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Multiple operating conditions in power systems including wind power sources significantly affect the damping of low frequency oscillation modes due to diverse generating and loading conditions, random wind speeds, line outage contingencies, etc. To cope with multiple operating conditions, this paper proposes the new parameter optimization technique of the power system stabilizer (PSS) and the doubly-fed induction generator (DFIG) wind turbine with the power oscillation damper (POD) based on the probability method. Different operating conditions are randomly generated by Monte Carlo simulation. Under the generated operating points, the particle swarm optimization of PSS and POD parameters is carried out to achieve the highest probability that the damping ratios of all oscillation modes are greater than the desired damping ratio for all operating points. Study results in the IEEE New England 39-bus system indicate that under the occurrence of faults, the PSS and POD optimized by the proposed method yield better stabilizing performance than the conventional PSS and POD over a wide range of operating points.

Power oscillation damping control by PSS and DFIG wind turbine under multiple operating conditions