A survey on deep learning role in distribution automation system: a new collaborative Learning-to-Learning (L2L) concept
This paper focuses on a powerful and comprehensive overview of Deep Learning (DL)
techniques on Distribution Automation System (DAS) applications to provide a complete …
techniques on Distribution Automation System (DAS) applications to provide a complete …
Application and progress of artificial intelligence technology in the field of distribution network voltage Control: A review
The increasing integration of distributed energy resources has led to heightened complexity
in distribution network models, posing challenges of uncertainty and volatility to the …
in distribution network models, posing challenges of uncertainty and volatility to the …
Safe off-policy deep reinforcement learning algorithm for volt-var control in power distribution systems
Volt-VAR control is critical to keeping distribution network voltages within allowable range,
minimizing losses, and reducing wear and tear of voltage regulating devices. To deal with …
minimizing losses, and reducing wear and tear of voltage regulating devices. To deal with …
Deep reinforcement learning based volt-var optimization in smart distribution systems
This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent
deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel …
deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel …
Consensus multi-agent reinforcement learning for volt-var control in power distribution networks
Volt-VAR control (VVC) is a critical application in active distribution network management
system to reduce network losses and improve voltage profile. To remove dependency on …
system to reduce network losses and improve voltage profile. To remove dependency on …
Multi-agent deep reinforcement learning for voltage control with coordinated active and reactive power optimization
The increasing penetration of distributed renewable energy resources causes voltage
fluctuations in distribution networks. The controllable active and reactive power resources …
fluctuations in distribution networks. The controllable active and reactive power resources …
Batch-constrained reinforcement learning for dynamic distribution network reconfiguration
Dynamic distribution network reconfiguration (DNR) algorithms perform hourly status
changes of remotely controllable switches to improve distribution system performance. The …
changes of remotely controllable switches to improve distribution system performance. The …
Two-stage deep reinforcement learning for inverter-based volt-var control in active distribution networks
Model-based Vol/VAR optimization method is widely used to eliminate voltage violations
and reduce network losses. However, the parameters of active distribution networks (ADNs) …
and reduce network losses. However, the parameters of active distribution networks (ADNs) …
Allocation of PV Systems with Volt/Var Control Based on Automatic Voltage Regulators in Active Distribution Networks
AM Shaheen, EE Elattar, NA Nagem, AF Nasef - Sustainability, 2023 - mdpi.com
This paper presents an optimal allocation methodology of photovoltaic distributed
generations (PVDGs) with Volt/Var control based on Automatic Voltage Regulations (AVRs) …
generations (PVDGs) with Volt/Var control based on Automatic Voltage Regulations (AVRs) …
Coordination of PV smart inverters using deep reinforcement learning for grid voltage regulation
Increasing adoption of solar photovoltaic (PV) presents new challenges to modern power
grid due to its variable and intermittent nature. Fluctuating outputs from PV generation can …
grid due to its variable and intermittent nature. Fluctuating outputs from PV generation can …