Switching Angles Optimization of Single Phase PWM DC-AC Inverter by Particle Swarm Optimizations
Takuya Shindo and Kenya Jin’no
Nippon Institute of Technology, 4-1 Gakuendai, Miyashiro-machi, Minamisaitama-gun, Saitama 345-8501, Japan
We consider the design procedure for a single-phase PWM DC-AC inverter using a particle swarm optimization algorithm. The switching operation is the most important component of the single-phase PWM DC-AC inverter. The PSO algorithm optimizes the switching angle effectively. The design procedure of the switching angle evaluates total harmonic distortion and the effective value of output. The proposed evaluation function restricts the scope to evaluating harmonic components. Based on numerical simulation results, we confirmed that the performance of the proposed design procedure was improved compared to the conventional sinusoidal PWM procedure. We develop an implementation circuit for our PWM DCAC inverter. By using the implemented circuit, we confirmed that results for implementation circuits are consistent with results for numerical simulations, indicating that the proposed algorithm exhibits better performance than the conventional sinusoidal PWM DC-AC inverter.
-  M. Azab, “Particle swarm optimization-based solutions for selective harmonic elimination in single-phase PWMinverters,” Int. J. of Power Electronics, Vol.2, No.2, pp. 125-142, 2010.
-  R. Sano, T. Shindo, K. Jin’no, and T. Saito, “PSO-based Multiple Optima Search Systems with Switched Topology,” in IEEE Congress on Evolutionary Computation (CEC), pp. 3301-3307, 2012.
-  T. Shindo and K. Jin’no, “Switching Angles Optimization of Single Phase PWMDC-AC Inverter by Particle Swarm Optimizations,” in Joint 6th Int. Conf. on Soft Computing and Intelligent Systems (SCIS) and 13th Int. Symposium on Advanced Intelligent Systems (ISIS), pp. 65-70, 2012.
-  K. Morita, T. Kurihara, T. Shindou, and K. Jin’no, “Design Procedure of Single Phase PWM DC-AC Inverter by Divided Optimization Algorithm,” in IEEE 10th Int. Conf. on Power Electronics and Drive Systems (PEDS), pp. 569-574, 2013.
-  S. Tzay-Farn, “Particle Swarm Optimization Algorithm for Energy-Efficient Cluster-Based Sensor Networks,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.89, No.7, pp. 1950-1958, 2006.
-  S. Barkat, E. Berkouk, andM. Boucherit, “Particle swarm optimization for harmonic elimination in multilevel inverters,” Electrical Engineering, Vol.91, No.4-5, pp. 221-228, 2009.
-  J. Kennedy and R. Eberhart, “Particle Swarm Optimization,” in IEEE Int. Conf. on Neural Networks, Vol.4, pp. 1942-1948, 1995.
-  J. Kennedy, “The particle swarm: Social adaptation of knowledge,” in IEEE Int. Conf. on Evolutionary Computation, pp. 303-308, 1997.
-  M. Clerc and J. Kennedy, “The Particle Swarm-Explosion, Stability, and Convergence in aMultidimensional Complex Space,” IEEE Trans. on Evolutionary Computation, Vol.6, No.1, pp. 58-73, 2002.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.