A review of deep reinforcement learning for smart building energy management
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 …
emission, raising severe energy and environmental concerns. Therefore, it is significant and …
[HTML][HTML] Residential Demand Side Management model, optimization and future perspective: A review
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 …
stability, and efficient power management. However, the load dynamics of the energy …
A comprehensive overview on demand side energy management towards smart grids: challenges, solutions, and future direction
Demand-side management, a new development in smart grid technology, has enabled
communication between energy suppliers and consumers. Demand side energy …
communication between energy suppliers and consumers. Demand side energy …
Home energy management system concepts, configurations, and technologies for the smart grid
Home energy management systems (HEMSs) help manage electricity demand to optimize
energy consumption and distributed renewable energy generation without compromising …
energy consumption and distributed renewable energy generation without compromising …
Closed-loop home energy management system with renewable energy sources in a smart grid: A comprehensive review
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 …
renewable energy, which has severe economic and environmental impacts, dominant the …
Deep learning in energy modeling: Application in smart buildings with distributed energy generation
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 …
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 …
widespread use of smart home appliances provide new opportunities for home energy …
[HTML][HTML] Future of energy management systems in smart cities: A systematic literature review
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 …
Homes Energy Management Systems (HEMSs). In the literature, many reviews have been …
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 …
scheduling of energy consumptions of smart home appliances and distributed energy …
An overview of demand response in smart grid and optimization techniques for efficient residential appliance scheduling problem
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 …
modern society. It avoids the shortcomings of traditional grids by incorporating new …