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DPGS: Data-driven photovoltaic grid-connected system exploiting
In the literature, a single-phase LCL photovoltaic grid-connected system was built, and a neural network was employed to improve both the photovoltaic grid-connected waveform and the
Data-driven dynamic modeling for inverter-based resources using
A data-driven dynamic model for inverter-based resources in power grids is proposed, which couples neural networks with a physical inverter interface, enabling the model output to follow...
Innovative neural network and fuzzy logic control techniques for single
This paper conducts a detailed analysis of both simulated and practical implementations of a system that integrates a photovoltaic (PV) panel, a DC-to-DC boost converter, and a DC-to-AC
Neural Networks Revolutionize Inverter-Based Resource Modeling
In a groundbreaking advance poised to reshape the future of power systems, researchers have harnessed the power of neural networks to develop a data-driven dynamic
Enhancing Power Quality in a PV/Wind Smart Grid with Artificial
In this paper, an enhanced inverter control (IC) and artificial neural network (ANN), combined as the ICANN technique, is used for optimizing and improving power quality in a microgrid
Comparative analysis of reinforcement learning and artificial neural
This research aims to explore the potential applications of artificial intelligence (AI) methods, such as reinforcement learning (RL) and artificial neural networks (ANN), in controlling inverter systems and
Smart Control for Solar PV-Grids to Enhance Power Quality using
In this paper, an advanced neural network-based control for the inverter is utilized to dynamically optimize inverter settings for the abatement of common power quality problems.
Neural Networks-Based Inverter Control: Modeling and Adaptive
Abstract—The optimal voltage control of inverter-based re-sources, especially under the high penetration of solar photo-voltaics, is critical to the stability of the distribution power system.
Neural Network Based Inverter Control for Improving Power
A three-phase grid-connected solar photovoltaic (GCPVS) system incorporating Modified Neural Network Based Proportional Integral (MNNPI) inverter control algorithm is designed.
Neural Networks-based Inverter Control: Modeling and Adaptive
mputational complexity as well as the coordinated operation performance of the voltage control opti-mization in the distribution power system limits the real-time applications. To mitigate this issue, a
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