A novel speed sensor-less vector control of Dual Stator Induction machine with space vector based advanced 9-zone hybrid PWM for grid connected wind energy generation system

Chatterjee, Shantanu; Chatterjee, Saibal

doi:10.1016/j.epsr.2018.02.021

Cited by 15 publications

(20 citation statements)

References 39 publications

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“…The DSIG is a six-dimensional system, that is composed of two identical three-phase stator windings, and one squirrel cage rotor [26,27]. The two split stator windings sets are connected in a star configuration, and are shifted by an electric angle  = 30° [10,11].…”

Section: Dual Star Induction Generator Model Figure 3 Representation Model Of the Dsig With Stator-rotor Orientationmentioning

confidence: 99%

Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System

Mesai-Ahmed¹,

Bentaallah²,

Cardoso³

et al. 2021

MMEP

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This paper presents a field-oriented control (FOC) of a dual star induction generator (DSIG) applied in a grid-connected wind energy conversion system. Currently, the dual star induction machine (DSIM) is increasingly used among multiphase machines. The machine has two star-connections, sharing the same stator offset, by an electrical angle of 30° and fed by two parallel converters. Maximum power point tracking (MPPT) is illustrated in a first stage, in order to extract a maximum of power under fluctuating wind speed. In a second stage, vector control of a DSIG with FOC is described. Finally, voltage oriented control (VOC) is used to ensure the power factor unity on the grid side. The main contribution of the presented paper is the application of a simple architecture of an artificial neural network (ANN) controller in order to improve the robustness and stability of the system, especially against the parameter change. In comparison with the conventional control, which is known by its sensitivity, the proposed neural MPPT with neural FOC (NMPPT-NFOC) presents better performance under normal and abnormal conditions. The robustness and effectiveness of the proposed control has been validated through illustrative simulation results with different functional zones, and for fixed and variable wind speed.

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Section: Dual Star Induction Generator Model Figure 3 Representation Model Of the Dsig With Stator-rotor Orientationmentioning

confidence: 99%

Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System

Mesai-Ahmed¹,

Bentaallah²,

Cardoso³

et al. 2021

MMEP

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“…The expression of torques due to the two stator windings of the machine can be represented as given in (17) and (18)…”

Section: Machine Modellingmentioning

confidence: 99%

“…From the expression of torques as given in (17) and (18) the expressions of i q1 and i q2 can be directly calculated by (19) and (20).…”

Section: Calculations Of Reference Values Of I Q1 and I Q2mentioning

confidence: 99%

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Stator flux‐oriented vector control of dual stator induction generator with time optimised 11‐zone hybrid PWM for grid connected wind energy generation system

Chatterjee

2018

IET Electric Power Applications

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This work presents a novel stator flux-oriented vector control (SFOVC) of a dual stator induction generator (DSIG) used for a grid connected, variable speed wind energy generation system. The DSIG consists of two stator windings electrically separated by an angle of 30° with dissimilar pole numbers, which are in the ratio of 1:3. In conventional vector control, the rotor flux is oriented along the d-axis of the rotor winding. However, the rotor variables are not easily accessible. So, in the SFOVC, the total flux is made to be oriented along the d-axis of the stator winding. SFOVC is advantageous as compared to conventional vector control because the stator variables are easily accessible and do not require any special arrangement for the measurement of variables which increases the robustness of the system. Here, two separate converters are used for the two stator windings of the machine and the converter switching is being controlled by a novel space vector based 11-zone hybrid pulse-width modulation (PWM). This special PWM results in better harmonic performance, reduced torque pulsation and minimal switching loss. The overall simulation is being performed in MATLAB Simulink environment and the simulated results are also being validated experimentally.

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“…The progress achieved in the domain of the power electronics permitted to construct some static converters at variable frequency. For high powers, the use of the synchronous machines associated multilevel inverters especially finds its application in the naval propulsion, electric traction and the renewable energy conversion [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control of Wind Energy Conversion System Using Dual Star Synchronous Machine and Three Level Converter

Berkani¹,

Negadi²,

Allaoui³

et al. 2019

IJES

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This paper investigates a dual star synchronous machine powered by two independent threelevel voltage source inverters integrated in a wind turbine system (Figure 1). The dual star synchronous machine is used in areas of high power industrial applications such as naval propulsion, traction systems and renewable energy. This use is motivated by several important advantages compared to classical three-phase machine. In this work, the machine side converters control the dq component current by a conventional method based PI regulator, and then the load side converters control the DC bus voltage using sliding mode approach and the RMS voltage load. The validity of the proposed control technique is verified by Matlab/Simulink. Simulation results presented in this paper confirm the validity and feasibility of the proposed control approach, and can be tested on experimental setup.

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A novel speed sensor-less vector control of Dual Stator Induction machine with space vector based advanced 9-zone hybrid PWM for grid connected wind energy generation system

Cited by 15 publications

References 39 publications

Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System

Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System

Stator flux‐oriented vector control of dual stator induction generator with time optimised 11‐zone hybrid PWM for grid connected wind energy generation system

Sliding Mode Control of Wind Energy Conversion System Using Dual Star Synchronous Machine and Three Level Converter

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