Thumbnail
Access Restriction
Open

Author Zhang, Limei ♦ Yang, Honglei ♦ Lv, Jing ♦ Liu, Yongfu ♦ Tang, Wei ♦ {"id":"U67431594","contrib_type":"Guest Editor","orcid":"http://orcid.org/0000-0001-9522-790X","surname":"Fadhel","given-names":"Mustafa I."}
Source Hindawi
Content type Text
Publisher Hindawi
File Format PDF
Copyright Year ©2018
Language English
Abstract Integrating with analysis of uncertainties, this paper presented a multiobjective optimization approach for coordinating different DG from the perspective of Distribution Network Operator (DISOPER). Aiming to three uncertain factors including fuzzy variable, random variable, and interval variable, the information entropy and interval analysis methods are adopted to construct multistate models of multisource uncertainty. The information entropy method is to convert fuzzy variable into equivalent random variable. Interval analysis method is to transform random variables into interval variables by setting a confidence level. Then plenty of simulation analysis based on the small probability event and expectation are investigated to reduce the computational burden and eliminate invalid computation. Subsequently, multiobjective formulations based on multistate are built by analyzing systematical power loss, voltage quality, reliability, and environment change provide some reference for DISOPER in dealing with access of privately owned DG units. Furthermore, based on network topology analysis and modified nondominated sorting genetic algorithm (NSGA), a combinatorial optimization method is proposed to reduce search space and solve the constructed formulations efficiently. Simulations are carried out on IEEE 37-bus systems and results are presented and discussed.
ISSN 20900147
Learning Resource Type Article
Publisher Date 2018-11-15
Rights License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e-ISSN 20900155
Journal Journal of Electrical and Computer Engineering
Volume Number 2018
Page Count 13


Open content in new tab

   Open content in new tab