PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load. Issue 2 (February 2017)

• Record Type: Journal Article
• Authors: Oshaba, A.; Ali, E.; Abd Elazim, S.
• Is Part Of: Neural computing & applications. Volume 28:Issue 2(2017)
• Page Start: 353
• Page End: 364
• Publication Date: 2017-02
• Subjects: Photovoltaic system -- Optimization algorithm -- Maximum power point tracking -- PI controller -- DC series motor pump system; Neural networks (Computer science) -- Periodicals; Neural circuitry -- Periodicals; Artificial intelligence -- Periodicals; Neural Networks (Computer) -- Periodicals; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux nerveux -- Périodiques; Intelligence artificielle -- Périodiques; 006.32
• DOI: 10.1007/s00521-015-2067-9
• Languages: English
• ISSNs: 0941-0643

Abstract

Abstract Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to maximize its output power. A new MPPT system has been suggested for PV–DC motor pump system by designing two PI controllers. The first one is used to reach MPPT by monitoring the voltage and current of the PV array and adjusting the duty cycle of the DC/DC converter. The second PI controller is designed for speed control of DC series motor by setting the voltage fed to the DC series motor through another DC/DC converter. The suggested design problem of MPPT and speed controller is formulated as an optimization task which is solved by artificial bee colony (ABC) to search for optimal parameters of PI controllers. Simulation results have shown the validity of the developed technique in delivering MPPT to DC series motor pump system under atmospheric conditions and tracking the reference speed of motor. Moreover, the performance of the ABC algorithm is compared with genetic algorithm for various disturbances to prove its robustness.