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| dc.contributor.author | WOLDEGEBRIEL, ASHEBIR | |
| dc.date.accessioned | 2024-12-11T06:36:10Z | |
| dc.date.available | 2024-12-11T06:36:10Z | |
| dc.date.issued | 2024-07 | |
| dc.identifier.uri | http://ir.bdu.edu.et/handle/123456789/16354 | |
| dc.description.abstract | An interconnected power system is continuously interrupted in many ways, which leads to a loss of stability. Either a big or minor disturbance is what leads to instability. In a synchronous generator, this disruption causes electromechanical oscillations. Automatic Voltage Regulation (AVR) plays a very important role to maintain system voltage and reactive power flow during any large disturbances. To improve synchronous generator stability in both steady state and faulty conditions, the Tis Abay II hydropower Plant employs AVR with classical controller. Better dynamic response is provided by classical controllers, such as PI and PID controllers, which are also relatively easy to build; however, they have a longer settling time and a maximum overshoot. When processing imperfect information, intelligent controllers can quickly make decisions and exhibit high adaptability to changing conditions. This thesis work presents the application of an intelligent AVR such as artificial neural networks (ANN) and fuzzy logic controller (FLC) for a hydropower system. Several scenarios have been used to test the system's performance (with AVR, PID, FLC, FLC-PID, ANN, and ANN-PID for comparison analysis, both under normal and faulty conditions). The ANN techniques are used for AVR of interconnected hydro power systems. The feed forward neural network controllers are developed and trained using Lavenberg-Marquardt (LM) back propagation algorithm under supervised training method with adequate amount of data that are generated. Under both steady state and transient conditions, ANN-PID significantly decreases settling time and dampens electromechanical oscillations of synchronous generators' rotor speed, load angle, electrical torque, and active power. The design was completed using the MATLAB/Simulink software, and the rise time, settling time, steady state error, and overshoot are all improved. The designed ANN-PID gave a rotor speed response with settling time 5sec and overshoot 0.4%, This is a better result than that of AVR based Excitation system with PID and FLC-PID controller with settling time and overshoot of 12sec, 8sec, 7.8sec and 1.1%, 1.1%, 1% respectively. Keywords: AI, ANN, AVR, FLC, PID, Lavenberg-Marquardt (LM), Transient Stability. | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Electrical and Computer Engineering | en_US |
| dc.title | COMPARATIVE STUDY BETWEEN FUZZY-PID AND ANN-PID CONTROLLERS FOR POWER SYSTEM TRANSIENT STABILITY ENHANCEMENT [CASE STUDY: TIS ABAY II HYDRO POWER PLANT] | en_US |
| dc.type | Thesis | en_US |
