A Monte Carlo Simulation Platform for Studying Low Voltage Residential Networks

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. Index Terms-Demand response, low voltage residential networks, microgrids, network simulation, power quality.1949-3029 c 2014 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.Ricardo Torquato (S'11) is currently pursuing the M.Sc. degree in electrical engineering from the University of Campinas, Campinas, Brazil. He is currently a Visiting Student with the University of Alberta, Edmonton, AB, Canada. His research interests include power quality and analysis of distribution systems.Qingxin Shi (S'11) is currently pursuing the M.Sc. degree in electrical engineering from the University of Alberta, Edmonton, AB, Canada.His research interests include power quality and power signaling.Wilsun Xu (M'90-SM'95-F'05) received the Ph.D. degree in electrical engineering from the

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