Photovoltaic Power Smoothing Predication Algorithm

Jayden Hasemann

Abstract


Power output from PV arrays is vulnerable to shadows caused by trees and buildings, but most commonly clouds. It is for this reason that an algorithm with the ability to predict power drops caused by such shadows has been explored and produced. Through a literature review, this paper is aimed at providing insight into existing technology in the field of prediction and detection of shadows, such as optical methods of prediction in clouds. A photovoltaic power smoothing prediction algorithm that is targeted to improve on existing methods is described through this paper. In this project, results of the prediction algorithm, which subsystems include; obtaining data from a solar panel, shadow detection, battery storage are presented, and future recommendations are explored. The final product of this fourth-year project was a developed power smoothing prediction algorithm that was based on short term and minor long term predictions of changing photovoltaic power, giving the ability to supply controlled power to a load under all weather conditions. The algorithm presented 76.77% detection accuracy and reduction in duration of fluctuations of more than 66.8%.

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