scholarly journals Operation Mode Transition of a Low-Voltage Single Phase Microgrid based on Synchronization Controller

Author(s):  
Qusay Salem ◽  
◽  
Khaled Alzaareer ◽  
Salman Harasis ◽  
◽  
...  
2013 ◽  
Vol 441 ◽  
pp. 281-285
Author(s):  
Kun Gao ◽  
Zhe Nan Zhang ◽  
Quan Sheng Zhu ◽  
Liang Yuan

The electric power short circuit breakdown may cause low voltage blocking of frequency-converter giving rise to power unit shutdown accident,three typical coal-fired power units are selected to emulate calculations on low voltage ride ability with considering threephase short-circuit earthing fault, threephase short-circuit earthing fault by impedance, single-phase short-circuit earthing fault ,indicating that the short-circuit fault of the lines integrating into power system would result in the voltage of house-service busbar dropping off to 25%-85%,especially threephase short-circuit earthing fault in small operation mode attacks on power unit auxiliary at the most, therefore auxiliary demands complete and dependable low voltage ride through ability. and puts forward to some reform suggestes.


2020 ◽  
Vol 36 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Dirk Schneider ◽  
Ralf Stark ◽  
Chloé Génin ◽  
Michael Oschwald ◽  
Konstantin Kostyrkin

2015 ◽  
Vol 30 (2) ◽  
pp. 1006-1011 ◽  
Author(s):  
Pedro M. S. Carvalho ◽  
Luis A. F. M. Ferreira ◽  
Joao J. E. Santana

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2118
Author(s):  
Elias Kaufhold ◽  
Simon Grandl ◽  
Jan Meyer ◽  
Peter Schegner

This paper introduces a new black-box approach for time domain modeling of commercially available single-phase photovoltaic (PV) inverters in low voltage networks. An artificial neural network is used as a nonlinear autoregressive exogenous model to represent the steady state behavior as well as dynamic changes of the PV inverter in the frequency range up to 2 kHz. The data for the training and the validation are generated by laboratory measurements of a commercially available inverter for low power applications, i.e., 4.6 kW. The state of the art modeling approaches are explained and the constraints are addressed. The appropriate set of data for training is proposed and the results show the suitability of the trained network as a black-box model in time domain. Such models are required, i.e., for dynamic simulations since they are able to represent the transition between two steady states, which is not possible with classical frequency-domain models (i.e., Norton models). The demonstrated results show that the trained model is able to represent the transition between two steady states and furthermore reflect the frequency coupling characteristic of the grid-side current.


2021 ◽  
Author(s):  
I. Mexis ◽  
G. Todeschini ◽  
F. Möller ◽  
J. Meyer
Keyword(s):  

2016 ◽  
Vol 78 (10-4) ◽  
Author(s):  
Amirullah Amirullah ◽  
Mochamad Ashari ◽  
Ontoseno Penangsan ◽  
Adi Soeprijanto

Randomly installed distributed generators (DGs) in households may cause unbalanced line current in a distribution network. This research presents a battery energy system for balancing of line current in a distribution network involving multi units of single phase photovoltaic (PV) distributed generators (DGs). In this paper, the PV generators were simulated consisting of a buck-boost DC/DC converter and single phase DC/AC inverter. It was connected to the distribution line through the low voltage 220 volt 50 Hz. The proposed phase balancing system uses battery energy storage and three single phase bidirectional inverters. The inverter is capable of injecting current or absorbing power from the line to the battery. This inverter operation is arranged to balance each distribution line separately, as well as to improve other power quality parameters, such as voltage and current harmonics. Simulation results show that the system was capable of improving the unbalanced line current from 15.59 % to 11, 48 % and unbalanced line voltage from 1.76 % to 0.58 %. The system was able for increasing current harmonics from 0.98 % to 1.03% and voltage harmonics from 38.96% to 39.08%.


2019 ◽  
Vol 66 (7) ◽  
pp. 1212-1216 ◽  
Author(s):  
O. D. Montoya ◽  
A. Garces ◽  
S. Avila-Becerril ◽  
G. Espinosa-Perez ◽  
F. M. Serra

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