A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch

Efficient Representation of Uncertainty for Stochastic Economic Dispatch

Stochastic economic dispatch models address uncertainties in forecasts of renewable generation output by considering a finite number of realizations drawn from a stochastic process model, typically via Monte Carlo sampling. Accurate evaluations of expectations or higher-order moments for quantities of interest, e.g., generating cost, can require a prohibitively large number of samples. We propo...

Stochastic Testing Method for Transistor-level Uncertainty Quantification

Design and fabrication uncertainties have become an important issue in nano-scale integrated circuit design. Such uncertainties are typically randomly distributed, as described by probability density functions extracted from measurements. Such device-level uncertainties can propagate to the upper circuit level, leading to significant variations in circuit performances (such as power dissipation...

Data-Driven Stochastic Multiscale Method

Introduction 1 Randomness manifests itself in many aspects of real-world problems, such as initial/boundary conditions, model parameters, measurements, to name a few. 2 Its effect may span many scales and grow with time through nonlinear interactions, which results in dramatic difference compared with that of the deterministic model. 3 A typical scenario occurring frequently in practice is that...

Incorporating stochastic analysis in wind turbine design: data-driven random temporal-spatial parameterization and uncertainty quantification

Wind turbines reliability is affected by stochastic factors in the turbulent inflow and wind turbine structures. On one hand, the variability in wind dynamics and the inherent stochastic structures result in random loads on wind turbine rotor and tower. On the other hand, the inherent structural uncertainties caused by imperfect control of manufacturing process introduce unpredictable failures ...

A Data-Driven Method for Robust Water Allocation under Uncertainty