Ammar, Fahmi (2024) Optimalisasi Multi-Objective Analisis Karakteristik Masa Pakai Sistem Penyimpanan Energi Baterai pada Stand-Alone Microgrid dengan Metode Prairie Dog Optimization. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Microgrid memiliki peran penting dalam memfasilitasi transisi menuju sumber energi bersih dan berkelanjutan. Mempertahankan microgrid yang stabil, handal, dan ekonomis dengan menggunakan energi terbarukan secara efisien sangatlah penting. Salah satu cara mengatasi masalah dalam pengoperasian microgrid adalah dengan memanfaatkan sistem penyimpanan energi baterai (Battery Energy Storage System, BESS). Menyelidiki karakteristik masa pakai dari sistem penyimpanan energi baterai juga diperlukan untuk membangun operasi microgrid yang efisien dan ekonomis. Dalam penelitian ini, model optimasi yang meminimalkan biaya pembangkitan dan memaksimalkan umur baterai telah diperhitungkan melalui aliran daya optimal dinamis (Dynamic Optimal Power Flow, DOPF). Penyimpanan daya dalam sistem BESS akan dikelola dengan mempertimbangkan sistem manajemen energi (EMS) dan pemantauan State of Charge (SOC) selama operasi untuk mengoptimalkan masa pakai baterai dan memastikan kinerja terbaik microgrid. Untuk mengoptimalkan model multi-objective tersebut, digunakan algoritma metaheuristik baru, Prairie Dog Optimization (PDO). Metode weighted sum digunakan untuk menggabungkan kedua fungsi objektif. Sistem IEEE 30 bus dengan modifikasi beban dinamik, sumber energi terbarukan, dan BESS digunakan untuk merepresentasikan stand-alone microgrid. Hasil pengujian menunjukkan bahwa nilai daya pembangkitan terbesar pada kasus 2d (5.564,57 kW) pembobotan biaya pembangkitan 0,4 dan life lost cost 0,6. Permbangkitan terkecil pada kasus 2a (5.563,27 kW) pembobotan biaya pembangkitan 1 dan life lost cost 0. Sebaliknya, Kasus 2a memiliki life loss cost tertinggi ($10,66), sedangkan kasus 2d memiliki life loss cost terendah ($5,75). Oleh karena itu, dapat disimpulkan bahwa kedua fungsi objektif tersebut berbanding terbalik.
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Microgrid has an important role in facilitating the transition to clean and sustainable energy sources. Maintain microgrid which is stable, reliable and economical by using renewable energy efficiently is very important. One way to overcome problems in operation microgrid is to utilize a Battery Energy Storage System (BESS). Investigating the lifetime characteristics of battery energy storage systems is also necessary to build efficient and economical microgrid operations. In this research, an optimization model that minimizes generation costs and maximizes battery life has been calculated through Dynamic Optimal Power Flow (DOPF). Power storage in the BESS system will be managed taking into account the energy management system (EMS) and monitoring State of Charge (SOC) during operation to optimize battery life and ensure the best performance of the microgrid. To optimize the model multi-objective In this case, a new metaheuristic algorithm is used, Prairie Dog Optimization (PDO). Method weighted sum used to combine the two objective functions. An IEEE 30 bus system with dynamic load modification, renewable energy sources, and BESS is used to represent stand-alone microgrid. The test results show that the largest generation power value is in case 2d (5,564.57 kW) with a weighting of generation costs of 0.4 and life lost cost 0.6. The smallest generation in case 2a (5,563.27 kW) weighting generation costs 1 and life lost cost 0. In contrast, Case 2a has life loss cost highest ($10.66), while case 2d has life loss cost lowest ($5.75). Therefore, it can be concluded that the two objective functions are inversely related.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | BESS, DOPF, lifetime, microgrid, Prairie Dog Optimization, BESS, DOPF, masa pakai, microgrid, Prairie Dog Optimization. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK201 Electric Power Transmission 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: | Fahmi Ammar |
| Date Deposited: | 31 Jul 2024 01:14 |
| Last Modified: | 31 Jul 2024 01:14 |
| URI: | http://repository.its.ac.id/id/eprint/110871 |
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