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Market-Based Decision Guidance Frame...

Altaleb, Hesham.

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Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration./
作者:	Altaleb, Hesham.
面頁冊數:	128 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-01(E), Section: B.
Contained By:	Dissertation Abstracts International77-01B(E).
標題:	Information technology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3720341
ISBN:	9781339013138

Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration.
Altaleb, Hesham.

Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration. - 128 p.

Source: Dissertation Abstracts International, Volume: 77-01(E), Section: B.

Thesis (Ph.D.)--George Mason University, 2015.

With the introduction of power energy markets deregulation, innovations have transformed once a static network into a more flexible grid. Microgrids have also been deployed to serve various purposes (e.g., reliability, sustainability, etc.). With the rapid deployment of smart grid technologies, it has become possible to measure and record both, the quantity and time of the consumption of electrical power. In addition, capabilities for controlling distributed supply and demand have resulted in complex systems where inefficiencies are possible and where improvements can be made. Electric power like other volatile resources cannot be stored efficiently, therefore, managing such resource requires considerable attention.

ISBN: 9781339013138Subjects--Topical Terms:

532993
Information technology.

Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration.
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500 $a Source: Dissertation Abstracts International, Volume: 77-01(E), Section: B.
500 $a Adviser: Alexander Brodsky.
502 $a Thesis (Ph.D.)--George Mason University, 2015.
520 $a With the introduction of power energy markets deregulation, innovations have transformed once a static network into a more flexible grid. Microgrids have also been deployed to serve various purposes (e.g., reliability, sustainability, etc.). With the rapid deployment of smart grid technologies, it has become possible to measure and record both, the quantity and time of the consumption of electrical power. In addition, capabilities for controlling distributed supply and demand have resulted in complex systems where inefficiencies are possible and where improvements can be made. Electric power like other volatile resources cannot be stored efficiently, therefore, managing such resource requires considerable attention.
520 $a Such complex systems present a need for decisions that can streamline consumption, delay infrastructure investments, and reduce costs. When renewable power resources and the need for limiting harmful emissions are added to the equation, the search space for decisions becomes increasingly complex. As a result, the need for a comprehensive decision guidance system for electrical power resources consumption and productions becomes evident.
520 $a In this dissertation, I formulate and implement a comprehensive framework that addresses different aspect of the electrical power generation and consumption using optimization models and utilizing collaboration concepts. Our solution presents a two-prong approach: managing interaction in real-time for the short-term immediate consumption of already allocated resources; and managing the operational planning for the long-run consumption.
520 $a More specifically, in real-time, we present and implement a model of how to organize a secondary market for peak-demand allocation and describe the properties of the market that guarantees efficient execution and a method for the fair distribution of collaboration gains. We also propose and implement a primary market for peak demand bounds determination problem with the assumption that participants of this market have the ability to collaborate in real-time. Moreover, proposed in this dissertation is an extensible framework to facilitate C&I entities forming a consortium to collaborate on their electric power supply and demand. The collaborative framework includes the structure of market setting, bids, and market resolution that produces a schedule of how power components are controlled as well as the resulting payment. The market resolution must satisfy a number of desirable properties (i.e., feasibility, Nash equilibrium, Pareto optimality, and equal collaboration profitability) which are formally defined in the dissertation.
520 $a Furthermore, to support the extensible framework components' library, power components such as utility contract, back-up power generator, renewable resource, and power consuming service are formally modeled. Finally, the validity of this framework is evaluated by a case study using simulated load scenarios to examine the ability of the framework to efficiently operate at the specified time intervals with minimal overhead cost.
590 $a School code: 0883.
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650 4 $a Energy. $3 876794
650 4 $a Alternative Energy. $3 1035473
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710 2 $a George Mason University. $b Information Technology. $3 2095426
773 0 $t Dissertation Abstracts International $g 77-01B(E).
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3720341