Journal of Soft Computing Paradigm
IRO Journals
Volume 3 — Issue 2 — June 2021

A Self Monitoring and Analyzing System for Solar Power Station using IoT and Data Mining Algorithms

https://doi.org/10.36548/jscp.2021.2.004
Subarna Shakya
Professor, Department of Electronics and Computer Engineering, Central Campus, Institute of Engineering, Pulchowk, Tribhuvan University, Pulchowk, Lalitpur,
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How to Cite

Shakya, Subarna. 2021. “A Self Monitoring and Analyzing System for Solar Power Station Using IoT and Data Mining Algorithms”. Journal of Soft Computing Paradigm 3 (2): 96-109. https://doi.org/10.36548/jscp.2021.2.004.
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Keywords

— Solar panel maintenance
— maximum power generation
— IoT
— data mining
— solar panel
Published: 26-06-2021

Abstract

Renewable energy sources are gaining a significant research attention due to their economical and sustainable characteristics. In particular, solar power stations are considered as one of the renewable energy systems that may be used in different locations since it requires a lower installation cost and maintenance than conventional systems, despite the fact that they require less area. In most of the small generating stations, space occupancy is controlled by placing the equipment on an open terrace. However, for large-scale power generating stations, acres of land are required for installation. Human employers face a challenging task in maintaining such a large area of power station. Through IoT and data mining techniques, the proposed algorithm would aid human employers in detecting the regularity of power generation and failure or defective regions in solar power systems. This allows performing a quick action for the fault rectification process, resulting in increased generating station efficiency.

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