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RSS FeedsEnergies, Vol. 11, Pages 2867: Low-Voltage Ride-Through Operation of Grid-Connected Microgrid Using Consensus-Based Distributed Control (Energies)

 
 

27 october 2018 00:01:31

 
Energies, Vol. 11, Pages 2867: Low-Voltage Ride-Through Operation of Grid-Connected Microgrid Using Consensus-Based Distributed Control (Energies)
 


Since the penetration of distributed energy resources (DERs) and energy storage systems (ESSs) into the microgrid (MG) system has increased significantly, the sudden disconnection of DERs and ESSs might affect the stability and reliability of the whole MG system. The low-voltage ride-through (LVRT) capability to maintain stable operation of the MG system should be considered. The main contribution of this study is to propose a distributed control, based on a dynamic consensus algorithm for LVRT operation of the MG system. The proposed control method is based on a hierarchical control that consists of primary and secondary layers. The primary layer is in charge of power regulation, while the secondary layer is responsible for the LVRT operation of the MG system. The droop controller is used in the primary layer to maintain power sharing among parallel-distributed generators in the MG system. The dynamic consensus algorithm is used in the secondary layer to control the accurate reactive power sharing and voltage restoration for LVRT operation. A comparison study on the proposed control method and centralized control method is presented in this study to show the effectiveness of the proposed controller. Different scenarios of communication failures are carried out to show the reliability of the proposed control method. The tested MG system and proposed controller are modeled in a MATLAB/Simulink environment to show the feasibility of the proposed control method.


 
68 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 11, Pages 2870: A New Input Selection Algorithm Using the Group Method of Data Handling and Bootstrap Method for Support Vector Regression Based Hourly Load Forecasting (Energies)
Energies, Vol. 11, Pages 2866: Accurate Fall Detection and Localization for Elderly People Based on Neural Network and Energy-Efficient Wireless Sensor Network (Energies)
 
 
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