[HTML][HTML] Application status and prospects of digital twin technology in distribution grid
Z Zhaoyun, L Linjun - Energy Reports, 2022 - Elsevier
With the continuous expansion of the scale of the power grid and the growth of the demand
for electricity, the digital and intelligent construction of distribution grids is urgently needed …
for electricity, the digital and intelligent construction of distribution grids is urgently needed …
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 …
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 …
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 …
Deep reinforcement learning enabled physical-model-free two-timescale voltage control method for active distribution systems
Active distribution networks are being challenged by frequent and rapid voltage violations
due to renewable energy integration. Conventional model-based voltage control methods …
due to renewable energy integration. Conventional model-based voltage control methods …
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 …
Model-free voltage control of active distribution system with PVs using surrogate model-based deep reinforcement learning
Accurate knowledge of the distribution system topology and parameters is required to
achieve good voltage control performance, but this is difficult to obtain in practice. This paper …
achieve good voltage control performance, but this is difficult to obtain in practice. This paper …
An adaptive distributionally robust model for three-phase distribution network reconfiguration
Distributed generator (DG) volatility has a great impact on system operation, which should
be considered beforehand due to the slow time scale of distribution network reconfiguration …
be considered beforehand due to the slow time scale of distribution network reconfiguration …
[HTML][HTML] Reliability-driven distribution power network dynamic reconfiguration in presence of distributed generation by the deep reinforcement learning method
S Malekshah, A Rasouli, Y Malekshah… - Alexandria Engineering …, 2022 - Elsevier
The reliability of the distribution network increasingly common by high penetration of
distributed generations. To address the reliability, this paper propose a new approach based …
distributed generations. To address the reliability, this paper propose a new approach based …
Real-time outage management in active distribution networks using reinforcement learning over graphs
Self-healing smart grids are characterized by fast-acting, intelligent control mechanisms that
minimize power disruptions during outages. The corrective actions adopted during outages …
minimize power disruptions during outages. The corrective actions adopted during outages …