Smart demand side management of low-voltage distribution networks using multi-objective decision making

F. Shahnia; M.T. Wishart; A. Ghosh; G. Ledwich; F. Zare

doi:10.1049/iet-gtd.2011.0781

Back

Smart demand side management of low-voltage distribution networks using multi-objective decision making

Journal article

Open access

Peer reviewed

Smart demand side management of low-voltage distribution networks using multi-objective decision making

F. Shahnia, M.T. Wishart, A. Ghosh, G. Ledwich and F. Zare

IET Generation, Transmission & Distribution, Vol.6(10)

2012

DOI: https://doi.org/10.1049/iet-gtd.2011.0781

Files and links (2)

pdf

smartside.pdfDownload View

Author’s Version Open Access

url

Link to Published Version *Subscription may be requiredView

Abstract

A novel intelligent online demand side management system is proposed for peak load management in low-voltage distribution networks. This method uses low-cost controllers with low-bandwidth two-way communication installed in custumers’ premises and at distribution transformers to manage the peak load while maximising customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by simulation of three different feeder types.

Details

Title: Smart demand side management of low-voltage distribution networks using multi-objective decision making
Authors/Creators: F. Shahnia (Author/Creator) - Curtin University
M.T. Wishart (Author/Creator) - Ergon Energy (Australia)
A. Ghosh (Author/Creator) - Queensland University of Technology
G. Ledwich (Author/Creator) - Queensland University of Technology
F. Zare (Author/Creator) - Queensland University of Technology
Publication Details: IET Generation, Transmission & Distribution, Vol.6(10)
Publisher: IET Digital Library
Identifiers: 991005544357807891
Copyright: © 2012 The Institution of Engineering and Technology
Murdoch Affiliation: Murdoch University
Language: English
Resource Type: Journal article

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Source: InCites

Metrics

224 File views/ downloads

49 Record Views

25 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Industry collaboration; Domestic collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.18 Power Systems & Electric Vehicles; 4.18.204 Smart Grid Optimization
Web Of Science research areas: Engineering, Electrical & Electronic
ESI research areas: Engineering