Power system dynamic stability enhancement via coordinated design of PSSs and SVC-based controllers using hierarchical real coded NSGA-II

Optimal coordination and tuning of PSSs and SVC-based controllers to enhance the dynamic power system stability using hierarchical non-dominated sorting genetic algorithms-II (HNSGA-II) is presented in this paper. The coordinated design problem of robust excitation and SVC-based controllers over a wide range of system configurations is formulated as a multi objective optimization problem with eigenvalue-based objective functions comprising a damping ratio, the number of PSSs and SVC-based controllers. The multi objective optimization will be solved by a HNSGA-II which is a metaheuristic based technique. The damping controllers are tuned to simultaneously shift the lightly damped and undamped electromechanical modes of all plants to a prescribed zone in the s-plane, and to self identify the appropriate choice of PSS and SVC-based controlled locations. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping ratio of the lightly damped electromechanical modes, the number of damping controller. The efficacy of this technique in damping local and interarea modes of oscillations in multimachine power systems is confirmed through eigenvalues analysis over many scenarios.