Sistem Estimasi State of Charge Baterai PV Grid Menggunakan Metode Coulomb Counting Berbasis Internet of Things

Al Aziz, Afifuddin Farhan (2023) Sistem Estimasi State of Charge Baterai PV Grid Menggunakan Metode Coulomb Counting Berbasis Internet of Things. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sistem pembangkit listrik tenaga surya di Indonesia menjadi semakin popular karena harga photovoltaic semakin murah dan seluruh daerah di Indonesia hampir tiap hari terpapar sinar matahari. Baterai menjadi bagian sistem yang sangat penting, mengingat sifat sumber energi photovoltaic yang tidak bisa menyuplai secara terus menerus (intermittent). Proses charge dan discharge baterai yang tidak baik, menjadikan umur baterai lebih singkat. Proses charge dan discharge yang baik membutuhkan informasi State of Charge (SOC) yang akurat. Beberapa metode pengukuran SOC baterai yang sederhana seperti estimasi berdasarkan tegangan baterai banyak dipakai, namun metode tersebut memiliki akurasi yang kurang baik sehingga diperlukan metode yang lebih akurat dalam melakukan estimasi SOC. Selain itu, banyaknya PLTS yang berada pada lokasi yang terisolir, sehingga dibutuhkan pemantauan SOC baterai secara jarak jauh. Pada Tugas akhir ini telah didesain dan diimplementasikan sistem estimasi SOC baterai menggunakan metode Coulomb Counting. Coulomb Counting merupakan salah satu metode estimasi SOC dengan cara menghitung muatan listrik yang masuk atau keluar baterai. Selain itu untuk memonitoring baterai tersebut, dilengkapi juga dengan teknologi IoT untuk memantau dari jarak jauh. Sistem ini meliputi pengestimasian SOC baterai pada saat discharge dan charge serta penyimpanan data ke database menggunakan salah satu perangkat IoT yaitu MQTT. Berdasarkan hasil pengujian, telah berhasil dibuat sistem estimasi SOC baterai dengan rata – rata error 3.33% dan telah ditambahkan sistem IoT yang dapat melakukan monitoring data secara real time dengan delay rata – rata 0.029 detik dalam setiap pengiriman data menuju database.
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The popularity of solar power generation systems in Indonesia has been on the rise due to the decreasing cost of photovoltaic technology and the abundant sunlight exposure across the country. Batteries play a vital role in these systems as they compensate for the intermittent nature of photovoltaic energy supply. However, inadequate charging and discharging processes can lead to reduced battery lifespan. Accurate State of Charge (SOC) information is crucial for optimizing these processes. While simple methods like voltage-based estimation are commonly used for SOC measurement, they often lack precision, necessitating the development of more accurate estimation methods. Additionally, with many solar power systems located in remote areas, remote monitoring of battery SOC becomes essential. This final project aims to design and implement a battery SOC estimation system using the Coulomb Counting method. Coulomb Counting involves calculating the electric charge entering or leaving the battery to estimate SOC. To facilitate remote monitoring, the system incorporates IoT technology. It includes SOC estimation during both charging and discharging processes, as well as data storage in a database using the MQTT protocol. Through testing, the battery SOC estimation system achieved an average error of 3.33%, and the integrated IoT system successfully provided real-time data monitoring with an average delay of 0.029 seconds for each data transmission to the database.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Photovoltaic, SOC Baterai, Coulomb Counting, IoT, Photovoltaic, Battery SOC, Coulomb Counting, IoT
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2945 Lead-acid batteries. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2960 Dye-sensitized solar cells. Solar batteries. Solar cells T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK351 Electric measurements.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	Al Aziz Afifuddin Farhan
Date Deposited:	26 Jul 2023 01:16
Last Modified:	26 Jul 2023 01:16
URI:	http://repository.its.ac.id/id/eprint/99425

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