widarsono, kukuh (2025) Dynamic Optimal Power Flow Pada Sistem Microgrid Mempertimbangkan Uncertainty Dan Baterai Management Sistem Menggunakan Whale Optimization. Doctoral thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Optimalisasi pembangkitan daya (Optimal Power Flow) tetap menjadi isu penting dalam operasi sistem tenaga listrik, seiring tuntutan efisiensi ekonomi dan kepedulian lingkungan. Selain mengejar biaya pembangkitan minimum (Economic Dispatch), integrasi energi terbarukan juga menjadi perhatian utama, meski menghadirkan tantangan intermitensi dan ketidakpastian. Karena itu, diperlukan pendekatan optimasi yang adaptif terhadap dinamika sistem dan integrasi energi terbarukan secara efektif. Penelitian ini mengusulkan penggunaan Improved Whale Optimization Algorithm (IWOA) dengan bobot adaptif berbasis Fuzzy Logic Controller untuk menyelesaikan permasalahan optimasi non-linier dan kompleks. Sistem tenaga dimodelkan selama 24 jam operasi, dengan integrasi Photovoltaic, Energy Storage (ES), dan Wind Turbine guna meningkatkan efisiensi dan keandalan. ES menyimpan energi saat surplus dan menyuplainya saat beban puncak untuk mengurangi beban pembangkit termal dan emisi karbon. Wind Turbine dimodelkan melalui fungsi biaya kompetitif berbasis distribusi Weibull serta mempertimbangkan pajak karbon guna mendorong pertumbuhan energi terbarukan. Hasil simulasi menunjukkan bahwa IWOA mampu menghasilkan biaya pembangkitan harian yang lebih rendah (selisih US$17–US$25/hari), iterasi lebih sedikit (20 vs 26), dan solusi yang lebih stabil dibandingkan WOA standar. Model ini juga menjaga keseimbangan pengisian dan pengosongan ES secara akurat, dengan State of Charge akhir yang konsisten dengan nilai awal. Penggunaan model biaya energi angin berbasis distribusi Weibull terbukti memberikan estimasi biaya yang lebih akurat dibandingkan pendekatan Levelized Cost of Energy konvensional. Dengan kebijakan pajak karbon sebesar US$40–US$50/MWh, simulasi menunjukkan bahwa pembangkit angin dapat menyuplai hingga 50% dari kapasitas terpasang harianya dan bersaing secara ekonomi dengan pembangkit berbahan bakar fosil.
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Optimal power generation (Optimal Power Flow) remains a critical issue in power system operations, driven by the increasing demands for economic efficiency and environmental sustainability. In addition to minimizing generation costs (Economic Dispatch), the integration of renewable energy sources has become a central focus, despite the inherent challenges of intermittency and supply uncertainty. Therefore, an optimization approach that can adapt to system dynamics and effectively accommodate renewable energy integration is essential. This study proposes the use of an Improved Whale Optimization Algorithm (IWOA) with adaptive weights generated by a Fuzzy Logic Controller to solve complex and non-linear optimization problems. The power system is modeled over a 24-hour operational period, incorporating Photovoltaic (PV), Energy Storage (ES), and Wind Turbine systems to enhance overall efficiency and reliability. The ES is utilized to store surplus energy and discharge it during peak demand periods, aiming to reduce the load on thermal generators and lower carbon emissions. Wind turbines are modeled with a more competitive cost function using the Weibull distribution and incorporating carbon tax considerations to promote renewable energy growth. Simulation results indicate that IWOA produces a lower daily generation cost (by US$17–US$25/day), requires fewer iterations (20 vs. 26), and yields more stable solutions compared to the standard WOA. The model also accurately maintains the balance of charging and discharging within the ES, with the final State of Charge (SoC) matching the initial level. Moreover, the wind energy cost model based on the Weibull distribution provides a more accurate cost estimate than the conventional Levelized Cost of Energy (LCOE) approach. With a carbon tax policy of US$40–US$50/MWh, simulations show that wind power can supply up to 50% of its installed daily capacity and compete economically with fossil-fuelbased generators
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Microgrid, Energi Terbarukan, Energy Storage, Improve Whale Optimization Algorithm, Weibull Microgrid, Renewable Energy, Energy Storage, Improve Whale Optimization Algorithm, Weibull. |
| 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. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20001-(S3) PhD Thesis |
| Depositing User: | Kukuh Widarsono |
| Date Deposited: | 22 Jul 2025 04:31 |
| Last Modified: | 22 Jul 2025 04:31 |
| URI: | http://repository.its.ac.id/id/eprint/120458 |
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