کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6776118 | 513527 | 2015 | 23 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quasi real-time ZIP load modeling for Conservation Voltage Reduction of smart distribution networks using disaggregated AMI data
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
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چکیده انگلیسی
This paper aims to investigate quasi real-time ZIP load models for new Smart Grid-based Volt-VAR Optimization (VVO) techniques. As recent VVO solutions are able to perform in quasi real-time using Advanced Metering Infrastructure (AMI) data, more accurate load modeling could give distribution network operators and/or planners more precise Conservation Voltage Regulation (CVR) and energy saving values at each operating time stage. Furthermore, more accurate load modeling of each quasi real-time stage could improve VVO efficiency. As type, amount and operating time of each residential appliance varies throughout a day, this paper aims to discover ZIP load model of each quasi real-time stage separately through disaggregated data (i.e. decomposing residential load consumption into home appliance consumptions). This paper shows that the energy conservation achieved by CVR operation through presented quasi real-time ZIP load modeling could lead AMI-based VVO solutions to higher level of accuracy and data resolution compared with conventional techniques. Therefore, this paper primarily introduces a new quasi real-time AMI-based VVO engine. Then, it investigates ZIP load model of each quasi real-time stage through statistical data to conserve energy consumption. To check the authenticity and the applicability of presented model in a whole system, 33-node distribution feeder is employed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sustainable Cities and Society - Volume 19, December 2015, Pages 1-10
Journal: Sustainable Cities and Society - Volume 19, December 2015, Pages 1-10
نویسندگان
Moein Manbachi, Hassan Farhangi, Ali Palizban, Siamak Arzanpour,