Rancang Bangun Sistem Solar Power Data Logger Berbiaya Rendah Menggunakan Metode Kalman Filter Berbasis Internet Of Things

Imaduddin, Muhammad Syafiq (2024) Rancang Bangun Sistem Solar Power Data Logger Berbiaya Rendah Menggunakan Metode Kalman Filter Berbasis Internet Of Things. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Turunnya harga pembelian dan kenaikan efisiensi performa pengoperasian panel surya disertai letak geografi Indonesia yang disinari sinar matahari sepanjang tahun menjadikan pembangkit listrik tenaga surya menjadi salah satu sistem yang banyak digunakan pada pembangkitan energi baru terbarukan. Akan tetapi, perencanaan untuk tercapainya performa yang optimal pada segala scenario diperlukan untuk menentukan keputusan instalasi. Bagian dari proses instalasi ini adalah dilakukannya studi data terkait radiasi surya pada wilayah tertentu untuk memprediksi seberapa tinggi pembangkitan panel PV yang dapat dilakukan dengan menggunakan solar power data logger yang dapat menerima dan merekam data daya radiasi surya pada wilayah potensial. Pada tugas akhir ini digunakan panel PV sebagai sensor radiasi matahari. Panel PV dihubungkan dengan rangkaian MPPT dengan metode beban optimal untuk memastikan energi surya yang diterima mencapai titik maksimum. Data yang diterima diproses menggunakan Kalman Filter agar estimasi data yang diperoleh lebih sedikit noise. Komunikasi IoT diterapkan untuk memonitoring sistem dengan mengirimkan data melalui koneksi internet. Hasil tugas akhir ini adalah telah dibuat sistem untuk menerima daya radiasi matahari langsung melalui panel PV dan proses Kalman Filter untuk memperoleh hasil yang lebih sedikit noise serta melakukan pengiriman data melalui komunikasi IoT protocol MQTT telah dilakukan. Daya yang diperoleh panel PV dipastikan selalu mencapai titik optimal dengan menggunakan kontrol variable beban berbasis MOSFET. Alat yang dirancang mampu bekerja secara otonom dan mempunyai penyimpanan non-volatil apabila terjadi gangguan komunikasi IoT serta bekerja dengan tegangan suplai 12V. Hasil keluaran data yang diperoleh adalah radiasi matahari dalam W/m² dengan hasil kalkulasi Kalman Filter yang mempunyai RMSE senilai 0.512 dari 2600 data set nilai radiasi matahari awal.
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The decrease in the purchase price and the improvement in the operational performance efficiency of solar panels, combined with Indonesia's geographical location that is illuminated by sunlight throughout the year, make solar power generation one of the widely used systems in new renewable energy generation. However, planning for optimal performance in various scenarios is necessary to make installation decisions. Part of this installation process involves conducting a study on solar radiation data in specific regions to predict the extent of PV panel generation that can be achieved using a solar power data logger capable of receiving and recording solar radiation power data in potential areas. In this final project, PV panels are used as solar radiation sensors. The PV panels are connected to an MPPT circuit with an optimal load method to ensure that the received solar energy reaches its maximum point. The received data is processed using a Kalman Filter to reduce estimation noise. IoT communication is applied to monitor the system by sending data through an internet connection. The outcome of this final project is the creation of a system that receives direct solar radiation power through PV panels, processes the data with a Kalman Filter to obtain results with less noise, and sends the data via IoT using the MQTT protocol. The power obtained from the PV panels is ensured to always reach the optimal point by using load variable control based on MOSFET. The designed device is capable of operating autonomously and has non-volatile storage in case of IoT communication disruptions while also working with a 12V supply voltage. The output data obtained is solar radiation in W/m², with Kalman Filter calculations yielding an RMSE of 0.512 from 2600 initial solar radiation data sets.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Tenaga Surya, PV, IoT, Solar, Data, Kalman Filter, Internet of Things.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001 Production of electric energy or power T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1056 Solar power plants. Ocean thermal power plants T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2960 Dye-sensitized solar cells. Solar batteries. Solar cells
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	MUHAMMAD SYAFIQ MADUDDIN
Date Deposited:	26 Jul 2024 00:53
Last Modified:	26 Jul 2024 00:53
URI:	http://repository.its.ac.id/id/eprint/108081

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