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Elimination of Low Order Harmonics in Multilevel Inverters Using Genetic Algorithm
Salehi, Reza,Farokhnia, Naeem,Abedi, Mehrdad,Fathi, Seyed Hamid The Korean Institute of Power Electronics 2011 JOURNAL OF POWER ELECTRONICS Vol.11 No.2
The selective harmonic elimination pulse width modulation (SHEPWM) switching strategy has been applied to multilevel inverters to remove low harmonics. Naturally, the related equations do not have feasible solutions for some operating points associated with the modulation index (M). However, with these infeasible points, minimizing instead of eliminating harmonics is performed. Thus, harmful harmonics such as the $5^{th}$ harmonic still remains in the output waveform. Therefore, it is proposed in this paper to ignore solving the equation associated with the highest order harmonics. A reduction in the eliminated harmonics results in an increase in the degrees of freedom. As a result, the lower order harmonics are eliminated in more operating points. A 9-level inverter is chosen as a case study. The genetic algorithm (GA) for optimization purposes is used. Simulation results verify the proposed method.
Salehi, Reza,Vahidi, Behrooz,Farokhnia, Naeem,Abedi, Mehrdad The Korean Institute of Electrical Engineers 2010 Journal of Electrical Engineering & Technology Vol.5 No.4
A new family of DC to AC converters, referred to as multilevel inverter, has received much attention from industries and researchers for its high power and voltage applications. One of the conventional techniques for implementing the switching algorithm in these inverters is optimized harmonic stepped waveform (OHSW). However, the major problem in using this technique is eliminating low order harmonics by solving the nonlinear and complex equations. In this paper, a new approach called the "bacterial foraging algorithm" (BFA) is employed. This algorithm eliminates and optimizes the harmonics in a multilevel inverter. This method has higher speed, precision, and convergence power compared with the genetic algorithm (GA), a famous evolutionary algorithm. The proposed technique can be expanded in any number of levels. The purpose of optimization is to remove some low order harmonics, as well as to ensure the fundamental harmonic retained at the desired value. As a case study, a 13-level inverter is chosen. The comparison results by MATLAB software between the two optimization methods (BFA and GA) have shown the effectiveness and superiority of BFA over GA where convergence is desired to achieve global optimum.
Elimination of Low Order Harmonics in Multilevel Inverters Using Genetic Algorithm
Reza Salehi,Naeem Farokhnia,Mehrdad Abedi,Seyed Hamid Fathi 전력전자학회 2011 JOURNAL OF POWER ELECTRONICS Vol.11 No.2
The selective harmonic elimination pulse width modulation (SHEPWM) switching strategy has been applied to multilevel inverters to remove low order harmonics. Naturally, the related equations do not have feasible solutions for some operating points associated with the modulation index (M). However, with these infeasible points, minimizing instead of eliminating harmonics is performed. Thus, harmful harmonics such as the 5<SUP>th</SUP> harmonic still remains in the output waveform. Therefore, it is proposed in this paper to ignore solving the equation associated with the highest order harmonics. A reduction in the eliminated harmonics results in an increase in the degrees of freedom. As a result, the lower order harmonics are eliminated in more operating points. A 9-level inverter is chosen as a case study. The genetic algorithm (GA) for optimization purposes is used. Simulation results verify the proposed method.
Reza-Salehi,Behrooz-Vahidi,Naeem-Farokhnia,Mehrdad-Abedi 대한전기학회 2010 Journal of Electrical Engineering & Technology Vol.5 No.4
A new family of DC to AC converters, referred to as multilevel inverter, has received much attention from industries and researchers for its high power and voltage applications. One of the conventional techniques for implementing the switching algorithm in these inverters is optimized harmonic stepped waveform (OHSW). However, the major problem in using this technique is eliminating low order harmonics by solving the nonlinear and complex equations. In this paper, a new approach called the "bacterial foraging algorithm" (BFA) is employed. This algorithm eliminates and optimizes the harmonics in a multilevel inverter. This method has higher speed, precision, and convergence power compared with the genetic algorithm (GA), a famous evolutionary algorithm. The proposed technique can be expanded in any number of levels. The purpose of optimization is to remove some low order harmonics, as well as to ensure the fundamental harmonic retained at the desired value. As a case study, a 13-level inverter is chosen. The comparison results by MATLAB software between the two optimization methods (BFA and GA) have shown the effectiveness and superiority of BFA over GA where convergence is desired to achieve global optimum.