Control and estimation techniques applied to smart microgrids: A review
The performance of microgrid operation requires hierarchical control and estimation
schemes that coordinate and monitor the system dynamics within the expected manipulated …
schemes that coordinate and monitor the system dynamics within the expected manipulated …
Reinforcement learning and its applications in modern power and energy systems: A review
With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …
other emerging technologies, there are increasing complexities and uncertainties for …
[HTML][HTML] A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings
Buildings are one of the main consumers of energy in cities, which is why a lot of research
has been generated around this problem. Especially, the buildings energy management …
has been generated around this problem. Especially, the buildings energy management …
Reinforcement learning for selective key applications in power systems: Recent advances and future challenges
With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …
modern power systems are confronted with new operational challenges, such as growing …
A review of microgrid energy management and control strategies
S Ahmad, M Shafiullah, CB Ahmed… - IEEE Access, 2023 - ieeexplore.ieee.org
Several issues have been reported with the expansion of the electric power grid and the
increasing use of intermittent power sources, such as the need for expensive transmission …
increasing use of intermittent power sources, such as the need for expensive transmission …
Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning
In this chapter, a novel data-driven method, which is called the deep deterministic policy
gradient (DDPG), is applied for optimally controlling the multi-zone residential heating …
gradient (DDPG), is applied for optimally controlling the multi-zone residential heating …
A multi-agent reinforcement learning-based data-driven method for home energy management
This paper proposes a novel framework for home energy management (HEM) based on
reinforcement learning in achieving efficient home-based demand response (DR). The …
reinforcement learning in achieving efficient home-based demand response (DR). The …
[HTML][HTML] A systematic review of machine learning techniques related to local energy communities
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 …
processes in several sectors, as in the case of electrical power systems. Machine learning …
Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning …
Y Li, F Bu, Y Li, C Long - Applied Energy, 2023 - Elsevier
Multi-uncertainties from power sources and loads have brought significant challenges to the
stable demand supply of various resources at islands. To address these challenges, a …
stable demand supply of various resources at islands. To address these challenges, a …
[HTML][HTML] Market mechanisms for local electricity markets: A review of models, solution concepts and algorithmic techniques
The rapidly increasing penetration of distributed energy resources (DERs) calls for a
hierarchical framework where aggregating entities handle the energy management …
hierarchical framework where aggregating entities handle the energy management …