Electrical load forecasting models: A critical systematic review

C Kuster, Y Rezgui, M Mourshed - Sustainable cities and society, 2017 - Elsevier
Electricity forecasting is an essential component of smart grid, which has attracted
increasing academic interest. Forecasting enables informed and efficient responses for …

A review of data-driven building performance analysis and design on big on-site building performance data

Z Tian, X Zhang, S Wei, S Du, X Shi - Journal of Building Engineering, 2021 - Elsevier
Building performance design (BPD) is a crucial pathway to achieve high-performance
buildings. Previous simulation-based BPD is being questioned due to the performance gaps …

Machine learning approaches for estimating commercial building energy consumption

C Robinson, B Dilkina, J Hubbs, W Zhang… - Applied energy, 2017 - Elsevier
Building energy consumption makes up 40% of the total energy consumption in the United
States. Given that energy consumption in buildings is influenced by aspects of urban form …

Supervised based machine learning models for short, medium and long-term energy prediction in distinct building environment

T Ahmad, H Chen, R Huang, G Yabin, J Wang, J Shair… - Energy, 2018 - Elsevier
The substantial measure of energy usage connected to the building atmosphere supports
and sustains power usage modeling diligence. Amongst the numerous strategies to …

Residential water and energy consumption prediction at hourly resolution based on a hybrid machine learning approach

C Wang, Z Li, X Ni, W Shi, J Zhang, J Bian, Y Liu - Water research, 2023 - Elsevier
Predicting water and energy consumption at high resolution over a short-term horizon is
critical for water and energy resource management. Water and energy are shown to be …

Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia

H Fan, IF MacGill, AB Sproul - Energy and Buildings, 2015 - Elsevier
The residential sector represents some 30% of global electricity consumption but the
underlying composition and drivers are still only poorly understood. The drivers are many …

[HTML][HTML] Estimating the building based energy consumption as an anthropogenic contribution to urban heat islands

P Boehme, M Berger, T Massier - Sustainable Cities and Society, 2015 - Elsevier
Today the implication of buildings' electricity demand on the outdoor climate around
buildings is not fully understood. For tropical cities like Singapore, where air-conditioning is …

Characterisation of Australian apartment electricity demand and its implications for low-carbon cities

MB Roberts, N Haghdadi, A Bruce, I MacGill - Energy, 2019 - Elsevier
Understanding of residential electricity demand has application in efficient building design,
network planning and broader policy and regulation, as well as in planning the deployment …

Urban energy flux: Spatiotemporal fluctuations of building energy consumption and human mobility-driven prediction

N Mohammadi, JE Taylor - Applied energy, 2017 - Elsevier
Urbanization is causing a significant increase in the amount, diversity, and complexity of
human activities, all of which have a substantial impact on energy consumption. Current …

A Reinforcement Learning Approach for Ensemble Machine Learning Models in Peak Electricity Forecasting

W Pannakkong, VT Vinh, NNM Tuyen… - Energies, 2023 - mdpi.com
Electricity peak load forecasting plays an important role in electricity generation capacity
planning to ensure reliable power supplies. To achieve high forecast accuracy, multiple …