کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6859422 | 1438702 | 2018 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-objective MILP model for distribution systems reliability optimization: A lightning protection system design approach
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
Lightning phenomenon is the main cause of power systems faults. These faults may cause momentary or permanent service interruptions, thus system reliability is inherently interdependent with lightning phenomenon. A literature review will show that state-of-the-art solutions have yet to present mathematical explicit models for the interdependency of such two phenomena. In this context, this paper presents a multi-objective mixed integer linear programing (MILP) model for distribution systems reliability optimization while considering lightning phenomenon interdependency. The presented multi-objective MILP model aims the simultaneous minimization of SAIFI and MAIFIE reliability indices and associated costs. These goals are achieved by optimizing the lightning protection system design, which includes selection and allocation of different types of grounding systems along distribution feeders, while considering simultaneously network characteristics. Validation is done using real-life 81 bus 23â¯kV distribution network data. Test results highlight the efficiency of the presented model in improving system reliability while reducing associated costs. The ease of implementation of design, formulation of parameters and encouraging test results indicate potential for real-life application. The multi-objective MILP model is currently used by a distribution utility as a reliability-oriented tool.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 98, June 2018, Pages 256-268
Journal: International Journal of Electrical Power & Energy Systems - Volume 98, June 2018, Pages 256-268
نویسندگان
Arturo Suman Bretas, Roberto José Cabral, Roberto Chouhy Leborgne, Gustavo Dorneles Ferreira, John Armando Morales,