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Optimal co-design of microgrids and ...

Whitefoot, John W.

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Optimal co-design of microgrids and electric vehicles: Synergies, simplifications and the effects of uncertainty.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimal co-design of microgrids and electric vehicles: Synergies, simplifications and the effects of uncertainty./
Author:	Whitefoot, John W.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2012,
Description:	137 p.
Notes:	Source: Dissertation Abstracts International, Volume: 73-11(E), Section: B.
Contained By:	Dissertation Abstracts International73-11B(E).
Subject:	Mechanical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3519750
ISBN:	9781267466235

Optimal co-design of microgrids and electric vehicles: Synergies, simplifications and the effects of uncertainty.
Whitefoot, John W.

Optimal co-design of microgrids and electric vehicles: Synergies, simplifications and the effects of uncertainty. - Ann Arbor : ProQuest Dissertations & Theses, 2012 - 137 p.

Source: Dissertation Abstracts International, Volume: 73-11(E), Section: B.

Thesis (Ph.D.)--University of Michigan, 2012.

The burgeoning electrification of automobiles is causing convergence of the transportation and electrical power systems. This is visible in localized micropower systems, or microgrids, that supply plug-in vehicles. Though each system is designed by a separate industry, the need to reduce petroleum use and greenhouse gas emissions directs us to study the interface between these systems and develop methods to design both systems simultaneously. A method is presented for optimal co-design of a microgrid and electric vehicles using a nested optimal dispatch problem to solve for the operation of the microgrid and vehicles. This nested structure is implemented within a sequential optimization and reliability analysis loop to solve for the desired system reliability given uncertainties in the power load and solar power supply.

ISBN: 9781267466235Subjects--Topical Terms:

649730
Mechanical engineering.

Optimal co-design of microgrids and electric vehicles: Synergies, simplifications and the effects of uncertainty.
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245 1 0 $a Optimal co-design of microgrids and electric vehicles: Synergies, simplifications and the effects of uncertainty.
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300 $a 137 p.
500 $a Source: Dissertation Abstracts International, Volume: 73-11(E), Section: B.
500 $a Adviser: Panos Y. Papalambros.
502 $a Thesis (Ph.D.)--University of Michigan, 2012.
520 $a The burgeoning electrification of automobiles is causing convergence of the transportation and electrical power systems. This is visible in localized micropower systems, or microgrids, that supply plug-in vehicles. Though each system is designed by a separate industry, the need to reduce petroleum use and greenhouse gas emissions directs us to study the interface between these systems and develop methods to design both systems simultaneously. A method is presented for optimal co-design of a microgrid and electric vehicles using a nested optimal dispatch problem to solve for the operation of the microgrid and vehicles. This nested structure is implemented within a sequential optimization and reliability analysis loop to solve for the desired system reliability given uncertainties in the power load and solar power supply.
520 $a The method is demonstrated for the case of co-designing a military microgrid and its all-electric tactical vehicles. The co-design approach results in a combined system design that minimizes capital investment and operating costs while meeting the reliability and performance requirements of both systems. The electric vehicles are shown to increase system reliability by providing energy storage without compromising their driving performance, and this support is shown to be robust to changes in the vehicle plug-in scheduling. The resulting optimal designs are highly-dependent on the input parameters, such as fuel cost and cost of capital equipment. For scenarios with high fuel costs and low battery prices, the co-design systems diverges significantly from separately-designed systems, resulting in improved performance and lower total costs.
590 $a School code: 0127.
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