Supplying a renewable energy single phase microgrid from a biomass generator using a three phase induction machine

2016 ◽  
Author(s):  
Petreus Dorin ◽  
Patarau Toma ◽  
Etz Radu ◽  
Lazar Eniko
Keyword(s):  
Renewable Energy ◽  
Single Phase ◽  
Induction Machine ◽  
Three Phase

Steady-State and Dynamic Behavior of a Single-Phase Self-Excited Induction Generator Using a Three-Phase Machine

2007 ◽  
Vol 8 (3) ◽  
Author(s):  
S. N. Mahato ◽  
M. P. Sharma ◽  
S. P. Singh
Keyword(s):  
Steady State ◽  
Reference Frame ◽  
Single Phase ◽  
Short Circuit ◽  
Induction Machine ◽  
Transient Behavior ◽  
Experimental Results ◽  
Induction Generator ◽  
State Variables ◽  
Three Phase

This paper presents the steady-state and transient behavior of a single-phase self-excited induction generator (SEIG) using a three-phase machine with one shunt and one series excitation capacitors for resistive and inductive loads. The generation scheme consists of one three-phase delta connected induction machine and two capacitors - one connected in parallel with one winding and the other in series with a single-phase load. The dynamic model of the system has been developed as a hybrid model considering the stator phase currents in abc reference frame and the rotor currents in stationary d-q axes reference frame as state variables. The simulated and experimental results are presented for different dynamic conditions such as initiation of self-excitation, load perturbation and short-circuit. The simulated results of the steady-state analysis have been compared with the transient and experimental results and a close agreement between them indicates the accuracy and effectiveness of the approach.

scholarly journals Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

2010 ◽  
Vol 20 (3) ◽  
pp. 363-376 ◽  
Author(s):  
Rudra Dash ◽  
Bidyadhar Subudhi
Keyword(s):  
Fault Detection ◽  
Induction Motor ◽  
Fault Location ◽  
Single Phase ◽  
Fuzzy Inference ◽  
Induction Machine ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Fuzzy Techniques

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniquesMotivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detection of a single phase induction motor, this paper studies the applicability these two approaches for detection of stator inter-turn faults in a three phase induction motor. Firstly, the paper develops an adaptive neural fuzzy inference system (ANFIS) detection strategy and then compares its performance with that of using a multi layer perceptron neural network (MLP NN) applied to stator inter-turn fault detection of a three phase induction motor. The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine.

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