Computational framework combining static and transient power system security evaluation using uncertainties

• Reviews previous probabilistic small signal and transient stability analyses.
• Proposes new taxonomy and a decoupled treatment for power system uncertainties.
• Suggests ad-hoc probabilistic state spaces for static and dynamic evaluations.
• Develops new set of probabilistic static and transient security indices.
• Illustrates applications of proposed new concepts using well known test system.

This paper presents a simplified but effective procedure to represent power system uncertainties that allow the development of a computational tool to tackle the power system probabilistic security problem from both the small signal stability (SSS) perspective, and the transient stability (TRS) analysis perspective. A set of examples using the New England test-system is presented and discussed. Among the advantages of the suggested method, the following points are evident: (i) the ability to discriminate between the three types of uncertainties (scenarios, fault events, and noise types) that permeate power systems and that are relevant to the system security; (ii) the capacity to use existing traditional tools from both small signal dynamic analysis and transient stability analysis to adapt them easily to the well-established concept of probabilistic adequacy assessment, without resorting to abstruse and hard-to-implement theoretical techniques; (iii) the enormous advantage of usual availability for the required statistical data (no hard-to-collect data are required); and (iv) proposal of a conceptual procedure that renders a highly combinatorial problem amenable to current state-of-the-art hardware resources, within acceptable limits of computational burden. Important practical results that one may wish to highlight are related to the effective representation of noise uncertainties through a straightforward combination of weighted histograms, and the successful performance of the new Apparent Stability Index – ASI.