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Abstract
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Article Information:
Simulation and Experimental Verification of Intelligence MPPT Algorithms for Standalone Photovoltaic Systems
M. Muthuramalingam and P.S. Manoharan
Corresponding Author: M. Muthuramalingam
Submitted: July 14, 2014
Accepted: September 13, 2014
Published: October 10, 2014 |
Abstract:
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This study presents compared with Fuzzy Logic Control (FLC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) Maximum Power Point Tracking (MPPT) algorithms, in terms of parameters like tracking speed, power extraction, efficiency and harmonic analysis under various irradiation and cell temperature conditions of Photovoltaic (PV) system. The performance of a PV array are affected by temperature and solar irradiation, In fact, in this system, the experimental implementation and the MATLAB based simulations are In this topology, each Cascaded H-Bridge Inverter (CHBI) unit is connected to PV module through an Interleaved Soft Switching Boost Converter (ISSBC). It also offers another advantage such as lower ripple current and switching loss compared to the conventional boost converter. The results are evaluated by simulation and experimental implemented on a 150 W PV panel prototype with the microcontroller platform. The simulation and hardware results show that ANFIS algorithm is more efficient than the FLC algorithm.
Key words: Cascade H-Bridge Inverter (CHBI), Interleaved Soft Switching Boost inverter (ISSBC), Maximum Power Point Tracking (MPPT), microcontroller, Photovoltaic (PV) system, ,
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Cite this Reference:
M. Muthuramalingam and P.S. Manoharan, . Simulation and Experimental Verification of Intelligence MPPT Algorithms for Standalone Photovoltaic Systems. Research Journal of Applied Sciences, Engineering and Technology, (14): 1695-1704.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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