Online controller modifying of a six-phase induction generator in phase opening occurrences

Taherzadeh, Mehdi; Carriere, S.; Bétin, F.; Joorabian, Mahmood; Kianinezhad, R.; Capolino, Gérard‐André

doi:10.1109/icelmach.2014.6960278

Cited by 6 publications

(2 citation statements)

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“…The same idea of currents averaging is discussed in papers [90,91], where the authors expand it to multiphase drives and propose their own criteria of fault detection. A similar method, which uses root mean square (RMS) values instead of averaging, was proposed in [86,87]. Calculation of square roots is a high load for the microcontroller even when using acceleration techniques [88,89], so it is desired to avoid it if possible.…”

Section: A Average Current Calculationmentioning

confidence: 99%

Phase Loss Detection Using Current Signals: A Review

Dianov

Anuchin

2021

IEEE Access

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This paper discusses open phase faults, which can happen in a system grid-converter-motor drive, and measures to properly handle this type of fault. The authors of this paper provide classification of algorithms used for the detection of the loss of phase and explain the distinctive features of each group of methods. They review existing algorithms, which are based on the analysis of the current signals, discuss their pros and cons and suggest possible areas of usage for each group of methods. The authors also propose one novel method for detection of open phase, which was developed for low-cost systems with low resolution analog-to digital converters (ADC). This paper mainly considers methods for three-phase motors as the most popular machines, however some algorithms can be used in multiphase drives. The authors of the paper also share their more than 20 years' experience combined, in this area, which was obtained by developing industrial and commercial drives, and focus on the requirements of the IEC/UL 60730 safety standard, where the phase-loss detection algorithm is one of the essential parts of control system.

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Section: A Average Current Calculationmentioning

confidence: 99%

Phase Loss Detection Using Current Signals: A Review

Dianov

Anuchin

2021

IEEE Access

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“…To integrate 6phase dual star induction generators in the main electricity grid, two three-phase AC/DC converters can be used, each connected with one of the stator's three-phase windings [18][19][20]. Due to the nonlinearities and multivariable structure of the associated state-space model the control and stabilization problem of 6-phase DSIGs is nontrivial [21][22][23][24]. Several attempts have been made to develop model-based control schemes for 6-phase DSIGs and to demonstrate robustness of the associated control loops to model uncertainty and perturbations [25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Optimal Control for Six-Phase Induction Generator-Based Renewable Energy Systems

Rigatos¹,

Abbaszadeh²,

Sari³

et al. 2023

J Energ Power Technol

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The article aims at optimizing six-phase induction generator-based renewable energy systems (6-phase IGs or dual star induction generators) through a novel nonlinear optimal control method. Six-phase induction generators appear to be advantageous compared to three-phase synchronous or asynchronous power generators, in terms of fault tolerance and improved power generation rates. The dynamic model of the six-phase induction generator is first written in a nonlinear and multivariable state-space form. It is proven that this model is differentially flat. The 6-phase IG is approximately linearized around a temporary operating point recomputed at each sampling interval to design the optimal controller. The linearization is based on first-order Taylor series expansion and the Jacobian matrices of the state-space model of the 6-phase IG. A stabilizing optimal (H-infinity) feedback controller is designed for the linearized state-space description of the six-phase IG. The feedback gains of the controller are computed by solving an algebraic Riccati equation at each iteration of the control method. Lyapunov analysis is used to demonstrate global stability for the control loop. The H-infinity Kalman Filter is also used as a robust state estimator, which allows for implementing sensorless control for 6-phase IG-based renewable energy systems. The nonlinear optimal control method achieves fast and accurate tracking of setpoints by the state variables of the 6-phase IG, under moderate variations of the control inputs.

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