EnergyPlus models for the benchmarking of residential buildings in Brunei Darussalam-Reference-Cited by-同舟云学术

EnergyPlus models for the benchmarking of residential buildings in Brunei Darussalam

Published:2018-06 Issue: Volume:169 Page:507-516
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Shabunko V.,Lim C.M.,Mathew S.

Funder

Brunei Research Council

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Building and Construction,Civil and Structural Engineering

Reference50 articles.

1. Key World Energy Statistics;IEA,2009

2. Peer review on energy efficiency in Brunei Darussalam, Final report 2013;APEC,2014

3. Energy White Paper, Energy Department, Brunei Darussalam. Available from: http://www.usasean.org/sites/default/files/uploads/Energy%20White%20Paper%202014.pdf (accessed May 2014).

4. The potential of demand-side management in energy-intensive industries for electricity markets in Germany;Paulus;Appl. Energy,2011

5. Department of electrical services. Available from: http://www.des.gov.bn/bdes/images/PDF_FILES/new%20tariff%202012%20chart.pdf (accessed October 2013).

Cited by 68 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. How to better match predicted loads of district heating system: A novel control approach focused on coupling source and network by data-driven methods;Applied Thermal Engineering;2024-07

2. Assessing Residential Building Energy Efficiency Using Evolutionary Dendritic Neural Regression;Electronics;2024-05-07

3. The impacts of residential buildings’ energy compliance standards on Iran’s GHG emissions toward achieving the Paris Agreement;Journal of Engineering Research;2024-03

4. Reconstituted data-driven air conditioning energy consumption prediction system employing occupant-orientated probability model as input and swarm intelligence optimization algorithms;Energy;2024-02

5. Forecasting building plug load electricity consumption employing occupant-building interaction input features and bidirectional LSTM with improved swarm intelligent algorithms;Energy;2024-02