Coordinated parameter design of STATCOM stabiliser and PSS using MSSA algorithm

A nonlinear programming model for simultaneously coordinated parameters design of power system stabiliser (PSS) and thyristor-based static synchronous compensator (STATCOM) stabiliser is presented. A modified simplex-simulated annealing (MSSA) algorithm is developed for solving the programming model. The MSSA can shift all eigenvalues of the system into specified regions on the s-plane for the preconfigured multiple operational points. The MSSA algorithm combines the merits of conventional simplex and simulated annealing methods together, such as global optimal solution, robustness to initial parameter settings and acceptable convergence speed and so on and also improves the ability of solving constrained optimisation problems. Numerical results including eigenvalue analysis and the nonlinear simulation on the 10-generator New England test power system are presented to indicate the effectiveness and potential engineering applications of the MSSA algorithm.

[1]  Glauco N. Taranto,et al.  Simultaneous tuning of power system damping controllers using genetic algorithms , 2000 .

[2]  Emile H. L. Aarts,et al.  Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing , 1990, Wiley-Interscience series in discrete mathematics and optimization.

[3]  P. Kundur,et al.  Application of Power System Stabilizers for Enhancement of Overall System Stability , 1989, IEEE Power Engineering Review.

[4]  Singiresu S. Rao,et al.  Optimization Theory and Applications , 1980, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  K. R. McClymont,et al.  Effect of High-Speed Rectifier Excitation Systems on Generator Stability Limits , 1968 .

[6]  P. Kundur,et al.  Power system stability and control , 1994 .

[7]  Nadarajah Mithulananthan,et al.  Comparison of PSS, SVC, and STATCOM controllers for damping power system oscillations , 2003 .

[8]  M. A. Abido,et al.  Robust design of multimachine power system stabilizers using simulated annealing , 2000 .

[9]  K. R. Padiyar,et al.  Tuning and performance evaluation of damping controller for a STATCOM , 2003 .

[10]  M. J. Gibbard,et al.  Robust design of fixed-parameter power system stabilisers over a wide range of operating conditions , 1991 .

[11]  Ganapati Panda,et al.  Application of a multivariable feedback linearization scheme for STATCOM control , 2002 .

[12]  M. A. Abido Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization , 2002, IEEE Power Engineering Review.

[13]  H. F. Wang,et al.  Phillips-Heffron model of power systems installed with STATCOM and applications , 1999 .

[14]  Y.-N. Yu,et al.  Pole-placement power system stabilizers design of an unstable nine-machine system , 1990 .

[15]  S. K. Tso,et al.  Refinement of conventional PSS design in multimachine system by modal analysis , 1993 .

[16]  Yuang-Shung Lee,et al.  STATCOM controller design for power system stabilization with sub-optimal control and strip pole assignment , 2002 .

[17]  V. A. Maslennikov,et al.  Method and software for coordinated tuning of power system regulators , 1997 .

[18]  S. Abe,et al.  A New Power System Stabilizer Synthesis in Multimachine Power Systems , 1983, IEEE Power Engineering Review.

[19]  H. F. Wang,et al.  Indices for selecting the best location of PSSs or FACTS-based stabilisers in multimachine power systems: a comparative study , 1997 .

[20]  M. A. Abido,et al.  Optimal multiobjective design of robust power system stabilizers using genetic algorithms , 2003 .

[21]  Chern-Lin Chen,et al.  Coordinated Synthesis of Multimachine Power System Stabilizer Using an Efficient Decentralized Modal Control (DMC) Algorithm , 1987, IEEE Transactions on Power Systems.

[22]  B. C. Papadias,et al.  Power System Stabilization via Parameter Optimization - Application to the Hellenic Interconnected System , 1987, IEEE Transactions on Power Systems.

[23]  Y. L. Abdel-Magid,et al.  Optimal design of power system stabilizers using evolutionary programming , 2002 .