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load frequency control of micro hydro power using fuzzy with particle swarm optimization a case study on jimma zone

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dc.contributor.author TESFAYE, ZERIHUN
dc.contributor.author Shiferaw, Dereje
dc.date.accessioned 2023-04-04T13:22:18Z
dc.date.available 2023-04-04T13:22:18Z
dc.date.issued 2023-02-26
dc.identifier.uri https://repository.ju.edu.et//handle/123456789/8102
dc.description.abstract Micro Hydro-Power Plants are a good solution for serving small community standalone power customers in places, not on the national distribution network. Frequency variations in a power system occur because of an imbalance between generation and load. When the frequency value of a power system reaches the emergency condition, the control strategy is initiated. If the total generation power is more than the total load power the system frequency will rise; otherwise, if the total generation power is less than the total load power, the system frequency will fall. The frequency controller controls the water flow rate by acting on the electric valves. When the customer loads are increased and decreased, the water flow needs to be proportionally regulated to keep the frequency constant. The system components may get damaged if the frequency is not maintained constant. Hence proper frequency control is very critical to the operation of the microgrid. In this thesis, a fuzzy logic-based frequency controller is designed and simulated. The optimal fuzzy membership functions of the fuzzy-based controllers were determined using Particle Swarm Optimization. A micro hydro power plant of menko toli was developed in MATLAB Simulink and the effectiveness of the controller designed is tested. The results were presented in this thesis. It also shows the results of a comparison of the PID controller and the developed fuzzy controller has been compared and presented based on overshoot and undershoots, peak, and the peak time of the system response. The simulation result showed that the most accurate and precise result was given by Fuzzy particle swarm optimization (FPSO) with a step response of Rise Time of 0.49msec, Settling Time of 2.3547 sec, overshoot of 0%, and Peak Time of 8.4m sec. The simulation results demonstrate that the viability of the designed fuzzy with particle swarm optimization-based controller is best in no-load and when a load is added to the micro hydro power plant en_US
dc.language.iso en_US en_US
dc.subject Load Frequency Controllers (LFC en_US
dc.subject Fuzzy Particle Swarm Optimization en_US
dc.subject Micro hydro power plant en_US
dc.title load frequency control of micro hydro power using fuzzy with particle swarm optimization a case study on jimma zone en_US
dc.type Thesis en_US


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