Adaptive Stochastic Optimization Techniques with Applications

by James A. Momoh

Overview

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 pro

Product Details

ISBN-13:	9781498782449
Publisher:	CRC Press
Publication date:	12/02/2015
Sold by:	Barnes & Noble
Format:	eBook
Pages:	442
File size:	7 MB

About the Author

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.

Table of Contents

Introduction. Static Optimization Techniques. Dynamic Optimization Techniques and Optimal Control. Decision Analysis Tools. Intelligent Systems. Evolutionary Programming and Heuristic Optimization. Stochastic and Adaptive Dynamic Programming Fundamentals. Introduction to Power System Applications. Optimal Power Flow. Vulnerability Assessment. Voltage/VAr. Unit Commitment. Control Coordination. Reliability and Reconfiguration. Smart Grid and Adaptive Dynamic Stochastic Optimization. Epilogue.

Editorial 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 (Bucuresti)

From the Publisher