Similarity: STUDI LITERATUR SISTEM PANEL SURYA BERBASIS MIKROKONTROLER ARDUINO DAN ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM

HAY, AYATULLAH and Suprapto, Bhakti Yudho (2022) Similarity: STUDI LITERATUR SISTEM PANEL SURYA BERBASIS MIKROKONTROLER ARDUINO DAN ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM. Turnitin Universitas sriwijaya.

Text (AVoER Similarity) Avoer13_Ayat_2021_iThenticate.pdf Download (2MB)

Abstract

Abstract: Power plants in the new and renewable energy (EBT) sector can solve the problem of electricity demand. Indonesia's current renewable energy sources are mini/micro hydro 450 MW, biomass 50 GW, 4.80 kWh/m2/day, wind power 36 m/s, and nuclear 3 GW. Solar energy cannot be used directly and must first be converted into electrical energy. Photovoltaic converters convert light energy directly into electrical energy. Researchers conducted a literature study on new solar-powered renewable energy sources using solar panels to learn how to write data based on Arduino microcontrollers and artificial neural networks. The Arduino Uno acts as a control element for any system, and ANFIS works better with solar PV arrays to track the sun's path across the sky

Item Type:	Other
Subjects:	#3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Mr. Bhakti Suprapto
Date Deposited:	25 Apr 2023 04:33
Last Modified:	25 Apr 2023 04:33
URI:	http://repository.unsri.ac.id/id/eprint/94893

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