Reinforcement learning in deregulated energy market: A comprehensive review
The increasing penetration of renewable generations, along with the deregulation and
marketization of power industry, promotes the transformation of energy market operation …
marketization of power industry, promotes the transformation of energy market operation …
A review on optimal energy management of multimicrogrid system considering uncertainties
Microgrid (MG) is one of the most effective solution to integrate distributed renewable energy
into power system. However, modern MG has several technical challenges such as …
into power system. However, modern MG has several technical challenges such as …
[HTML][HTML] Hierarchical optimal configuration of multi-energy microgrids system considering energy management in electricity market environment
J Zhao, W Wang, C Guo - International Journal of Electrical Power & Energy …, 2023 - Elsevier
Aiming at the global environmental pressure and energy crisis, an optimal configuration
method of a multi-energy microgrids system is proposed in the context of the electricity …
method of a multi-energy microgrids system is proposed in the context of the electricity …
A novel energy management method for networked multi-energy microgrids based on improved DQN
The networked Multi-Energy Microgrids (MEMGs) can significantly improve the economic
efficiency of operation through energy cooperation and complementarity. However, the …
efficiency of operation through energy cooperation and complementarity. However, the …
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 …
Neural-network-based control with dynamic event-triggered mechanisms under DoS attacks and applications in load frequency control
The paper is concerned with the supplementary control based on adaptive dynamic
programming (ADP) for a class of discrete-time networked system with the simultaneous …
programming (ADP) for a class of discrete-time networked system with the simultaneous …
[HTML][HTML] Two-Stage experimental intelligent dynamic energy management of microgrid in smart cities based on demand response programs and energy storage …
R Sepehrzad, A Hedayatnia, M Amohadi… - International Journal of …, 2024 - Elsevier
Power variations due to uncertainties create fluctuations in voltage/frequency (V/F). Most
critical microgrid's (MG) challenge in smart cities is V/F stability considering uncertainties in …
critical microgrid's (MG) challenge in smart cities is V/F stability considering uncertainties in …
Meta-reinforcement learning-based transferable scheduling strategy for energy management
In Home Energy Management System (HEMS), the scheduling of energy storage equipment
and shiftable loads has been widely studied to reduce home energy costs. However …
and shiftable loads has been widely studied to reduce home energy costs. However …
An enhanced jellyfish search optimizer for stochastic energy management of multi-microgrids with wind turbines, biomass and PV generation systems considering …
The energy management (EM) solution of the multi-microgrids (MMGs) is a crucial task to
provide more flexibility, reliability, and economic benefits. However, the energy management …
provide more flexibility, reliability, and economic benefits. However, the energy management …
A home energy management approach using decoupling value and policy in reinforcement learning
Considering the popularity of electric vehicles and the flexibility of household appliances, it
is feasible to dispatch energy in home energy systems under dynamic electricity prices to …
is feasible to dispatch energy in home energy systems under dynamic electricity prices to …