[HTML][HTML] Residential Demand Side Management model, optimization and future perspective: A review

S Panda, S Mohanty, PK Rout, BK Sahu, M Bajaj… - Energy Reports, 2022 - Elsevier
The residential load sector plays a vital role in terms of its impact on overall power balance,
stability, and efficient power management. However, the load dynamics of the energy …

A review of deep reinforcement learning for smart building energy management

L Yu, S Qin, M Zhang, C Shen, T Jiang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Global buildings account for about 30% of the total energy consumption and carbon
emission, raising severe energy and environmental concerns. Therefore, it is significant and …

Home energy management system concepts, configurations, and technologies for the smart grid

U Zafar, S Bayhan, A Sanfilippo - IEEE access, 2020 - ieeexplore.ieee.org
Home energy management systems (HEMSs) help manage electricity demand to optimize
energy consumption and distributed renewable energy generation without compromising …

[HTML][HTML] A comprehensive overview on demand side energy management towards smart grids: challenges, solutions, and future direction

MS Bakare, A Abdulkarim, M Zeeshan, AN Shuaibu - Energy Informatics, 2023 - Springer
Demand-side management, a new development in smart grid technology, has enabled
communication between energy suppliers and consumers. Demand side energy …

Closed-loop home energy management system with renewable energy sources in a smart grid: A comprehensive review

AO Ali, MR Elmarghany, MM Abdelsalam… - Journal of Energy …, 2022 - Elsevier
Nowadays, energy plays a prominent role in all aspects of our life. So far, unclean and non-
renewable energy, which has severe economic and environmental impacts, dominant the …

Deep learning in energy modeling: Application in smart buildings with distributed energy generation

SA Nabavi, NH Motlagh, MA Zaidan, A Aslani… - IEEE …, 2021 - ieeexplore.ieee.org
Buildings are responsible for 33% of final energy consumption, and 40% of direct and
indirect CO 2 emissions globally. While energy consumption is steadily rising globally …

Home energy management systems: A review of the concept, architecture, and scheduling strategies

B Han, Y Zahraoui, M Mubin, S Mekhilef… - IEEE …, 2023 - ieeexplore.ieee.org
Growing electricity demand, the deployment of renewable energy sources and the
widespread use of smart home appliances provide new opportunities for home energy …

[HTML][HTML] Energy management of smart home with home appliances, energy storage system and electric vehicle: A hierarchical deep reinforcement learning approach

S Lee, DH Choi - Sensors, 2020 - mdpi.com
This paper presents a hierarchical deep reinforcement learning (DRL) method for the
scheduling of energy consumptions of smart home appliances and distributed energy …

[HTML][HTML] Future of energy management systems in smart cities: A systematic literature review

U ur Rehman, P Faria, L Gomes, Z Vale - Sustainable Cities and Society, 2023 - Elsevier
Massive advancements have been noticed on the Internet of Things (IoT) integrating smart
Homes Energy Management Systems (HEMSs). In the literature, many reviews have been …

[HTML][HTML] An overview of demand response in smart grid and optimization techniques for efficient residential appliance scheduling problem

A Shewale, A Mokhade, N Funde, ND Bokde - Energies, 2020 - mdpi.com
Smart grid (SG) is a next-generation grid which is responsible for changing the lifestyle of
modern society. It avoids the shortcomings of traditional grids by incorporating new …