Modeling, simulation and control tools for nZEB: A state-of-the-art review

Santos-Herrero, Jose Maria; López-Guede, José Manuel; Flores-Abascal, Iván

doi:10.1016/j.rser.2021.110851

Cited by 37 publications

(16 citation statements)

References 51 publications

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“…Accordingly, with the current Machine Learning models, it is possible to carry out predictive analytics on any type of data, especially in its application to Sustainable Energy Systems, as extensively explained by Donti et al 34 using algorithms that imitate human cognitive functions through ANN because they stand out in the analysis and optimization processes. Therefore, there is a great potential in using these tools to optimize the methodology applied in the modelling and simulation of the thermal behaviour, as well as the energy consumption of a building, as indicated by Santos-Herrero et al 35 in its overview of MPC in building climatization.…”

Section: Methodsmentioning

confidence: 99%

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Energy and thermal modelling of an office building to develop an artificial neural networks model

Santos-Herrero

López-Guede

Flores-Abascal

et al. 2022

Sci Rep

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Nowadays everyone should be aware of the importance of reducing CO2 emissions which produce the greenhouse effect. In the field of construction, several options are proposed to reach nearly-Zero Energy Building (nZEB) standards. Obviously, before undertaking a modification in any part of a building focused on improving the energy performance, it is generally better to carry out simulations to evaluate its effectiveness. Using Artificial Neural Networks (ANNs) allows a digital twin of the building to be obtained for specific characteristics without using very expensive software. This can simulate the effect of a single or combined intervention on a particular floor or an event on the remaining floors. In this paper, an example has been developed based on ANN. The results show a reasonable correlation between the real data of the Operative Temperature with the Energy Consumption and their estimates obtained through an ANN model, trained using an hourly basis, on each of the floors of an office building. This model confirms it is possible to obtain simulations in existing public buildings with an acceptable degree of precision and without laborious modelling, which would make it easier to achieve the nZEB target, especially in existing public office buildings.

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Section: Methodsmentioning

confidence: 99%

“…In our case study, with 8,760 tuples for each year, the most decisive data of a building's energy systems have firstly been analysed to control the factors that could cause a significant influence, as indicated in the paper developed by Santos et al 35 ; while data that could cause errors have also been refined.…”

Section: Case Studymentioning

confidence: 99%

Energy and thermal modelling of an office building to develop an artificial neural networks model

Santos-Herrero

López-Guede

Flores-Abascal

et al. 2022

Sci Rep

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“…As such, a single-family house was examined with regards to its thermal performance in warm and cold seasons. A reference building model was developed in Indoor Climate and Energy building performance simulation software (IDA-ICE), which is a third-party authorized and validated indoor climate and building energy modelling tool [31].…”

Section: Simulated Building Profile and Prerequisitesmentioning

confidence: 99%

“…In order to improve building energy efficiency a multidisciplinary approach is required, that addresses various combined factors such as building's architectural features, building materials, insulation quality of the building envelope, HVAC operation, as well as occupants' behaviour [31].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Heating and Cooling Loads for a Well-Insulated Single-Family House under Variable Climate Pattern

Prozuments

Staveckis

Zemītis

et al. 2021

Environmental and Climate Technologies

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Single family houses consume substantially more thermal energy per floor area compared to multi-apartment buildings to satisfy space heating or cooling demand. Over the past decades there has been an undisputed evidence of a temperature rise across the world that has led to a growing concern of more extreme weather patterns and regular seasonal heat waves globally. As such, building occupants are at a continuously growing risk to overheating exposure inside the premises. Within the framework of this study a single-family house was examined with respect to its thermal performance in warm and cold seasons. A simulation model was developed in IDA-ICE software to evaluate annual thermal energy demand for a reference scenario, 3 shading scenarios and for an optimized scenario. At an optimized scenario that incorporates mechanical ventilation with a heat recovery unit and enhanced thermal performance of the external building elements, the annual thermal energy demand in the proposed single-family house was reduced by 39.5 % compared to the reference scenario, which is a significant step towards meeting nearly zero energy building criteria.

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“…Building energy simulation (BES) tools are often chosen for building design and optimization and analysis of existing buildings' performance, including their retrofit. These tools allow for analyzing different scenarios and solutions, including renewable energy technologies [3][4][5], HVAC systems improvements [6], and passive solutions [7]. A detailed review of BES tools is presented in [8].…”

Section: Introductionmentioning

confidence: 99%

Development and Analysis of a Dynamic Energy Model of an Office Using a Building Management System (BMS) and Actual Measurement Data

et al. 2021

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Calibration of the energy model of a building is one of the essential tasks required to determine the efficiency of building management systems, and both their own and other systems’ improvement potential. In order to make the building energy model as accurate as possible, it is necessary to collect comprehensive data on its operation and sometimes to assess the missing information. This paper represents the process of developing an energy model for an administrative building and its calibration procedure, using detailed long-term measurement and building management system (BMS) data. Indoor air temperature, CO₂ concentration, and relative humidity were experimentally measured and evaluated separately. Such dual application of data reduces the inaccuracy of the assumptions made and assesses the model’s accuracy. The DesignBuilder software developed the building model. During the development of the model, it was observed that the actual energy consumption needs to be assessed, as the assumptions made during the design about the operation and management of HVAC systems often do not coincide with the actual situation. After integrating BMS information on HVAC management into the building model, the resulting discrepancy between the model results and the actual heat consumption was 6.5%. Such a model can be further used to optimize management decisions and assess energy savings potential.

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Modeling, simulation and control tools for nZEB: A state-of-the-art review

Cited by 37 publications

References 51 publications

Energy and thermal modelling of an office building to develop an artificial neural networks model

Energy and thermal modelling of an office building to develop an artificial neural networks model

Evaluation of Heating and Cooling Loads for a Well-Insulated Single-Family House under Variable Climate Pattern

Development and Analysis of a Dynamic Energy Model of an Office Using a Building Management System (BMS) and Actual Measurement Data

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