  The increasing uncertainty level caused by growing renewable energy sources
(RES) and aging transmission networks poses a great challenge in the assessment
of total transfer capability (TTC) and available transfer capability (ATC). In
this paper, a novel data-driven sparse polynomial chaos expansion (DDSPCE)
method is proposed for estimating the probabilistic characteristics (e.g.,
mean, variance, probability distribution) of probabilistic TTC (PTTC).
Specifically, the proposed method, requiring no pre-assumed probabilistic
distributions of random inputs, exploits data sets directly in estimating the
PTTC. Besides, a sparse scheme is integrated to improve the computational
efficiency. Numerical studies on the modified IEEE 118-bus system demonstrate
that the proposed DDSPCE method can achieve accurate estimation for the
probabilistic characteristics of PTTC with a high efficiency. Moreover,
numerical results reveal the great significance of incorporating discrete
random inputs in PTTC and ATC assessment, which nevertheless was not given
sufficient attention.
