Adaptive Stochastic Optimization Techniques With Applications

This book presents new trends in optimization methods that can be used to handle the stochastic, predictive nature of large-scale system problems in power and energy. The author provides decision tools and techniques for heuristic optimization and adaptive dynamic programming. He also reviews the latest research in optimization techniques derived from static optimization, decision support tools, and heuristic and adaptive dynamic programming for handling problems with stochastic, predictive, and adaptive behavior. In addition to easy-to-follow algorithms and illustrative engineering examples, the author also includes benchmark problems from power systems using state-of-the-art optimization.

James A. Momoh is a Professor of Electrical and Computer Engineering and the Director of the Center for Energy Systems and Control at Howard University, Washington, D.C.