DocumentCode
684312
Title
Power quality assessment of offshore wind farm based on PSCAD/EMTDC models
Author
Ruixiang Sun ; Wenjun Yan ; Qiang Yang ; Zhejing Bao ; Jie Zhang
Author_Institution
Coll. of Electr. Eng., Zhejiang Univ., Hangzhou, China
fYear
2013
fDate
19-21 Oct. 2013
Firstpage
339
Lastpage
344
Abstract
This work aims to carry out an assessment of power quality at the Point of Common Coupling (PCC) in the scenario of offshore wind farm integrated into the power network whilst reduce the impact of index discrepancy and uncertainty. We acquire the judgmental matrix by using analytic hierarchy process (AHP) and obtain the index weights for power quality assessment by combining the compatibility matrix methodology and entropy weight method with connection degree modeling in Set Pair Analysis (SPA) theory. The compatibility matrix method can effectively address the challenge that it is difficult to inspect the consistency by judgmental matrix. The power quality index weights determination can vary for different experts. The existing analytical solutions have not thoroughly considered the issue of index discrepancy and uncertainty. We adopt SPA theory to cope with and minimize the certainty and uncertainty which are introduced from the differences of subjective knowledge of experts. The proposed assessment approach is studied through numerical analysis based on the power quality measurements obtained from PSCAD/EMTDC models. The statistical and fuzzy judgmental method is applied to process the measurements. As a result, the power quality assessment can be estimated.
Keywords
offshore installations; power system CAD; wind power plants; PSCAD/EMTDC models; analytic hierarchy process; connection degree modeling; fuzzy judgmental method; index discrepancy; judgmental matrix; offshore wind farm; point of common coupling; power quality assessment; power quality index; set pair analysis theory; statistical method; uncertainty; Analytical models; EMTDC; Numerical models; PSCAD; Power measurement; Power quality; Weaving;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (ICACI), 2013 Sixth International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4673-6341-9
Type
conf
DOI
10.1109/ICACI.2013.6748527
Filename
6748527
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