IoT based Smart Small Scale Solar Energy Planning using Evolutionary Fuzzy Association Rule Mining

Authors : Wirarama Wedashwara; Tatang Mulyana; I Wayan Agus Arimbawa; Andy Hidayat Jatmika; Ariyan Zubaidi
article cite 9 Year 2020
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Abstract

Along-Track Stereo Sun Glitter (ATSSG) shows Indonesia especially Lombok has high solar energy potential, not only on large scale but also small scale such as for hybrid-based electricity savings. The amount of energy that can be saved through solar power is difficult to predict without measurement and planning. The paper proposed the Smart Small Scale Solar Energy Planning using Internet of Things (IoT) by collaborating Wireless Sensor Network (WSN) as data collector and Evolutionary Fuzzy Association Rule Mining (EFARM) as Decision Support System (DSS). WSN collects data generated solar energy by the solar panel and direct current (DC) energy usage by electrical devices. Then both collected data are processed by EFARM through an interpretation of tree-based fuzzy rule extractor to conclude the potential of energy efficiency. The Evaluation is carried out for two weeks using two solar panels with light intensity, temperature, and humidity sensors as a comparison for environment condition and generated energy. Through evaluation EFARM has shown the capability to Interpreted patterns of generated energy and energy consumption by achieving a high average of supports(0.247,0.236), confidence(0.393,0.219) and scores(0.335,0.127) for full-length rules; describe the rules correlation between generated energy and energy consumption to conclude the potential of energy efficiency, and make decision support for the number of panels and batteries to be added with relatively low mean square error (6.094).


Concepts :
Solar Radiation and Photovoltaics
IoT-based Smart Home Systems
Engineering and Technology Innovations
article cite 9 Year 2020 source
SDGs
Affordable and clean energy
Citations by Year
YearCount
2020 9