Applied Mathematics for Restructured Electric Power Systems: - download pdf or read online

By Joe H. Chow, Felix F. Wu, James A. Momoh

ISBN-10: 0387234705

ISBN-13: 9780387234700

Utilized arithmetic for Restructured electrical energy platforms: Optimization, keep an eye on, and Computational Intelligence comprises chapters in keeping with paintings provided at a countrywide technology origin workshop equipped in November 2003. The subject matter of the workshop used to be using utilized arithmetic to unravel demanding strength approach difficulties. The parts integrated keep watch over, optimization, and computational intelligence. as well as the introductory bankruptcy, this e-book contains 12 chapters written via popular specialists of their revered fields. every one bankruptcy follows a three-part structure: (1) an outline of an enormous energy process challenge or difficulties, (2) the present perform and/or specific learn methods, and (3) destiny examine instructions. jointly, the technical parts mentioned are voltage and oscillatory balance, energy method defense margins, hierarchical and decentralized regulate, balance tracking, embedded optimization, neural community keep watch over with adaptive critic structure, regulate tuning utilizing genetic algorithms, and cargo forecasting and part prediction. This quantity is meant for strength platforms researchers and pros charged with fixing electrical and gear procedure problems.

Table of Contents

Cover

Applied arithmetic for Restructured electrical energy Systems:
Optimization, keep an eye on, and Computational Intelligence

Copyright - ISBN: 0387234705

Contents

List of Figures

List of Tables

Preface

Contributing Authors

1 utilized arithmetic for Restructured electrical strength Systems

1 Introduction
2 Workshop Presentations
three Synopses of the Articles during this Compilation
four Conclusions

2 Reactive energy and Voltage keep watch over matters in electrical strength Systems

1 Introduction
2 Reactive Power
three Reactive energy in Operations
four A basic Illustration
five demanding situations in Voltage keep an eye on and similar Security
6 Conclusions

3 id of susceptible destinations utilizing Voltage balance Margin
Index

1 Introduction
2 easy Mathematical Model
three program of the hot option to huge Scale energy Systems
four Simulation Results
five Conclusions
6 destiny Work

4 Bifurcation and Manifold dependent method for Voltage and Oscillatory
Stability overview and Control

1 Introduction
2 id of Saddle Node, Hopf Bifurcation, and Damping
Margins
2.1 id of severe eigenvalue
2.2 Damping margin identification
2.3 Example
three Tracing Margin Boundaries
3.1 Boundary predictor
3.2 Boundary corrector
3.3 Computation result
four additional Extensions
4.1 optimum margin boundary: fee established security
4.2 quickly and gradual time scales
4.3 impression on strength process security
five examine Needs

5 online ATC overview for Large-Scale energy platforms: Framework and
Tool

1 Introduction
2 move Capability
three Transaction-Dependent ATC
four procedure Modeling
five determine serious Contingencies for Static Security
6 Estimating Load Margins to nostril Points
7 Estimating Load Margins to Static protection Violations
eight determine serious Contingencies for Dynamic Security
nine answer Algorithm
10 Numerical Studies
eleven Conclusions

6 Automating Operation of enormous electrical strength structures Over Broad
Ranges of Supply/Demand and kit Status

1 Introduction
2 electrical strength Grids as complicated community Systems
2.1 Assumptions underlying trendy operation of hierarchical
systems
2.2 Implications of violating monotone response
2.3 the main problem: tracking and keep watch over outside
monotone reaction method conditions
three present working perform: difficulties and Open Questions
3.1 old difficulties of working lower than stress
3.2 a few attainable strategies and their shortcomings
four Multi-Layered Modeling, Estimation and keep watch over method to
coping with electrical strength Networks Over large levels of Operating
Conditions
4.1 complete non-linear dynamics of electrical energy systems
4.2 Disturbance- and control-driven multi-layered models
4.3 A large-scale quasi-stationary model
4.4 Multi-layered procedure constraints
five Multi-Layered Estimation and Control
5.1 Quasi-stationary kingdom estimators
5.2 Multi-layered keep watch over approach
5.3 computerized non permanent dispatch and unit dedication over
vast levels of stipulations and kit status
5.4 specific case: modern-day hierarchical control
6 Structural Spatial Aggregation: coping with huge Network
Complexity through Systematic Estimation and Control
6.1 Quasi-stationary country estimators
7 Conclusions and Open Questions

7 powerful regulate of huge energy structures through Convex Optimization

1 Introduction
2 Exciter keep watch over layout utilizing Linear Matrix Inequalities
three a few Simulation Results
four New examine Directions
4.1 layout of decentralized output control
4.2 Coordinated layout of strength process stabilizers and robust
feedback
4.3 keep watch over layout with info trade between
subsystems
five Conclusions

8 Instability tracking and keep watch over of strength Systems

1 Introduction
2 Participation Factors
2.1 Modal participation factors
2.2 Input-to-state participation factors
three Precursor-Based Monitoring
four Case Studies
4.1 Single-generator process with dynamic load
4.2 unmarried generator hooked up to an unlimited bus
4.3 Three-generator nine-bus energy system
five Conclusions and urged destiny Research
Appendix: Parameter Values for the turbines in Sections 4.1 and
4.2

9 Dynamic Embedded Optimization and capturing equipment for energy System
Performance Assessment

1 Introduction
2 Model
2.1 Hybrid systems
2.2 Trajectory sensitivities
three Dynamic Embedded Optimization
four taking pictures Methods
4.1 restrict cycles
4.2 Grazing phenomena
five demanding situations in Dynamic functionality Enhancement
6 Conclusions

10 Computational Intelligence ideas For keep watch over of proof Devices

1 Introduction
2 proof units and standard Control
2.1 Static Compensators (STATCOM)
2.2 Static Synchronous sequence Compensator (SSSC)
2.3 Unified energy circulate Controller (UPFC)
three Adaptive Neurocontrol of evidence Devices
3.1 Neuroidentifier
3.2 Neurocontroller
3.3 wanted reaction predictor
3.4 Adaptive neurocontrol of a STATCOM dependent strength system
3.5 Adaptive neurocontrol of a UPFC dependent energy system
four optimum Neurocontrol with Adaptive Critic Designs
4.1 optimum DHP neurocontrol of a Static Synchronous Series
Compensator (SSSC)
five Conclusions
6 destiny Research

11 Placement and Coordinated Tuning of regulate units for Capacity
and defense Enhancement utilizing Metaheuristics

1 Introduction
2 challenge Formulation
2.1 the location problem
2.2 The coordinated tuning problem
2.3 The mixed placement and tuning problem
three The Metaheuristcs Approach
four optimum security units Placement in Distribution Networks
4.1 Proposed approach
4.2 Genetic set of rules formulation
4.3 Computational results
five Coordinated Tuning of strength method Controls
5.1 challenge formulation
5.2 strong tuning utilizing GAs
5.3 try out results
5.4 suggestions sign selection
5.5 strong decentralized control
5.6 Time simulation results
6 Conclusions and extra Developments
Appendix: Genetic Algorithms

12 Load Forecasting

1 Introduction
2 vital elements for Forecasts
three Forecasting Methods
3.1 Medium- and long term load forecasting methods
3.2 momentary load forecasting methods
four destiny learn Directions
five Conclusions

13 autonomous part research innovations for energy procedure Load
Estimation

1 Introduction
2 autonomous part Analysis
2.1 ICA resource estimation model
2.2 ICA resource assumptions
2.3 aim capabilities for the maximization of source
independence
2.4 FastICA resource estimation algorithm
three software of ICA for Load Profile Estimation
3.1 Linear blending types for load profile estimation
3.2 Preprocessing of load profile data
3.3 getting rid of indeterminacy of ICs
3.4 FastICA established load profile estimation algorithm
four Case Studies
4.1 facts generation
4.2 mistakes measures
4.3 effects for energetic load profile estimation
4.4 effects for reactive load profile estimation
4.5 effects for harmonic load profile estimation
five Conclusions
6 destiny Research

Index

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Additional info for Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence

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A. Pai. Energy h n c t i o n Analysis for Power System Stability. Kluwer Academic Publishers, Boston, 1989. W. Taylor. Power System Voltage Stability. McGraw Hill, New York, 1994. [9] T. Van Cutsem and C. Vounas. Voltage Stability of Electric Power Systems. Kluwer Academic Publishers, Boston, 1998. REFERENCES 9 [lo] R. Podmore. Identification of Coherent Generators for Dynamic Equivalents. IEEE Transactions on Power Apparatus and Systems, PAS-97:1344-1354, 1978. H. Chow, G. V. Kokotovic, B. R. Winkelman.

Computational Intelligence: A Logical Approach. Oxford University Press, New York, 1998. Chapter 2 REACTIVE POWER AND VOLTAGE CONTROL ISSUES IN ELECTRIC POWER SYSTEMS Peter W. edu Abstract This chapter was prepared primarily for "non power" engineers to introduce reactive power and voltage control concepts, and to identify several issues that remain as research challenges in this area. It begins with basic definitions and information on reactive power, and then focuses on problems that have been known for many years and have surfaced recently in power system operations.

We hope that the materials, together with suggested research directions, will offer applied mathematicians and power system engineers and researchers ideas for future investigations. References [I] S. C. Adrian, K. Imhof, and S. Mukherjee. Implementation of a Lagrangian Relaxation Based Unit Commitment Problem. IEEE Transactions on Power Systems, 4:1373-1380, 1989. A. Z. Zhu. Improved Interior Point Method for OPF Problems. IEEE Transactions on Power System, 14:11141120, 1999. [3] A. Monticelli.

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Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence by Joe H. Chow, Felix F. Wu, James A. Momoh


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