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Probabilistic analysis to analyze uncertainty incorporating copula theory

Li, B ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1007/s42835-021-00863-w
  3. Publisher: Korean Institute of Electrical Engineers , 2022
  4. Abstract:
  5. The emerging trend of distribution generation with existing power system network leads uncertainty factor. To handle this uncertainty, it is a provocation for the power system control, planning, and operation engineers. Although there are numerous techniques to model and evaluate these uncertainties, but in this paper the integration of Copula theory with Improved Latin-hypercube Sampling (ILHS) are incorporated for Probabilistic load Flow (PLF) evaluation. In probabilistic research approaches, the dominant interest is to achieve appropriate modelling of input random variables and reduce the computational burden. To address the said problem, Copula theory is applied to execute the modelling and interaction among input random variables of the active power system network. Considering the real discrete data, the ILHS is adopted. The load flow accessibility of the power system is carefully modeled by considering the dependence and uncertainty factors. Modified IEEE 14-bus system is employed to analyze the efficiency and performance of the proposed model using active power system network. Output power of two wind energy farms situated in New Jersey are obtained for accuracy comparison. The proposed technique shows the superiority in PLF evaluation. © 2021, The Korean Institute of Electrical Engineers
  6. Keywords:
  7. Copula Theory ; Correlation ; Modified Latin-Hypercube Sampling ; Monte Carlo Simulation ; Computation theory ; Electric load flow ; Electric power system planning ; Random variables ; Wind power ; Distribution generation ; Efficiency and performance ; Input random variables ; Latin hypercube sampling ; Power system controls ; Power system networks ; Probabilistic analysis ; Probabilistic load flow ; Uncertainty analysis
  8. Source: Journal of Electrical Engineering and Technology ; Volume 17, Issue 1 , 2022 , Pages 61-71 ; 19750102 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s42835-021-00863-w