December 2015
Intermediate to advanced
442 pages
10h 10m
English
Content preview from Adaptive Stochastic Optimization Techniques with Applications
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7 Stochastic and Adaptive Dynamic Programming Fundamentals
7.1 Overview
This chapter provides an overview of stochastic programming (SP) and adaptive dynamic programming (ADP) principle, formulation, variants, and potential applications to power systems control, operation, and planning problems. Applications of these methods in power system, finance, and other areas are in use.
7.2 Introduction to Stochastic Programming
Stochastic programming (SP) is an approach used whenever randomness and uncertainty present in a system. SP can be formulated as a linear integer, mixed integer, or nonlinear problem with uncertainty and randomness present into the problem [1]. Dantzing and Beale first introduced this method in 1955 [2,3].
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