Title :
Robust design of multimachine power system stabilizers using simulated annealing
Author_Institution :
Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
fDate :
9/1/2000 12:00:00 AM
Abstract :
Robust design of multimachine power system stabilizers (PSSs) using simulated annealing (SA) optimization technique is presented in this paper. The proposed approach employs SA to search for optimal parameter settings of a widely used conventional fixed-structure lead-lag PSS (CPSS). The parameters of the proposed simulated annealing based power system stabilizer (SAPSS) are optimized in order to shift the system electromechanical modes at different loading conditions and system configurations simultaneously to the left in the s-plane. Incorporation of SA as a derivative-free optimization technique in PSS design significantly reduces the computational burden. One of the main advantages of the proposed approach is its robustness to the initial parameter settings. In addition, the quality of the optimal solution does not rely on the initial guess. The performance of the proposed SAPSS under different disturbances and loading conditions is investigated for two multimachine power systems. The eigenvalue analysis and the nonlinear simulation results show the effectiveness of the proposed SAPSS´s to damp out the local as well as the interarea modes and enhance greatly the system stability over a wide range of loading conditions and system configurations
Keywords :
eigenvalues and eigenfunctions; power system stability; simulated annealing; conventional fixed-structure lead-lag PSS; derivative-free optimization technique; eigenvalue analysis; electromechanical modes shifting; interarea modes; loading conditions; multimachine power system stabilizers; nonlinear simulation; optimal parameter settings; optimization technique; robust design; s-plane; simulated annealing; simulated annealing based power system stabilizer; system stability enhancement; Analytical models; Computational modeling; Design optimization; Eigenvalues and eigenfunctions; Power system analysis computing; Power system simulation; Power system stability; Power systems; Robustness; Simulated annealing;
Journal_Title :
Energy Conversion, IEEE Transactions on