電力システム応用<br>Electric Power System Applications of Optimization(2 NED)

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電力システム応用
Electric Power System Applications of Optimization(2 NED)

  • 著者名:Momoh, James A.
  • 価格 ¥13,450 (本体¥12,228)
  • CRC Press(2017/12/19発売)
  • ポイント 122pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9781420065862
  • eISBN:9781351834841

ファイル: /

Description

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

Contents. Chapter 1. Introduction. Chapter 2. Electric Power System Models. Chapter 3. Power-Flow Computations. Chapter 4. Constrained Optimization and Applications. Chapter 5. Linear Programming and Applications. Chapter 6. Interior Point Methods. Chapter 7. Nonlinear Programming. Chapter 8. Dynamic Programming. Chapter 9. Lagrangian Relaxation. Chapter 10. Decomposition Method. Chapter 11 State Estimation. Chapter 12. Optimal Power Flow. Chapter 13. Pricing. Chapter 14 Unit Commitment. Chapter 15. Genetic Algorithms. Chapter 16. Functional Optimization, Optimal Control and Adaptive Dynamic Programming. Index