Distributed Reactive Power Optimization for Energy Internet via Multiagent Deep Reinforcement Learning With Graph Attention Networks
Author:
Affiliation:
1. College of Engineering, Peking University, Beijing, China
2. Digital Research Institute, ENN Group, Beijing, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9424/10550081/10477966.pdf?arnumber=10477966
Reference31 articles.
1. Clustered Effective Reactive Reserve to Secure Dynamic Voltage Stability in Power System Operation
2. Stochastic Optimal Control Scheme for Battery Lifetime Extension in Islanded Microgrid via a Novel Modeling Approach
3. Reactive Power Control for Distributed Generation Power Plants to Comply With Voltage Limits During Grid Faults
4. Reactive Power Compensation and Optimization Strategy for Grid-Interactive Cascaded Photovoltaic Systems
5. A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context
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1. Temporal graph convolutional network for multi-agent reinforcement learning of action detection;Applied Soft Computing;2024-09
2. A two‐stage reactive power optimization method for distribution networks based on a hybrid model and data‐driven approach;IET Renewable Power Generation;2024-08-28
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