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    An Optimization Framework for Decision Making in Large, Collaborative Energy Supply Systems

    Source: Journal of Energy Resources Technology:;2016:;volume( 138 ):;issue: 005::page 51601
    Author:
    DuPont, Bryony
    ,
    Azam, Ridwan
    ,
    Proper, Scott
    ,
    Cotilla
    ,
    Hoyle, Christopher
    ,
    Piacenza, Joseph
    ,
    Oryshchyn, Danylo
    ,
    Zitney, Stephen E.
    ,
    Bossart, Stephen
    DOI: 10.1115/1.4032521
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As demand for electricity in the U.S. continues to increase, it is necessary to explore the means through which the modern power supply system can accommodate both increasing affluence (which is accompanied by increased percapita consumption) and the continually growing global population. Though there has been a great deal of research into the theoretical optimization of largescale power systems, research into the use of an existing power system as a foundation for this growth has yet to be fully explored. Current successful and robust power generation systems that have significant renewable energy penetration—despite not having been optimized a priori—can be used to inform the advancement of modern power systems to accommodate the increasing demand for electricity. This work explores how an accurate and stateoftheart computational model of a large, regional energy system can be employed as part of an overarching power systems optimization scheme that looks to inform the decision making process for next generation power supply systems. Research scenarios that explore an introductory multiobjective power flow analysis for a case study involving a regional portion of a large grid will be explored, along with a discussion of future research directions.
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      An Optimization Framework for Decision Making in Large, Collaborative Energy Supply Systems

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    http://yetl.yabesh.ir/yetl1/handle/yetl/160891
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    contributor authorDuPont, Bryony
    contributor authorAzam, Ridwan
    contributor authorProper, Scott
    contributor authorCotilla
    contributor authorHoyle, Christopher
    contributor authorPiacenza, Joseph
    contributor authorOryshchyn, Danylo
    contributor authorZitney, Stephen E.
    contributor authorBossart, Stephen
    date accessioned2017-05-09T01:27:43Z
    date available2017-05-09T01:27:43Z
    date issued2016
    identifier issn0195-0738
    identifier otherjert_138_05_051601.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/160891
    description abstractAs demand for electricity in the U.S. continues to increase, it is necessary to explore the means through which the modern power supply system can accommodate both increasing affluence (which is accompanied by increased percapita consumption) and the continually growing global population. Though there has been a great deal of research into the theoretical optimization of largescale power systems, research into the use of an existing power system as a foundation for this growth has yet to be fully explored. Current successful and robust power generation systems that have significant renewable energy penetration—despite not having been optimized a priori—can be used to inform the advancement of modern power systems to accommodate the increasing demand for electricity. This work explores how an accurate and stateoftheart computational model of a large, regional energy system can be employed as part of an overarching power systems optimization scheme that looks to inform the decision making process for next generation power supply systems. Research scenarios that explore an introductory multiobjective power flow analysis for a case study involving a regional portion of a large grid will be explored, along with a discussion of future research directions.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleAn Optimization Framework for Decision Making in Large, Collaborative Energy Supply Systems
    typeJournal Paper
    journal volume138
    journal issue5
    journal titleJournal of Energy Resources Technology
    identifier doi10.1115/1.4032521
    journal fristpage51601
    journal lastpage51601
    identifier eissn1528-8994
    treeJournal of Energy Resources Technology:;2016:;volume( 138 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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