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 …
A state-of-the-art review and bibliometric analysis on the sizing optimization of off-grid hybrid renewable energy systems
The development of off-grid hybrid renewable energy systems (HRESs) is essential to rural
electrification and global decarbonization. Based on 299 journal papers in the recent five …
electrification and global decarbonization. Based on 299 journal papers in the recent five …
Applications of reinforcement learning for building energy efficiency control: A review
Q Fu, Z Han, J Chen, Y Lu, H Wu, Y Wang - Journal of Building Engineering, 2022 - Elsevier
The wide variety of smart devices equipped in modern intelligent buildings and the
increasing comfort requirements of occupants for the environment make the control of …
increasing comfort requirements of occupants for the environment make the control of …
Multi-agent deep reinforcement learning based distributed control architecture for interconnected multi-energy microgrid energy management and optimization
Environmental and climate change concerns are pushing the rapid development of new
energy resources (DERs). The Energy Internet (EI), with the power-sharing functionality …
energy resources (DERs). The Energy Internet (EI), with the power-sharing functionality …
[HTML][HTML] A survey of artificial intelligence methods for renewable energy forecasting: Methodologies and insights
The efforts to revolutionize electric power generation and produce clean and sustainable
electricity have led to the exploration of renewable energy systems (RES). This form of …
electricity have led to the exploration of renewable energy systems (RES). This form of …
Modeling and optimal dispatch of a carbon-cycle integrated energy system for low-carbon and economic operation
G Zhang, W Wang, Z Chen, R Li, Y Niu - Energy, 2022 - Elsevier
Energy efficiency and greenhouse gas emissions mitigation are important topics in modern
energy systems research. In this study, power-to-gas (P2G), carbon capture, supercritical CO …
energy systems research. In this study, power-to-gas (P2G), carbon capture, supercritical CO …
Data-driven optimal energy management for a wind-solar-diesel-battery-reverse osmosis hybrid energy system using a deep reinforcement learning approach
Significant dependence on fossil fuels and freshwater shortage are common problems in
remote and arid regions. In this context, the operation of a wind-solar-diesel-battery-reverse …
remote and arid regions. In this context, the operation of a wind-solar-diesel-battery-reverse …
Prediction of SOx–NOx emission from a coal-fired CFB power plant with machine learning: Plant data learned by deep neural network and least square support vector …
The circulating fluidized bed boiler is an advanced clean energy technology that has
received much attention in the power industry due to its fuel flexibility. In this study, a deep …
received much attention in the power industry due to its fuel flexibility. In this study, a deep …
Soft actor-critic–based multi-objective optimized energy conversion and management strategy for integrated energy systems with renewable energy
As an essential development direction of energy internet, integrated energy system with
interdisciplinary techniques is of great significance to promote multi-energy cooperation …
interdisciplinary techniques is of great significance to promote multi-energy cooperation …
Optimal operation of integrated electricity and heat system: A review of modeling and solution methods
The optimal operation of the integrated electricity and heat systems (IEHS) can bring
environmental benefits, reduce the operational cost, and achieve high penetration levels of …
environmental benefits, reduce the operational cost, and achieve high penetration levels of …