Open AccessProbabilistic evaluation of available load supply capability of distribution networks as an index for wind turbines allocation
Author(s) -
Arabi Alireza,
Ramezani Maryam,
Falaghi Hamid
Publication year - 2016
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2015.0350
Subject(s) - wind power , probabilistic logic , cholesky decomposition , computer science , mathematical optimization , latin hypercube sampling , reliability engineering , control theory (sociology) , monte carlo method , engineering , mathematics , electrical engineering , statistics , eigenvalues and eigenvectors , physics , control (management) , quantum mechanics , artificial intelligence
This study deals with placement of wind turbines in distribution networks for maximising the probabilistic index of load supply capability (LSC). To calculate this index, one of the most accurate and efficient probabilistic simulation methods known as Latin hypercube sampling is used. Variations of load and output power of wind turbines are considered in the probabilistic evaluation of LSC. Moreover, the constraints of maximum voltage drop and current carrying capacity of conductors are considered as the limiting factors of the network LSC. Since there is a correlation between the network load and the output power of wind turbines, considering this correlation in simulations will push the results closer to reality. Therefore, the Cholesky decomposition approach is used to take into account the correlation between the input variables of the problem. Casestudiesare carried out on the 33‐bus IEEE distribution network. The results of case studies demonstrate the effectiveness of the proposed methodology.