Electricity Pricing

Book description

Electricity Pricing: Regulated, Deregulated and Smart Grid Systems presents proven methods for supplying uninterrupted, high-quality electrical power at a reasonable price to the consumer. Illustrating the evolution of the power market from a monopoly to an open access system, this essential text:

  • Covers voltage stability analysis of longitudinal power supply systems using an artificial neural network (ANN)
  • Explains how to improve performance using flexible alternating current transmission systems (FACTS) and high-voltage direct current (HVDC)
  • Takes into account operating constraints as well as generation cost, line overload, and congestion for expected and inadvertent loading stress
  • Goes beyond FACTS and HVDC to provide multi-objective optimization algorithms for the deregulated power market
  • Proposes the use of stochastic optimization techniques in the smart grid, preparing the reader for future development

Electricity Pricing: Regulated, Deregulated and Smart Grid Systems offers practical solutions for improving stability, reliability, and efficiency in real-time systems while optimizing electricity cost.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Table of Contents
  7. List of Figures
  8. List of Tables
  9. Preface
  10. About the Authors
  11. List of Principal Symbols
  12. List of Abbreviations
  13. 1. Prologue
    1. 1.1 Motivation of the Book
    2. 1.2 Contributions of the Book
    3. 1.3 Organization of the Book
  14. 2. Background and Literature Survey
    1. 2.1 Introduction
    2. 2.2 Power Network Performance Evaluation
      1. 2.2.1 Importance of Voltage Stability on Performance Evaluation
        1. Classical Methods of Ascertaining Stability
        2. Neo-Classical Methods of Ascertaining Stability
      2. 2.2.2 Significance of Compensation Techniques
        1. Series and Shunt Compensation Employing FACTS Devices
        2. Employment of HVDC Link
      3. 2.2.3 Optimization Methods with System Performance and Cost Emphasis
        1. Classical and Neo-Classical Optimization Methods
        2. Application of Optimization Methods in Regulated and Deregulated Power Networks
      4. 2.2.4 Enrichment of Cost-Governed System Performance in Smart Grid Arena
    3. 2.3 Concluding Remarks on Existing Efforts
    4. Annotating Outline
  15. 3. Analysis of Voltage Stability of Longitudinal Power Supply System Using an Artificial Neural Network
    1. 3.1 Introduction
    2. 3.2 Theoretical Development of Voltage Stability and Voltage Collapse
      1. 3.2.1 Theoretical Background of Voltage Instability and Its Causes
      2. 3.2.2 Few Relevant Analytical Methods and Indices for Voltage Stability Assessment
        1. The PV and VQ Curves for the Small System
        2. Singular Values
        3. Eigenvalue Decomposition
        4. Modal Analysis
        5. Voltage Stability Index L
        6. Fast Voltage Stability Index (FVSI) and Line Quality Factor (LQF)
        7. Global Voltage Stability Indicator
        8. Voltage Collapse Proximity Indicator (VCPI)
        9. Proximity Indices of Voltage Collapse
        10. Identification of Weak Bus of Power Network
        11. Diagonal Element Ratio
        12. Line Voltage Stability Index
        13. Local Load Margin
        14. Voltage Ratio Index
    3. 3.3 Theory of ANN
      1. 3.3.1 Attributes of ANNs
        1. Building Block of ANNs
        2. Building Layers of ANNs
        3. Structures of Neural Networks
        4. Training Algorithms of Neural Networks
    4. 3.4 Analysis of Voltage Stability of Multi-Bus Power Network
      1. 3.4.1 Classical Analysis of Voltage Stability
      2. 3.4.2 Application of ANN on Voltage Stability Analysis
    5. 3.5 Summary
    6. Annotating Outline
  16. 4. Improvement of System Performances Using FACTS and HVDC
    1. 4.1 Introduction
    2. 4.2 Development of FACTS Controllers
      1. 4.2.1 Modeling of Shunt Compensating Device
        1. Conventional Model of SVC
        2. Shunt Variable Susceptance Model of SVC
        3. Firing Angle Model of SVC
      2. 4.2.2 Modeling of Series Compensating Device
        1. Variable Series Impedance Power Flow Model of TCSC
        2. Firing Angle Power Flow Model of TCSC
    3. 4.3 Prologue of High-Voltage Direct Current (HVDC) System
      1. 4.3.1 Modeling of DC Link
    4. 4.4 Improvement of System Performance Using FACTS and HVDC
      1. 4.4.1 Improvement of Voltage Profile of Weak Bus Using SVC
      2. 4.4.2 Application of ANN for the Improvement Voltage Profile Using SVC
      3. 4.4.3 Application of TCSC and HVDC for Upgrading of Cost-Constrained System Performance
        1. Determination of the Weakest Link in the System under Stressed and Contingent Conditions
        2. Performance of TCSC and the HVDC Interconnection Link Separately in Stressed Conditions
        3. Performance of TCSC and the HVDC Interconnection Link during Line Contingency
        4. Cost Comparison of TCSC and the HVDC Link
    5. 4.5 Summary
    6. Annotating Outline
  17. 5. Multi-Objective Optimization Algorithms for Deregulated Power Market
    1. 5.1 Introduction
    2. 5.2 Deregulated Power Market Structure
    3. 5.3 Soft Computing Methodologies for Power Network Optimizations
      1. 5.3.1 Overview of Genetic Algorithm
      2. 5.3.2 Overview of Particle Swarm Optimization
      3. 5.3.3 Overview of Differential Evolution
    4. 5.4 Algorithms for Utility Optimization with Cost and Operational Constraints
      1. 5.4.1 Genetic Algorithm-Based Cost-Constrained Transmission Line Loss Optimization
      2. 5.4.2 GA-Based Generation Cost-Constrained Redispatching Schedules of GENCOs
    5. 5.5 Congestion Management Methodologies
      1. 5.5.1 Generator Contribution-Based Congestion Management Using Multi-Objective GA
      2. 5.5.2 DE- and PSO-Based Cost-Governed Multi-Objective Solutions in Contingent State
      3. 5.5.3 Mitigation of Line Congestion and Cost Optimization Using Multi-Objective PSO
      4. 5.5.4 Swarm Intelligence-Based Cost Optimization for Contingency Surveillance
        1. Development of Value of Lost Load (VOLL)
        2. Development of Value of Congestion Cost (VOCC)
        3. Development of Value of Excess Loss (VOEL)
    6. 5.6 Summary
    7. Annotating Outline
  18. 6. Application of Stochastic Optimization Techniques in the Smart Grid
    1. 6.1 Introduction
    2. 6.2 Smart Grid and Its Objectives
      1. 6.2.1 Concept of the Smart Grid
      2. 6.2.2 Elementary Objectives of the Smart Grid and Demand Response
      3. 6.2.3 Demand Response-Based Architecture of the Smart Grid
      4. 6.2.4 Effect of DR on the Smart Grid Scenario
      5. 6.2.5 Cost Component of the Smart Grid
        1. Cost Components for the Smart Grid: Transmission Systems and Sub-Stations End
        2. Cost Components for the Smart Grid: Distribution End
        3. Cost Components of the Smart Grid: Consumer End
      6. 6.2.6 Smart Grid: Cost-Benefit Analysis
    3. 6.3 Swarm Intelligence-Based Utility and Cost Optimization
      1. 6.3.1 Cost Objective and Operating Constraints of the Work
      2. 6.3.2 Theory of Cost-Regulated Curtailment Index (CI)
      3. 6.3.3 Cost Realization Methodology Implementation with Swarm Intelligence
      4. 6.3.4 Implementation of the Cost-Effective Methodology with DR Connectivity
    4. 6.4 Summary
    5. Annotating Outline
  19. 7. Epilogue
    1. 7.1 Summary and Conclusions
    2. 7.2 Future Scope
  20. References
  21. Appendix A: Description of Test Systems
  22. Appendix B: Development of System Performance Indices
  23. Index

Product information

  • Title: Electricity Pricing
  • Author(s): Sawan Sen, Samarjit Sengupta, Abhijit Chakrabarti
  • Release date: September 2018
  • Publisher(s): CRC Press
  • ISBN: 9781351831031