An Optimization Framework for Decision Making in Large, Collaborative Energy Supply SystemsSource: Journal of Energy Resources Technology:;2016:;volume( 138 ):;issue: 005::page 51601Author:DuPont, Bryony
,
Azam, Ridwan
,
Proper, Scott
,
Cotilla
,
Hoyle, Christopher
,
Piacenza, Joseph
,
Oryshchyn, Danylo
,
Zitney, Stephen E.
,
Bossart, Stephen
DOI: 10.1115/1.4032521Publisher: 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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contributor author | DuPont, Bryony | |
contributor author | Azam, Ridwan | |
contributor author | Proper, Scott | |
contributor author | Cotilla | |
contributor author | Hoyle, Christopher | |
contributor author | Piacenza, Joseph | |
contributor author | Oryshchyn, Danylo | |
contributor author | Zitney, Stephen E. | |
contributor author | Bossart, Stephen | |
date accessioned | 2017-05-09T01:27:43Z | |
date available | 2017-05-09T01:27:43Z | |
date issued | 2016 | |
identifier issn | 0195-0738 | |
identifier other | jert_138_05_051601.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/160891 | |
description 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | An Optimization Framework for Decision Making in Large, Collaborative Energy Supply Systems | |
type | Journal Paper | |
journal volume | 138 | |
journal issue | 5 | |
journal title | Journal of Energy Resources Technology | |
identifier doi | 10.1115/1.4032521 | |
journal fristpage | 51601 | |
journal lastpage | 51601 | |
identifier eissn | 1528-8994 | |
tree | Journal of Energy Resources Technology:;2016:;volume( 138 ):;issue: 005 | |
contenttype | Fulltext |