Modelado de caja gris en eficiencia energética de edificios
una revisíon de literatura
DOI:
https://doi.org/10.46421/encacelacac.v18i1.7227Palabras clave:
Revision, Simulación del rendimiento energético, Caja grisResumen
El artículo aborda la aplicación de la modelización de caja gris en la simulación del rendimiento energético de los edificios, destacando su capacidad para equilibrar precisión y simplicidad al integrar conocimientos físicos con datos empíricos. La revisión sistemática de la literatura, siguiendo la metodología PRISMA 2020, identificó 40 estudios relevantes que demuestran la eficacia de este enfoque en la optimización del consumo energético, especialmente en sistemas HVAC. La modelización de caja gris permite la calibración de modelos con datos reales, proporcionando predicciones más precisas y reduciendo el tiempo de procesamiento en comparación con los modelos de caja blanca y negra.
Citas
Afram, A., et al. (2018). "Development and performance comparison of low-order black-box models for a residential HVAC system." JOURNAL OF BUILDING ENGINEERING 15: 137-155.
Ahmad, T., et al. (2018). "A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: A review." ENERGY AND BUILDINGS 165: 301-320.
Altieri, D., et al. (2023). "Numerical analysis of low-cost optimization measures for improving energy efficiency in residential buildings." Energy 273: 127257.
Andriamamonjy, A., et al. (2019). "Automated grey box model implementation using BIM and Modelica." ENERGY AND BUILDINGS 188: 209-225.
Arroyo, J., et al. (2020). "Identification of multi-zone grey-box building models for use in model predictive control." JOURNAL OF BUILDING PERFORMANCE SIMULATION 13(4): 472-486.
Aruta, G., et al. (2023). "Optimizing heating operation via GA- and ANN-based model predictive control: Concept for a real nearly-zero energy building." Energy and Buildings 292: 113139.
Attoue, N., et al. (2019). "Determination of the Optimal Order of Grey-Box Models for Short-Time Prediction of Buildings' Thermal Behavior." BUILDINGS 9(9).
Bagle, M., et al. (2022). Identifying grey-box models from archetypes of apartment block buildings. PROCEEDINGS OF BUILDING SIMULATION 2021: 17TH CONFERENCE OF IBPSA. 17: 1091-1098.
Beagon, P., et al. (2020). "Closing the gap between simulation and measured energy use in home archetypes." ENERGY AND BUILDINGS 224.
Berger, J., et al. (2022). "Assessing the wall energy efficiency design under climate change using POD reduced order model." Energy and Buildings 268: 112187.
Brastein, O. M., et al. (2020). "Analysing uncertainty in parameter estimation and prediction for grey-box building thermal behaviour models." ENERGY AND BUILDINGS 224.
Brastein, O. M., et al. (2019). "Parameter estimation for externally simulated thermal network models." ENERGY AND BUILDINGS 191: 200-210.
Brastein, O. M., et al. (2018). "Parameter estimation for grey-box models of building thermal behaviour." ENERGY AND BUILDINGS 169: 58-68.
Chalabi, Z., et al. (2015). "Risk analysis of housing energy efficiency interventions under model uncertainty." Energy and Buildings 109: 174-182.
Cibin, N., et al. (2023). "Machine learning-based algorithms to estimate thermal dynamics of residential buildings with energy flexibility." JOURNAL OF BUILDING ENGINEERING 65.
De Coninck, R., et al. (2016). "Toolbox for development and validation of grey-box building models for forecasting and control." JOURNAL OF BUILDING PERFORMANCE SIMULATION 9(3): 288-303.
Eze, F., et al. (2024). "Experimental and simulated evaluation of inverse model for shallow underground thermal storage." Case Studies in Thermal Engineering 59: 104535.
Fan, C., et al. (2018). "Unsupervised data analytics in mining big building operational data for energy efficiency enhancement: A review." Energy and Buildings 159: 296-308.
Frahm, M., et al. (2022). Multi-Zone Grey-Box Thermal Building Identification with Real Occupants. PROCEEDINGS OF THE 2022 THE 9TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION, BUILDSYS 2022: 484-487.
Gourlis, G. and I. Kovacic (2016). "A study on building performance analysis for energy retrofit of existing industrial facilities." APPLIED ENERGY 184: 1389-1399.
Gray, F. M. and M. Schmidt (2018). "A hybrid approach to thermal building modelling using a combination of Gaussian processes and grey-box models." ENERGY AND BUILDINGS 165: 56-63.
Green, C. and S. Garimella (2021). "Residential microgrid optimization using grey-box and black-box modeling methods." ENERGY AND BUILDINGS 235.
Guidotti, R., et al. (2019). "A Survey of Methods for Explaining Black Box Models." ACM COMPUTING SURVEYS 51(5).
Gunay, B., et al. (2023). "Estimating energy savings from HVAC controls fault correction through inverse greybox model-based virtual metering." ENERGY AND BUILDINGS 282.
Gunay, B., et al. (2017). "Characterization of a building's operation using automation data: A review and case study." BUILDING AND ENVIRONMENT 118: 196-210.
Hollick, F. P., et al. (2020). "Thermal performance of occupied homes: A dynamic grey-box method accounting for solar gains." ENERGY AND BUILDINGS 208.
Hossain, M. M., et al. (2021). "Identifying grey-box thermal models with Bayesian neural networks." ENERGY AND BUILDINGS 238.
K, A., et al. (2018). Comparative Analysis of White-, Gray- and Black-Box Models for Thermal Simulation of Indoor Environment: Teaching Building Case Study. 2018 Building Performance Analysis Conference and SimBuild co-organized by ASHRAE and IBPSA-USA, ASHRAE/IBPSA-USA. 8: 173-180.
Lecocq, E., et al. (2025). "Development of physically coherent grey-box models for residential buildings using a simplified adjustment method." ENERGY AND BUILDINGS 328.
Leprince, J., et al. (2022). "Fifty shades of grey: Automated stochastic model identification of building heat dynamics." ENERGY AND BUILDINGS 266.
Li, Y., et al. (2021). "Grey-box modeling and application for building energy simulations-A critical review." RENEWABLE & SUSTAINABLE ENERGY REVIEWS 146.
Mazzarella, L. and M. Pasini (2009). "Building energy simulation and object-oriented modelling: Review and reflections upon achieved results and further developments." IBPSA 2009 - International Building Performance Simulation Association 2009.
Morkunaite, L., et al. (2023). Digital Twin for Grey Box modeling of Multistory residential building thermal dynamics. 2023 IEEE 9TH WORLD FORUM ON INTERNET OF THINGS, WF-IOT.
Roman, N. D., et al. (2020). "Application and characterization of metamodels based on artificial neural networks for building performance simulation: A systematic review." ENERGY AND BUILDINGS 217.
Shamsi, M. H., et al. (2020). Uncertainty Quantification In Predictive Modelling Of Heat Demand Using Reduced-order Grey Box Models. PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA: 4507-4514.
Shi, Z. X., et al. (2020). On Formulation and Training of Grey-box Thermal Model for Low-rise Residential Buildings. PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA: 838-844.
Struck, C. and J. Hensen (2007). On supporting design decisions in conceptual design addressing specification uncertainties using performance simulation. BUILDING SIMULATION 2007, VOLS 1-3, PROCEEDINGS.
Talib, A., et al. (2023). "Grey-box and ANN-based building models for multistep-ahead prediction of indoor temperature to implement model predictive control." ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 126.
Tohidi, S. S., et al. (2022). From white-box to grey-box modelling of the heat dynamics of buildings. BUILDSIM NORDIC 2022. 362.
Vivian, J., et al. (2024). "A comparison between grey-box models and neural networks for indoor air temperature prediction in buildings." JOURNAL OF BUILDING ENGINEERING 84.
Walnum, H. T., et al. (2020). Influence of inputs knowledge on Grey-box models for Demand Response in Buildings. PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA: 4729-4736.
Wang, Z. Q. and Y. X. Chen (2019). "Data-driven modeling of building thermal dynamics: Methodology and state of the art." ENERGY AND BUILDINGS 203.
Yu, X. J., et al. (2021). "Data pre-processing and optimization techniques for stochastic and deterministic low-order grey-box models of residential buildings." ENERGY AND BUILDINGS 236.
Yu, X. J., et al. (2020). Investigation of the Model Structure for Low-Order Grey-Box Modelling of Residential Buildings. PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA: 5076-5083.
Yu, X. J., et al. (2024). "Comparison of time-invariant and adaptive linear grey-box models for model predictive control of residential buildings." BUILDING AND ENVIRONMENT 254.
Yu, X. J., et al. (2022). "Influence of data pre-processing and sensor dynamics on grey-box models for space-heating: Analysis using field measurements." BUILDING AND ENVIRONMENT 212.
Yu, X. J., et al. (2017). An evolving experience learned for modelling thermal dynamics of buildings from live experiments: the Flexhouse story. POWER AND ENERGY SYSTEMS ENGINEERING, (CPESE 2017). 141: 233-239.
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2025 ENCONTRO NACIONAL DE CONFORTO NO AMBIENTE CONSTRUÍDO
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
