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Optimal reactive power dispatch using stochastic chance-constrained programming
(2012-11-27)
Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage ...
Optimal reactive power dispatch using stochastic chance-constrained programming
(2012-11-27)
Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage ...
Multistep stochastic mirror descent for risk-averse convex stochastic programs based on extended polyhedral risk measures
(EMAp - Escola de Matemática Aplicada, 2016)
We consider risk-averse convex stochastic programs expressed in terms of extended polyhedral risk measures. We derive computable con dence intervals on the optimal value of such stochastic programs using the Robust Stochastic ...
Building a stochastic programming model from scratch: a harvesting management example
(Routledge, 2016)
We analyse how to deal with the uncertainty before solving a stochastic optimization problem and we apply it to a forestry management problem. In particular, we start from historical data to build a stochastic process for ...
Stochastic modeling and control of bioreactors
(Elsevier, 2017)
In this work we propose a stochastic model for a sequencing-batch reactor (SBR) and for a chemostat. Both models are described by systems of Stochastic Differential Equations (SDEs), which are obtained as limits of suitable ...
Non-asymptotic confidence bounds for the optimal value of a stochastic program
(EMAp - Escola de Matemática Aplicada, 2016)
We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper ...