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Optimization under Uncertainty of a ...

ProQuest Information and Learning Co.

Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage./
作者:	Zheng, Yingying.
面頁冊數:	1 online resource (170 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Contained By:	Dissertation Abstracts International79-09B(E).
標題:	Energy. -
電子資源:	click for full text (PQDT)
ISBN:	9780355969023

Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage.
Zheng, Yingying.

Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage. - 1 online resource (170 pages)

Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.

Thesis (Ph.D.)--University of California, Davis, 2018.

Includes bibliographical references

The growing energy demands and needs for reducing carbon emissions call more and more attention to the development of renewable energy technologies and management strategies. Microgrids have been developed around the world as a means to address the high penetration level of renewable generation and reduce greenhouse gas emissions while attempting to address supply-demand balancing at a more local level.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355969023Subjects--Topical Terms:

784773
Energy.
Index Terms--Genre/Form:

554714
Electronic books.

Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage.
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245 1 0 $a Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage.
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300 $a 1 online resource (170 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
500 $a Adviser: Bryan Jenkins.
502 $a Thesis (Ph.D.)--University of California, Davis, 2018.
504 $a Includes bibliographical references
520 $a The growing energy demands and needs for reducing carbon emissions call more and more attention to the development of renewable energy technologies and management strategies. Microgrids have been developed around the world as a means to address the high penetration level of renewable generation and reduce greenhouse gas emissions while attempting to address supply-demand balancing at a more local level.
520 $a This dissertation presents a model developed to optimize the design of a biomass-integrated renewable energy microgrid employing combined heat and power with energy storage. A receding horizon optimization with Monte Carlo simulation were used to evaluate optimal microgrid design and dispatch under uncertainties in the renewable energy and utility grid energy supplies, the energy demands, and the economic assumptions so as to generate a probability density function for the cost of energy. Case studies were examined for a conceptual utility grid-connected microgrid application in Davis, California. The results provide the most cost effective design based on the assumed energy load profile, local climate data, utility tariff structure, and technical and financial performance of the various components of the microgrid. Sensitivity and uncertainty analyses are carried out to illuminate the key parameters that influence the energy costs. The model application provides a means to determine major risk factors associated with alternative design integration and operating strategies.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Energy. $3 784773
650 4 $a Industrial engineering. $3 679492
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a University of California, Davis. $b Biological Systems Engineering. $3 1181698
773 0 $t Dissertation Abstracts International $g 79-09B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10638229 $z click for full text (PQDT)

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