Wicaksana, Fericko Satya (2021) Perencanaan Penentuan Lokasi Dan Kapasitas Optimal Baterai dalam Meningkatkan Resiliensi Sistem Mikrogrid. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Mikrogrid merupakan salah satu sistem kelistrikan interkoneksi dengan berbagai macam sumber energi dalam menghasilkan energi listrik. Sistem mikrogrid dapat mengalami pemadaman berkepanjangan ketika adanya gangguan (kontingensi) tak terduga karena kesalahan manusia atau bencana alam. Pada penelitian ini akan membahas mengenai resiliensi mikrogrid, yaitu kemampuan pemulihan beban setelah terjadinya pemadaman atau kontingensi. Integrasi Battery Energy Storage (BES) dapat berkontribusi sebagai pembangkit tambahan dan dapat mengembalikan suplai daya ke beban secara langsung jika terjadi kontingensi. Dalam mengintegrasikan BES perlu adanya perencanaan penentuan lokasi dan kapasitas optimal, sehingga dapat meningkatkan resiliensi sistem mikrogrid. Pada penelitian ini digunakan metode Hybrid Multi-Objective Particle Swarm Optimization (H-MOPSO) yang merupakan gabungan metode Multi-Objective Particle Swarm Optimisation (MOPSO) dan Non-Dominated Sorting Genetic Algoritm II (NSGA II) dalam menentukan peletakan BES yang optimal. Fungsi Objektif yang digunakan dalam penelitan ini adalah memaksimalkan keuntungan tahunan dan meminimalkan pelepasan daya tahunan. Selain itu dengan menerapkan konsep Security Constraint dengan metode Line Outage Distribution Factor (LODF) dalam membuat batasan sekuriti saluran untuk mengatasi saluran overload saat kontingensi terjadi. Hal ini bertujuan agar system microgrid lebih siap dan cepat dalam mengatasi gangguan walaupun tanpa ada kondisi re-dispatch
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A microgrid is an electrical system that is interconnected with various energy sources to produce electrical energy. Microgrid systems can experience prolonged outages when unexpected disruptions (contingencies) occur due to human error or natural disasters. This study will discuss microgrid resilience, namely the ability to recover after death or contingency loads. Battery Energy Storage (BES) integration can contribute to the additional generation and can immediately return the power supply to load in the event of a contingency. In integrating BES, it is necessary to plan the optimal location and capacity, so as to increase the resilience of the microgrid system. In this study, the Hybrid Multi-Objective Particle Swarm Optimization (H-MOPSO) method is used, which is a combination of the Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA II) methods to determine the optimal placement of BES. . The objective function used in this study is to maximize annual gain and minimize annual power release. In addition, by applying the concept of Security Constraint with the Line Outage Distribution Factor (LODF) method in creating channel boundaries, it can overcome line overloads when contingencies occur. This is intended to make the microgrid system more ready and quick to solve problems even without re-sending conditions
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Battery Energy Storage, H-MOPSO, Kontingensi, Mikrogrid, Resiliensi, Battery Energy Storage, H-MOPSO, Contingency, Microgrid, Resiliency |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK201 Electric Power Transmission T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001 Production of electric energy or power T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7868.P6 Power supply |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis |
| Depositing User: | Fericko Satya Wicaksana |
| Date Deposited: | 17 Feb 2021 06:27 |
| Last Modified: | 02 Jul 2024 13:58 |
| URI: | http://repository.its.ac.id/id/eprint/82663 |
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