The Experts below are selected from a list of 26121 Experts worldwide ranked by ideXlab platform
Jason Frank - One of the best experts on this subject based on the ideXlab platform.
-
APPLYING A Splitting Technique TO ESTIMATE ELECTRICAL GRID RELIABILITY Wander Wadman
2015Co-Authors: Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment, and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when using an equivalent Crude Monte Carlo method. We show further that a bad choice for the time step size or for the importance function may endanger this squared relative error.
-
APPLYING A Splitting Technique TO ESTIMATE ELECTRICAL GRID RELIABILITY Wander Wadman
2015Co-Authors: Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when an equivalent Crude Monte Carlo method is used.
-
Applying a Splitting Technique to estimate electrical grid reliability
2013 Winter Simulations Conference (WSC), 2013Co-Authors: Wander Wadman, Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment, and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when using an equivalent Crude Monte Carlo method. We show further that a bad choice for the time step size or for the importance function may endanger this squared relative error.
Daan Crommelin - One of the best experts on this subject based on the ideXlab platform.
-
APPLYING A Splitting Technique TO ESTIMATE ELECTRICAL GRID RELIABILITY Wander Wadman
2015Co-Authors: Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment, and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when using an equivalent Crude Monte Carlo method. We show further that a bad choice for the time step size or for the importance function may endanger this squared relative error.
-
APPLYING A Splitting Technique TO ESTIMATE ELECTRICAL GRID RELIABILITY Wander Wadman
2015Co-Authors: Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when an equivalent Crude Monte Carlo method is used.
-
Applying a Splitting Technique to estimate electrical grid reliability
2013 Winter Simulations Conference (WSC), 2013Co-Authors: Wander Wadman, Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment, and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when using an equivalent Crude Monte Carlo method. We show further that a bad choice for the time step size or for the importance function may endanger this squared relative error.
Wander Wadman - One of the best experts on this subject based on the ideXlab platform.
-
Applying a Splitting Technique to estimate electrical grid reliability
2013 Winter Simulations Conference (WSC), 2013Co-Authors: Wander Wadman, Daan Crommelin, Jason FrankAbstract:As intermittent renewable energy penetrates electrical power grids more and more, assessing grid reliability is of increasing concern for grid operators. Monte Carlo simulation is a robust and popular Technique to estimate indices for grid reliability, but the involved computational intensity may be too high for typical reliability analyses. We show that various reliability indices can be expressed as expectations depending on the rare event probability of a so-called power curtailment, and explain how to extend a Crude Monte Carlo grid reliability analysis with an existing rare event Splitting Technique. The squared relative error of index estimators can be controlled, whereas orders of magnitude less workload is required than when using an equivalent Crude Monte Carlo method. We show further that a bad choice for the time step size or for the importance function may endanger this squared relative error.
Walaa M. Moursi - One of the best experts on this subject based on the ideXlab platform.
-
douglas rachford Splitting for the sum of a lipschitz continuous and a strongly monotone operator
Journal of Optimization Theory and Applications, 2019Co-Authors: Walaa M. Moursi, Lieven VandenbergheAbstract:The Douglas–Rachford method is a popular Splitting Technique for finding a zero of the sum of two subdifferential operators of proper, closed, and convex functions and, more generally, two maximally monotone operators. Recent results concerned with linear rates of convergence of the method require additional properties of the underlying monotone operators, such as strong monotonicity and cocoercivity. In this paper, we study the case, when one operator is Lipschitz continuous but not necessarily a subdifferential operator and the other operator is strongly monotone. This situation arises in optimization methods based on primal–dual approaches. We provide new linear convergence results in this setting.
-
the forward backward algorithm and the normal problem
Journal of Optimization Theory and Applications, 2018Co-Authors: Walaa M. MoursiAbstract:Abstract The forward–backward Splitting Technique is a popular method for solving monotone inclusions that have applications in optimization. In this paper, we explore the behaviour of the algorithm when the inclusion problem has no solution. We present a new formula to define the normal solutions using the forward–backward operator. We also provide a formula for the range of the displacement map of the forward–backward operator. Several examples illustrate our theory.
-
The forward-backward algorithm and the normal problem
arXiv: Optimization and Control, 2016Co-Authors: Walaa M. MoursiAbstract:The forward-backward Splitting Technique is a popular method for solving monotone inclusions that has applications in optimization. In this paper we explore the behaviour of the algorithm when the inclusion problem has no solution. We present a new formula to define the normal solutions using the forward-backward operator. We also provide a formula for the range of the displacement map of the forward-backward operator. Several examples illustrate our theory.
Giovanni Russo - One of the best experts on this subject based on the ideXlab platform.
-
high order numerical methods for the space non homogeneous boltzmann equation
Journal of Computational Physics, 2003Co-Authors: Francis Filbet, Giovanni RussoAbstract:In this paper we present accurate methods for the numerical solution of the Boltzmann equation of rarefied gas. The methods are based on a time Splitting Technique. The transport is solved by a third order accurate (in space) positive and flux conservative (PFC) method. The collision step is treated by a Fourier approximation of the collision integral, which guarantees spectral accuracy in velocity, coupled with several high order integrators in time. Strang Splitting is used to achieve second order accuracy in space and time. Several numerical tests illustrate the properties of the methods.
