Optimization of Power System Operation

This book applies the latest applications of new technologies to power system operation and analysis, including new and important areas that are not covered in the previous edition. With the addition of end–of–chapter exercises, this book will be a valuable tool for students and professionals.

Optimization of Power System Operation covers both traditional and modern technologies, including power flow analysis, steady–state security region analysis, security constrained economic dispatch, multi–area system economic dispatch, unit commitment, optimal power flow, smart grid operation, optimal load shed, optimal reconfiguration of distribution network, power system uncertainty analysis, power system sensitivity analysis, analytic hierarchical process, neural network, fuzzy theory, genetic algorithm, evolutionary programming, and particle swarm optimization, among others.  New topics such as the wheeling model, multi–area wheeling, the total transfer capability computation in multiple areas, are also addressed. 

The new edition of this book continues to provide engineers and academics with a complete picture of the optimization of techniques used in power system operation, several important additions have been made.

Addresses advanced methods and optimization technologies and their applications in power systems New chapters include: Steady State Security Regions, Optimal Load Shedding, Optimal Reconfiguration of Electric Distribution Network, and Uncertainty Analysis in Power Systems New hot topics covered in detail include: Application of Renewable Energy and Operation of Smart Grid End–of–chapter exercises added
Some contents are analyzed and discussed for the first time in detail in this book. Power engineers, operators, and planners will be able to benefit from this insightful source, as well as advanced undergraduate and graduate students.


Preface to the Second Edition

Preface to the First Edition

1. Introduction

1.1 Power Systems Basics

1.2 Conventional Methods

1.3 Intelligent Search Methods

1.4 Application of Fuzzy Set Theory

References

2. Power Flow Analysis

2.1 Mathematical Model of Power Flow

2.2 Newton–Raphson Method

2.3 Gauss–Seidel Method

2.4 P–Q Decoupling Method

2.5 DC power flow

2.6 State Estimation

Problems and Exercises

References

3. Sensitivity Calculation

3.1 Introduction

3.2 Loss Sensitivity Calculation

3.3 Calculation of Constrained Shift Sensitivity Factors

3.4 Perturbation Method for Sensitivity Analysis

3.5 Voltage Sensitivity Analysis

3.6 Real–Time Application of Sensitivity Factors

3.7 Simulation Results

3.8 Conclusion

Problems and Exercises

References

4. Classic Economic Dispatch

4.1 Introduction

4.2 Input–Output Characteristic of Generator Units

4.3 Thermal System Economic Dispatch Neglecting Network Losses

4.4 Calculation of Incremental Power Losses

4.5 Thermal System Economic Dispatch with Network Losses

4.6 Hydrothermal System Economic Dispatch

4.7 Economic Dispatch by Gradient Method

4.8 Classic Economic Dispatch by Genetic Algorithms

4.9 Classic Economic Dispatch by Hopfield Neural Network

Appendix: Optimization Methods Used in Economic Operation

Problems and Exercises

References

5. Security Constrained Economic Dispatch

5.1 Introduction

5.2 Linear Programming Method

5.3 Quadratic Programming Method

5.4 Network Flow Programming Method

5.5 Nonlinear Convex Network Flow Programming Method

5.6 Two–Stage Economic Dispatch Approach

5.7 Security Constrained ED by Genetic Algorithm

Appendix: Network Flow Programming

Problems and Exercises

References

6. Multiarea Systems Economic Dispatch

6.1 Introduction

6.2 Economy of Multiarea Interconnection

6.3 Wheeling

6.4 Multiarea Wheeling

6.5 MAED Solved by Nonlinear Convex Network Flow Programming

6.6 Nonlinear Optimization Neural Network Approach

6.7 Total Transfer Capability Computation in Multiareas

Appendix: Comparison of Two Optimization Neural Network Models

Problems and Exercises

References

7. Unit Commitment

7.1 Introduction

7.2 Priority Method

7.3 Dynamic Programming Method

7.4 Lagrange Relaxation Method

7.5 Evolutionary Programming–Based Tabu Search Method

7.6 Particle Swarm Optimization for Unit Commitment

7.7 Analytic Hierarchy Process

Problems and Exercises

References

8. Optimal Power Flow

8.1 Introduction

8.2 Newton Method

8.3 Gradient Method

8.4 Linear Programming OPF

8.5 Modified Interior Point OPF

8.6 OPF with Phase Shifter

8.7 Multiple–Objectives OPF

8.8 Particle Swam Optimization for OPF

Problems and Exercises

References

9. Steady–State Security Regions

9.1 Introduction

9.2 Security Corridors

9.3 Traditional Expansion Method

9.4 Enhanced Expansion Method

9.5 Fuzzy Set and Linear Programming

Appendix: Linear Programming

Problems and Exercises

References

10. Application of Renewable Energy

10.1 Introduction

10.2 Renewable Energy Resources

10.3 Operation of Grid–Connected PV System

10.4 Voltage Calculation of Distribution Network

10.5 Frequency Impact of PV Plant in Distribution Network

10.6 Operation of Wind Energy

10.7 Voltage Analysis in Power System with Wind Energy

Problems and Exercises

References

11. Optimal Load Shedding

11.1 Introduction

11.2 Conventional Load Shedding

11.3 Intelligent Load Shedding

11.4 Formulation of Optimal Load Shedding

11.5 Optimal Load Shedding with Network Constraints

11.6 Optimal Load Shedding without Network Constraints

11.7 Distributed Interruptible Load Shedding

11.8 Undervoltage Load Shedding

11.9 Congestion Management

Problems and Exercises

References

12. Optimal Reconfiguration of Electric Distribution Network

12.1 Introduction

12.2 Mathematical Model of DNRC

12.3 Heuristic Methods

12.4 Rule–Based Comprehensive Approach

12.5 Mixed–Integer Linear Programming Approach

12.6 Application of GA to DNRC

12.7 Multiobjective Evolution Programming to DNRC

12.8 Genetic Algorithm Based on Matroid Theory

APPENDIX: Evolutionary Algorithm of Multi–objective Optimization

Problems and Exercises

References

13. Uncertainty Analysis in Power System

13.1 Introduction

13.2 Definition of Uncertainty

13.3 Uncertainty Load Analysis

13.4 Uncertainty Power Flow Analysis

13.5 Economic Dispatch with Uncertainties

13.6 Hydrothermal System Operation with Uncertainty

13.7 Unit Commitment with Uncertainties

13.8 VAR Optimization with Uncertain Reactive Load

13.9 Probabilistic Optimal Power Flow

13.10 Comparison of Deterministic and Probabilistic Method

Problems and Exercises

References

14. Operation of Smart Grid

14.1 Introduction

14.2 Definition of Smart Grid

14.3 Smart Grid Technologies

14.4 Smart Grid Operation

14.5 Two Stage Approach for Smart Grid Dispatch

14.6 Operation of Virtual Power Plants

14.7 Smart Distribution Grid

14.8 Microgrid Operation

14.9 A New Phase Angle Measurement Algorithm

Problems and Exercises

Reference

Author Biography

Index

Jizhong Zhu is a Senior Principal Power Systems Engineer as well as a Fellow with ALSTOM Grid Inc, USA. In addition to his industry experience, Dr. Zhu has worked at Howard University in Washington, D.C., the National University of Singapore, Brunel University in England, and Chongqing University in China. A Senior Member of the IEEE and an honorable advisory professor of Chongqing University, he has published six books as an author and co–author, as well as about two hundred papers in the international journals and conferences. His research interest is in the analysis, operation, planning and control of power systems as well as applications of renewable energy.