A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems With Renewables

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) available (ATC). In this paper, novel data-driven sparse polynomial chaos expansion (DDSPCE) method is proposed for estimating probabilistic characteristics (e.g., mean, variance, probability distribution) TTC (PTTC). Specifically, method, requiring no pre-assumed distributions random inputs, exploits data sets directly PTTC. Besides, scheme integrated to improve computational efficiency. Numerical studies on modified IEEE 118-bus system demonstrate that DDSPCE can achieve accurate estimation PTTC with high Moreover, numerical results reveal significance incorporating discrete inputs ATC assessment, which nevertheless was not given sufficient attention.