REAL TIME STABILITY CONTROL OF HYBRID POWER MICRO-GRID NETWORKS BASED ON ANN CONTROLLER / PATIENT SONY MUTUNDA; SUPERVISOR: ASST. PROF. DR. ZIYA DEREBOYLU, CO-SUPERVISOR: ASST. PROF. DR. MOEIN JAZAYERI
Dil: İngilizce 2023Tanım: xiii, 122 sheets: charts, tables; 30 cm. 1 CD ROMİçerik türü:- text
- unmediated
- volume
Thesis
| Materyal türü | Geçerli Kütüphane | Koleksiyon | Yer Numarası | Durum | Notlar | İade tarihi | Barkod | Materyal Ayırtmaları | |
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Thesis
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CIU LIBRARY Tez Koleksiyonu | Tez Koleksiyonu | YL 3201 M88 2023 (Rafa gözat(Aşağıda açılır)) | Kullanılabilir | Electrical-Electronic Engineering Department | T3594 | |||
Suppl. CD
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CIU LIBRARY Görsel İşitsel | Tez Koleksiyonu | YL 3201 M88 2023 (Rafa gözat(Aşağıda açılır)) | Kullanılabilir | Electrical-Electronic Engineering Department | CDT3594 |
Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Electrical-Electronic Engineering Department
Includes References (sheets 109-115)
ABSTRACT
In recent years, the use of interconnection of multiple power source generators that
are usually located upstream and included in transmission network are getting more
complex and difficult to manage. According to the upstream electricity grid
conditions, micro-grids can operate in grid-connected and islanded modes. Also, to
maintain the frequency and voltage stability as fast as possible whenever the
possibility of irregularity and disturbance are defined is the critical role which is
played by the energy storage system. The microgrid system used in this research
serves as the basis for both an overview of the microgrid's local functioning and an
effective control system that uses an artificial neural network controller to optimize
stability and improve the analysis of the microgrid's power irregularity. The proposed
microgrid is composed of wind sources, solar power sources, which will supply
power as efficiently as possible as input of the system and monitor the DC voltage
regulation and keep it stable at the DC bus of the microgrid. Due to the weakness of
the conventional PID controller itself to maintain the stability in no linear system and
adapt to the load and generators in the hybrid power system; the proposed system
comes to the existence and will be simulated on MATLAB Simulink and as a result,
the performance of the proposed ANN control system will be evaluated regarding the
conventional PID. The simulation results further demonstrated that the ANN
controller is more accurate and efficient than the PID and the adaptation capacity of
the ANN in the system is better than the PID as result the ANN outperform the PID
in regulation of the DC voltage.
Keywords: Artificial Neural Network, Battery Energy Storage System, Microgrid,
Proportional Integral Derivative, Power System, Photovoltaic System, Wind Energy
Conversion System.