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 d...

wind power generation is variable and uncertain. in the power systems with high penetration of wind power, determination of equivalent operating reserve is the main concern of systems operator. in this paper, a model is proposed to determine operating reserves in simultaneous market clearing of energy and reserve by stochastic programming based on scenarios generated via monte carlo simulation ...

Ordinary differential equations(ODEs) with stochastic processes in their vector field, have lots of applications in science and engineering. The main purpose of this article is to investigate the numerical methods for ODEs with Wiener and Compound Poisson processes in more than one dimension. Ordinary differential equations with Ito diffusion which is a solution of an Ito stochastic differentia...

local bus network is the most popular transit mode and the only available transit mode in the majority of cities of the world. increasing the utility of this mode which increases its share from urban trips is an important goal for city planners. timetable setting as the second component of bus network design problem (network route design timetable setting vehicle assignment crew assignment) hav...

using greedy clustering method to solve capacitated location-routing problem with fuzzy demands abstract in this paper, the capacitated location routing problem with fuzzy demands (clrp_fd) is considered. in clrp_fd, facility location problem (flp) and vehicle routing problem (vrp) are observed simultaneously. indeed the vehicles and the depots have a predefined capacity to serve the customerst...

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...

This paper focuses on a nonlinear stochastic model for financial simulation and forecasting based on assumptions of multivariate stochastic correlation, with an application to the European market. We present in particular the key elements of a structured hierarchical econometric model that can be used to forecast financial and commodity markets relying on statistical and simulation methods. The...

contrary to the long period ground motions that can be predicted and estimated, high frequency ground motions have random character and behave stochastically. stochastic modeling methods are usually used for the modeling of high frequency ground motions where there are not strong ground motion records. stochastic methods are of two kinds: in the first one, the seismic source is considered as a ...

ABSTRACT - Cultivation of legumes in crop rotations results in atmosphere nitrogen fixation. After harvesting, part of this external nitrogen remains in soil and is used by subsequent crops. This implies that producers would gain from lowering the amount of nitrogen fertilizer in their fields. In this study, stochastic simulation is used to generate probability distributions of net present valu...

Discrete-event simulation based optimization is the process of finding the optimum design of a stochastic system when the performance measure(s) could only be estimated via simulation. Randomness in simulation outputs often challenges the correct selection of the optimum. We propose an algorithm that merges Ranking and Selection procedures with a large class of random search methods for continu...