Stochastic Robust Mathematical Programming Model for Power System Optimization

A Robust Optimization Perspective on Stochastic Programming

In this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for random variables termed the forward and backward deviations. These deviation measures capture distributional asymmetry and lead to better approximations of chance constraints. Using a linear decision rule, we also propose a tractable approximation approach for solvi...

A Robust Optimization Perspective of Stochastic Programming

In this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for bounded random variables known as the forward and backward deviations. These deviation measures capture distributional asymmetry and lead to better approximations of chance constraints. We also propose a tractable robust optimization approach for obtaining robust so...

Stochastic Programming Model for Power Generation

We consider power system expansion planning under uncertainty. In our approach, integer programming and stochastic programming provide a basic framework. We develop a multistage stochastic programming model in which some of the variables are restricted to integer values. By utilizing the special property of the problem, called block separable recourse, the problem is transformed into a two-stag...

A Stochastic Optimization Model for Groundwater Management

A Stochastic Optimization Model for Groundwater Management