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Optimal operation of microgrid under...

Ding, Zhaohao.

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Optimal operation of microgrid under a stochastic environment.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Optimal operation of microgrid under a stochastic environment./
作者:	Ding, Zhaohao.
面頁冊數:	125 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-11(E), Section: B.
Contained By:	Dissertation Abstracts International76-11B(E).
標題:	Electrical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3709712
ISBN:	9781321854053

Optimal operation of microgrid under a stochastic environment.
Ding, Zhaohao.

Optimal operation of microgrid under a stochastic environment. - 125 p.

Source: Dissertation Abstracts International, Volume: 76-11(E), Section: B.

Thesis (Ph.D.)--The University of Texas at Arlington, 2015.

With its technological and regulatory innovation of scale and structure, microgrids have been developed all over the world as a mean to address the high penetration level of renewable generation, reduce the greenhouse gas emission, and provide economical solutions for the currently non-electrified area. The operation of microgrid requires resource planning for those fossil-fuel based generators, energy storage systems, and demand resources if demand side management is implemented. Due to the stochastic nature of renewable energy resources, load behaviors and market prices, enormous uncertainties are involved in the microgrid operation and scheduling problems for both short-term and longer term. These uncertainties may result in a non-optimal operation or even jeopardizing the reliability of the microgrid if they are not fully considered in the scheduling stage.

ISBN: 9781321854053Subjects--Topical Terms:

649834
Electrical engineering.

Optimal operation of microgrid under a stochastic environment.
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500 $a Source: Dissertation Abstracts International, Volume: 76-11(E), Section: B.
500 $a Adviser: Wei-Jen Lee.
502 $a Thesis (Ph.D.)--The University of Texas at Arlington, 2015.
520 $a With its technological and regulatory innovation of scale and structure, microgrids have been developed all over the world as a mean to address the high penetration level of renewable generation, reduce the greenhouse gas emission, and provide economical solutions for the currently non-electrified area. The operation of microgrid requires resource planning for those fossil-fuel based generators, energy storage systems, and demand resources if demand side management is implemented. Due to the stochastic nature of renewable energy resources, load behaviors and market prices, enormous uncertainties are involved in the microgrid operation and scheduling problems for both short-term and longer term. These uncertainties may result in a non-optimal operation or even jeopardizing the reliability of the microgrid if they are not fully considered in the scheduling stage.
520 $a This dissertation applies stochastic modeling and optimization techniques to address the challenges brought by uncertainties in the microgrid operation through. The microgrid day-ahead scheduling problem, demand side management scheduling problem, and medium-term operation scheduling problem are modelled via stochastic approaches to achieve the optimal operation decisions under an environment with high degree of uncertainties. Meanwhile, a microgrid carbon emission co-optimized scheduling algorithm is also proposed to address the carbon emission in the microgrid operation. Correspondingly, the uncertainty models and solving methods for those formulations are also proposed by this dissertation and numerical results are presented for verification and illustration purpose.
590 $a School code: 2502.
650 4 $a Electrical engineering. $3 649834
650 4 $a Alternative Energy. $3 1035473
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710 2 $a The University of Texas at Arlington. $b Electrical Engineering. $3 1018571
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