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Distributed decision-making in elect...

Zhang, Zhong.

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Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS).

Record Type:	Electronic resources : Monograph/item
Title/Author:	Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS)./
Author:	Zhang, Zhong.
Description:	130 p.
Notes:	Source: Dissertation Abstracts International, Volume: 65-09, Section: B, page: 4758.
Contained By:	Dissertation Abstracts International65-09B.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3145695
ISBN:	0496045687

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS).
Zhang, Zhong.

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS). - 130 p.

Source: Dissertation Abstracts International, Volume: 65-09, Section: B, page: 4758.

Thesis (Ph.D.)--Iowa State University, 2004.

In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.

ISBN: 0496045687Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS).
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245 1 0 $a Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS).
300 $a 130 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-09, Section: B, page: 4758.
500 $a Major Professor: James D. McCalley.
502 $a Thesis (Ph.D.)--Iowa State University, 2004.
520 $a In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.
590 $a School code: 0097.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Energy. $3 876794
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710 2 0 $a Iowa State University. $3 1017855
773 0 $t Dissertation Abstracts International $g 65-09B.
790 1 0 $a McCalley, James D., $e advisor
790 $a 0097
791 $a Ph.D.
792 $a 2004
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