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Comparison of energy-efficiency benchmarking methodologies for residential buildings
Abstract Benchmarking with defined metrics is an excellent tool to track progress and obtain the desired goals. Benchmarking end-use energy in the residential sector has been a topic of great interest among researchers in recent times. This research analyses the buildings’ energy performance based on a devised benchmarking procedure for residential buildings in the Indian city of Jaipur. Creation of benchmarking system involves collection, analysis and verification of the results obtained from a similar set of data into consideration. This study explores the relationship between the Energy Performance Index (EPI) and with other influencing factors like; Area, end-use appliances (Fridge, AC, Cooler, etc.) to ensure the contribution of each variable towards the buildings’ end-use energy consumption. In this study, information has been collected and analysed from over 2700 houses of Jaipur City. The independent and dependent variables have been identified, and a five-star benchmarking framework has been developed. There are very few studies available investigating the effectiveness of various benchmarking techniques, the domain still lacks a comparative performance study of black-box and gray-box benchmarking techniques. This study has selected two black box approaches and one gray box approach to design a benchmarking model and has compared the energy performance of sample buildings. According to the Pearson and Spearman correlation coefficients, Multiple Linear Regression (MLR) and Bayesian ranking scores are the most consistent for energy benchmarking of the residential building sector. This study proposes a novel implementation of the composite indicator (C.I.) as a platform for designing energy benchmarking tables. Finally, the study concludes with recommendations for future work to employ numerous or hybrid combinations of benchmarking methodologies that are expected to provide a more accurate depiction of the energy performance of buildings.
Comparison of energy-efficiency benchmarking methodologies for residential buildings
Abstract Benchmarking with defined metrics is an excellent tool to track progress and obtain the desired goals. Benchmarking end-use energy in the residential sector has been a topic of great interest among researchers in recent times. This research analyses the buildings’ energy performance based on a devised benchmarking procedure for residential buildings in the Indian city of Jaipur. Creation of benchmarking system involves collection, analysis and verification of the results obtained from a similar set of data into consideration. This study explores the relationship between the Energy Performance Index (EPI) and with other influencing factors like; Area, end-use appliances (Fridge, AC, Cooler, etc.) to ensure the contribution of each variable towards the buildings’ end-use energy consumption. In this study, information has been collected and analysed from over 2700 houses of Jaipur City. The independent and dependent variables have been identified, and a five-star benchmarking framework has been developed. There are very few studies available investigating the effectiveness of various benchmarking techniques, the domain still lacks a comparative performance study of black-box and gray-box benchmarking techniques. This study has selected two black box approaches and one gray box approach to design a benchmarking model and has compared the energy performance of sample buildings. According to the Pearson and Spearman correlation coefficients, Multiple Linear Regression (MLR) and Bayesian ranking scores are the most consistent for energy benchmarking of the residential building sector. This study proposes a novel implementation of the composite indicator (C.I.) as a platform for designing energy benchmarking tables. Finally, the study concludes with recommendations for future work to employ numerous or hybrid combinations of benchmarking methodologies that are expected to provide a more accurate depiction of the energy performance of buildings.
Comparison of energy-efficiency benchmarking methodologies for residential buildings
Gupta, Gyanesh (Autor:in) / Mathur, Sanjay (Autor:in) / Mathur, Jyotirmay (Autor:in) / Nayak, Bibhu Kalyan (Autor:in)
Energy and Buildings ; 285
17.02.2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
EPI , Energy Performance Index , SFA , Stochastic Frontier Analysis , MLR , Multiple Linear Regression , DT , Decision Tree , C.I , Composite Indicator , ANN , Artificial Neural Network , NBC , National Building Council , PCA , Principal Component Analysis , BHK , Bedroom, Hall, and Kitchen , EWS , Economic Weaker Section , EUI , Energy Use Intensity , LIG , Lower Income Group , CBECS , Commercial Buildings Energy Consumption Survey , MIG , Middle Income Group , HVAC , Heating and Ventilation and Air Conditioning , HIG , High Income Group , SVM , Support Vector Machine , BR , Bayesian Regression , DEA , Data Envelopment Analysis , Energy-efficiency benchmarking , Composite indicator , Energy benchmarking methodologies , Comparative performance
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