In this paper, a stochastic two-stage model is offered for optimization of the day-ahead scheduling of the microgrid. System uncertainties including dispatchable distributed generation and energy storage contingencies are considered in the stochastic model. For handling uncertainties, Monte Carlo simulation is employed for generation several scenarios and then a reduction method is used to decr...

the determination of gyration radius is a strong research for configuration of a macromolecule. italso reflects molecular compactness shape. in this work, to characterize the behavior of theprotein, we observe quantities such as the radius of gyration and the average energy. we studiedthe changes of these factors as a function of temperature for acetylcholine receptor protein in gasphase with n...

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems [1], have been subject to multiple analyses in research, with the aim of characterizing the technology’s usefulness for optimization and sampling tasks [2–16]...

T HE importance of Monte Carlo methods for inference in science and engineering problems has grown steadily over the past decade. This growth has largely been propelled by an explosive increase in accessible computing power. In association with this growth in computing, it has become clear that Monte Carlo methods can significantly expand the class of problems that can be addressed practically....

We pursue the development and application of the recently introduced linear optimization method for determining the optimal linear and nonlinear parameters of Jastrow-Slater wave functions in a variational Monte Carlo framework. In this approach, the optimal parameters are found iteratively by diagonalizing the Hamiltonian matrix in the space spanned by the wave function and its first-order der...

Kinetic Monte Carlo simulation was applied to investigation of kinetics and mechanism of oxalic acid degradation by direct and heterogeneous catalytic ozonation. La-containing perovskites including LaFeO3, LaNiO3, LaCoO3 and LaMnO3 was studied as catalyst for oxalic acid ozonation. The reaction kinetic mechanisms of each abovementioned catalytic systems has been achieved. The rate constants val...

In the area of financial mathematics Monte Carlo simulation is often successfully used to estimate the prices of certain products. However in many cases calibrating Monte Carlo based models to market prices turns out to be difficult due to stochastic noise arising in the objective functionals. This noise can be reduced by the use of fixed point-sets of random numbers which are reused for every ...

Probabilistic Finite Element (FE) models have recently been developed to assess the impact of experimental variability present in knee wear simulator on predicted Total Knee Replacement (TKR) mechanics by determining the performance envelope of joint kinematics and contact mechanics. The gold standard for this type of analysis is currently the Monte Carlo method, however, this requires a larger...

This paper investigates Monte Carlo techniques for construction of compact wavefunctions for the internal atomic motion of the D 3 O + ion. The polarization force field models of Stillinger, et al. and of Ojamae, et al. were used. Initial pair product wavefunctions were obtained from the asymptotic high temperature many-body density matrix after contraction to atom pairs using Metropolis Monte ...

We consider unconstrained optimization problems where only “stochastic” estimates of the objective function are observable as replicates from a Monte Carlo oracle. The Monte Carlo oracle is assumed to provide no direct observations of the function gradient. We present ASTRO-DF — a class of derivative-free trust-region algorithms, where a stochastic local interpolation model is constructed, opti...