[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 …

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 …

[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 …

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 …

Reinforcement learning: theory and applications in hems

O Al-Ani, S Das - Energies, 2022 - mdpi.com
The steep rise in reinforcement learning (RL) in various applications in energy as well as the
penetration of home automation in recent years are the motivation for this article. It surveys …