Systematic Literature Review on Battery Management Systems and predicting Solar Big Data
DOI:
https://doi.org/10.33050/sensi.v9i2.2909Keywords:
bigdata tenaga surya, Systematic Literature Review, algoritma ELM, algoritma JSTAbstract
Penelitian ini bertujuan untuk menganalisis sistem manajemen baterai dengan memprediksi tenaga surya melalui bigdata ditinjau dari kajian literatur. Dengan adanya pertumbuhan biaya integrasi, pengelolaan limbah yang semakin rumit, variabilitas daya listrik yang berdampak sosio-lingkungan sehingga membutuhkan model sektor listrik baru dengan memanfaatkan tenaga surya. Oleh karenanya penelitian ini merupakan hasil tinjauan literature review dengan prinsip systematic literature review untuk memprediksi tenaga surya dalam pengelolaan listrik dengan sistem baterai. Metode Systematic Literature Review (SLR) digunakan untuk mendefinisikan dan mengevaluasi literatur dalam rangkaian makalah. Pencarian menggunakan 41 makalah untuk evaluasi sebelumnya, menunjukkan bahwa model yang digunakan untuk memprediksi tenaga surya adalah eksperimen akademik jangka panjang. Algoritma ELM (Extreme Learning Machine) menjadi pilihan dalam pengelolaan listrik dengan tenaga surya melalui system baterai dibandingkan dengan algoritma JST (Jaringan Syaraf Tiruan).
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