Reinforcement learning algorithms: A brief survey
Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …
Strategies for controlling microgrid networks with energy storage systems: A review
Distributed Energy Storage Systems are considered key enablers in the transition from the
traditional centralized power system to a smarter, autonomous, and decentralized system …
traditional centralized power system to a smarter, autonomous, and decentralized system …
An assessment of multistage reward function design for deep reinforcement learning-based microgrid energy management
Reinforcement learning based energy management strategy has been an active research
subject in the past few years. Different from the baseline reward function (BRF), the work …
subject in the past few years. Different from the baseline reward function (BRF), the work …
Fusion of microgrid control with model-free reinforcement learning: Review and vision
Challenges and opportunities coexist in microgrids as a result of emerging large-scale
distributed energy resources (DERs) and advanced control techniques. In this paper, a …
distributed energy resources (DERs) and advanced control techniques. In this paper, a …
Reinforcement learning-based intelligent control strategies for optimal power management in advanced power distribution systems: A survey
Intelligent energy management in renewable-based power distribution applications, such as
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …
Multi-agent hierarchical reinforcement learning for energy management
The increasingly complex energy systems are turning the attention towards model-free
control approaches such as reinforcement learning (RL). This work proposes novel RL …
control approaches such as reinforcement learning (RL). This work proposes novel RL …
[HTML][HTML] Data-driven energy management of virtual power plants: A review
A virtual power plant (VPP) refers to an active aggregator of heterogeneous distributed
energy resources (DERs), which creates a promising pathway to expand renewable energy …
energy resources (DERs), which creates a promising pathway to expand renewable energy …
Predictive models development using gradient boosting based methods for solar power plants
N Aksoy, I Genc - Journal of Computational Science, 2023 - Elsevier
Being able to predict the power to be generated by solar power plants in a smart grid,
microgrid or nanogrid with high accuracy and speed brings a lot of advantages in the …
microgrid or nanogrid with high accuracy and speed brings a lot of advantages in the …
A review of microgrid energy management strategies from the energy trilemma perspective
The energy sector is undergoing a paradigm shift among all the stages, from generation to
the consumer end. The affordable, flexible, secure supply–demand balance due to an …
the consumer end. The affordable, flexible, secure supply–demand balance due to an …
[HTML][HTML] Optimal energy management in a grid-tied solar PV-battery microgrid for a public building under demand response
F Wamalwa, A Ishimwe - Energy Reports, 2024 - Elsevier
Commercial buildings consume a substantial amount of energy, underscoring the need for
consumption optimization. Embedded microgrids combined with demand side management …
consumption optimization. Embedded microgrids combined with demand side management …