Intelligent knowledge based systems in electrical power engineering

Transcription

1 Intelligent knowledge based systems in electrical power engineering

2 JOIN US ON THE INTERNET VIA WWW, GOPHER, FTP OR WWW: GOPHER: gopher.thomson.com A ^ ^ FTP: ftp.thomson.com w findit@kiosk.thomson.com

3 Intelligent knowledge based systems in electrical power engineering J.R. McDonald Centre for Electrical Power Engineering University of Strathclyde Scotland, GM. Burt Centre for Electrical Power Engineering University of Strathclyde Scotland, J.S. Zielinski Department of Informatics University of Lodz Poland and S.DJ. McArthur Centre for Electrical Power Engineering University of Strathclyde Scotland, SPRINGER-SCIENCE+BUSINESS MEDIA, B.V

4 First edition Springer Science+Business Media Dordrecht Originally published by Chapman & Hall in 1997 Softcover reprint of the hardcover 1st edition 1997 Typeset in 10/12 Palatino by Florencetype Ltd, Stoodleigh, Devon ISBN ISBN (ebook) DOI / Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright Designs and Patents Act, 1988, this publication may not be reproduced, stored, or transmitted, in any form or by any means, without the prior permission in writing of the publishers or in the case of reprographic reproduction only in accordance with the terms of the licences issued by the Copyright Licensing Agency in the, or in accordance with the terms of licences issued by the appropriate Reproduction Rights Organization outside the. Enquiries concerning reproduction outside the terms stated here should be sent to the publishers at the London address printed on this page. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. A catalogue record for this book is available from the British Library ( 5/ Printed on permanent acid-free text paper, manufactured in accordance with ANSI/NISO Z and ANSI/NISO Z (Permanence of Paper).

5 Contents List of contributors xi Introduction 1 Part One A General Overview of Intelligent Knowledge Based systems 1 An introduction to intelligent knowledge based systems 5 Jerzy S. Zielinski and Stephen D.J. McArthur 1.1 Computers and artificial intelligence A short history Current trends in applied AI Definition and terminology of IKBSs Definitions Terminology The architecture Of IKBSs The implementation cycle of IKBSs 11 References 11 2 Intelligent knowledge based system development 13 Jerzy S. Zielinski and Stephen D.J. McArthur 2.1 Historical review General information IKBS tools Applications of IKBSs IKBS generations IKBSs in technology Opportunities and bottlenecks in IKBS development Discussion of costs and benefits 17 References 17

6 VI Further reading Contents 19 Part Two The Application of Intelligent Knowledge Based Systems in Electrical Power Engineering 3 Comments on contemporary power systems and other engineering systems Jerzy S. Zielinski 3.1 Main characteristics of electrical power systems 3.2 Problems in electrical power system operation 3.3 Computer applications in power systems A short history Some remarks on hardware and software IKBSs 3.4 Some remarks on the relationships between phenomena in power systems and other fields of engineering 3.5 Conclusions References 4 Forecasting and planning in power systems U. George Knight 4.1 Introduction 4.2 Planning tasks in the extension of power systems 4.3 Forecasting tasks in the extension of power systems 4.4 The evolution of techniques for system planning and forecasting 4.5 The characteristics of system planning and forecasting tasks in relation to IKBSs Algorithmic, human and expert system capabilities The characteristics of planning and forecasting tasks in relation to IKBSs Frequency of study Retention of expertise 4.6 Areas of research and development 4.7 Descriptions of some proposed and actual applications of IKBSs in generation expansion planning A decision tree and IKBS model A combined dynamic programming, IKBSs and fuzzy sets approach 4.8 Descriptions of some proposed and actual applications of IKBSs in transmission network planning

7 Contents An IKBS for the preliminary design of power transmission networks Development of an IKBS for long-term planning of power transmission networks Descriptions of some proposed and actual applications of IKBSs in distribution network planning EHV /HV substation location and HV network design Connection of new customers Descriptions of some proposed and actual IKBSs in power system analysis Interactive load flow for power system planning Support to load flow calculations Support for transient stability studies Demand forecasting Trends and conclusions 71 References 72 5 Design of electrical plant and systems 75 Stefano Massucco 5.1 Introduction General overview Reasons for the application of IKBSs to design and planning The state of the art in IKBS applications for the design of electrical plant and systems Introduction Applications to large systems Applications to systems of limited dimensions Applications to the design of specific subsystems or equipment An IKBS application: electrical auxiliary system design in a power station Problem formulation The IKBS approach: building the knowledge base and design procedure Conclusions 95 Acknowledgements 96 References 97 6 Intelligent knowledge based systems in condition monitoring 99 Barclay Weir 6.1 Introduction 99 vii

8 viii Contents 6.2 Types of electrical machines Condition monitoring IKBSs in condition monitoring Applications Some Successful applications TURBOMAC GenAID GEMS TOGA MOTORMON Summary 116 References Alarm processing 119 David J. Young and James R. McDonald 7.1 Introduction The history of alarm processing Message routing Message prioritization Advanced alarm-processing techniques Review of previous work The practical problems of alarm processing Speed of operation Limited scope of telemetry Missing alarm messages Unreliable time ordering of alarms Arrival rate of alarms is not constant Multiple simultaneous events Development of an alarm-processing expert system Setting initial targets Identification of knowledge and data requirements for the IKBS Identification of existing data and knowledge Knowledge acquisition Identification of approach and IKBS techniques Identification of language or tools for IKBS construction Knowledge base design User interface design IKBS construction - knowledge base and user interface Prototyping Testing Installation and integration 142

9 Contents ix 7.5 A case study: APEX Details of APEX construction Example of APEX operation Performance Conclusion 152 References Event and fault diagnosis 155 Graeme M. Burt and James R. McDonald 8.1 Introduction to the problem of fault diagnosis Events Reasons for fault diagnosis Basis for diagnosis Reasons for a fault diagnosis system IKB5-based fault diagnosis Review of IKBSs for network fault diagnosis The 'automatic system trouble analysis' system IKBSs based on AST A ideas A distributed approach Fault diagnosis using object-oriented features Localized fault diagnosis Applications where SCADA data is lacking A system suited to parallel implementation A system for distribution feeders CRAFT - customer restoration and fault testing SEPT An IKBS developed by Amantegui et al Further comments The development of an IKBS for fault diagnosis: RESPONDD Introduction Structure of the diagnosis: its results Structure of the diagnosis: its mechanics An initial prototype: wait-and-see Hypothesizer strategy Hypothesizer gut reaction Evolution of hypothesizing strategies for central diagnosis Dealing with uncertainty Network data requirements Qualitative simulation Modelling knowledge Demonstration of the developed system Case study 187

10 x Contents Hypothesizer diagnosis 8.5 Final remarks References Other applications in power system operation and control 195 Jerzy S. Zielinski 9.1 Voltage/reactive power control Emergency control and restoration Real-time processing The testing of equipment Transformers Protection relays Substations Management systems Electrical and other industries 201 References Future trends in intelligent systems in power systems 206 Alan Moyes 10.1 Introduction The importance of knowledge Knowledge acquisition Model-based reasoning Case-based reasoning Data mining Integrated solutions for complex problems Control and monitoring architecture Integrated IKBSs Conclusions 215 References 216 Index 219

11 Contributors Graeme M. Burt Centre for Electrical Power Engineering, Department of Electrical and Electronic Engineering, University of Strathclyde, Royal College Building, 204 George Street, Glasgow G1 1XW, U. George Knight Department of Electrical and Electronic Engineering, Imperial College of Science, Technology and Medicine, Exhibition Road, London SW7 2BT, Stefano Massucco EPSL, Electrical Engineering Department, University of Genoa, Via ai' Opera Pia, 11a, Genoa, Italy Stephen D.J. McArthur Centre for Electrical Power Engineering, Department of Electrical and Electronic Engineering, University of Strathclyde, Royal College Building, 204 George Street, Glasgow G1 1XW, James R. McDonald Centre for Electrical Power Engineering,

12 xii Contributors Department of Electrical and Electronic Engineering, University of Strathclyde, Royal College Building, 204 George Street, Glasgow G1 1XW, Alan Moyes Centre for Electrical Power Engineering, Department of Electrical and Electronic Engineering, University of Strathclyde, Royal College Building, 204 George Street, Glasgow G1 1XW, Barclay Weir Technology Division, ScottishPower plc, 47 Hawbank Road, East Kilbride G74 5EG, David J. Young Scottish Nuclear, Electrical and Control Design Department, 3 Redwood Crescent, Peel Park, East Kilbride G74 5PR, J erzy S. Zielinski Department of Informatics, University of Lodz, 39 Rewolucji 1905r Str., Lodz, Poland