deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. in this paper, generation reliability is considered, and a method for its assessment using intelligent systems is proposed. also, because of power market and generators’ forced outages stochastic behavior, monte carlo simulation is used for reliability evaluation. generation reli...

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 ...

background: monte carlo (mc) modeling of a linear accelerator is a prerequisite for monte carlo dose calculations in external beam radiotherapy. in this study, a simple and efficient model was developed for elekta sl-25 linear accelerator using mcnp4c monte carlo code materials and methods: the head of elekta sl-25 linac was simulated for 6 and 18 mv photon beams using mcnp4c mc code. energy sp...

Background: The aim of this study was to develop and implement a Monte Carlo framework for evaluation of patient specific out-of-field organ equivalent dose (OED). Materials and Methods: Dose calculations were performed using a Monte Carlo-based model of Oncor linac and tomographic phantoms. Monte Carlo simulations were performed using EGSnrc user codes. Dose measurements were performed using r...

we compare two approaches for a markovian model in flexible manufacturing systems (fmss) using monte carlo simulation. the model which is a development of fazlollahtabar and saidi-mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (agv) namely, the reliability of machines and the reliability of agvs in a multiple agv jobsho...

We study optimal stochastic (or Monte Carlo) quadrature formulas for convex functions. While nonadaptive Monte Carlo methods are not better than deterministic methods we prove that adaptive Monte Carlo methods are much better. Abstract. We study optimal stochastic (or Monte Carlo) quadrature formulas for convex functions. While nonadaptive Monte Carlo methods are not better than deter-ministic ...