Estimating thermal parameters of a commercial building: A meta-heuristic approach

Wani, Mubashir; Hafiz, Faizal; Swain, Akshya; Ukil, Abhisek

doi:10.1016/j.enbuild.2020.110537

Cited by 11 publications

(4 citation statements)

References 25 publications

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“…Numerous investigations today focus on knowing the energy conditions of buildings to detect energy efficiency [7][8][9][10][11][12]. Estimating energy efficiency has been the subject of research since the late 1980s, as there was already awareness that the energy performance of the building is decisive for this [13,14]. In the 1990s, the thermal response to heat input was identified; as a consequence, in the 2000s, work began with energy models to estimate thermal parameters through simulations [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…In the 2010s, computer programs were developed to perform these energy simulations to quantify the energy savings of buildings and verify the results obtained in simplified models [18][19][20]. In recent years, it has been confirmed that the energy performance of buildings is conditioned by their physical characterization, which is why the aim is to estimate different climatic situations, a fact that especially benefits residential typology [13,21].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the Thermal Properties of Buildings in Eastern Almería (Spain) during the Summer in a Mediterranean Climate

Sáez-Pérez,

García Ruiz,

Tajani

2024

Sustainability

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Within a context in which temperatures are increasing due to global warming, it is important to assess the capacity of buildings, old and modern, to respond to this new situation. Recent studies have highlighted the importance of understanding more about the thermal properties of traditional constructions. This study quantifies the impact of the high summer temperatures typical of the Mediterranean climate on traditional farmhouses in Eastern Almería (Spain). The study group of farmhouses was divided into three models representative of the different types of Eastern Almería vernacular architecture. Energy consumption in the three models was simulated using EnergyPlus. The three models were assessed in free-floating conditions. The window-to-wall ratio and U-factor values were studied in order to evaluate potential benefits in terms of energy efficiency. Outdoor and indoor temperatures were compared. Finally, an adaptive thermal comfort analysis was performed according to ASHRAE 55. Results highlight the ability of Eastern Almería farmhouses to mitigate extreme temperatures.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of the Thermal Properties of Buildings in Eastern Almería (Spain) during the Summer in a Mediterranean Climate

Sáez-Pérez,

García Ruiz,

Tajani

2024

Sustainability

View full text Add to dashboard Cite

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“…Its application confirms that the energy performance of a building is strongly influenced by its envelope and physical characteristics, undoubtedly linked to the climatic conditions of the surroundings. All of this necessitates the development of estimation methodologies applied to diverse climatic situations [26], considering the impact of construction typologies and the material composition of building units [27].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Thermal Behavior in Different Seasons in Building Heritage: Case Study of the Royal Hospital of Granada

Sáez-Pérez,

García Ruiz,

Durán-Suárez

et al. 2023

Buildings

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The present investigation carries out a thermal evaluation of two rooms located in the Royal Hospital of Granada (Rector’s Office). This is a heritage building where have been done studies that allow the as-sessment of possible improvements in future interventions that guarantee improvement in en-ergy and regulatory compliance are decisive. This article presents for the first time, through energy simulation, the behavior of two rooms in two temporal periods, thermally extreme (summer and winter) and with opposite orientations. This has allowed the potential benefits to be considered in real climate conditions. The results demonstrate and quantify that considering the location, orientation, arrangement of openings, and inclusion of transition zones between the exterior and the interior, an improvement in thermal comfort is obtained. The southwesterly orientation is favorable in the winter period and the northeasterly orientation in the summer period. It is also confirmed that the arrangement of thick masonry walls responds adequately in climates with high thermal amplitudes, favoring the mitigation of extreme conditions. It is concluded by stating that the orientation and the construction components are the main responsible factors for the thermal capacity in this type of building. In this context, the use of non-destructive study methods offers valuable scientific support through the results obtained.

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“…Likewise, Le et al [38] conducted a comparison and proved the higher efficacy of genetic algorithm (GA) versus among an artificial bee colony (ABC), imperialist competitive algorithm (ICA), and particle swarm optimization (PSO) for the HL prediction. Further applications of metaheuristicoptimized techniques can be sufficiently found in the literature [39][40][41].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Machine Learning Approach for Forecasting Thermal Energy Demand of Buildings

et al. 2022

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Recent developments in indirect predictive methods have yielded promising solutions for energy consumption modeling. The present study proposes and evaluates a novel integrated methodology for estimating the annual thermal energy demand (DAN), which is considered as an indicator of the heating and cooling loads of buildings. A multilayer perceptron (MLP) neural network is optimally trained by symbiotic organism search (SOS), which is among the strongest metaheuristic algorithms. Three benchmark algorithms, namely, political optimizer (PO), harmony search algorithm (HSA), and backtracking search algorithm (BSA) are likewise applied and compared with the SOS. The results indicate that (i) utilizing the properties of the building within an artificial intelligence framework gives a suitable prediction for the DAN indicator, (ii) with nearly 1% error and 99% correlation, the suggested MLP-SOS is capable of accurately learning and reproducing the nonlinear DAN pattern, and (iii) this model outperforms other models such as MLP-PO, MLP-HSA and MLP-BSA. The discovered solution is finally expressed in an explicit mathematical format for practical uses in the future.

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Estimating thermal parameters of a commercial building: A meta-heuristic approach

Cited by 11 publications

References 25 publications

Assessment of the Thermal Properties of Buildings in Eastern Almería (Spain) during the Summer in a Mediterranean Climate

Assessment of the Thermal Properties of Buildings in Eastern Almería (Spain) during the Summer in a Mediterranean Climate

Comparative Analysis of Thermal Behavior in Different Seasons in Building Heritage: Case Study of the Royal Hospital of Granada

An Optimized Machine Learning Approach for Forecasting Thermal Energy Demand of Buildings

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