Research and Experimental Implementation of a CV-FOINC Algorithm Using MPPT for PV Power System

This research suggests maximum power point tracking (MPPT) for the solar photovoltaic (PV) power scheme using a new constant voltage (CV) fractional order incremental conductance (FOINC) algorithm. The PV panel has low transformation efficiency and power output of PV panel depends on the change in weather conditions. Possible extracting power can be raised to a battery load utilizing a MPPT algorithm. Among all the MPPT strategies, the incremental conductance (INC) algorithm is mostly employed due to easy implementation, less fluctuations and faster tracking, which is not only has the merits of INC, fractional order can deliver a dynamic mathematical modelling to define non-linear physiognomies. CV-FOINC variation as dynamic variable is exploited to regulate the PV power toward the peak operating point. For a lesser scale photovoltaic conversion scheme, the suggested technique is validated by simulation with dissimilar operating conditions. Contributions are made in numerous aspects of the entire system, including new control algorithm design, system simulation, converter design, programming into simulation environment and experimental setup. The results confirm that the small tracking period and practicality in tracking of photovoltaic array.

[1]  Suttichai Premrudeepreechacharn,et al.  Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system , 2005 .

[2]  Jensak Eakburanawat,et al.  Development of a thermoelectric battery-charger with microcontroller-based maximum power point tracking technique , 2006 .

[3]  Chengbin Ma,et al.  Fractional-order control: Theory and applications in motion control [Past and present] , 2007, IEEE Industrial Electronics Magazine.

[4]  Yiannis S. Boutalis,et al.  A novel maximum power point tracking method for PV systems using fuzzy cognitive networks (FCN) , 2007 .

[5]  Mamadou Lamine Doumbia,et al.  An improved maximum power point tracking method for photovoltaic systems , 2008 .

[6]  Jian-Liung Chen,et al.  Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method , 2011 .

[7]  A. Messai,et al.  FPGA-based real time implementation of MPPT-controller for photovoltaic systems , 2011 .

[8]  Rached Dhaouadi,et al.  Efficiency Optimization of a DSP-Based Standalone PV System Using Fuzzy Logic and Dual-MPPT Control , 2012, IEEE Transactions on Industrial Informatics.

[9]  Ahmed M. Kassem,et al.  MPPT control design and performance improvements of a PV generator powered DC motor-pump system based on artificial neural networks , 2012 .

[10]  Xiao Lu,et al.  Matlab/Simulink-Based Research on Maximum Power Point Tracking of Photovoltaic Generation , 2012 .

[11]  Mohammed A. Hannan,et al.  Intelligent maximum power point tracking for PV system using Hopfield neural network optimized fuzzy logic controller , 2012 .

[12]  Muhammad Amjad,et al.  A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm , 2012 .

[13]  Sharifah Saon,et al.  Development of Optimum Controller based on MPPT for Photovoltaic System during Shading Condition , 2013 .

[14]  Ming-Tsung Tsai,et al.  Maximum power point tracking on stand-alone solar power system: Three-point-weighting method incorporating mid-point tracking , 2013 .

[15]  Seyed Mohammad Sadeghzadeh,et al.  A high performance maximum power point tracker for PV systems , 2013 .

[16]  Ebrahim Babaei,et al.  Mathematical modeling of buck–boost dc–dc converter and investigation of converter elements on transient and steady state responses , 2013 .

[17]  R. Arulmurugan,et al.  Improved Fractional Order VSS Inc-Cond MPPT Algorithm for Photovoltaic Scheme , 2014 .

[18]  Tamil Nadu India,et al.  Performance Calculation of Electrical Energy Output and Power Conversion Efficiency of Standalone PV System , 2014 .

[19]  R. Arulmurugan,et al.  Model and design of a fuzzy-based Hopfield NN tracking controller for standalone PV applications , 2015 .