Analisis Stabilitas Frekuensi Sistem Tenaga Listrik Melalui Pengaturan Optimal Power System Stabilizer dan Inersia Virtual Dengan Algoritma Adaptive Gbest-Guided Gravitational Search

Pramudhita, Faizal Dian (2025) Analisis Stabilitas Frekuensi Sistem Tenaga Listrik Melalui Pengaturan Optimal Power System Stabilizer dan Inersia Virtual Dengan Algoritma Adaptive Gbest-Guided Gravitational Search. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Integrasi teknologi energi baru-terbarukan (EBT) yang telah banyak diimplementasikan secara luas menjadi tantangan bagi sistem tenaga listrik. Hal ini terjadi karena pembangkit EBT tidak memiliki kemampuan inersia dan redaman layaknya generator konvensional. Akibatnya, saat terjadi gangguan, osilasi yang terjadi akan lebih parah dan dapat memperburuk kestabilan sistem tenaga Listrik (STL). Sehingga dalam tesis ini diusulkan metode kontrol hibrida untuk memperbaiki kestabilan STL menggunakan Power System Stabilizer (PSS) bertipe IEEE-PSS2B dan virtual inersia berbasis Superconducting Magnetic Energy Storage (SMES) dengan parameter yang dioptimasi menggunakan Adaptive Gbest-Guided Gravitational Search Algorithm (GGSA). Simulasi dilakukan menggunakan perangkat lunak MATLAB/Simulink dengan sistem yang menggunakan mesin tunggal yang terintegrasi dengan pembangkit Photovoltaic (PV). Hasil simulasi menunjukkan bahwa GGSA memberikan hasil penalaan yang lebih baik dibandingkan GSA dengan perbaikan fungsi objektif IAE, ITAE, ISE, dan ITSE masing-masing sebesar 50,06%; 44,16%; 41,83%; dan 39,30%. Penerapan VIC-PSS yang ditala menggunakan GGSA mampu mendemonstrasikan kemampuan redaman yang baik pada sistem dengan berbagai tingkat penetrasi EBT. Nilai rata-rata undershoot dan overshoot turun masing-masing sebesar 16,45% dan 35,45%. Sedangkan nilai rerata indeks performa pada skenario tanpa penetrasi turun sebesar 44,54%, pada skenario penetrasi 15% dapat turun sebesar 46,28%, dan pada skenario penetrasi 60% turun sebesar 40,72%.

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The integration Renewable Energy Sources (RES), which have been widely implemented, poses challenges for power systems. This is because RES generators lack the inertia and damping capabilities of conventional generators. As a result, when disturbances occur, the oscillations are more severe and can worsen the stability of the power system. Therefore, this thesis proposes a hybrid control method to improve power system stability using an IEEE-PSS2B type Power System Stabilizer (PSS) and virtual inertia based on Superconducting Magnetic Energy Storage (SMES), with parameters optimized using the Adaptive Gbest-Guided Gravitational Search Algorithm (GGSA). Simulations were conducted using MATLAB/Simulink software on a system with a single machine integrated with a Photovoltaic (PV) generator. The simulation results show that GGSA provides better tuning results compared to GSA, with improvements in the objective functions IAE, ITAE, ISE, and ITSE by 50.06%, 44.16%, 41.83%, and 39.30%, respectively. The application of VIC-PSS tuned using GGSA demonstrates good damping capabilities in systems with various levels of RES penetration. The average values of undershoot and overshoot decreased by 16.45% and 35.45%, respectively. Meanwhile, the average performance index in the no-penetration scenario decreased by 44.54%, in the 15% penetration scenario by 46.28%, and in the 60% penetration scenario by 40.72%.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Adaptive Gbest-Guided Gravitational Search Algorithm, Power System Stabilizer, Stabilitas, Superconducting Magnetic Energy Storage, Virtual Inertia Control.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001 Production of electric energy or power
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1010 Electric power system stability. Electric filters, Passive.
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1087 Photovoltaic power generation
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2941 Storage batteries
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User: Faizal Dian Pramudhita
Date Deposited: 22 Jan 2025 03:01
Last Modified: 22 Jan 2025 03:01
URI: http://repository.its.ac.id/id/eprint/116569

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