Detection of malfunctioning photovoltaic cells in solar panel

Abstract

Solar energy plays a significant role in electricity generation in today's society. Solar panels are used to generate solar energy. Solar panel consists collection of PV cells which produce the solar power. The amount of electricity produced may be reduced if PV cells fail. Fortunate acknowledgment of deficiencies in Photovoltaic cells can save time, tries and upkeep costs of turning gear. In order to prevent the genuine relationship of vibration pickup to the machine instrument, a non-contact type vibration pickup has been organised and manufactured in this survey to obtain vibration data for Photovoltaic cells prosperity when considering underweight and speed assortment. The main objective is to identify the malfunctioning photovoltaic cells in solar panel. Feature extraction and dimensionality reduction are being applied to the collected data sets. The dimensionality of the removed features was diminished using Principal Component Analysis (PCA) and from that point on the picked features were situated organized by importance using the Sequential Floating Forward Selection (SFFS) method for lessening the amount of data components and noticing the best rundown of capacities.