Robust Coordinated Control Of FACTS Devices In Large Power .

Robust Coordinated Control ofFACTS Devices in Large Power SystemsVon der Fakultät für Ingenieurwissenschaften derUniversität Duisburg-Essenzur Erlangung des akademischen Grades einesDoktoringenieurs (Dr. –Ing.)genehmigte DissertationvonLijun CaiausHebei, P.R. ChinaReferent: Prof. Dr.-Ing. habil. István ErlichKorreferent: Prof. Dr.-Ing. Edmund HandschinTag der mündlichen Prüfung: 16.02.2004

Bibliografische Information Der Deutschen BibliothekDie Deutsche Bibliothek verzeichnet diese Publikation in der DeutschenNationalbibliografie; detaillierte bibliografische Daten sind im Internet überhttp://dnb.ddb.de abrufbar.c Copyright Logos Verlag Berlin 2004Alle Rechte vorbehalten.ISBN 3-8325-0570-9Logos Verlag BerlinComeniushof, Gubener Str. 47,10243 BerlinTel.: 49 030 42 85 10 90Fax: 49 030 42 85 10 92INTERNET: http://www.logos-verlag.deLijun Cai, Robust Coordinated Control of FACTS Devices in Large Power SystemsPublished by Logos Verlag Berlin 2004, ISBN 3-8325-0570-9Gedruckt mit Unterstützung des Deutschen Akademischen Austauschdienstes

This work is gratefully dedicated to:my dear mother, my father, my sisterand my lovely wife

AcknowledgementForemost, I would like to express my sincere gratitude and appreciation to myadvisor, Univ. Professor Dr.-Ing. habil. István Erlich, for his support, patience, andencouragement throughout my Ph.D study. His technical and editorial advice wasessential to the completion of this dissertation. He is not only my supervisor but alsoencouraged and challenged me throughout my academic researches.I am also grateful to my co-advisor, Univ. Professor Dr.–Ing. Edmund Handschinfrom the university of Dortmund, for reading previous drafts of this dissertation andproviding many valuable comments that improved the presentation and contents of thisdissertation.My thanks also go to the other members of my examination board, Professor Dr.–Ing.G. Zimmer, Professor Dr.–Ing. S.X. Ding and Professor Dr.–Ing. A. Czylwik for theirvaluable comments and suggestions.Furthermore, I would like to thank all members of the institute for contributing tosuch an inspiring and pleasant atmosphere. Special thanks go to Dipl.-Ing. GeorgiosStamtsis and Dipl.-Ing. Getachew Befekadu for the discussions, cooperation andreading of the manuscript.Finally, I would like to acknowledge the financial support of the German AcademicExchange Service (DAAD) for giving me the opportunity to pursue my doctorial degreein Germany.Lijun CaiDuisburg GermanyFebruary , 2004

AbstractWith the rapid development of power electronics, Flexible AC Transmission Systems(FACTS) devices have been proposed and implemented in power systems. FACTSdevices can be used to control power flow and enhance system stability. There is anincreasing interest in using FACTS devices in the operation and control of powersystems. However, their coordination with the conventional damping controllers inaiding of power system oscillation damping is still an open problem. Therefore, it isessential to investigate the coordinated control of FACTS devices and traditional powersystem controllers in large power systems.The followings are areas of research achieved in this thesis: FACTS modeling and controller design: FACTS devices are modeled usingthe current injection method and the FACTS damping controllers aredeveloped using the residue method in this thesis. This residue approach is apractical method for FACTS damping controller design in large powersystems. Optimal choice and allocation of FACTS devices: FACTS devices can beused to control power flows. Therefore, provided optimal locations, FACTSdevices can be used to achieve the optimal power flow without any constraintviolation and thus to increase the utilization of the lowest cost generation inpower systems. FACTS types and locations should be reasonably chosenaccording to their contribution to the general objective of power systemeconomic generation and dispatch. In this research, using the geneticalgorithms, the locations of the FACTS devices, their types and rated valuesare optimized simultaneously. The objective cost function, which consists ofthe investment costs for FACTS devices and the generation costs, isminimized. Adaptive FACTS transient controller design using ANFIS technology:This research deals with the development of adaptive FACTS transient

stability controller using Adaptive Network based Fuzzy Inference System(ANFIS) technology. The approach adaptively activates the FACTS transientstability controller in large power systems during large disturbances. Thedesign aspects and their implementation in form of fuzzy-adaptive switchingcontroller are presented. Furthermore, ANFIS technology is employed for theparameter optimization of the proposed controller. This approach is realizedin a large power system and it is proved to be an effective method for theadaptive transient control of FACTS devices. Simultaneous coordinated tuning of FACTS damping controller andconventional Power System Stabilizers (PSSs): In this research, using thelinearized power system model and the parameter-constrained non-linearoptimization algorithm, interactions among FACTS controller and PSScontrollers are considered. The controller parameters are optimizedsimultaneously to achieve a global optimal damping behavior. By realizing ina large power system, this approach is proved to be a general optimal tuningmethod for multi-controller parameters. Robust FACTS loop-shaping POD (Power Oscillation Damping)controller design in large power systems: This study deals with the FACTSrobust loop-shaping POD controller design in large power systems. Byapplying the model reduction and modern robust loop-shaping controltechnique, the FACTS robust loop-shaping POD controller is realized. Thiscontroller exploits the advantages of both conventional loop-shaping andmodern H robust control technique. Moreover, it is a decentralized approachand suitable for FACTS controller design in real large power systems. Theperformance of the proposed control scheme has fulfilled the robust stabilityand robust performance criteria. Furthermore, non-linear simulation hasproved that using the proposed controller, the power oscillation dampingbehavior is also satisfactory under large disturbances.

ContentsLIST OF FIGURES AND TABLES .viiList of Figures.viiList of Tables . ixCHAPTER 1 INTRODUCTION . 11.1Introduction of FACTS devices . 11.2Practical application of FACTS devices . 51.3Objectives of the dissertation. 71.4Outlines of the dissertation . 9CHAPTER 2 FACTS MODELING AND CONTROLLER DESIGN . 112.1FACTS modeling. 112.1.1FACTS devices . 112.1.2Current injection model for FACTS devices . 122.2FACTS controllers. 162.2.1FACTS steady-state controller. 172.2.2FACTS transient stability controller. 182.2.3FACTS POD controller . 192.3Single FACTS POD controller design. 192.3.1FACTS POD controller design – linear approach . 192.3.1.1Modal analysis for power system . 202.3.1.2FACTS POD controller design. 252.3.2FACTS POD controller design–non-linear approach. 292.3.2.1Non-linear parameter optimization for FACTS controller . 292.3.2.2Simulation result. 312.4Multi-FACTS coordinated POD controller design. 322.4.1Traditional sequential design . 322.4.2Fuzzy-logic based coordinated controller design . 332.4.2.1Fuzzy approach for coordination of POD controllers. 35

iiContents2.4.2.2Simulation results.392.4.2.3Conclusion of fuzzy coordinated control scheme .412.5Comments on the FACTS damping controller design.42CHAPTER 3 SELECTION OF THE PROPER LOCATIONS FOR FACTSDEVICES .433.1Introduction .433.2ATC criterion.443.3Steady-state stability criterion .453.4Economic criterion .493.4.1Cost functions.503.4.1.1Generation cost function .503.4.1.2Cost functions for FACTS devices .513.4.2Optimal FACTS allocation.523.4.3Genetic algorithm.543.4.3.1Encoding .543.4.3.2Initial population .563.4.3.3Fitness calculation.583.4.3.4Reproduction .583.4.3.5Crossover.593.4.3.6Mutation .613.4.4Case study .633.4.4.1Case 1 — Voltage congestion at bus 2.643.4.4.2Case 2 — Active power flow congestion.643.4.53.5Conclusions of GA optimization method.65Comments on the allocation of FACTS devices.66CHAPTER 4 ADAPTIVE FACTS TRANSIENT CONTROLLER DESIGNUSING ANFISTECHNOLOGY .674.1Introduction .674.2Switching strategy for FACTS transient controller.684.3Fuzzy adaptive switching controller.694.3.1Structure of the fuzzy adaptive switching controller .694.3.2Fuzzy-logic loop.71

Contentsiii4.3.2.1Fuzzification . 714.3.2.2Inference . 724.3.2.3Defuzzification . 724.3.34.4Protection loop. 73ANFIS training. 734.4.1ANFIS structure. 734.4.2ANFIS training . 754.4.2.1Fine-tuning of the membership functions. 764.4.2.2Training of the fuzzy inference system . 764.4.3Training data . 764.4.4Training results . 784.4.4.1Membership functions . 784.4.4.2Fuzzy inference system. 794.5Simulation results . 804.6Conclusion . 81CHAPTER 5 SIMULTANEOUS COORDINATED TUNING OF FACTS PODAND PSSCONTROLLERS FOR DAMPING OF POWERSYSTEM OSCILLATIONS . 835.1Introduction. 835.2PSS and FACTS POD controller. 845.2.1PSS controller . 845.2.2FACTS POD controller . 845.2.3Conventional approach . 855.3Simultaneous coordinated tuning method. 865.3.1Linearized system model . 875.3.2Non-Linear optimization technique . 885.3.3Practical application. 905.4Simulation results . 905.4.1Dominant eigenvalues. 905.4.2Root-locus. 915.4.3Optimized system performance . 925.4.4System performance under different operating condition . 93

ivContents5.4.55.5Non-linear simulation results .93Conclusion.94CHAPTER 6 ROBUST FACTS LOOP-SHAPING POD CONTROLLERDESIGN IN LARGE POWER SYSTEMS .956.1Introduction .956.2System model and performance criteria .966.2.16.2.1.1General model .966.2.1.2Loop transfer function and sensitivities .976.2.1.3Loop-shaping.986.2.26.3General concepts of feedback control system .96Robust performance criteria .996.2.2.1Normalization of inputs and outputs .996.2.2.2Power system performance under uncertainties.99FACTS robust loop-shaping POD controller design .1046.3.1Model reduction .1056.3.2FACTS loop-shaping controller design.1076.3.3Robust loop-shaping design using coprime factors.1086.4Simulation results.1116.4.1Nominal stability .1116.4.2Nominal performance.1136.4.3FACTS robust loop-shaping controller design.1146.4.3.1System model reduction.1146.4.3.2FACTS robust loop-shaping controller design .1156.4.4Robust stability and robust performance.1186.4.5Non-linear simulation results .1216.5Summary .122CHAPTER 7 CONCLUSIONS AND FUTURE WORKS .1237.1Conclusions .1237.2Future works.125APPENDICES.127Appendix 1 .127Appendix 2 .130

ContentsvAppendix 3. 130Appendix 4. 131REFERENCES . 133LIST OF SYMBOLS . 139Latin Symbols. 139Greek Symbols . 147LIST OF ABBREVIATIONS . 149CURRICULUM VITAE . 151PUBLISHED PAPERS . 153DEVELOPED PROGRAMS. 154

viContents

List of Figures and TablesList of FiguresFigure 1.1Functional diagrams of FACTS devices. 3Figure 2.1Equivalent circuit diagrams of the considered FACTS devices . 12Figure 2.2TCSC mathematical model for dynamic analysis . 14Figure 2.3Mathematical model of TCPST . 14Figure 2.4Mathematical model of SVC . 15Figure 2.5Mathematical model of UPFC . 16Figure 2.6Series FACTS steady-state power flow controller . 17Figure 2.7Shunt FACTS steady-state controller .

robust loop-shaping POD controller design in large power systems. By applying the model reduction and modern robust loop-shaping control technique, the FACTS robust loop-shaping POD controller is realized. This controller exploits the advantages of both conventional loop-shaping and modern . H robust control technique.