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A good quality stability model is a key factor for accurate power system operations.Inaccurate parameters of the stability models affect the decision making which paves the way for serious consequences. Thus, it is necessary to calibrate the stability model parameters in a regular manner. There are several calibration methods in the literature which are based on simultaneous estimation of the parameters and states. However, not all of the model parameters are well estimable simultaneously. Simultaneous estimation of parameters with high collinearity may result in biased calibration results. In this paper, the trajectory sensitivity method is used to detect the sensitive parameters and construct the sensitivity matrix. Then, parameters with high linear dependency are identified using the sensitivity matrix. It is shown that, despite the high sensitivity of a parameter, its estimability degrades as the collinearity with other parameters increase. In this paper an identifiability analysis that detects the collinearity among the sensitive parameters is proposed. The proposed method is validated using WSCC 9-Bus System. [ABSTRACT FROM AUTHOR]

• Applicable to systems measured by both SCADA and PMUs. • Detects ill-conditioning due to parameters, error variances, and topology. • Computational performance is comparable with that of the FD-WLS. • Accuracy is comparable with that of the WLS. • Improved bad data processing for ill-conditioned systems. Considering the increase in power system size and the number of PMUs, the utilization of a computationally efficient yet accurate static state estimator is crucial. The fast-decoupled WLS estimator (FD-WLS) is the most common method employed in industrial applications, thanks to its computational efficiency and ease of implementation. However, it is known that FD-WLS fails in the presence of an ill-conditioned power system, e.g., a power system with high R/X ratio and large difference between measurement error variances. This paper proposes a partitioning strategy for ill-conditioned power systems. The proposed method forms two types of sub-systems, such that one can apply FD-WLS in the type-1 sub-systems, and conventional formulation of WLS should be applied in the type-2 sub-systems. The utilization of the proposed method enables a computational performance comparable to that of FD-WLS and an accuracy comparable to that of the centralized solution. [ABSTRACT FROM AUTHOR]