An improved hybrid PV‐wind power system with MPPT for water pumping applications. (6th November 2019)

• Record Type: Journal Article
• Authors: Priyadarshi, Neeraj; Padmanaban, Sanjeevikumar; Bhaskar, Mahajan Sagar; Blaabjerg, Frede; Holm‐Nielsen, Jens Bo
• Is Part Of: International transactions on electrical energy systems. Volume 30:Number 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-11-06
• Subjects: artificial bee colony -- CUK converter -- inverter -- maximum power point tracking -- particle swarm optimization -- photovoltaic -- space vector pulse‐width modulation -- wind; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.12210
• Languages: English
• ISSNs: 2050-7038

Abstract

SUMMARY: This work articulates the hybrid photovoltaic‐wind power system development for water pump applications. The proposed control scheme is based on modified Artificial Bee Colony (ABC)‐based on Maximum Power Point Tracking (MPPT) algorithm.. On power circuit part, the single CUK converter‐fed induction motor driven a centrifugal pump and has been employed, which improves the system overall performance. The proposed MPPT control provides the smooth propagation of the motor operation as well as forces the photovoltaic system to operate always in maximum power point (MPP) region. Further, the modified ABC algorithm strengthens searching competency and has been employed for the achievement of local optimal maximum power point (MPP) under partial shade conditions with high accuracy and zero oscillation around MPP region when compared with other optimized algorithms. Particle swarm optimization‐space vector pulse‐width modulation (PSO‐SVPWM) was adapted for the inverter; control with standard v/f control is implemented in this work for better speed regulation and reduction in total harmonic distortion. Moreover, the power balance of the integrated hybrid system to the DC bus has been discussed with practicality. This article also explains the comparison of different MPPT algorithms and includes PSO, ant colony optimization, firefly algorithm, and ABC under fast‐changing environmental conditions. In the case of classical ABC method, only one scout bee is responsible to achieve the local maximum. The proposed modified ABC has been used to improve searching capacity, with the addition of scout bees. Experimental results are presented and reveal that the modified ABC algorithm performs 7.5 times faster than the standard PSO technique. Prototype model in hardware setup is developed with MATLAB/Simulink interfaced with dSPACE DS 1104.