NDLI: Issues in integrating existing multi-agent systems for power engineering applications

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2005 Intelligent Systems Application to Power Systems - Welcome to ISAP 2005

2005 Intelligent Systems Application to Power Systems - Committee Listing

2005 Intelligent Systems Application to Power Systems - Preface

2005 Intelligent Systems Application to Power Systems - Sponsors

2005 Intelligent Systems Application to Power Systems - author index

2005 Intelligent Systems Application to Power Systems - Copyright

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Tutorial on Intelligent Optimization and Control for Power Systems: An Introduction

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An expert system for diagnosis of digital relay operation

Incremental knowledge-based partial discharge diagnosis in oil-filled power transformers

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An incremental modeling approach with a hierarchical structure and progressive accuracy using dyadic wavelet-based neural networks

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Coordinated tuning of AVRs and PSSs by multiobjective genetic algorithms

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Concepts and approaches in multi-agent systems for power applications

Issues in integrating existing multi-agent systems for power engineering applications

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Comparison of two metaheuristics with mathematical programming methods for the solution of OPF

Para-consistent case-based reasoning

Unit commitment using adaptive dynamic programming

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A polynomial chaos theory approach to uncertainty in electrical engineering

Computation of Contingency Probabilities for Electric Transmission Decision Problems

Market feedback for bounding future uncertainties in power system planning

Dynamic planning of medium voltage open-loop distribution networks under uncertainty

Proceedings of International Conference on Intelligent System Application to Power Systems

Issues in integrating existing multi-agent systems for power engineering applications

Content Provider	IEEE Xplore Digital Library
Author	Catterson, V.M. Davidson, E.M. McArthur, S.D.J.
Copyright Year	2005
Description	Author affiliation: Inst. for Energy & Environ., Strathclyde Univ., Glasgow (Catterson, V.M.; Davidson, E.M.; McArthur, S.D.J.)
Abstract	Multi-agent systems (MAS) have proven to be an effective platform for diagnostic and condition monitoring applications in the power industry. For example, a multi-agent system architecture, entitled condition monitoring multi-agent system (COMMAS) (McArthur et al., 2004), has been applied to the ultra high frequency (UHF) monitoring of partial discharge activity inside transformers. Additionally, a multi-agent system, entitled protection engineering diagnostic agents (PEDA) (Hossack et al., 2003), has demonstrated the use of MAS technology for automated and enhanced post-fault analysis of power systems disturbances based on SCADA and digital fault recorder (DFR) data. In this paper, the authors propose the integration of COMMAS and PEDA as a means of offering enhanced decision support to engineers tasked with managing transformer assets. By providing automatically interpreted data related to condition monitoring and power system disturbances, the proposed integrated system offer engineers a more comprehensive picture of the health of a given transformer. Defects and deterioration in performance can be correlated with the operating conditions it experiences. The integration of COMMAS and PEDA has highlighted the issues inherent to the inter-operation of existing multi-agent systems and, in particular, the issues surrounding the use of differing ontologies. The authors believe that these issues need to be addressed if there is to be widespread deployment of MAS technology within the power industry. This paper presents research undertaken to integrate the two MAS and to deal with ontology issues
File Size	541458
File Format	PDF
ISBN	1599751747
DOI	10.1109/ISAP.2005.1599296
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	ISAP
Subject Keyword	Condition monitoring Power engineering Multiagent systems Power system protection Transformers Data engineering Systems engineering and theory Power industry Power system faults Power engineering and energy
Content Type	Text
Resource Type	Article

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