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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 ...
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 ...
Stochastic security-constrained generation expansion planning based on linear distribution factors
(2016)
This study proposes to apply an efficient formulation to solve the stochastic security-constrained generation capacity expansion planning problem using power transmission distribution factors (PT) and line outage distribution ...
Constrained Optimization With Stochastic Feasibility Regions Applied To Vehicle Path Planning
(SPRINGERDORDRECHT, 2016)
Approximation Algorithms For K-level Stochastic Facility Location Problems
(Springer New York LLC, 2016)
Var Planning Problem Considering Conditional Value-at-Risk Assessment
(Ieee, 2014-01-01)
This paper presents the reactive power planning solution under risk assessment through the CVaR (Conditional-Value-at-Risk) using stochastic programming. Load uncertainty is modeled by distribution function. Uncertainty ...
Var planning problem considering conditional value-at-risk assessment
(2014-01-01)
This paper presents the reactive power planning solution under risk assessment through the CVaR (Conditional-Value-at-Risk) using stochastic programming. Load uncertainty is modeled by distribution function. Uncertainty ...