Electric Power System Applications of Optimization Power Engineering Willis 1st Edition by James Momoh ISBN 978-1420065862 1420065862

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Product details: 

ISBN 10:  1420065862

ISBN 13: 978-1420065862

Author:  James A. Momoh

As the demand for energy continues to grow, optimization has risen to the forefront of power engineering research and development. Continuing in the bestselling tradition of the first edition, Electric Power System Applications of Optimization, Second Edition presents the theoretical background of optimization from a practical power system point of view, exploring advanced techniques, new directions, and continuous application problems.

The book provides both the analytical formulation of optimization and various algorithmic issues that arise in the application of various methods in power system planning and operation. The second edition adds new functions involving market programs, pricing, reliability, and advances in intelligent systems with implemented algorithms and illustrative examples. It describes recent developments in the field of Adaptive Critics Design and practical applications of approximate dynamic programming. To round out the coverage, the final chapter combines fundamental theories and theorems from functional optimization, optimal control, and dynamic programming to explain new Adaptive Dynamic Programming concepts and variants.

 

With its one-of-a-kind integration of cornerstone optimization principles with application examples, this second edition propels power engineers to new discoveries in providing optimal supplies of energy.

Table of contents: 

1. Introduction

2. Electric Power System Models

3. Power Flow Computations

4. Constrained Optimization and Applications

5. Linear Programming and Applications

6. Interior Point Methods

7. Nonlinear Programming

8. Dynamic Programming

9. Illustrative Example of the Decomposition Technique

10. Conclusions

11. References

Optimal Power Flow
12. OPF Fuel Cost Minimization
13. OPF Active Power Loss Minimization
14. OPF VAr Planning
15. OPF Adding Environmental Constraints

Dynamic Programming Details
16. Characteristics of Dynamic Programming
17. Concept of Suboptimization and the Principle of Optimality
18. Formulation of Dynamic Programming
19. Backward and Forward Recursion
20. Computational Procedure in Dynamic Programming
21. Computational Economy in DP
22. Conversion of a Final Value Problem into an Initial Value Problem
23. Conclusions
24. Problem Set
25. References

Lagrangian Relaxation
26. Concepts
27. The Subgradient Method for Setting the Dual Variables
28. Setting Tk
29. Comparison with Linear Programming-Based Bounds
30. An Improved Relaxation
31. Summary of Concepts
32. Past Applications
33. Summary
34. Illustrative Examples
35. Conclusions
36. Problem Set
37. References

Decomposition Method
38. Formulation of the Decomposition Problem
39. Algorithm of Decomposition Technique

Optimization Techniques
40. Commonly Used Optimization Technique LP
41. Commonly Used Optimization Technique NLP
42. Illustrative Examples
43. Conclusions
44. Problem Set
45. References

Unit Commitment
46. Formulation of Unit Commitment
47. Optimization Methods
48. Illustrative Example
49. Updating t in the Unit Commitment Problem
50. Unit Commitment of Thermal Units Using Dynamic Programming
51. Illustrative Problems
52. Problem Set
53. References

Genetic Algorithms
54. Definition and Concepts Used in Genetic Computation
55. Genetic Algorithm Approach
56. Theory of Genetic Algorithms
57. The Schemata Theorem
58. General Algorithm of Genetic Algorithms
59. Application of Genetic Algorithms
60. Application to Power Systems
61. Illustrative Examples

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Tags: James Momoh, Electric Power, System Applications, Optimization Power Engineering