Validation of a Bayesian-based method for defining residential archetypes in urban building energy models

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• 作者：Julia Sokol^a ; ^{sokol@mit.edu} ; Carlos Cerezo Davila^b ; Christoph F. Reinhart^b
• 关键词：Urban building energy modeling ; Building archetypes ; Bayesian calibration ; Residential building stock
• 刊名：Energy and Buildings
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：134
• 期：Complete
• 页码：11-24
• 全文大小：2665 K
• 卷排序：134

文摘

Existing approaches to Urban Building Energy Modeling and calibration are described. A new Bayesian approach to defining and calibrating building archetypes is proposed. A model of 2662 buildings is created and calibrated with the proposed method. An uncalibrated model is compared to results of annual and monthly calibration.