Towards Enabling a Comprehensive Criticality Analysis in State Estimation

Critical Data Visualization to Enhance Protection Schemes for State Estimation

“…As mentioned in the introduction, this paper's objective is not to address the methods published so far on CA. For this purpose, sufficient material is supplied by the research reported in [16], [17], [18], [19], [20], [21] . Here, the interest falls upon how to achieve a better understanding, interpretation, and practical application of CA.…”

“…The problem of efficiently computing critical tuples of diverse cardinalities has been recently addressed [17], gaining substantial progress in [20]. However, CA results are tricky to interpret and synthesize, mainly due to the problem's combinatorial nature.…”

“…There are studies to identify not only C1s and C2s but Cks, composed of measurements, measuring units (devices used to acquire a group of measurements at a given bus), and network branches [18], [19]. High-performance computation platforms built upon GPUs have been developed to make a fast, thorough CA [20]. It is noteworthy that CA constitutes a tricky problem of compute-intensive combinatorial nature.…”

“…It is worth illustrating the CA results obtained using a highperformance computation platform [20] on a nine-bus measuring system [21] with G depicted in Fig. 1.…”

“…The creation of G(V, E, k) is obtained using Algorithm 1. Matrix A (Adjacency, defined above) and the SE process matrices [1], [ CA is performed (Step 4) through the high-performance computation platform detailed in [20]. In the sequel, Algorithm 2 is described as a fast but suboptimal procedure for identifying Ck-sets; it searches only for maximal cliques.…”