An improved power conditioning system for grid integration of solar power using ANFIS based FOPID controller
Power loss become common while integrating with common grid and in specific when power produced through Solar. This is the very lacking area which this proposal implements an Adaptive Neuro Fuzzy Inference System (ANFIS) based controller of Fractional Order Proportional Integral Derivative (FOPID) u...
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Published in | Microprocessors and microsystems Vol. 74; p. 103030 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier B.V
01.04.2020
Elsevier BV |
Subjects | |
Online Access | Get full text |
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Summary: | Power loss become common while integrating with common grid and in specific when power produced through Solar. This is the very lacking area which this proposal implements an Adaptive Neuro Fuzzy Inference System (ANFIS) based controller of Fractional Order Proportional Integral Derivative (FOPID) used for Tracking of Maximum PP of Grid Integrated Solar Power Conditioning System. The proposed work advances with different ambient light conditions for maximum power point traction. In this work a clear-cut Photo Voltaic (PV Cell) model has been developed and an intensive and operative training data have been extracted from the developed controller. This produced dataset have been the feeder input for the ANFIS structure in turn to locate the Tracking of Maximum PP (MPPT). Traction of MPPT is done, the FOPID controller is enforced by matching the voltage from the array of Photo Voltaic cell with attained or reference voltage produced by the ANFIS structure. In the meantime driving this PV array, DC to DC converter's duty cycle is controlled for producing maximum power from the structure. The duty cycle in FOPID controller is generated through calculating the error within the reference voltage and PV voltage. Those values are then simulated through Math Lab and the Simulation results show that this proposed work efficiency is better than the regularly employed controllers in the solar power production and conditioning system |
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ISSN: | 0141-9331 1872-9436 |
DOI: | 10.1016/j.micpro.2020.103030 |