[HTML][HTML] Recent advances in data mining and machine learning for enhanced building energy management

X Zhou, H Du, S Xue, Z Ma - Energy, 2024‏ - Elsevier
Due to the recent advancements in the Internet of Things and data science techniques, a
wide range of studies have investigated the use of data mining (DM) and machine learning …

[HTML][HTML] A taxonomy of machine learning applications for virtual power plants and home/building energy management systems

S Sierla, M Pourakbari-Kasmaei, V Vyatkin - Automation in Construction, 2022‏ - Elsevier
A Virtual power plant is defined as an information and communications technology system
with the following primary functionalities: enhancing renewable power generation …

[HTML][HTML] Modeling and forecasting electricity consumption amid the COVID-19 pandemic: Machine learning vs. nonlinear econometric time series models

L Charfeddine, E Zaidan, AQ Alban, H Bennasr… - Sustainable Cities and …, 2023‏ - Elsevier
Accurately modeling and forecasting electricity consumption remains a challenging task due
to the large number of the statistical properties that characterize this time series such as …

Knowledge graph based trajectory outlier detection in sustainable smart cities

U Ahmed, G Srivastava, Y Djenouri, JCW Lin - Sustainable Cities and …, 2022‏ - Elsevier
Graph-based intelligent systems are emerging in the field of transportation systems.
Knowledge graphs help to provide semantic and interconnectivity capabilities to the …

Machine learning based demand response scheme for IoT enabled PV integrated smart building

P Balakumar, T Vinopraba… - Sustainable Cities and …, 2023‏ - Elsevier
The short-term forecasting of electric power consumption and renewable energy generation
with high efficiency and advanced demand side management is essential for improving the …

Model-Free HVAC Control in Buildings: A Review

P Michailidis, I Michailidis, D Vamvakas… - Energies, 2023‏ - mdpi.com
The efficient control of HVAC devices in building structures is mandatory for achieving
energy savings and comfort. To balance these objectives efficiently, it is essential to …

A novel hybrid Harris hawk optimization and sine cosine algorithm based home energy management system for residential buildings

K Paul, D Hati - Building Services Engineering Research & …, 2023‏ - journals.sagepub.com
Smart grid technology has given users the ability to regulate their home energy in a much
more effective manner. In such scenarios, Home Energy Management (HEM) potentially …

Renewable energy management in smart home environment via forecast embedded scheduling based on Recurrent Trend Predictive Neural Network

M Nakıp, O Çopur, E Biyik, C Güzeliş - Applied Energy, 2023‏ - Elsevier
Smart home energy management systems help the distribution grid operate more efficiently
and reliably, and enable effective penetration of distributed renewable energy sources …

Rough knowledge enhanced dueling deep Q-network for household integrated demand response optimization

Y Su, T Zhang, M Xu, M Tan, Y Zhang, R Wang… - Sustainable Cities and …, 2024‏ - Elsevier
Implementing a household integrated demand response (HIDR) can be an effective solution
to save energy and reduce carbon emissions in household multi-energy system (HMES) …

Safe reinforcement learning method integrating process knowledge for real-time scheduling of gas supply network

P Zhou, Z Xu, X Zhu, J Zhao, C Song, Z Shao - Information Sciences, 2023‏ - Elsevier
Gas supply networks play a crucial role in steel enterprises because they provide
downstream customers with the gas required for production. In this paper, the real-time …