Quasi real-time ZIP load modeling for Conservation Voltage Reduction of smart distribution networks using disaggregated AMI data

被引:14
作者
Manbachi, Moein [1 ]
Farhangi, Hassan [2 ]
Palizban, Ali [2 ]
Arzanpour, Siamak [1 ]
机构
[1] SFU, Sch Mechatron Syst Engn, 250,13450,102nd Ave, Surrey, BC V3T 0A3, Canada
[2] BCIT, Burnaby, BC V5G 3H2, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Conservation Voltage Reduction; Disaggregation; Distribution network; Energy conservation; Smart Grid; Volt-VAR Optimization; ZIP load model; CVR;
D O I
10.1016/j.scs.2015.06.004
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 10
页数:10
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