Low-carbon urban–rural modern energy systems with energy resilience under climate change and extreme events in China—A state-of-the-art review
Y Zhou - Energy and Buildings, 2024 - Elsevier
Climate-adaptive energy resilience and low-carbon transformation are mainstreams to
combat with climate change uncertainty, rural energy poverty, and urban modern energy …
combat with climate change uncertainty, rural energy poverty, and urban modern energy …
Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load
Y Lu, Y Xiang, Y Huang, B Yu, L Weng, J Liu - Energy, 2023 - Elsevier
The increasing integration of distributed resources, such as distributed generations (DGs),
energy storage systems (ESSs), and flexible loads (FLs), has ushered in a new era for the …
energy storage systems (ESSs), and flexible loads (FLs), has ushered in a new era for the …
Revealing the degradation patterns of lithium-ion batteries from impedance spectroscopy using variational auto-encoders
Y Liu, Q Li, K Wang - Energy Storage Materials, 2024 - Elsevier
The aging life estimation of lithium-ion batteries (LIBs) is of great significance to the use,
maintenance and economic analysis of energy storage systems. The estimation method of …
maintenance and economic analysis of energy storage systems. The estimation method of …
Coordinated energy management for integrated energy system incorporating multiple flexibility measures of supply and demand sides: A deep reinforcement learning …
J Liu, Y Li, Y Ma, R Qin, X Meng, J Wu - Energy Conversion and …, 2023 - Elsevier
With the development of energy Internet and intelligent buildings, the interactions of supply
and demand sides of integrated energy system (IES) offer an attractive route for flexible …
and demand sides of integrated energy system (IES) offer an attractive route for flexible …
A novel supercapacitor degradation prediction using a 1D convolutional neural network and improved informer model
H Zhang, Z Yi, L Kang, Y Zhang… - Protection and Control of …, 2024 - ieeexplore.ieee.org
Safety and reliability are crucial for the next-generation supercapacitors used in energy
storage systems, while accurate prediction of the degradation trajectory and remaining …
storage systems, while accurate prediction of the degradation trajectory and remaining …
Data-driven energy management system for flexible operation of hydrogen/ammonia-based energy hub: A deep reinforcement learning approach
In the context of carbon neutrality, multi-energy systems are being designed to enhance the
integration of renewable energy, and the deployment of large-scale energy storage …
integration of renewable energy, and the deployment of large-scale energy storage …
Multi-Objective Interval Optimization Dispatch of Microgrid via Deep Reinforcement Learning
C Mu, Y Shi, N Xu, X Wang, Z Tang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper presents an improved deep reinforcement learning (DRL) algorithm for solving
the optimal dispatch of microgrids under uncertaintes. First, a multi-objective interval …
the optimal dispatch of microgrids under uncertaintes. First, a multi-objective interval …
Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement …
Abstract Power-to-ammonia (P2A) technology has attracted more and more attention since
ammonia is recognized as a natural zero-carbon fuel. In this context, this paper constructs a …
ammonia is recognized as a natural zero-carbon fuel. In this context, this paper constructs a …
Optimal planning of hybrid energy storage systems using curtailed renewable energy through deep reinforcement learning
Energy management systems are becoming increasingly important to utilize the
continuously growing curtailed renewable energy. Promising energy storage systems, such …
continuously growing curtailed renewable energy. Promising energy storage systems, such …
Low‐carbon economic dispatch of the combined heat and power‐virtual power plants: A improved deep reinforcement learning‐based approach
Y Tan, Y Shen, X Yu, X Lu - IET renewable power generation, 2023 - Wiley Online Library
To realize the national strategies for carbon emission reduction, electric power industries
should undergo reforms to cope with the multiple challenges of decarbonization …
should undergo reforms to cope with the multiple challenges of decarbonization …