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A review on the basics of building energy estimation

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TLDR
In this paper, the authors provide an up-to-date review on the basics of building energy estimation and propose a classification for energy estimation models based on the different classifications found in the literature review.
Abstract
Energy security, environmental concerns, thermal comfort, and economic matters are driving factors for the development of research on reducing energy consumption and the associated greenhouse gas emissions in every sector of the economy. Building energy consumption estimation has become a key approach to achieve the goals on energy consumption and emissions reduction. Energy performance of building is complicated since it depends on multiple variables associated to the building characteristics, equipment and systems, weather, occupants, and sociological influences. This paper aims to provide an up-to-date review on the basics of building energy estimation. Regarding models, a classification for energy estimation models is proposed based on the different classifications found in the literature review. The paper focuses on models developed with whole building energy simulation software and their validation. This focus is justified because of the importance that whole building energy tools have gained on areas such as green building design, and analysis of energy conservation strategies and retrofits. Since a suitable weather file is a major component for reliably simulations, the section about weather data provides pertinent information.

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Citations
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Journal ArticleDOI

A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries)

TL;DR: In this article, the status and current trends of energy consumption, CO2 emissions and energy policies in the residential sector, both globally and in those ten countries, were reviewed, and it was found that global residential energy consumption grew by 14% from 2000 to 2011, where population, urbanization and economic growth have been the main driving factors.
Journal ArticleDOI

A review of data-driven building energy consumption prediction studies

TL;DR: A review of the studies that developed data-driven building energy consumption prediction models, with a particular focus on reviewing the scopes of prediction, the data properties and the data preprocessing methods used, the machine learning algorithms utilized for prediction, and the performance measures used for evaluation is provided in this paper.
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A review on time series forecasting techniques for building energy consumption

TL;DR: The various combinations of the hybrid model are found to be the most effective in time series energy forecasting for building and the nine most popular forecasting techniques based on the machine learning platform are analyzed.
Journal ArticleDOI

Regression analysis for prediction of residential energy consumption

TL;DR: In this article, simple and multiple linear regression analysis along with a quadratic regression analysis were performed on hourly and daily data from a research house, and the time interval of the observed data showed to be a relevant factor defining the quality of the model.
Journal ArticleDOI

Modeling and forecasting building energy consumption: A review of data-driven techniques

TL;DR: A review of studies developing data-driven models for building scale applications with a focus on the input data characteristics and data pre-processing methods, the building typologies considered, the targeted energy end-uses and forecasting horizons, and accuracy assessment.
References
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Journal ArticleDOI

Bayesian Calibration of computer models

TL;DR: A Bayesian calibration technique which improves on this traditional approach in two respects and attempts to correct for any inadequacy of the model which is revealed by a discrepancy between the observed data and the model predictions from even the best‐fitting parameter values is presented.
Journal ArticleDOI

Modeling of end-use energy consumption in the residential sector: A review of modeling techniques

TL;DR: In this paper, the authors provide an up-to-date review of the various modeling techniques used for modeling residential sector energy consumption, focusing on the strengths, shortcomings and purposes.
Journal ArticleDOI

A review on the prediction of building energy consumption

TL;DR: In this paper, the authors present a review of recent developed models for predicting building energy consumption, which include elaborate and simplified engineering methods, statistical methods and artificial intelligence methods, and further prospects are proposed for additional research reference.
Journal ArticleDOI

A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries)

TL;DR: In this article, the status and current trends of energy consumption, CO2 emissions and energy policies in the residential sector, both globally and in those ten countries, were reviewed, and it was found that global residential energy consumption grew by 14% from 2000 to 2011, where population, urbanization and economic growth have been the main driving factors.
Journal ArticleDOI

Energy models for demand forecasting—A review

TL;DR: In this paper an attempt is made to review the various energy demand forecasting models to accurately predict the future energy needs.
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