Optimal planning of solar photovoltaic and battery storage systems for grid-connected residential sector: Review, challenges and new perspectives

R Khezri, A Mahmoudi, H Aki - Renewable and Sustainable Energy …, 2022 - Elsevier
Integration of solar photovoltaic (PV) and battery storage systems is an upward trend for
residential sector to achieve major targets like minimizing the electricity bill, grid …

Reinforcement learning and its applications in modern power and energy systems: A review

D Cao, W Hu, J Zhao, G Zhang, B Zhang… - Journal of modern …, 2020 - ieeexplore.ieee.org
With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …

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 …

Ten questions concerning reinforcement learning for building energy management

Z Nagy, G Henze, S Dey, J Arroyo, L Helsen… - Building and …, 2023 - Elsevier
As buildings account for approximately 40% of global energy consumption and associated
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …

[HTML][HTML] A systematic review of machine learning techniques related to local energy communities

A Hernandez-Matheus, M Löschenbrand, K Berg… - … and Sustainable Energy …, 2022 - Elsevier
In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …

Reinforcement learning for selective key applications in power systems: Recent advances and future challenges

X Chen, G Qu, Y Tang, S Low… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …

[HTML][HTML] Real-time energy scheduling for home energy management systems with an energy storage system and electric vehicle based on a supervised-learning …

THB Huy, HT Dinh, DN Vo, D Kim - Energy Conversion and Management, 2023 - Elsevier
With rising energy costs and concerns about environmental sustainability, there is a growing
need to deploy Home Energy Management Systems (HEMS) that can efficiently manage …

[HTML][HTML] Smart home energy management systems: Research challenges and survey

A Raza, L **gzhao, Y Ghadi, M Adnan, M Ali - Alexandria engineering …, 2024 - Elsevier
Electricity is establishing ground as a means of energy, and its proportion will continue to
rise in the next generations. Home energy usage is expected to increase by more than 40 …

Multi-agent deep reinforcement learning for HVAC control in commercial buildings

L Yu, Y Sun, Z Xu, C Shen, D Yue… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In commercial buildings, about 40%-50% of the total electricity consumption is attributed to
Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic …

Deep learning in smart grid technology: A review of recent advancements and future prospects

M Massaoudi, H Abu-Rub, SS Refaat, I Chihi… - IEEE …, 2021 - ieeexplore.ieee.org
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …