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Due to the deregulation of the electrical market, difficulty in acquiring rights-ofway to build new transmission lines, and steady increase in power demand, <br /> <br /> <br /> maintaining power system stability becomes evermore difficult and a very challenging problem. In large...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/15664 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Due to the deregulation of the electrical market, difficulty in acquiring rights-ofway to build new transmission lines, and steady increase in power demand, <br />
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maintaining power system stability becomes evermore difficult and a very challenging problem. In large, interconnected power systems, as the tie lines become more stressed, the small-signal stability problem often occurs. This kind of stability problem can be observed in the appearance of lightly damped lowfrequency oscillations. These oscillations, if increasing in magnitude, can sever <br />
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the system entirely and finally result in system collapse. Therefore, proper control design becomes essential for improvement of operation and control of power systems. <br />
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The aim of this final project is to examine the ability of Power System Stabilizer (PSS) to damp low-frequency oscillations in a power system. PSS is a supplementary control device which acts through the generator excitation system for additional damping torque. Uncoordinated control interaction of multiple PSS’s results in destabilizing interactions among the controllers, further exacerbating the overall system damping ratio. Hence, simultaneous coordinated tuning is needed. The problem of optimal placement and tuning of single and multiple PSS controllers are solved using the Genetic Algorithms (GA) with the <br />
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purpose of finding the most suitable locations and controller parameters to maximize the overall system damping. The proposed method for simultaneous placement and tuning of power system damping controllers with PSS, based on genetic algorithms, is tested on the twoarea four-generators power system. The effectiveness of this method is confirmed through transient nonlinear simulation and eigenvalues analysis. |
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