Sharif Digital Repository

This paper provides a general methodology for evaluating the reliability of microgrids embedding conventional and renewable energy sources (RESs), as well as energy storage systems (ESSs). The developed reliability assessment model is then leveraged to investigate the impact of different resource scheduling methods on the reliability. The technique applied in this article to assess microgrid reliability is based on the sequential Monte Carlo simulation. In this approach, the coincidence of faults is considered, aside from the annual generation pattern of RESs, i.e., wind and photovoltaic, and the network load profiles. For the sake of considering priority of the microgrid loads, two... 

Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo algorithm for calculating VaR and ES based on Gaussian Mixture Models is introduced. Gaussian Mixture Models are able to cluster input data with respect to market's conditions and therefore no correlation matrices are needed for risk computation. Sampling from each cluster with respect to their weights and then calculating the volatility-adjusted stock returns leads to possible scenarios for prices of assets. Our results on a sample of US stocks show that... 

The reactive extraction behavior on the mean drop size and distribution for synergistic extraction of vanadium from sulfate medium with di-(2-ethylhexyl) phosphoric acid (D2EHPA) and its mixture with tributyl phosphate (TBP) in kerosene has been interpreted in the modified rotating disc contactor column. In batch experiments, the maximum extraction efficiency was obtained in the single extraction system with 0.29 molar D2EHPA at an equilibrium pH of 2, whereas the extraction percentage was significantly increased by adding 0.3 molar TBP into the same D2EHPA concentration due to the synergistic effect. The solvent extraction process has been optimized by applying the central composition... 

Studying the mechanical performance of concrete after being exposed to high temperatures is an important step in the damage assessment of buildings and fire safety applications. However, predicting the compressive strength of GPC accurately after exposure to high temperatures is a challenging task. In this paper, artificial neural network (ANN) and support vector regression (SVR) models were developed to predict the compressive strength of geopolymer concrete (GPC) at high temperatures ranging from 100 °C to 1000 °C. A series of experiments consisting of different mix designs were conducted at elevated temperatures to prepare a dataset. Besides experiments' results, the data of previously... 

The selection of a suitable duty factor (DF) remains a major challenge in respiratory-gated treatments. Therefore, this study aims at presenting a new methodology for fast optimizing the gating window width (duty factor (DF)) in respiratory-gated proton partial breast irradiation (PBI). To do so, GATE Monte Carlo simulations were performed for various target sizes and locations in supine and prone positions. Three different duty factors of 20, 25, and 33% were considered. Sparing factors (SF) for four organs-at-risk (OARs) were then assessed. The weighted-sum method was employed to search for an optimal DF. The results indicate that an SF higher than unity was obtained for all plans. The SF...