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Abstract
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Article Information:
Adaptive Critic Based Neuro-Fuzzy Tracker for Improving Conversion Efficiency in PV Solar Cells
Halimeh Rashidi, Saeed Niazi and Jamshid Khorshidi
Corresponding Author: Halimeh Rashidi
Submitted: December 06, 2011
Accepted: January 04, 2012
Published: August 01, 2012 |
Abstract:
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The output power of photovoltaic systems is directly related to the amount of solar energy collected
by the system and it is therefore necessary to track the sun’s position with high accuracy. This study proposes
multi-agent adaptive critic based nero fuzzy solar tracking system dedicated to PV panels. The proposed tracker
ensures the optimal conversion of solar energy into electricity by properly adjusting the PV panels according
to the position of the sun. To evaluate the usefulness of the proposed method, some computer simulations are
performed and compared with fuzzy PD controller. Obtained results show the proposed control strategy is very
robust, flexible and could be used to get the desired performance levels. The response time is also very fast.
Simulation results that have been compared with fuzzy PD controller show that our method has the better
control performance than fuzzy PD controller.
Key words: Agent critic, fuzzy logic, neural network, PMDC motor, PV solar cell, solar tracker system,
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Cite this Reference:
Halimeh Rashidi, Saeed Niazi and Jamshid Khorshidi, . Adaptive Critic Based Neuro-Fuzzy Tracker for Improving Conversion Efficiency in PV Solar Cells. Research Journal of Applied Sciences, Engineering and Technology, (15): 2316-2322.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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