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Adaptive Stochastic Optimization Techniques with Applications




ISBN 9781439829783
Published November 24, 2015 by CRC Press
414 Pages 85 B/W Illustrations

 
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Book Description

Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on optimization techniques used to solve problems with adaptive, dynamic, and stochastic features. Presenting modern advances in static and dynamic optimization, decision analysis, intelligent systems, evolutionary programming, heuristic optimization, stochastic and adaptive dynamic programming, and adaptive critics, this book:

  • Evaluates optimization methods for handling operational planning, Voltage/VAr, control coordination, vulnerability, reliability, resilience, and reconfiguration issues
  • Includes mathematical formulations, algorithms for implementation, illustrative engineering examples, and case studies from actual power systems
  • Discusses the limitations of current optimization techniques in meeting the challenges of smart electric grids

Adaptive Stochastic Optimization Techniques with Applications describes cutting-edge optimization methods used to address large-scale system problems applicable to power, energy, communications, transportation, and economics.

Table of Contents

Introduction
Intelligent Systems and Adaptive Dynamic Programming Techniques
Outline
References
Suggested Readings

CLASSICAL OPTIMIZATION TECHNIQUES

Static Optimization Techniques
Introduction
Definition
Applications of Static Optimization
Constraints and Limitation of Static Optimization Techniques
Solution Techniques
Conclusion
Problem Set
References
Suggested Readings

Dynamic Optimization Techniques and Optimal Control
Introduction
Definitions of Dynamic Programming
Dynamic Programming Formulations
Optimal Control
Pontryagin’s Minimum Principle
Illustrative Examples
Conclusions
Problem Set
References
Suggested Readings

Decision Analysis Tools
Introduction
Classification of Decision Analysis
Decision Analysis Techniques Based on Probability Methods
Analytical Hierarchical Programming (AHP)
Analytical Network Process (ANP)
Cost-Benefit Analysis
Risk Assessment Strategy for Decision Support
Game Theory
Illustrative Examples
Conclusion
Problem Set
References
Suggested Readings

Intelligent Systems
Introduction
Expert Systems
Fuzzy Logic Systems
Artificial Neural Networks
Genetic Algorithm
Application of Intelligent System to Power System
Illustrative Examples
Conclusion
Problem Set
References
Suggested Readings

Evolutionary Programming and Heuristic Optimization
Introduction
Particle Swarm Optimization
Ant Colony Optimization
Genetic Algorithm
Annealing Method
Pareto Multiples Optimization
Tabu Search Optimization Method
Conclusion
References
Suggested Readings

Stochastic and Adaptive Dynamic Programming Fundamentals
Overview
Introduction to Stochastic Programming
Stochastic Programming Variants
Definition of ADP
ADP Formulation
Illustrative Examples
Conclusion
Problem Set
References
Suggested Readings

APPLICATIONS TO POWER SYSTEMS

Introduction to Power System Applications
Overview of Power System Optimization Models
Overview of Power System Applications

Optimal Power Flow
Introduction
History of Optimum Power Flow (OPF) Computation
OPF Problem Formulations and Computation
Methods Used in OPF
Cases
Conclusion
Problem Set
References
Suggested Readings

Vulnerability Assessment
Introduction
Generalized Model for Vulnerability Assessment
Methods Used in Vulnerability Assessment
Vulnerability Assessment Challenges
Cases
Conclusion
Problem Set
References
Suggested Readings

Voltage/VAr
Introduction
History of Voltage/VAr Control
Models and Formulation
Methods Used in Voltage/VAr
Cases
Conclusion
Problem Set
References
Suggested Readings

Unit Commitment
Introduction
History of Unit Commitment Optimization
Objective Function
A Simple Merit Order Scheme
Methods for Unit Commitment
Challenges Facing Unit Commitment Optimization
Cases
Conclusion
Problem Set
References
Suggested Readings

Control Coordination
Introduction
Control Strategy
Coordinated Control Design
Problem Definition and Formulation
Methods Used in Control Coordination
Cases
Conclusion
Problem Set
References
Suggested Readings

Reliability and Reconfiguration
Introduction
Reliability
Reconfiguration
Optimization of Reliability and Reconfiguration
Cases
Conclusion
Problem Set
References
Suggested Readings

Smart Grid and Adaptive Dynamic Stochastic Optimization
Introduction
Power Grid Generation Level in Smart Grid
Bulk Power System Automation of Smart Grid at Transmission Level
Distribution System of the Power Grid
End User/Appliance Level of the Smart Grid
Design Smart Grid Using Advanced Optimization and Control Techniques
Applications for Dynamic Stochastic Optimum Power Flow (DSOPF)
DSOPF Application to Smart Grid
Computational Challenges for the Development of Smart Grid
Cases
Conclusion
References
Suggested Readings

Epilogue
Design of Optimal Future Grid with Different Distributed Energy Resources with the Capability for Sustainability, Economies of Scale, and Resilient to Different Attacks
Storage and Energy Management under Uncertainties
Transmission Challenges and Optimization for Smart Grid
Next-Generation Distribution Grid

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Author(s)

Biography

James A. Momoh is a professor at Howard University and the director of the Centre for Energy Systems and Control (CESaC) at Howard University. He is well known for his achievements in engineering education and his extensive research in optimization, power systems, and smart grids/micro grids. He is a distinguished fellow of the Nigerian Society of Engineers (NSE), a fellow of the Institute of Electrical and Electronics Engineers (IEEE), a fellow of the Nigerian Academy of Engineering (NAE), and a fellow member of the Nigerian Academy of Science (NAS). He served as program director at the National Science Foundation (NSF) from 2001-2004 and as Electrical and Computer Engineering (EECE) Department chair at Howard University for 11 years. He holds a PhD from Howard University, an MSEE from Carnegie Mellon University, and an MS in systems engineering from the University of Pennsylvania. He is a recipient of numerous awards, including the coveted 1987 NSF Presidential Young Investigator award. Dr. Momoh has published several technical papers and bestselling textbooks on power systems, optimization, and smart grids.

Reviews

"The book serves as a pioneering work for addressing many of the computational challenges, speci cally, the power system optimization problems with adaptive dynamic stochastic and predictive characteristics."I. M. Stancu-Minasian (Bucure□sti)