CÁLCULO DE LOS ÁNGULOS ÓPTIMOS DE CONMUTACIÓN PARA UN INVERSOR MULTINIVEL UTILIZANDO EVOLUCIÓN DIFERENCIAL (CALCULATION OF OPTIMAL SWITCHING ANGLES FOR A MULTILEVEL INVERTER USING DIFFERENTIAL EVOLUTION)

Oscar Sánchez Vargas, Susana Estefany De León Aldaco, Jesús Aguayo Alquicira, Eligio Flores Rodríguez, Ricardo Eliú Lozoya Ponce

Resumen


Resumen
Actualmente en varios trabajos de investigación se han utilizado los métodos metaheurísticos para minimizar de forma efectiva la distorsión armónica total (THD, Total Harmonic Distortion) en inversores multinivel, ya que estos proporcionan tiempo de cálculo y resultados efectivos. Dentro de estos métodos la evolución diferencial ha sido el algoritmo que en recientes años se ha implementado para la reducción de la THD.
Este trabajo presenta el algoritmo de Evolución Diferencial (ED) para encontrar los ángulos de conmutación óptimos en un inversor multinivel en cascada de siete niveles para eliminar los armónicos de orden inferior. Los armónicos impares de orden inferior no pueden eliminarse fácilmente, ya que contienen ecuaciones no lineales trascendentales, resultantes de la serie de Fourier. Las soluciones a estas ecuaciones son complicadas y requieren mucho tiempo. También este trabajo se centra en la búsqueda de los parámetros iniciales del algoritmo de Evolución Diferencial para observar cual combinación se desempeña mejor, tanto en rapidez como fiabilidad para encontrar una THD mínima casi óptima.
Además, realizó una simulación de un inversor multinivel en cascada de siete niveles con carga RL en Simulink para validar los resultados, además de realizar diferentes iteraciones variando los parámetros para así verificar cuál de estos proporciona una mejor búsqueda de los ángulos de conmutación, además de brindar una discusión de los resultados obtenidos.
Palabras Clave: Evolución Diferencial, Inversor Multinivel, Métodos metaheurísticos, Reducción de THD.

Abstract
In different research papers, metaheuristic methods have been used to effectively minimize the Total Harmonic Distortion (THD) in multilevel inverters, since they provide calculation time and effective results. Among these methods, differential evolution has been the algorithm that has been implemented in recent years for THD reduction.
This paper presents the Differential Evolution (DE) algorithm to find the optimal switching angles in a seven-level cascaded multilevel inverter to eliminate the lower order harmonics. The lower-order odd harmonics cannot be easily eliminated, as they contain transcendental non-linear equations, resulting from the Fourier series. The solutions to these equations are complicated and time consuming. Also, this work focuses on finding the initial parameters of the Differential Evolution algorithm to observe which combination performs best, both in speed and reliability to find a near-optimal minimum THD.
It also performed a simulation of a seven-level cascaded multilevel inverter with RL load in Simulink to validate the results, in addition to performing different iterations varying the parameters to verify which of these provides a better search of the switching angles, in addition to providing a discussion of the results obtained.
Keywords: Differential Evolution, Metaheuristic Methods, Multilevel Inverter, THD Reduction.

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Referencias


AMJAD, A. M., SALAM, Z. & SAIF, A. M. A. 2015. Application of differential evolution for cascaded multilevel VSI with harmonics elimination PWM switching. International Journal of Electrical Power & Energy Systems, 64, 447-456.

BILAL, PANT, M., ZAHEER, H., GARCIA-HERNANDEZ, L. & ABRAHAM, A. 2020. Differential Evolution: A review of more than two decades of research. Engineering Applications of Artificial Intelligence, 90.

BLUM, C., ROLI, A. & ALBA, E. 2005. An Introduction to Metaheuristic Techniques. In: ZOMAYA, A. Y. (ed.) Parallel Metaheuristics A New Class of Algorithms A JOHN WILEY & SONS, INC., PUBLICATION.

CASTILLO, E. J. 2019. Esquema Adaptativo para el Manejo de Restricciones de Límite en Problemas de Optimización Numérica Restringida. Doctorado, Universidad Veracruzana.

DE-LEÓN, S., CALLEJA, H. & AGUAYO, J. 2015. Metaheuristic Optimization Methods Applied to Power Converters: A Review. IEEE Transactions on Power Electronics, 30, 6791-6803.

GUTIÉRREZ, D., LÓPEZ, J. M. & VILLA, W. M. 2016. Metaheuristic Techniques Applied to the Optimal Reactive Power Dispatch: A Review. IEEE LATIN AMERICA TRANSACTIONS.

HAMZAH, H. H., PONNIRAN, A., KASIRAN, A. N., HARIMON, M. A., GENDUM, D. A. & YATIM, M. H. 2018. A Single Phase 7-Level Cascade Inverter Topology with Reduced Number of Switches on Resistive Load by Using PWM. Journal of Physics: Conference Series, 995.

JUÁREZ-CASTILLO, E., PÉREZ-CASTRO, N. & MEZURA-MONTES, E. 2017. An Improved Centroid-Based Boundary Constraint-Handling Method in Differential Evolution for Constrained Optimization. International Journal of Pattern Recognition and Artificial Intelligence, 31.

KABALCı, E. 2021. Multilevel Inverters Introduction and Emergent Topologies. In: KABALCı, E. (ed.) Multilevel Inverters.

MALIK, H., IQBAL, A., JOSHI, P., ·, S. A. & BAKHSH, F. I. 2021. Metaheuristic and Evolutionary Computation: Algorithms and Applications.

MAJED, A., SALAM, Z. & AMJAD, A. M. 2017. Harmonics elimination PWM based direct control for 23-level multilevel distribution STATCOM using differential evolution algorithm.Electric Power Systems Research, 152, 48-60

MEDINA, I. R. 2014. Algoritmos bioinspirados: Una revisión según sus fundamentos biológicos., University of Manchester.

MEZURA-MONTES, E., MIRANDA-VARELA, M. E. & DEL CARMEN GÓMEZ-RAMÓN, R. 2010. Differential evolution in constrained numerical optimization: An empirical study. Information Sciences, 180, 4223-4262.

MONTES, E. M. 2006. Paradigmas emergentes en algoritmos bio-inspirados. In: ALFAOMEGA (ed.) Inteligencia Aritificial. Alfaomega.

NAIDU, P. A. & SINGH, V. 2018. Speed control of induction motor and control of multilevel inverter output with optimal PI controller using DE and GSA optimization technique 3rd International Conference on Communication and Electronics Systems (ICCES)

PATIL, S. D. & KADWANE, S. G. 2017. Application of Optimization Technique in SHE Controlled Multilevel Inverter. International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS-2017).

PRICE, K., STORN, R. & LAMPINEN, J. 2005. Differential Evolution A practical Approach to Global Optimization, Alemania.

RONKKONEN, J., KUKKONEN, S. & PRICE, K. V. 2005. Real-Parameter Optimization with Differential Evolution. 2005 IEEE Congress on Evolutionary Computation. Edinburgh, UK.

SÁNCHEZ-VARGAS, O., DE LEÓN-ALDACO, S. E., AGUAYO-ALQUICIRA, J. & LÓPEZ-NÚÑEZ, A. R. 2021. Evolutionary Metaheuristic Methods Applied to Minimize the THD in Inverters: A Systematic Review. European Journal of Electrical Engineering, 23, 237-245.

SALAM, Z., AMJAD, A. M. & MAJED, A. 2013. Using Differential Evolution to Solve the Harmonic Elimination Pulse Width Modulation for Five Level Cascaded Multilevel Voltage Source Inverter. 2013 1st International Conference on Artificial Intelligence, Modelling and Simulation. Kota Kinabalu, Malaysia.

SALAM, Z., MAJED, A. & AMJAD, A. M. 2015. Design and implementation of 15-level cascaded multi-level voltage source inverter with harmonics elimination pulse-width modulation using differential evolution method. IET Power Electronics, 8, 1740-1748.

STONIER, A. A., CHINNARAJ, G., KANNAN, R. & MANI, G. 2020. Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applications. Circuit World, ahead-of-print.

WEI, S., WU, B., LI, F. & SUN, X. 2003. Control Method for Cascaded H-Bridge Multilevel Inverter with Faulty Power Cells. Eighteenth Annual IEEE Applied Power Electronics Conference and Exposition, 2003. Miami Beach, FL, USA.

ZHANG, J. & SANDERSON, A. C. 2009. Adaptive Differential Evolution A Robust Approach to Mutimodal Problem Optimization.






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