Developing feedback model for power system dynamic sensitivity analysis

Since sensitivity analysis provides information on changes of the system dynamics with respect to changes of system parameters, it has been long recognized as an important tool for power system small-signal stability analysis and controller designs. Sensitivity analysis is now much more important due to all the anticipated changes of future power systems, so more efficient and feasible methods are needed. The current sensitivity analysis methods are either simulation based or eigenvalue based. The eigenvalues and/or the time domain trajectories of the investigated system are solved for scenarios both before and after the parameter changes to evaluate the impacts of these changes on the system dynamics. However, both methods are actually numerically based, so often insufficient in fully revealing system physical characteristics. This paper analyzes the drawbacks of the available methods for analyzing the dynamic impacts of parameter changes in a power system and then develops a feedback-based model for sensitivity analysis. The model is easier to identify the dynamic interactions of components; meanwhile, it also offers a new perspective on sensitivity analysis from the frequency domain. Case studies of increasing complexity demonstrate fully that the application of the proposed method reveals new insights on power system dynamics that conventional methods could not do.