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- Title
Space Transformation-Based Interdependency Modelling for Probabilistic Load Flow Analysis of Power Systems.
- Authors
LI Xue; CHEN Hao-jie; LU Pan; DU Da-jun
- Abstract
Dependence among random input variables affects importantly the results of probabilistic load flow (PLF), system economic operation, and system security. To solve this problem, the main objectiveness of the paper is to analyze the performance of several schemes/or simulating correlated variables combined with the point estimate method (PEM). Unllke the existing works that considering one singl e scheme combin ed with Monte Carlo simulation (MCS) or PEM, by neglecting the correl ation among random input variables, four sche mes w ere presented/or disposing the dependence of correlated random variabl es, including Nata/trans/ormation / polynomial normal trans/ormation (PNT) combined with orthogonal trans/ormation (OT)/el em en tary transformation (ET). Combining with the 2m + 1 approach of PEM, a space transformation-based formulation was proposed and adopted for solving the PLF. The proposed approach is applied in the mod/ed IEEE 30-bus system whill considering correlated wind generations and load demands. Numerical results show the of the proposed approach compared with those obtained from the MCS. Results also show that the scheme of combining Nata/transformation and ET with PEM provides the best performance.
- Subjects
ELECTRIC power systems; PROBABILISTIC number theory; LOAD flow control (Electric power systems); ORTHOGONAL trajectories; FIX-point estimation
- Publication
Journal of Donghua University (English Edition), 2016, Vol 33, Issue 5, p734
- ISSN
1672-5220
- Publication type
Article