Application of the Artificial Neural Network (ANN) Method as MPPT Photovoltaic for DC Source Storage
(*) Corresponding author
This paper shows the details of the design of DC-DC Boost Converter as the Maximum Power Point Tracker (MPPT). This technique is used to optimize the potential of energy generated by photovoltaics. The changing of the duty cycle in the switching Boost Converter process will affect the amount of photovoltaic (PV) power output. Boost Converter is chosen because the output voltage of PV arrays is smaller than the DC source storage one. In this study, the Artificial Neural Network (ANN) algorithm has been applied as a method to search as Maximum Power Point (MPP). ANN learning data has been used to adjust the duty cycle of Boost Converter so that the Boost Converter output voltage and current change and the output power reaches MPP, which is the target data. The design results have been implemented using 3 pieces of PV, each one having 100WP of power. The experimental results show that the proposed method can optimize PV output power for DC source storage with an average power increase of 56.22% compared to PV output power without using MPPT control.
Copyright © 2019 Praise Worthy Prize - All rights reserved.
Attia, H., Artificial Neural Networks Based Maximum Power Point Tracking Photovoltaic System for Remote Park LED Lighting Applications, (2018) International Review on Modelling and Simulations (IREMOS), 11 (6), pp. 396-405.
Dib, K., Chenni, R., A Combined MPPT Algorithm for Photovoltaic Systems Based Arduino Microcontroller, (2018) International Journal on Energy Conversion (IRECON), 6 (2), pp. 66-75.
Sathish Kumar Kollimalla Mahesh Kumar Mishra, Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance, IEEE Transactions on Sustainable Energy, 2014.
Taohid Latif1, Syed R. Hussain, Design of a charge controller based on SEPIC and Buck topology using modified Incremental Conductance MPPT, 8th International Conference on Electrical and Computer Engineering, 2014.
Mohammadmehdi Seyedmahmoudian, Rasoul Rahmani, Saad Mekhilef, Amanullah Maung Than Oo, Alex Stojcevski, Tey Kok Soon, Alireza Safdari Ghandhari, Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method, IEEE Transactions on Sustainable Energy, 2015.
Suman Kumar Roy, Shoeb Hussain, Mohammad Abid Bazaz, Implementation of MPPT Technique for Solar PV System Using ANN, 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2017.
Nezha El Hichami, Ahmed Abbou, Saloua Marhraoui, Salaheddine Rhaili, Comparison Between Both Commands Photovoltaic MPPT of the System: Algorithm P&O and IncCond, using converter BOOST, 2017 International Conference on Engineering and Technology, 2017.
Sabir Messalti, Abd Ghani Harrag, Abd Elhamid Loukriz, A New Neural Networks MPPT controller for PV Systems, 6th International Renewable Energy Congress (IREC), 2015.
Rajeshree Patil, Harsha Anantwar, Comparative Analysis of Fuzzy Based MPPT for Buck and Boost Converter Topologies for PV Application, 2017 International Conference on Smart Technologies for Smart Nation (SmartTechCon), 2017.
Moirangthem Dennis Singh, Shine V J, Varaprasad Janamala, Application of Artificial Neural Networks in Optimizing MPPT Control for Standalone Solar PV System, 2014 International Conference on Contemporary Computing and Informatics (IC3I), 2014.
Daniel W. Hart, Power Electronics, 2011.
Motahhir, S., El Ghzizal, A., Sebti, S., Derouich, A., Shading Effect to Energy Withdrawn from the Photovoltaic Panel and Implementation of DMPPT Using C Language, (2016) International Review of Automatic Control (IREACO), 9 (2), pp. 88-94.
Ajdid, R., Ouassaid, M., Maaroufi, M., Modeling and Simulation of a Novel Photovoltaic Solar System, (2017) International Journal on Energy Conversion (IRECON), 5 (6), pp. 171-179.
Fri, A., El Bachtiri, R., El Ghzizal, A., Improved MPPT Algorithm for Controlling a PV System Grid Connected for Rapid Changes of Irradiance, (2016) International Review of Automatic Control (IREACO), 9 (1), pp. 11-20.
El Azzaoui, M., Mahmoudi, H., Boudaraia, K., Sensorless Fuzzy MPPT Technique of Solar PV and DFIG Based Wind Hybrid System, (2017) International Review on Modelling and Simulations (IREMOS), 10 (3), pp. 152-159.
Attia, H., A Stand-Alone Solar PV System with MPPT Based on Fuzzy Logic Control for Direct Current Portable House Applications, (2018) International Review on Modelling and Simulations (IREMOS), 11 (6), pp. 377-385.
Hwu, K., Yau, Y., Applying Improved Boost Converter and Simple Tracking Concept to Achieving MPPT under Shading Conditions, (2017) International Review of Electrical Engineering (IREE), 12 (3), pp. 195-203.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2023 Praise Worthy Prize