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  • Rule-based Energy Management System in an Experimental Microgrid with the Presence of Time of Use Tariffs

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    Author(s)
    Moghimi, Mojtaba
    Leskarac, Domagoj
    Bennett, Christopher
    Lu, Junwei
    Stegen, Sascha
    Griffith University Author(s)
    Lu, Junwei
    Bennett, Christopher J.
    Stegen, Sascha
    Leskarac, Dom
    Moghimi, Mojtaba
    Year published
    2016
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    Abstract
    This paper aims to investigate a method of peak load shaving through the utilization of solar PV and battery energy storage whilst creating a cost effective Energy Management System (EMS). This is achieved by utilizing a rule-sets to manage and optimize a scheduling system with a forecasting algorithm. As Time of Use (ToU) tariffs change throughout the day, a cost benefit can be achieved when a smart energy storage system is appropriately employed. The EMS operation is tested on an experimental microgrid with commercial load considering payback period calculation.This paper aims to investigate a method of peak load shaving through the utilization of solar PV and battery energy storage whilst creating a cost effective Energy Management System (EMS). This is achieved by utilizing a rule-sets to manage and optimize a scheduling system with a forecasting algorithm. As Time of Use (ToU) tariffs change throughout the day, a cost benefit can be achieved when a smart energy storage system is appropriately employed. The EMS operation is tested on an experimental microgrid with commercial load considering payback period calculation.
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    Journal Title
    MATEC Web of Conferences
    Volume
    70
    DOI
    https://doi.org/10.1051/matecconf/20167010011
    Copyright Statement
    © The Authors, published by EDP Sciences, 2016 This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Power and Energy Systems Engineering (excl. Renewable Power)
    Publication URI
    http://hdl.handle.net/10072/123647
    Collection
    • Journal articles

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