Arnadinata, Rafi (2022) Optimasi Penentuan Lokasi Dan Kapasitas Dynamic Voltage Restorer (Dvr) Menggunakan Self-Adaptive Modified Firefly Algorithm (Samfa) Untuk Meningkatkan Kualitas Daya Listrik Pada Sistem Distribusi. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kebutuhan manusia pada energi listrik saat ini semakin meningkat. Hal ini diakibatkan oleh meningkatnya populasi dan perkembangan teknologi yang sangat pesat. Peningkatan kebutuhan ini menimbulkan permasalahan kualitas daya listrik pada jaringan distribusi, seperti deviasi tegangan yang berlebih dan distorsi harmonisa. Harmonisa yang melebihi batas dapat menyebabkan gangguan dan meningkatnya kerugian daya pada sistem, sehingga diperlukan upaya dalam mengatasi permasalahan tersebut. Salah satu mitigasi yang dapat dilakukan adalah dengan memasang Dynamic Voltage Restorer (DVR) pada sistem. Namun, pemasangan Dynamic Voltage Restorer (DVR) ini juga perlu diperhatikan lokasi dan kapasitasnya, sehingga biaya investasi dapat diminimalkan dan hasil mitigasi dapat dimaksimalkan. Pada tugas akhir ini, metode Self-Adaptive Modified Firefly Algorithm (SAMFA) digunakan untuk mendapatkan lokasi dan kapasitas Dynamic Voltage Restorer (DVR) yang optimal pada sistem distribusi IEEE 33 Bus menggunakan software MATLAB. Hasil menggunakan metode SAMFA lalu dibandingkan dengan hasil menggunakan metode Firefly Algorithm (FA). Hasil simulasi menunjukkan bahwa pemasangan DVR dengan jumlah DVR yang paling optimal, yaitu 4 DVR dapat menurunkan THD tegangan dan deviasi tegangan hingga memenuhi batas standar, serta mengurangi kerugian daya hingga mencapai 31,05 % untuk daya aktif dan 29,45 % untuk daya reaktif. Selain itu, optimasi menggunakan metode Self-Adaptive Modified Firefly Algorithm (SAMFA) dapat menghasilkan nilai fungsi objektif total yang lebih rendah dibandingkan metode Firefly Algorithm (FA). Hasil simulasi menunjukkan bahwa metode SAMFA dapat memberikan performa yang lebih baik dibandingkan metode FA dalam optimasi penentuan lokasi dan kapasitas DVR.
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The human need for electrical energy is currently increasing. This is due to the increasing population and rapid technological developments. This increase in demand causes problems in the quality of electrical power in the distribution network, such as excessive voltage deviation and harmonic distortion. Harmonics that exceed the limit can cause interference and increase power losses in the system, so efforts are needed to overcome these problems. One of the mitigations that can be done is to install a Dynamic Voltage Restorer (DVR) on the system. However, the installation of the Dynamic Voltage Restorer (DVR) also needs to be considered for its location and capacity, so that investment costs can be minimized and mitigation results can be maximized. In this final project, the Self-Adaptive Modified Firefly Algorithm (SAMFA) method is used to obtain the optimal location and capacity of the Dynamic Voltage Restorer (DVR) on the IEEE 33 Bus distribution system using MATLAB software. The results using the SAMFA method are then compared with the results using the Firefly Algorithm (FA) method. The simulation results show that the installation of a DVR with the most optimal number of DVRs, namely 4 DVRs can reduce the THD voltage and voltage deviation to meet the standard limits, and reduce power losses up to 31.05% for active power and 29.45% for reactive power. In addition, optimization using the Self-Adaptive Modified Firefly Algorithm (SAMFA) method can result in lower total objective function value than the Firefly Algorithm (FA). The simulation results show that the SAMFA method can provide better performance than the FA method in optimizing the location and capacity of the DVR.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Dynamic Voltage Restorer, Self-Adaptive Modified Firefly Algorithm, Harmonisa. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Marsudiyana - |
| Date Deposited: | 15 Jun 2026 04:59 |
| Last Modified: | 15 Jun 2026 04:59 |
| URI: | http://repository.its.ac.id/id/eprint/133809 |
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