Improving the Stability of An Interconnected Power System Using Genetic Eigenvalue Technique



Improving the power stability of an interconnected Nigerian 330KV 48 bus power system was developed using Genetic Eigenvalue Technique to mitigate the challenges of proper placement of power system stabilizer due to its highly dynamic and nonlinear nature. In order to eliminate load losses, equipment malfunctioning, and other quality issues, unnecessary tripping and cascaded failures in system network, power system stabilizers are installed to improve system stability. The operational and process data of 330KV power system grid network, cable distance meter (CDM-75), Transmission line calculator (AWR version) were sampled at Transmission Company of Nigeria Osogbo, Osun State of Nigeria. The Genetic Eigenvalue technique was used to generate eigenvalues, damping ratios and participation factors for proper placement of PSS (Power System Stabilizers) to mitigate the effect of transmission line and power plant outage contingencies. The PSSs were placed using Genetic Eigenvalue Analysis technique performed better than PSS placed based on conventional Arnoldi eigenvalue technique. The simulation results for base case voltage profile and for the trajectories of the impact of contingencies were plotted on the MATLAB/SUMULINK environment. From the output plots, the percentage of voltage instability suppression time improvement of Genetic technique over Arnoldi is 51.86%. Oscillation suppression at generator 1, is 74%, and that of generator 3 is 79%, and finally at generator 5 is 76.98%. PSS placed on Nigerian 330KV 48 bus plant and transmission line of an interconnected power system case study power system based on  genetic analysis suppressed voltage oscillation faster compared to the time it took the PSS based on the conventional Arnoldi eigenvalue analysis technique.

Keywords: Power Stability- Genetic Eigenvalue, ArnoldiEigenvalue, PSS.

DOI: 10.7176/JETP/11-1-03

Publication date: January 31st 2021

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ISSN (Paper)2224-3232 ISSN (Online)2225-0573

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