GA-Optimized Fuzzy-Based MPPT Technique for Abruptly Varying Environmental Conditions
| Autor: | T. P. Imthias Ahamed, S. Sheik Mohammed, D. Devaraj |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Adaptive neuro fuzzy inference system
General Computer Science Neuro-fuzzy Computer science 020209 energy 020208 electrical & electronic engineering Photovoltaic system 02 engineering and technology Fuzzy logic Maximum power point tracking System model Control theory Genetic algorithm 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering MATLAB computer computer.programming_language |
| Zdroj: | Journal of The Institution of Engineers (India): Series B. 102:497-508 |
| ISSN: | 2250-2114 2250-2106 |
| Popis: | This paper presents and discusses the Fuzzy-based MPPT technique optimized using the Genetic Algorithm (GA). The proposed GA simultaneously produces optimized ranges of both membership functions and the rule base of fuzzy. MATLAB coded GA to optimize the Fuzzy Logic Controller (FLC) is integrated with the Simulink model of the Photovoltaic (PV) system and training is performed online by operating the PV system for different conditions. GA provides the optimized membership functions and rule base of FLC upon completion of training. FLC is developed using the optimized values obtained from the training. The SPV system model with the GA-optimized fuzzy MPPT is built and simulation is performed. For a more realistic study, analysis of PV system under abruptly varying weather conditions is carried out using real-time data of a particular day on which the changes are very frequent. Besides, simulation of solar PV system is carried out with fuzzy MPPT and Artificial Neuro Fuzzy Inference System (ANFIS) MPPT for similar cases, the results are presented and discussed. The results show that the GA-optimized FLC-based MPP tracking method has better performance with improved tracking accuracy and faster response under all weather conditions. |
| Databáze: | OpenAIRE |
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