Permata, Vicky Pria (2018) Alokasi Ekonomis Untuk Sistem Penyimpan Energi dengan Mempertimbangkan Distribusi Tenaga Angin. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sistem penyimpan energi telah banyak digunakan, seiring meningkatnya penggunaan pembangkit listrik energi terbarukan. Salah satu kelebihan dari sistem penyimpan energi adalah dapat meminimalkan biaya operasi sistem dan memperbaiki profil tegangan. Namun, pemasangan penyimpan energi dengan lokasi dan ukuran yang kurang sesuai akan menyebabkan biaya operasi sistem yang kurang optimal dan mengancam stabilitas tegangan, khususnya pada sistem yang memiliki pembangkit listrik tenaga angin. Karena sifat angin yang tidak pasti, sehingga menyebabkan daya yang disalurkan pembangkit listrik tenaga angin ke sistem berubah-ubah. Algoritma Hybrid Multi-Objective Particle Swarm Optimization (HMOPSO) digunakan untuk mencari lokasi dan ukuran penyimpan energi yang optimal dalam pertimbangan ketidak-pastian distribusi tenaga angin. Algoritma HMOPSO mengkombinasikan algoritma Multi-Objective Particle Swarm Optimization (MOPSO) dengan teknik aliran daya Newton-Raphson dan five-point estimation method (5PEM). Metode 5PEM digunakan untuk mendiskritisasi distribusi tenaga angin. Selanjutnya, dilakukan analisis probabilitas biaya. Sistem IEEE 30-bus digunakan untuk melakukan beberapa studi kasus. Hasil simulasi dari setiap studi kasus menunjukkan perlunya alokasi sistem penyimpan energi secara optimal dan memperlihatkan keefektifan metode yang dilakukan. ============= The energy storage system has been widely used, along with the increasing use of renewable energy. One of the advantages of energy storage systems is that it can minimize system operating costs and improve voltage profiles. However, the installation of energy storage with less suitable locations and sizes will result in non-optimal operating costs and threatening voltage stability, especially on systems with wind power. Due to the uncertain of the wind speed, it causes the power that the wind power generated into the system changes. Hybrid Multi-Objective Particle Swarm Optimization (HMOPSO) algorithm is used to find the optimal energy storage location and size in consideration of wind power uncertainty. The HMOPSO algorithm combines the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with a power flow Newton-Raphson technique and five-point estimation method (5PEM). The 5PEM method is used to discretizing wind power distribution. Furthermore, a cost probability analysis is performed. The IEEE 30-bus system is used to conduct some case studies. The simulation results from each case study clearly demonstrate the need for optimal allocation of energy storage systems, and the effectiveness of the proposed method.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | analisis probabilitas biaya, five-point estimation method, multi-objective particle swarm optimization, sistem penyimpan energi. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1322.6 Electric power-plants |
| Divisions: | Faculty of Electrical Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Vicky Pria Permata |
| Date Deposited: | 01 Dec 2018 16:47 |
| Last Modified: | 23 Apr 2021 04:53 |
| URI: | http://repository.its.ac.id/id/eprint/53013 |
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