DocumentCode
1757182
Title
A Monte Carlo Simulation Platform for Studying Low Voltage Residential Networks
Author
Torquato, Ricardo ; Qingxin Shi ; Wilsun Xu ; Freitas, Wilson
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
Volume
5
Issue
6
fYear
2014
fDate
Nov. 2014
Firstpage
2766
Lastpage
2776
Abstract
The smart grid vision has resulted in many demand side innovations such as nonintrusive load monitoring techniques, residential micro-grids, and demand response programs. Many of these techniques need a detailed residential network model for their research, evaluation, and validation. In response to such a need, this paper presents a sequential Monte Carlo (SMC) simulation platform for modeling and simulating low voltage residential networks. This platform targets the simulation of the quasi-steady-state network condition over an extended period such as 24 h. It consists of two main components. The first is a multiphase network model with power flow, harmonic, and motor starting study capabilities. The second is a load/generation behavior model that establishes the operating characteristics of various loads and generators based on time-of-use probability curves. These two components are combined together through an SMC simulation scheme. Four case studies are presented to demonstrate the applications of the proposed platform.
Keywords
Monte Carlo methods; distributed power generation; load flow; power system harmonics; smart power grids; SMC simulation scheme; demand response programs; demand side innovations; load-generation behavior model; low voltage residential networks; motor starting; multiphase network model; nonintrusive load monitoring techniques; power flow; power harmonic; quasi-steady-state network condition; residential microgrids; sequential Monte Carlo simulation platform; smart grid vision; time 24 h; time-of-use probability curves; Home appliances; Load modeling; Low voltage; Microgrids; Monte Carlo methods; Power quality; Demand response; low voltage residential networks; microgrids; network simulation; power quality;
fLanguage
English
Journal_Title
Smart Grid, IEEE Transactions on
Publisher
ieee
ISSN
1949-3053
Type
jour
DOI
10.1109/TSG.2014.2331175
Filename
6853399
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