Hakim, Lutfi (2022) Analisis Stabilitas Frekuensi Pada Optimasi Setting Controller Virtual Inertia Control (VIC) Superconducting Magnetic Energy Storage (SMES) Menggunakan Firefly Algorithm. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pengintegrasian pembangkit sumber energi baru terbarukan, seperti photovoltaic (PV), ke dalam sistem kelistrikan konvensional mengalami peningkatan setiap tahunnya. Hal ini memiliki efek negatif terhadap total nilai inersia dan damping sistem. Hal ini terjadi karena pembangkit sumber energi terbarukan membutuhkan komponen seperti inverter untuk terhubung ke sistem tenaga. Inverter adalah suatu perangkat yang tidak mekiliki inersia karena tidak terdapat benda berputar yang menjadi penghasil inersia. Pada sistem, kestabilan frekuensi sangat bergantung dengan jumlah inersia dan damping dari sistem itu sendiri. Untuk memungkinkan pemasangan unit pembangkit sumber energi terbarukan ke sistem tenaga, perlu adanya suatu strategi kontrol yang dapat menyediakan bantuan inersia ke sistem tenaga yang dinamakan Virtual Inertia Control (VIC). Dalam penerapannya, VIC terdiri dari inverter, kontrol yang sesuai untuk menghasilkan inersia, dan sistem penyimpan energi, salah satunya adalah Superconducting Magnetic Energy Storage (SMES). SMES digunakan karena kelebihannya dalam mentransfer daya dengan cepat dan efisiensi yang tinggi. Untuk mengoptimalkan kontrol respon daya inersia tiruan yang dapat dilakukan VIC terhadap SMES untuk perbaikan frekuensi, perlu dilakukan pengoptimalan nilai dari karakteristik inersia dan damping virtual. Salah satu metode yang dapat digunakan adalah metode Firefly Algorithm (FA). Hasil yang didapat adalah pemasangan VIC berbasis SMES dapat menurunkan overshoot dan menangkap nadir frekuensi akibat adanya perubahan beban dan integrasi PV. Optimasi parameter SMES dapat memepercepat waktu kestabilan sistem setelah terjadi perubahan frekuensi dan memperkecil nilai eror.
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The integration of the generation of renewable energy sources, such as photovoltaic (PV), into the electricity system is increasing every year. This has a negative effect on the total inertia and damping values of the system. This is because the generation of renewable energy sources requires components such as inverters to be connected to the power system. Inverter is inertialess. There is no rotating mass that produces inertia. In the system, frequency stability is highly dependent on the amount of inertia and damping of the system. To support the integration of renewable energy source generating units into the power system, it is necessary to have a control strategy that can provide inertial to the power system which is Virtual Inertia Control (VIC). In its application, VIC consists of an inverter, a suitable control for generating inertia, and an energy storage system, one of which is Superconducting Magnetic Energy Storage (SMES). SMES is used because of the advantages in transferring power quickly and high efficiency. To optimize the inertial power response that can be performed by VIC on SMES for frequency improvement, it is necessary to optimize the values of the virtual inertia and damping characteristics. One method that can be used is the Firefly Algorithm (FA) method. The results obtained are SMES-based VIC installation can reduce overshoot and capture nadir frequencies due to load changes and PV integration. The SMES optimization parameter can accelerate the system stability time after a frequency change and reduce the error value.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSE 621.31 Hak a-1 2022 |
| Uncontrolled Keywords: | Photovoltaic integration, Virtual Inertia Control, Superconducting Magnetic Energy Storage, Optimization, Firefly Algorithm, Frequency Stability. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1010 Electric power system stability. Electric filters, Passive. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | - Davi Wah |
| Date Deposited: | 13 May 2024 05:11 |
| Last Modified: | 13 May 2024 05:11 |
| URI: | http://repository.its.ac.id/id/eprint/107929 |
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