Enhancing the Output Characteristics of a Photovoltaic Position Sensor Using a Feed-Forward Neural Network

Abstract:

Tracking solar-power devices often employ photovoltaic position sensors to detect the angle of misalignment between the axis of mounted solar panels and that of sunlight. The nonlinear input-output characteristics of this type of sensors tend to complicate controller design in such systems. This paper presents a nonlinear mathematical model of the photovoltaic position sensor. A three-layer feedforward neural network was trained to linearise the characteristics of the sensor. The MATLAB neural network tool (nntool) was used for neural network training. A final error of was obtained after training. Simulation of the neural network showed that linear sensor characteristics could be reproduced throughout the domain of sensor operation.

• Periodical: Advanced Materials Research (Volumes 62-64)
• Pages: 506-511
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.62-64.506
• Online since: February 2009
• Authors: John T. Agee, S. Masupe, M. Jeffrey, Adisa A. Jimoh
• Keywords: Feedforward Neural Network, Nonlinear Characteristic, Photovoltaic Sensor, Solar Tracker

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