Paper Title

Maximum power point tracker using fuzzy logic controller for solar power traffic light

Authors

Rakshe Harsha Lahu , Sangale Bhagyashri Babasaheb , Sapkal Priyanka Balasaheb , Prof. Burungale V. D.

Keywords

Abstract

Photovoltaic has become one of the strongestcandidates as a secondary energy source. This is because the problem of fossil energy depletion becomes more severe. The term photovoltaic refers to the phenomenon involving the conversion of sunlight into electrical energy via a solar cell. Under certain temperature and light intensity, there is only single maximum-power point (MPP) in a normal cell. Therefore, maximum power point tracking (MPPT) of the solar cell is essential as far as the system efficiency is concerned. Recently, various MPPT techniques have been implemented on a microcontroller unit (MCU) in several solar-powered applications. For example, a RISC microcontroller was employed to realize MPPT using a Perturbation and Observation Method (P&O) method for abattery charging application. For a transportation industry, one of sectors that gain benefits from such a system, a solar-powered light-flasher (SPLF) isdeveloped. Besides, a hill-climbing algorithm, which is similar to P&O method, is also implemented on RISC microcontroller for an illumination application. The sophisticated Artificial Intelligent (Al) methods, such as Artificial Neural Network (ANN)and Fuzzy Logic Control (FLC), have been developed for solar-powered applications. For FLC, an inference engine is time-consuming. Thus, the relation between input and output of FLC can be stored in a memory-limited lookup table (LUT). The implementations of FLC stored in LUT for MPPT have been successfully implemented for a solar power battery charger (SPBC) and an SPLF, respectively. Comparatively, the conventional MPPT methods can give poorer performances, but implementation is alwayseasier. Al methods, on the other hand, perform better, but their structure is generally more complicated and requiresrelatively high performance processor. Therefore, Al isnot suitable for some applications where cost is a prime concern. Furthermore, they still lacks of the adaptability required for MPPT controller to efficiently deal with time-varying environments. An alternative to overcome the problem of adaptability is a Self-Organizing Fuzzy Logic Controller (SOFLC) originally proposed byProcyk and Mamdani. By self-organizing, it is meant that the controller can recursively adjust its associated fuzzy rule in accordance with a desired response. Besides, the technique is simple and can be efficiently realized by Look-Up Table (LUT), offering a cost-effective solution to hardware implementation., the authors introduced an application of SOFLC for MPPT in a solar-powered battery charging system Nonetheless, the applications a standalone of solar-powered system has been not investigated. In this paper, the implementation of the Self-Organizing Fuzzy Logic Controller for a Solar-powered Traffic Light Equipment (SOFLC-SPTLE) with built-in MPPT is presented. A low-cost PIC16F876A RISC MCU is employed for the algorithm processing, and it is integrated to a boost converter to form a solar powered battery charging system. There is no external sensory unit required for the system.

How To Cite

"Maximum power point tracker using fuzzy logic controller for solar power traffic light", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 5, page no.460 - 480, May-2017, Available :https://ijsdr.org/papers/IJSDR1705083.pdf

Issue

Volume 2 Issue 5, May-2017

Pages : 460 - 480

Other Publication Details

Paper Reg. ID: IJSDR_170455

Published Paper Id: IJSDR1705083

Downloads: 000347047

Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1705083

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1705083

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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