A MPPT algorithm for the wind power harvesting using the matrix converter

2017 ◽  
Author(s):  
Asit Kumar Mondal ◽  
Satyajit Saha ◽  
T. Halder
Keyword(s):  
Wind Power ◽  
Matrix Converter ◽  
Power Harvesting ◽  
The Matrix

scholarly journals Modelling and analysis of a NTVV-SVM based three-level twin-step matrix converter

2018 ◽  
Vol 7 (4) ◽  
pp. 2672
Author(s):  
Shamsher Ansari ◽  
Aseem Chandel ◽  
SMIEEE . ◽  
Zulfiqar Ali Sheikh
Keyword(s):  
High Power ◽  
Theoretical Study ◽  
Matrix Converter ◽  
Matrix Converters ◽  
Output Performance ◽  
The Matrix ◽  
Power Switches ◽  
Converter Topology ◽  
Vector Modulation ◽  
Ac Converters

Recently the tremendous advancement has been seen in the field of matrix converter topology. For high power drive applications, industries often need high power AC-AC converters like three level matrix converter because it is having the ability to generate a set of balanced sine waves for inputs as well as outputs. The three level matrix converters possess better output performance with reduced harmonic contents compared to all two-stage indirect matrix converters. In this matrix converter topology, the idea of neutral-point clamped-VSI is employed to the inversion step of the matrix converter circuitry. To control the power switches the gate signals are produced using NTVV based space vector modulation. To justify the theoretical study a complete model of a three-level twin-step matrix converter has been designed in Matlab/Simulink and its performances are analysed.  

A computationally efficient torque and flux ripple reduction by active vector optimization approach using direct torque control–based model predictive torque control for matrix converter–fed permanent magnet synchronous motor

2022 ◽  
pp. 014233122110688
Author(s):  
JD Anunciya ◽  
Arumugam Sivaprakasam
Keyword(s):  
Permanent Magnet ◽  
Real Time ◽  
Permanent Magnet Synchronous Motor ◽  
Direct Torque Control ◽  
Synchronous Motor ◽  
Matrix Converter ◽  
Torque Control ◽  
Optimization Approach ◽  
The Real ◽  
The Matrix

The Matrix Converter–fed Finite Control Set–Model Predictive Control is an efficient drive control approach that exhibits numerous advantageous features. However, it is computationally expensive as it employs all the available matrix converter voltage vectors for the prediction and estimation. The computational complexity increases further with respect to the inclusion of additional control objectives in the cost function which degrades the potentiality of this technique. This paper proposes two computationally effective switching tables for simplifying the calculation process and optimizing the matrix converter active prediction vectors. Here, three prediction active vectors are selected out of 18 vectors by considering the torque and flux errors of the permanent magnet synchronous motor. In addition, the voltage vector location segments are modified into 12 sectors to boost the torque dynamic control. The performance superiority of the proposed concept is analyzed using the MATLAB/Simulink software and the real-time validation is conducted by implementing in the real-time OPAL-RT lab setup.

Static Synchronous Compensator based on the Matrix Converter

2019 ◽  
Author(s):  
L. Ramon Merchan-Villalba ◽  
Jose M. Lozano-Garcia ◽  
Alejandro Pizano-Martinez ◽  
Xiomara Gonzalez-Ramirez ◽  
Hector J. Estrada-Garcia ◽  
...  
Keyword(s):  
Matrix Converter ◽  
Static Synchronous Compensator ◽  
The Matrix

scholarly journals Reduction of Prediction Errors for the Matrix Converter with an Improved Model Predictive Control

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 3029 ◽  
Author(s):  
Shuang Feng ◽  
Chaofan Wei ◽  
Jiaxing Lei
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Prediction Models ◽  
Sampling Period ◽  
Continuous Model ◽  
Matrix Converter ◽  
Prediction Errors ◽  
Current Harmonics ◽  
The Matrix ◽  
Improved Model

In this paper, an improved model predictive control (MPC) is proposed for the matrix converter (MC). First, the conventional MPC which adopts the separately discretized prediction models is discussed. It shows that the conventional MPC ignores the input–output interaction in every sampling period. Consequently, additional prediction errors arise, resulting in more current harmonics. Second, the principle of the improved MPC is presented. With the interaction considered, the integral state-space equation of the whole MC system is constructed and discretized to obtain the precise model. The eigenvalue analysis shows that the proposed prediction model has the same eigenvalues with the continuous model, and thus is more accurate than the conventional one to describe the MC’s behavior in every sampling period. Finally, experimental results under various working conditions prove that the proposed approach can always increase the control accuracy and reduce the harmonic distortions, which in turn requires smaller filter components.

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