Paisey, Fourys Yudo Setiawan (2026) Adaptive Droop Control Berbasis PI Dan Fuzzy Logic Untuk Optimalisasi Power Sharing Pada Sistem DC Nanogrid. Doctoral thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sistem DC microgrid dan DC nanogrid merupakan solusi potensial dalam integrasi sumber energi terbarukan dan sistem penyimpanan energi terdistribusi. Namun, metode droop control konvensional masih memiliki keterbatasan dalam akurasi pembagian daya akibat variasi resistansi saluran serta belum mempertimbangkan kondisi state of charge (SoC) baterai, yang dapat menyebabkan ketidakseimbangan distribusi daya dan penurunan efisiensi sistem. Penelitian ini mengusulkan metode adaptive droop control berbasis Proportional–Integral (PI) dan fuzzy logic control (FLC) dalam kerangka kontrol hirarkis untuk meningkatkan akurasi pembagian daya, kestabilan tegangan bus DC, serta keseimbangan SoC pada sistem DC nanogrid. Parameter droop disesuaikan secara adaptif berdasarkan kondisi arus, SoC, dan pengaruh resistansi saluran, sementara pengendali PI digunakan untuk mengurangi deviasi tegangan bus DC.
Metode yang diusulkan divalidasi melalui simulasi MATLAB/Simulink pada berbagai kondisi operasi, termasuk variasi beban, perubahan daya pembangkit, serta perbedaan resistansi saluran dan kondisi SoC. Hasil menunjukkan bahwa metode ini mampu menghasilkan pembagian daya yang mendekati kondisi ideal (1:1:1), meningkatkan keseimbangan SoC antar baterai, serta menjaga kestabilan tegangan bus DC dengan deviasi yang lebih kecil dibandingkan metode konvensional.
Kontribusi utama penelitian ini adalah pengembangan strategi kontrol adaptif berbasis PI dan fuzzy logic yang mampu mengatasi pengaruh resistansi saluran sekaligus mengintegrasikan pembagian daya dan manajemen energi secara simultan dalam sistem DC nanogrid. Pendekatan ini menawarkan solusi yang lebih adaptif, efisien, dan andal untuk implementasi sistem energi terdistribusi berbasis energi terbarukan.
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DC microgrid and DC nanogrid systems have emerged as promising solutions for the integration of renewable energy sources and distributed energy storage systems. However, conventional droop control methods still exhibit limitations in power-sharing accuracy due to variations in line resistance and the lack of consideration for battery State of Charge (SoC), which may lead to unequal power distribution and reduced system efficiency. This research proposes a hierarchical control framework incorporating Proportional–Integral (PI)-based and Fuzzy Logic Control (FLC)-based adaptive droop control strategies to enhance power-sharing accuracy, maintain DC bus voltage stability, and improve SoC balancing in DC nanogrid systems. The droop parameters are adaptively adjusted according to current conditions, battery SoC, and line resistance effects, while the PI controller is employed to mitigate DC bus voltage deviations. The proposed methods are validated through MATLAB/Simulink simulations under various operating conditions, including load variations, generation power fluctuations, differences in line resistance, and varying battery SoC levels. The simulation results demonstrate that the proposed approach achieves power sharing close to the ideal ratio (1:1:1), improves SoC balancing among battery units, and maintains DC bus voltage stability with lower voltage deviations compared to conventional control methods.
The main contribution of this research lies in the development of adaptive control strategies based on PI and fuzzy logic techniques that effectively compensate for the effects of line resistance while simultaneously integrating power-sharing and energy management functions within a DC nanogrid system. The proposed approach provides a more adaptive, efficient, and reliable solution for the implementation of renewable energy-based distributed energy systems.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | DC nanogrid, adaptive droop control, fuzzy logic control, PI controller, power sharing, DC nanogrid, adaptive droop control, fuzzy logic control, PI controller, power sharing |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20001-(S3) PhD Thesis |
| Depositing User: | Fourys Yudo Setiawan Paisey |
| Date Deposited: | 31 Jul 2026 07:55 |
| Last Modified: | 31 Jul 2026 07:55 |
| URI: | http://repository.its.ac.id/id/eprint/140639 |
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