Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles

Abstract

The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.     

Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis

In this paper we present results of unsupervised cross-lingual speaker adaptation applied to text-to-speech synthesis. The application of our research is the personalisation of speech-to-speech translation in which we employ a HMM statistical framework for both speech recognition and synthesis. This framework provides a logical mechanism to adapt synthesised speech output to the voice of the user by way of speech recognition. In this work we present results of several different unsupervised and cross-lingual adaptation approaches as well as an end-to-end speaker adaptive speech-to-speech translation system. Our experiments show that we can successfully apply speaker adaptation in both unsupervised and cross-lingual scenarios and our proposed algorithms seem to generalise well for several language pairs. We also discuss important future directions including the need for better evaluation metrics.     

A simulation-based approach to study stochastic inventory-planning games

Non-cooperative decision-making problems in a decentralized supply chain can be characterized and studied using a stochastic game model. In an earlier paper, the authors developed a methodology that uses machine learning for finding (near) optimal policies for non-zero sum stochastic games, and applied their methodology on an N-retailer and W-warehouse inventory-planning problem. The focus of this paper is on making the methodology more amenable to practical applications by making it completely simulation-based. It is also demonstrated, through numerical example problems, how this methodology can be used to find (near) equilibrium policies, and evaluate short-term rewards of stochastic games. Short-term rewards of stochastic games could be, in many instances, more critical than equilibrium rewards. To our knowledge, no methodology exists in the open literature that can capture the short-term behaviour of non-zero sum stochastic games as examined in this paper.     

Performance analysis for queueing systems with close down periods and server under maintenance

A single server queue subject to maintenance of the server and the close down period is considered. We obtain explicit expressions for the transient probabilities of the system size, the server under maintenance state and the close down period. The time-dependent performance measures of the system and the probability density function of the first-passage-time to reach the maintenance state are discussed. The corresponding steady state analysis and key performance measures of the system are also presented. Finally, the effect of various parameters on system performance measures is demonstrated by a numerical example.     

Special sensor microwave imager data in field experiments: FIFE-1987

Estimation of regional soil moisture is of importance to the hydrological modelling community for validating the accuracy of model predictions and to the climate community for use in regional and global climate models. Soil moisture estimation is done in two ways, viz., estimation using models and estimation using satellite data. Both these methods have to be corroborated using in situ field data. The present paper examines the feasibility of using observations of brightness temperature from the Special Sensor Microwave Imager (SSM/I) for small scale/catchment scale studies. The simulations of the 19 and 37 GHz brightness temperatures are carried out for a period of 13 days between 6 and 21 August 1987. The comparisons between the simulated and the observed brightness temperatures are good and the errors can be explained based on the atmospheric and surface conditions. Sensitivity analysis of the brightness temperatures to leaf area index, soil moisture and soil temperatures shows interesting characteristics. The errors in the simulated brightness temperatures can be explained by variability in the input parameters. This study shows that such an approach holds promise for local and regional studies of the land surface.     

Bimodal variation of SST and related physical processes over the North Indian Ocean: special emphasis on satellite observations

Using sea surface temperature (SST) and wind speed retrieved by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), for the period of 1998–2003, we have studied the annual cycle of SST and confirmed the bimodal distribution of SST over the north Indian Ocean. Detailed analysis of SST revealed that the summer monsoon cooling (winter cooling) over the eastern Arabian Sea (Bay of Bengal) is more prominent than winter cooling (summer monsoon cooling). A sudden drop in surface short wave radiation by 57 W m^?2 (74 W m^?2) and rise in kinetic energy per unit mass by 24 J kg^?1 (26 J kg^?1) over the eastern Arabian Sea (Bay of Bengal) is observed in summer monsoon cooling period. The subsurface profiles of temperature and density for the spring warming and summer monsoon cooling phases are studied using the Arabian Sea Monsoon Experiment (ARMEX) data. These data indicate a shallow mixed layer during the spring warming and a deeper mixed layer during the summer monsoon cooling. Deepening of the mixed layer by 30 to 40 m with corresponding cooling of 2°C is found from warming to summer monsoon cooling in the eastern Arabian Sea. The depth of the 28°C isotherm in the eastern Arabian Sea during the spring warming is 80 m and during summer monsoon cooling it is about 60 m, while over the Bay of Bengal the 28°C isotherm is very shallow (35 m), even during the summer monsoon cooling. The time series of the isothermal layer depth and mixed layer depth during the warming phase revealed that the formation of the barrier layer in the spring warming phase and the absence of such layers during the summer cooling over the Arabian Sea. However, the barrier layer does exist over the Bay of Bengal with significant magnitude (20–25 m). The drop in the heat content with in first 50 m of the ocean from warming to the cooling phase is about 2.15 × 10⁸ J m^?2 over the Arabian Sea.     

Improved field emission from multiwall carbon nanotubes with nano-size defects produced by ultra-low energy ion bombardment

Multiwalled carbon nanotubes were irradiated with ultra-low energy (few eV) nitrogen and hydrogen ions using a microwave discharge. These ultra-low energy plasma-ions remain confined to the nanotube walls, transferring their maximum energy to the carbon atoms, and produce extraordinary structural changes to the carbon nanotube pillars as well as within the carbon nanotubes. Conical shaped emitters and nanotube structures with nano-defects are produced that exhibit remarkable field emission with ultra-low turn-on electric field (∼0.16 V/μm) and a >300-fold increase in the maximum emission current density compared to non-irradiated nanotubes. Doping of nitrogen is also identified due to such irradiation processes.     

Design of Efficient Ce<Subscript>x</Subscript>M<Subscript>1−x</Subscript>O<Subscript>2−δ</Subscript> (M = Zr,Hf, Tb and Pr) Nanosized Model Solid Solutions for CO Oxidation

Abstract  

Nanosized Ce_xM_1−xO_2−δ (M = Zr, Hf, Tb and Pr) solid solutions were prepared by a modified coprecipitation method and thermally treated at different temperatures from 773 to 1073 K in order to ascertain the thermal behavior. The structural and textural properties of the synthesized samples were investigated by means of X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM), BET surface area, X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy (RS) techniques. The catalytic efficiency has been performed towards oxygen storage/release capacity (OSC) and CO oxidation activity. The characterization results indicated that the obtained solid solutions exhibit defective cubic fluorite structure. The solid solutions of ceria–hafnia, ceria–terbia and ceria–praseodymium exhibited good thermal stability up to 1073 K. A new Ce_0.6Zr_0.4O₂ phase along with Ce_0.75Zr_0.25O₂ was observed in the case of ceria–zirconia solid solution due to more Zr⁴⁺ incorporation in the ceria lattice at higher calcination temperatures. The reducibility of ceria has been increased upon doping with Zr⁴⁺, Hf⁴⁺, Tb^3+/4+ and Pr^3+/4+ cations. This enhancement is more in case of Hf⁴⁺ doped ceria. Among various solid solutions investigated, the ceria–hafnia combination exhibited better OSC and CO oxidation activity. The high efficiency of Ce–Hf solid solution was correlated with its superior bulk oxygen mobility and other physicochemical characteristics.     

Thermopower Studies of Polycrystalline Ag Doped LaMnO3 Manganites

The effects of silver doping on the magnetotransport and thermopower of La_1?x Ag _x MnO₃ (0.05≤x≤0.30) have been investigated. For the sample with x=0.05, temperature dependent resistivity exhibits an insulating behavior, while thermopower is found to be large and negative over the measured temperature range. An increase in the Ag doping enhances the conductivity and shifts the metal-insulator transition temperature toward high temperature side. The low temperature thermopower data has been explained in terms of diffusion, magnon drag, and phonon drag effects and found that the magnon drag effect dominates in this region. Finally, the electrical transport in the high temperature region has been analyzed by using adiabatic small polaron hopping mechanism.