2021.116894.
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.
Khattak, S. H. et al. (2014) ‘Analysing the use of waste factory heat through exergy analysis’, in Eceee Industrial Summer Study Proceedings, pp. 179–189. Available at: https://www.eceee.org/library/conference_proceedings/eceee_Industrial_Summer_Study/2014/2-sustainable-production-design-and-supply-chain-initiatives/analysing-the-use-of-waste-factory-heat-through-exergy-analysis/.
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.
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.
Kim, C. et al. (2016) ‘Optimized operation method for an active chilled beam with VAV system’, Science and Technology for the Built Environment. Taylor & Francis, 22(4), pp. 372–378. doi: 10.1080/23744731.2016.1158044.
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.
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. (2019a) ‘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.
Lan, L., Wood, K. L. and Yuen, C. (2019b) ‘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.
Lavigne, K. et al. (2014) ‘Demand Response Strategies in a Small All-Electric Commercial Building in Quebec’, in eSim 2014.
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.
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.
Lee, P. et al. (2013) ‘Probabilistic risk assessment of the energy saving shortfall in energy performance contracting projects-A case study’, Energy and Buildings, 66, pp. 353–363. doi: 10.1016/j.enbuild.2013.07.018.
Lee, P. et al. (2016) ‘Analysis of an air-cooled chiller replacement project using a probabilistic approach for energy performance contracts’, Applied Energy. Elsevier Ltd, 171, pp. 415–428. doi: 10.1016/j.apenergy.2016.03.035.
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.
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.
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.
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.
Liu, J., Chen, X., et al. (2020) ‘Energy storage and management system design optimization for a photovoltaic integrated low-energy building’, Energy. Elsevier BV, 190, p. 116424. Available at: https://www.sciencedirect.com/science/article/pii/S036054421932119X (Accessed: 24 January 2020).
Liu, J., Wang, M., et al. (2020) ‘Techno-economic design optimization of hybrid renewable energy applications for high-rise residential buildings’, Energy Conversion and Management, 213, p. 112868. doi: https://doi.org/10.1016/j.enconman.2020.112868.
Liu, J., Cao, S., et al. (2021) ‘Energy planning of renewable applications in high-rise residential buildings integrating battery and hydrogen vehicle storage’, Applied Energy, 281, p. 116038. doi: https://doi.org/10.1016/j.apenergy.2020.116038.
Liu, J., Chen, X., et al. (2021) ‘Hybrid renewable energy applications in zero-energy buildings and communities integrating battery and hydrogen vehicle storage’, Applied Energy, 290, p. 116733. doi: https://doi.org/10.1016/j.apenergy.2021.116733.
Liu, J. et al. (2022) ‘Net-zero energy management and optimization of commercial building sectors with hybrid renewable energy systems integrated with energy storage of pumped hydro and hydrogen taxis’, Applied Energy, 321, p. 119312. doi: https://doi.org/10.1016/j.apenergy.2022.119312.
Liu, J. et al. (2023) ‘Study on optimum energy fuel mix for urban cities integrated with pumped hydro storage and green vehicles’, Applied Energy, 331, p. 120399. doi: https://doi.org/10.1016/j.apenergy.2022.120399.
Liu, J., Yang, H. and Zhou, Y. (2021) ‘Peer-to-peer trading optimizations on net-zero energy communities with energy storage of hydrogen and battery vehicles’, Applied Energy, 302, p. 117578. doi: https://doi.org/10.1016/j.apenergy.2021.117578.
Liu, S. et al. (2020) ‘Effectiveness of passive design strategies in responding to future climate change for residential buildings in hot and humid Hong Kong’, Energy and Buildings, 228, p. 110469. doi: https://doi.org/10.1016/j.enbuild.2020.110469.
Liu, Y. et al. (2023) ‘Optimization of top-floor rooms coupling cool roofs, natural ventilation and solar shading for residential buildings in hot-summer and warm-winter zones’, Journal of Building Engineering, 66, p. 105933. doi: https://doi.org/10.1016/j.jobe.2023.105933.
Lordan, F. et al. (2016) ‘Energy-Aware Programming Model for Distributed Infrastructures’, in 2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP). IEEE, pp. 413–417. doi: 10.1109/PDP.2016.39.
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.
Luo, N. et al. (2022) ‘Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling’, Applied Energy, 309, p. 118372. doi: https://doi.org/10.1016/j.apenergy.2021.118372.
Luo, Z. et al. (2022) ‘Study on dual-objective optimization method of life cycle energy consumption and economy of office building based on HypE genetic algorithm’, Energy and Buildings, 256, p. 111749. doi: https://doi.org/10.1016/j.enbuild.2021.111749.
Lutzenhiser, L. et al. (2012) ‘Lifestyles , Buildings and Technologies: What Matters Most?’, in ACEEE Summer Study on Energy Efficiency in Buildings. Pacific Grove, CA, pp. 256–270. Available at: http://www.aceee.org/files/proceedings/2012/data/papers/0193-000034.pdf.
Malkawi, A. and Waegel, A. (2013) ‘Rapid Modeling of Buildings with Calibrated Normative Models’, in BS 2013 - 13th Int. IBPSA Conference. Chambery, France.
Manandhar, R. et al. (2015) ‘A Study on Passive Cooling Strategies for Buildings in Hot Humid Region of Nepal’, KIEAE Journal. Korea Institute of Ecological Architecture and Environment, 15(1), pp. 53–60. doi: 10.12813/kieae.2015.15.1.053.
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.
María Calama-González, C., Suárez, R. and Luis León-Rodríguez, Á. (2022) ‘Mitigation of climate change in Mediterranean existing social dwellings through numerical optimization of building stock models’, Energy and Buildings, 266, p. 112109. doi: https://doi.org/10.1016/j.enbuild.2022.112109.
Martinez-Soto, A. et al. (2021) ‘Towards low-carbon housing in Chile: Optimisation and life cycle analysis of energy-efficient solutions’, Case Studies in Thermal Engineering, 28, p. 101579. doi: https://doi.org/10.1016/j.csite.2021.101579.
Martinez, N. A. (2014) ‘Solving the Black Box : Inverse Approach for Ideal Building Dynamic Behaviour Using Multi-Objective Optimization with Energyplus’, in Proceedings of 8th Windsor Conference: Counting the Cost of Comfort in a changing World, Cumberland Lodge, Windsor, UK, pp. 10–13.
Martínez, S. et al. (2020) ‘Model calibration and exergoeconomic optimization with NSGA-II applied to a residential cogeneration’, Applied Thermal Engineering. Elsevier Ltd, 169, p. 114916. doi: https://doi.org/10.1016/j.applthermaleng.2020.114916.
McCartan, S. and Kvilums, C. (2014a) ‘Development of interior design strategies as an integral part of a marine passive design methodology for passenger vessels operating within the Mediterranean’, in RINA, Royal Institution of Naval Architects - Marine Design, Papers, pp. 143–167. Available at: https://www.researchgate.net/publication/287319883_Development_of_interior_design_strategies_as_an_integral_part_of_a_marine_passive_design_methodology_for_passenger_vessels_operating_within_the_Mediterranean.
McCartan, S. and Kvilums, C. (2014b) ‘THE UTILIZATION OF PASSIVE DESIGN STRATEGIES WITHIN THE DESIGN PROCESS OF PASSENGER VESSELS OPERATING WITHIN THE MEDITERRANEAN TO SUPPORT EEDI COMPLIANCE’, in RINA, Royal Institution of Naval Architects - Influence of EEDI on Ship Design. Royal Institution of Naval Architects, pp. 147–161. Available at: http://curve.coventry.ac.uk/open/items/b34950c9-1ef6-44fa-8cec-e8f9e0729469/1/.
Moret, S., Noro, M. and Papamichael, K. (2013) ‘Daylight harvesting: A multivariate regression linear model for predicting the impact on lighting, cooling, and heating’, in BSA2013 - Building Simulation Applications Conference. Bozen, Italy, pp. 39–48. Available at: https://www.researchgate.net/publication/315381011_Daylight_harvesting_a_multivariate_regression_linear_model_for_predicting_the_impact_on_lighting_cooling_and_heating.
Naderi, E. E. E. E. et al. (2020) ‘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, 169, p. 106570. doi: https://doi.org/10.1016/j.buildenv.2019.106570.
Naji, S., Aye, L. and Noguchi, M. (2021) ‘Sensitivity analysis on energy performance, thermal and visual discomfort of a prefabricated house in six climate zones in Australia’, Applied Energy, 298, p. 117200. doi: https://doi.org/10.1016/j.apenergy.2021.117200.
Nateghi, S. et al. (2023) ‘Multi-objective optimization of a multi-story hotel’s energy demand and investing the money saved in energy supply with solar energy production’, Energy for Sustainable Development, 72, pp. 33–41. doi: https://doi.org/10.1016/j.esd.2022.11.010.
Neale, J. et al. (2022) ‘Accurate identification of influential building parameters through an integration of global sensitivity and feature selection techniques’, Applied Energy, 315, p. 118956. doi: https://doi.org/10.1016/j.apenergy.2022.118956.
Nutkiewicz, A. et al. (2022) ‘Cool roofs can mitigate cooling energy demand for informal settlement dwellers’, Renewable and Sustainable Energy Reviews, 159, p. 112183. doi: https://doi.org/10.1016/j.rser.2022.112183.
Ordóñez, F. et al. (2021) ‘Sensitivity analysis of the variables affecting indoor thermal conditions on unconditioned dwellings in equatorial high-altitude regions from an experimentally validated model’, Advances in Building Energy Research. Taylor & Francis, 15(4), pp. 442–465. doi: 10.1080/17512549.2019.1582437.
Pachano, J. E. and Bandera, C. F. (2021) ‘Multi-step building energy model calibration process based on measured data’, Energy and Buildings, 252, p. 111380. doi: https://doi.org/10.1016/j.enbuild.2021.111380.
Pachano, J. E., Peppas, A. and Bandera, C. F. (2022) ‘Seasonal adaptation of VRF HVAC model calibration process to a mediterranean climate’, Energy and Buildings, 261, p. 111941. doi: https://doi.org/10.1016/j.enbuild.2022.111941.
Pajek, L. et al. (2023) ‘A multi-aspect approach to energy retrofitting under global warming: A case of a multi-apartment building in Montenegro’, Journal of Building Engineering, 63, p. 105462. doi: https://doi.org/10.1016/j.jobe.2022.105462.
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, p. 117116. doi: https://doi.org/10.1016/j.apenergy.2021.117116.
Pajek, L., Potočnik, J. and Košir, M. (2022) ‘The effect of a warming climate on the relevance of passive design measures for heating and cooling of European single-family detached buildings’, Energy and Buildings, 261, p. 111947. doi: https://doi.org/10.1016/j.enbuild.2022.111947.
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.
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).
Pejić, P. Č., Petković, D. L. and Krasić, S. M. (2014) ‘The effect of architectural façade design on energy savings in the student dormitory’, Thermal Science, 18(3), pp. 979–988. doi: 10.2298/TSCI1403979P.
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.
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.
Porritt, S. M. et al. (2011) ‘Assessment of interventions to reduce dwelling overheating during heat waves considering annual energy use and cost’, in CIBSE Technical Symposium 2011. Leicester, UK.
Porritt, S. M. et al. (2012) ‘Ranking of interventions to reduce dwelling overheating during heat waves’, Energy and Buildings, 55(0), pp. 16–27. doi: http://dx.doi.org/10.1016/j.enbuild.2012.01.043.
Porritt, S. M. et al. (2013) ‘Heat wave adaptations for UK dwellings and development of a retrofit toolkit’, International Journal of Disaster Resilience in the Built Environment, 4(3), pp. 269–286. doi: 10.1108/IJDRBE-08-2012-0026.
Poudel, N. and Blouin, V. Y. (2014) ‘US Map Visualization of Optimal Properties of Phase Change Materials for Building Efficiency’, ARCC Conference Repository. Available at: http://www.arcc-journal.org/index.php/repository/article/view/217 (Accessed: 18 September 2015).
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, 254, p. 120041. doi: https://doi.org/10.1016/j.jclepro.2020.120041.
Qiu, Z. et al. (2021) ‘Identification of passive solar design determinants in office building envelopes in hot and humid climates using data mining techniques’, Building and Environment, 196, p. 107566. doi: https://doi.org/10.1016/j.buildenv.2020.107566.
Rahif, R. et al. (2022) ‘Impact of climate change on nearly zero-energy dwelling in temperate climate: Time-integrated discomfort, HVAC energy performance, and GHG emissions’, Building and Environment, 223, p. 109397. doi: https://doi.org/10.1016/j.buildenv.2022.109397.
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.
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.
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.
Randjelovic, D. et al. (2021) ‘Investigation of a passive design approach for a building facility: a case study’, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. Taylor & Francis, pp. 1–19. doi: 10.1080/15567036.2021.1938761.
Rawlings, J. et al. (2014) ‘A CLUSTERING APPROACH TO SUPPORT SME CARBON REDUCTION Technologies for Sustainable Built Environments Centre , University of Reading . UK School of Construction Management and Engineering , University of Reading , Reading . UK Henley Business School , Uni’, in BSO 2014.
Ren, J. et al. (2022) ‘Developing a collaborative control strategy of a combined radiant floor cooling and ventilation system: A PMV-based model’, Journal of Building Engineering, 54, p. 104648. doi: https://doi.org/10.1016/j.jobe.2022.104648.
Roberts, J. A. et al. (2022) ‘Impact of active façade control parameters and sensor network complexity on comfort and efficiency: A residential Italian case-study’, Energy and Buildings, 255, p. 111650. doi: https://doi.org/10.1016/j.enbuild.2021.111650.
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.
Rostami, M. and Heravi, G. (2022) ‘Assessing the Economic Challenges Toward the Implementation of Performance-Based Energy Code for Non-Residential Buildings in Iran’, Iranian Journal of Science and Technology - Transactions of Civil Engineering. Springer Science and Business Media Deutschland GmbH, 46(6), pp. 4737–4749. doi: 10.1007/S40996-022-00975-X/TABLES/10.
Ruggeri, A. G. et al. (2020) ‘Planning energy retrofit on historic building stocks: A score-driven decision support system’, Energy and Buildings, 224, p. 110066. doi: https://doi.org/10.1016/j.enbuild.2020.110066.
Sakiyama, N. R. M. et al. (2021) ‘Natural ventilation potential from weather analyses and building simulation’, Energy and Buildings, 231, p. 110596. doi: https://doi.org/10.1016/j.enbuild.2020.110596.
Salimi, S. and Hammad, A. (2020) ‘Optimizing energy consumption and occupants comfort in open-plan offices using local control based on occupancy dynamic data’, Building and Environment, 176, p. 106818. doi: 10.1016/j.buildenv.2020.106818.
Samuelson, H. W., Baniassadi, A. and Gonzalez, P. I. (2020) ‘Beyond energy savings: Investigating the co-benefits of heat resilient architecture’, Energy, 204, p. 117886. doi: https://doi.org/10.1016/j.energy.2020.117886.
Saryazdi, S. mohammad E. et al. (2022) ‘Data-driven performance analysis of a residential building applying artificial neural network (ANN) and multi-objective genetic algorithm (GA)’, Building and Environment, 225, p. 109633. doi: https://doi.org/10.1016/j.buildenv.2022.109633.
Saurbayeva, A., Memon, S. A. and Kim, J. (2023) ‘Sensitivity analysis and optimization of PCM integrated buildings in a tropical savanna climate’, Journal of Building Engineering, 64, p. 105603. doi: https://doi.org/10.1016/j.jobe.2022.105603.
Schwartz, Y., Raslan, R. and Mumovic, D. (2015) ‘Multi-objective genetic algorithms for the minimisation of the life cycle carbon footprint and life cycle cost of the refurbishment of a residential complex’s envelope: a case study’, in Simulation Series. San Diego, CA, USA: Society for Computer Simulation International, pp. 189–196. Available at: http://dl.acm.org/citation.cfm?id=2873021.2873047 (Accessed: 2 June 2016).
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.
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.
Shi, D. et al. (2022) ‘Climate adaptive optimization of green roofs and natural night ventilation for lifespan energy performance improvement in office buildings’, Building and Environment, 223, p. 109505. doi: https://doi.org/10.1016/j.buildenv.2022.109505.
Shin, M.-S., Rhee, K.-N. and Jung, G.-J. (2020) ‘Optimal heating start and stop control based on the inferred occupancy schedule in a household with radiant floor heating system’, Energy and Buildings, 209, p. 109737. doi: https://doi.org/10.1016/j.enbuild.2019.109737.
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.
Sterling, R. et al. (2014) ‘Improving whole building energy simulation with artificial neural networks and real performance data’, in Building Simulation and Optimisation Conference.
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.
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.
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.
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.
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.
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.
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.
Torres-Rivas, A. et al. (2021) ‘Systematic combination of insulation biomaterials to enhance energy and environmental efficiency in buildings’, Construction and Building Materials, 267, p. 120973. doi: https://doi.org/10.1016/j.conbuildmat.2020.120973.
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.
Vanhoutteghem, L. et al. (2015) ‘Impact of façade window design on energy, daylighting and thermal comfort in nearly zero-energy houses’, Energy and Buildings, 102, pp. 149–156. doi: 10.1016/j.enbuild.2015.05.018.
Vanhoutteghem, L. and Svendsen, S. (2014) ‘Modern insulation requirements change the rules of architectural design in low-energy homes’, Renewable Energy, 72, pp. 301–310. doi: 10.1016/j.renene.2014.07.005.
Wang, D. et al. (2022) ‘Evaluation of the relative differences in building energy simulation results’, Building Simulation. Tsinghua University, 15(11), pp. 1977–1987. doi: 10.1007/S12273-022-0903-2/METRICS.
Witt, H. et al. (2015) ‘Simulation of energy use in UK supermarkets using EnergyPlus’, in Proceedings of the 14th International Conference of the International Building Performance Simulation Association (BS2015). Hyderabad, India: © International Building Performance Simulation Association (IBPSA), pp. 1095–1102. Available at: https://dspace.lboro.ac.uk/dspace-jspui/handle/2134/21174 (Accessed: 2 June 2016).
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, p. 105747. doi: https://doi.org/10.1016/j.ecolind.2019.105747.
Xue, Q., Wang, Z. and Chen, Q. (2022) ‘Multi-objective optimization of building design for life cycle cost and CO2 emissions: A case study of a low-energy residential building in a severe cold climate’, Building Simulation. Tsinghua University, 15(1), pp. 83–98. doi: 10.1007/S12273-021-0796-5/METRICS.
Yadollahi, M. et al. (2022) ‘Life cycle cost analysis of near zero energy buildings benefited from earth-sheltering’, International Journal of Construction Management. Taylor & Francis, pp. 1–13. doi: 10.1080/15623599.2022.2085498.
Yoon, N. and Heo, Y. (2022) ‘Weather-based operation strategy for a dynamically compartmentalized double-skin façade system’, Building and Environment, 226, p. 109755. doi: https://doi.org/10.1016/j.buildenv.2022.109755.
Yoon, N., Min, D. and Heo, Y. (2022) ‘Dynamic compartmentalization of double-skin façade for an office building with single-sided ventilation’, Building and Environment, 208, p. 108624. doi: https://doi.org/10.1016/j.buildenv.2021.108624.
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.
Zeferina, V., Wood, R., 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.
Zeferina, V., Birch, C., 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.
Zeferina, V. et al. (2021) ‘Sensitivity analysis of cooling demand applied to a large office building’, Energy and Buildings, 235, p. 110703. doi: https://doi.org/10.1016/j.enbuild.2020.110703.
Zhang, B. et al. (2017) ‘Invariant probabilistic sensitivity analysis for building energy models’, Journal of Building Performance Simulation. Taylor & Francis, 10(4), pp. 392–405. doi: 10.1080/19401493.2016.1265590.
Zhao, J. and Du, Y. (2020) ‘Multi-objective optimization design for windows and shading configuration considering energy consumption and thermal comfort: A case study for office building in different climatic regions of China’, Solar Energy, 206, pp. 997–1017. doi: https://doi.org/10.1016/j.solener.2020.05.090.
Zhao, Z., Li, H. and Wang, S. (2022) ‘Identification of the key design parameters of Zero/low energy buildings and the impacts of climate and building morphology’, Applied Energy, 328, p. 120185. doi: https://doi.org/10.1016/j.apenergy.2022.120185.
Zhong, X. et al. (2020) ‘Comprehensive evaluation of energy and indoor-PM2.5-exposure performance of residential window and roller blind control strategies’, Energy and Buildings, 223, p. 110206. doi: https://doi.org/10.1016/j.enbuild.2020.110206.
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, 12(7), pp. 1891–1920. Available at: https://link.springer.com/article/10.1007/s12053-019-09812-z (Accessed: 24 January 2020).
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.