Short Term Training Program (STTP)

MALAVIYA NATIONAL INSTITUTE

OF TECHNOLOGY JAIPUR

announces

a

Short Term Training Program

(STTP)

on

(March 7-11, 2013)

Patron

Prof. I. K. Bhat

Director, MNIT, Jaipur

Convener

Prof. K. R. Niazi

Course Coordinators

Dr. Nikhil Gupta

Dr. Anil Swarnkar

Organised by

Department of Electrical Engineering

Malaviya National Institute of Technology

Jaipur - 302017

Introduction

In the recent years, the concept of smart grid is taking shape with broader objectives to improve reliability, efficiency, power quality and safety of power delivery and its usage. It has become necessary to identify issues and problems associated with realization of modern power systems. The present trend towards deregulation in power sector is forcing electric utilities to improve their efficiency and reduce cost whereas customers are becoming more sensitive to reliability and power quality. Moreover, the competitive business environment is also forcing utilities to maximize the utilization of available resources which may lead to stressed operating conditions. These stressed operating conditions, if not taken care of, may lead to increased system losses, poor voltage profiles, overloading of lines and terminal equipments, poor power factor,voltage instability and harmonic distortion.Modern power systems are characterised by extensive system interconnections, distributed generation and increasing dependence on control for optimum utilization of existing resources. The increasing demand for electric power coupled with resources and environmental constraints pose several challenges to power system planner. The main challenges may be power system stability and security enhancement, Tieline power frequency control also called Automatic Generation Control (AGC), low frequency oscillations, energy control centre with Supervisory Control and Data Acquisition (SCADA) for centralized computer monitoring and control of generation, transmission and distribution, Automation at distribution side, deregulation and scheduling to increase competition and lowering consumer prices. The restructuring and deregulation of electric utilities, together with recent progress in technology, introduces unprecedented challenges and opportunities for power system researchers and engineers.

Objective

This programme is aimed at familiarizing teachers from academic institutes/research organizations and engineers from industries about the concepts in power system operation and control, the analytical approaches, and various new techniques being currently used to improve the performance of power systems.

Contents

The outline of the programme coverage is as under:

 Smart grid, smart distribution system

 AI application to power system.

 Distributed generation,

 Renewable energy sources

 Economic load dispatch

 Restructuring of power system and deregulation

 FACTS

 Automatic generation control

 Power system stability

 Power system reliability

 Applications of power electronics in power system.

 Power quality

Eligibility

Faculty members/Research scholars/ PG students from academic Institutions (Engineering Colleges/Universities / Research organizations) and practicing engineers from Industry.

Registration Fee

Participation from Industry: Rs. 3000/-

Institutional Participants/Faculty members: Rs. 2000/-

Students (Limited) FreeAccommodation will be provided to outstationparticipants on prior request and availability. The registration fee includes working lunch. No TA/DA will be paid.

Extended date of receiving applications: 4th March 2013

Superheterodyne Receiver

Superheterodyne Receiver

ABSTRACT

This paper discusses the basic design concepts of the Superheterodyne receiver in both single and double conversion forms, together with potential problems associated with each architecture.

This tutorial will describe a simple receiver architecture based on the super-heterodyne method of frequency translation.
A simple receiver could consist of an RF amplifier, band-pass filter and some form of demodulator. There is however a problem with this scheme in that the band-pass filter needs to be (1) Very narrow) and (2) tuneable.
We only want a single carrier and so the filter needs to be wide enough to allow the carrier (and it’s associated modulation side-bands) to pass through the filter whilst rejecting everything else. Secondly the narrow filter has to be tuneable over the frequencies of interest.
This is a very difficult requirement especially if the wanted signal is very high frequency.
A possible solution to this problem is to use the super-heterodyne receiver.

GSM using TDMA

GSM using TDMA

ABSTRACT               
   
Since the evolution of man he has always tried learn and gain as much as possible for himself and his community, to relate him self to the various cultures castes and creeds of mankind. This Quest for realizing and exploring has lead to inventive thinking and a constant probation and to relate to each other throughout the world they have fore bared the gap of communication to expunge one such a minuscule but major hurdle a common Global System for communications was founded communication on the move with a bit to bit elaboration was analyzed and the forth presentation bears the facts of a Global System For Mobile communication and on which basis it is employed along with the assets & environment   .

RADIAL BASIS NETWORKS(ARTIFICIAL NEURAL NETWORKS)

RADIAL BASIS NETWORKS(ARTIFICIAL NEURAL NETWORKS)
 
ABSTRACT

             RADIAL BASIS NETWORKS is similar to ARTIFICIAL NEURAL NETWORKS,but it differs in number of neurons. They are faster when compared to artificial neural network for a particular application.
Radial basis networks can be designed very quickly in two different ways. The first design method, newrbe, finds an exact solution. The function newrbe creates radial basis networks with as many radial basis neurons as there are input vectors in the training data. The second method, newrb, finds the smallest network that can solve the problem within a given error goal.

           Typically, far fewer neurons are required by newrb than are returned newrbe. However, because the number of radial basis neurons is proportional to the size of the input space, and the complexity of the problem, radial basis networks can still be larger than backpropagation networks.
A generalized regression neural network (GRNN) is often used for function approximation. It has been shown that, given a sufficient number of hidden neurons, GRNNs can approximate a continuous function to an arbitrary accuracy.
Probabilistic neural networks (PNN) can be used for classification problems. Their design is straightforward and does not depend on training. A PNN is guaranteed to converge to a Bayesian classifier providing it is given enough training data. These networks generalize well. The GRNN and PNN have many advantages, but they both suffer from one major disadvantage. They are slower to operate because they use more computation than other kinds of networks to do their function approximation or classification.

ELECTRONIC NOSE

ELECTRONIC NOSE

ABSTRACT

The perception of volatile compounds by the human nose is of great importance in evaluating the quality of foods. Therefore, it is not surprising that repeated efforts have been made over the years to introduce instruments operating on a similar principle as the human nose: the “electronic nose” is an instrument that encloses the human sensitivity to the objectivity of the instrumental response and supplies results similar to the human nose and in short time.
An electronic nose is “an instrument which comprises an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system capable of recognising simple or complex odours”. It can be regarded as a modular system comprising a set of active materials which detect the odour, associated sensors which transduce the chemical quantity into electrical signals, followed by appropriate signal conditioning and processing to classify known odours or identify unknown odours. Research has been carried out into the use of thin and thick film semiconducting (inorganic and organic) materials for odour sensing. Research effort is now centered upon the use of arrays of metal oxide and conducting polymer odour sensors. The latter are particularly exciting because their molecular structure can be engineered for a particular odour-sensing application. The electronic nose finds wide applications in the food industry. Future developments in the use of hybrid micro sensor arrays and the development of adaptive artificial neural networking techniques will lead to superior electronic noses.

ELECTRICAL IMPEDANCE TOMOGRAPHY

ELECTRICAL IMPEDANCE TOMOGRAPHY

ABSTRACT

Imbalances in regional lung ventilation, with gravity-dependent collapse and over distention of nondependent zones, are likely associated to ventilator-induced lung injury. Electric impedance tomography is a new imaging technique that is potentially capable of monitoring those imbalances. The aim of this study was to validate electrical impedance tomography measurements of ventilation distribution, by comparison with dynamic computerized tomography in a heterogeneous population of critically ill patients under mechanical ventilation. This thesis is concerned with Electrical Impedance Tomography (EIT), a medical imaging technique in which pictures of the electrical conductivity distribution of the body are formed from current and voltage data taken on the body surface. The focus of the thesis is on the mathematical aspects of reconstructing the conductivity image from the measured data. Electrical impedance tomography (EIT) is to reconstruct an impedance distribution in an object of interest from electrical measurement on the boundary of the object. Because of its non-invasiveness, portability and practical utilities, EIT has been actively studied since 1970s and led to many useful and inspiring results. The primary focus of this work is the visualization of multiphase flows (specifically suspensions of neutral buoyant and buoyant particles at low Reynolds number) using EIT.  This imaging technique can lead to a better understanding of the nature of these multiphase flows. Therefore, electrical impedance tomography helps in determining the optimal mechanical ventilation in a patient with acute lung injury.

SP for Smart Biometric Solutions

DSP for Smart Biometric Solutions

ABSTRACT

Biometrics is the science of measuring and statistically analyzing biological data. In information technology, biometrics refers to the use of a person’s biological characteristics for personal identification and authentication. Fingerprint, iris-scan, retinal-scan, voiceprint, signature, handprint and facial features are some of the most common types of human biometrics. Digital signal processors (DSPs), which are specially designed single-chip digital microcomputers that process electrical signals generated by electronic sensors (e.g., cameras, fingerprint sensors, microphones, etc.), will help to revolutionize this world of biometrics. The core of the biometric authentication process is made up of image processing and pattern matching or minutiae comparison algorithms. And the programmable DSP, with an architecture well-suited for implementing complex mathematical algorithms, can efficiently address all the processing needs of such a system. The following information introduces the concept of a complete biometrics system solution based on semiconductor components, development tools, and software solutions. Additionally, the various concepts that outline the inherent advantages of a DSP in a biometric system - better accuracy, faster recognition and lower cost, all leading to smarter biometrics - will also be covered.

Application of Artificial Neural Network for Short Term Load Forecasting in Electrical Power System

Application of Artificial Neural Network for Short Term Load Forecasting in Electrical Power System

ABSTRACT

    This paper presents a method for short term load forecasting in eectric power system using artificial neural network. A multilayered feed forward network with back propagation learning algorithm is used because its good generalising property. The input to the neural network is in terms of past load data which was heuristically chosen such that they reflect the trend, load shape as well as some influence of weather. The weather data is not used to train the metwork. The network is trained to predict one hour ahead load forecasting. The generalisation capability of the neural network is also studied. Simulation results using the system data are presented.

Real time Radiography

Real time Radiography

ABSTRACT

Real-time radiography (RTR), or real-time radioscopy, is a nondestructive test (NDT) method whereby an image is produced electronically rather than on film so that very little lag time occurs between the item being exposed to radiation and the resulting image. In most instances, the electronic image that is viewed, results from the radiation passing through the object being inspected and interacting with a screen of material that fluoresces or gives off light when the interaction occurs. The fluorescent elements of the screen form the image much as the grains of silver form the image in film radiography. The image formed is a “positive image” since brighter areas on the image indicate where higher levels of transmitted radiation reached the screen. This image is the opposite of the negative image produced in film radiography. In other words, with RTR, the lighter, brighter areas represent thinner sections or less dense sections of the test object.

Real-time radiography is a well-established method of NDT having applications in automotive, aerospace, pressure vessel, electronic, and munition industries, among others. The use of RTR is increasing due to a reduction in the cost of the equipment and resolution of issues such as the protecting and storing digital images. Since RTR is being used increasingly more, these educational materials were developed by the North Central Collaboration for NDT Education (NCCE) to introduce RTR to NDT technician students. NCCE is a collaborative effort between Northeast Iowa Community College (Peosta, IA) Cowley County Community College (Arkansas City, KS), Southeast Community College (Milford, NE), Ridgewater Community College (Hutchinson, MN) and Iowa State University (Ames, IA). Partial funding for this effort was provided by the National Science Foundation.

Remote control of electronic equipment

Remote control of electronic equipment

Abstract

In this paper we present a vehicle for a complete engineering and scientists practical formation. It is made possible by the use of virtual instrumentation, not in the sense of a simulation tool, but as the remote access to facilities located in related research laboratories. Internet World Wide Web provides a best way to materialize this remote access, reducing the requirements in the educational laboratory to workstations (WS) or personal computers (PC) with the habitual Internet access.

SAEM TECHNOLOGY

SAEM TECHNOLOGY

Abstract:
        Automation has invaded all streams and now the power sector too with Smart Assessing Energy Meter (SAEM) Technology, which employs a digitally automated wireless energy meter -Digital Compatible Wireless Energy Meter (DCW). SAEM Technology has a potential of transmitting/receiving digital data/signals between Data Monitoring Centre (DMC) and Energy Meter, it has due date warning signal and   ensured supply truncation to the consumers who haven’t settled the bill even after the due date. SAEM has high precision, fault deduction capability, void of man hours, void pay for assessors, it handcuff’s the thefts.

Transmission Improvement of Useful Signals through Energy Saving Glass Windows Using Frequency Selective Surfaces

Transmission Improvement of Useful Signals through Energy Saving Glass Windows Using Frequency Selective Surfaces

Abstract

Energy saving glass windows are becoming very popular in building design due to their effective shielding against infrared signals. These windows mainly help in providing thermal insulation to the buildings keeping them cold in summer and hot in winter. This effective shielding is obtained by depositing multiple layers of metallic oxides on glass surface using special processes. Besides providing effective thermal insulation, the presence of such coating also attenuates the transmission of mobile phone signals, GPS signals etc. To overcome this drawback, we propose a solution to this problem by employing bandpass frequency selective surfaces on two types of energy saving glass windows.

Nonlinearity of Anti-Parallel Schottky Diodes For Mixer Applications

Nonlinearity of Anti-Parallel Schottky Diodes For Mixer Applications

Abstract

This work investigates the nature of nonlinearities in an anti-parallel combination of Schottky diodes, which is often used as a frequency converting device or a mixer. An anti-parallel Schottky diode pair mixer requires only half the local oscillator frequency and this property makes it very attractive at millimeter-wave frequencies. The sources of nonlinearity in a metal-semiconductor Schottky junction are the junction resistance caused by the thermionic emission of electrons across the barrier and the junction capacitance resulting from the charge seperation across the barrier. The mixing terms of utmost importance in an anti-parallel diode pair mixer are the wanted fundamental frequency converted product, the unwanted third-order frequency converted product and the undesirable second-order local oscillator breakthruough. This work aims to discover which; among the nonlinear sources is the primary contributor in the generation of unwanted third-order products. An anti-parallel diode pair has an anti-symmetrical current-voltage characteristic about the origin and a symmetrical capacitance-voltage characteristic about the Y-axis. In other words the current in the diode pair is an odd function of applied voltage whereas the capacitance is an even function of applied voltage. When both nonlinearities are described by a polynomial model extracted from measurements, the resistive nonlinearity contains only odd power terms and the capacitive nonlinearity is a sum of even power terms. The nonlinear resistance with only the odd power terms will be the dominant of the two in generating the unwanted third-order products where as the capacitive nonlinearity will be the primary contributor of local oscillator breakthrough. This work supports such an assertion by means of analysis, simulation and measurement. The results demonstrate the dominance of nonlinear resistance over junction capacitance in the generation of third-order products in an anti-parallel diode pair mixer. Understanding the nonlinearities involved also enables us to optimise the physical structure and geometry of the diode for good mixer performance.

In Search of Scalable Models for FET and HEMT Structures

In Search of Scalable Models for FET and HEMT Structures

Abstract

FET and HEMT transistors designed to operate up to frequencies of 50GHz and beyond continue to be used for microwave and millimetre wave applications such as terrestrial and satellite communication, automotive radar and aerospace systems. These systems typically demand that the transistor based circuits have excellent wideband performance in terms of one or more of the following parameters – noise figure, linearity, power-added-efficiency, or saturated power handling. The optimal transistor geometry will vary widely for each scenario so circuit designers require transistor models for the full range of possible device sizes. Typically, a foundry will allow the unit-gate-width (UGW) and the number-of-gate-fingers (NOF) to be varied. In this context scalable models become very attractive as the measurement and characterisation of every possible geometry can be avoided. The following presentation will give an outline of some of the approaches that are proving to be successful in realising scalable models.

Rank-Based Statistical Localization in Sensor Networks

Rank-Based Statistical Localization in Sensor Networks

Abstract:

In the applications of WSNs, positions of sensor nodes are critical prerequisite information for successful operation. Although remarkable progresses has been achieved in the so-called Range-Based methods utilizing inter-node range measurements, in realistic environment, it is generally hard for the distance measurement to exactly match the true Euclidean value, owing to the randomness and unpredictability of notorious wireless channels. Localization qualities of Range-Based methods, as a result, are closely related to the channel conditions; once the radio channel is contaminated with large measurement noise, localization accuracy would drastically deteriorate. We try to improve localization performance under the atrocious network conditions mentioned above by providing a robust Rank-Based method, as a special case and improvement of Range-Based methods. With a predefined signal model, locations of sensor node could be statistically estimated merely based on rank-order information of distance measurements. Without applying actual metric measurement values, our method has remarkable advantage over traditional Range-Based methods which suffer from the measurement insufficiency problem, and is more robust to the fluctuation of measurement noise.

Microvascular Imaging using Optical Coherence Tomography and High Frequency Ultrasound

Microvascular Imaging using Optical Coherence Tomography and High Frequency Ultrasound

Abstract:

Microvascular imaging is a fundamental technique in biomedical research. Recent advances in optics and ultrasonics have resulted in improvements for visualizing the cardiac dynamics and fine vascular networks in animals or human. We will review the common principles for blood flow imaging in optics and ultrasonics, and discuss the recent implementations of vascular sensitive optical coherence tomography (OCT) and high frequency ultrasound (HFUS) systems/algorithms.

Exploration and Mapping of Sound Synthesis Feature Vector Space

Exploration and Mapping of Sound Synthesis Feature Vector Space

Abstract

A report on recent work concerning the exploration and mapping of sound synthesizer feature space is presented. The feature vector space for different sound synthesis algorithms was investigated in various ways. Large scale maps of this space were generated, to provide an insight into the space of all possible sounds for different sound synthesis algorithms. First, a data set is generated by rendering many sounds from a sound synthesis algorithm, each with randomised settings. These sounds are then transformed into feature vector space using feature vectors such as MFCCs and perceptually weighted power spectra. This high-dimensional data set is translated to a low-dimensional space for human exploration using Multi-Dimensional Scaling (MDS). MDS aims to make a lower-dimensional map of a larger space whilst maintaining relative distances between points in both spaces. An interactive tool was developed which allows the rapid exploration of 2D MDS maps of feature vector space by a user.Different sound synthesis algorithms and audio feature vectors are compared using this tool. Finally, a fine grained analysis of the inter-point feature vector space is carried out in order to compare the smoothness of this space for different feature vectors.

NON-CONVENTIONAL ENERGY SOURCES

NON-CONVENTIONAL ENERGY SOURCES

ABSTRACT

Energy was, is & will remain the basic foundation which determines the stability of economic development of any nation. In a world, which is threatened with the non-availability of fuel, oil supplies & menace of nuclear war, one is bound to look into the future energy prospects with considerable skepticism. The tides are caused by the gravitational forces of moon & sun on the ocean water & are affected by the spinning of earth around its axis & the relative positions of earth, moon & sun. Tides are periodically renewed & hence tidal energy is renewable energy. This paper mainly emphasizes on capsizing the most of alternate power generation using Ocean Thermal Energy Conversion (OTEC) & Tidal Energy.

OCEAN THERMAL ENEGRY CONVERSION (OTEC):

Ocean covers 71% of earth’s surface. On an average day, 60 million sq. meter of tropical sea absorbs an amount of solar radiation equivalent in heat content to about 245 billion barrels of oil. India has 15 million sq. meter of tropical water zone. OTEC available for India is 180,000 MW. OTEC is more convenient than wave & tidal energy. The capacity in single unit is up to 400 MW.

WORKING PRINCIPLE OF OTEC:

The surface of the ocean waters are at a temperature of 28-30ºC. This temperature decreases with depth and at a depth of about 1000m we get a temperature of 6-8ºC. This is a consequence of the Lambert's law of radiation according to which the intensity of radiation exponentially decreases with depth and so the surface receives more solar radiation (also called insolation) compared to the waters below. Moreover, warm water is less dense and hence stays at the top. Hence, the temperature distribution available in the ocean is stable and the temperature difference remains constant more or less throughout the year.

DEMAND SIDE MANAGEMENT

DEMAND SIDE MANAGEMENT

ABSTRACT

Power system planning has become considerably more complex today because of uncertainties in load growth, fuel prices & fuel availability & concern for environment. New options such as clean coal, technologies, storage & renewable technologies; demand side management & co-generation are being pursued as solution to meet these new challenges.

Power shortages have been in force in India ever since seventies. The state electricity boards have resorted to restricting consumption in order to meet the rapid growth in demand from various consumer categories. The cuts have ranged from 10 to 60 % in several state electricity boards. The question of load management through the pricing option has been only tried on a limited scale in very less boards in the country.

This paper presents “Need for demand side management” & importance of pricing mechanism & also impact of the experiences of the utilities who have adopted prizing as a means load management & identify the factors that would have to be considered in order to implement an efficient prizing mechanism for load management.

POWER RESTRUCTING SYSTEM (ISLANDING SYSTEM FOR POWER PLANTS)

POWER RESTRUCTING SYSTEM (ISLANDING SYSTEM FOR POWER PLANTS)

ABSTRACT

In India internal Grid system is used, which is more useful for the continuation of the electric supply. Grid islanding scheme is a set of protective relays, connected at the incomer bus-these relays will sense a disturbance in the grid and give a trip command to the incomer breaker whenever the grid disturbance exceeds a set limit. By opening the incomer breaker, the plant is isolated from the grid. When the frequency begins to decrease (due to peak loads or heavy faults) the network is split into definite sections at predetermined points by frequency relays. The difference between output and load is reduced in every section by load shedding or load equalization in every island.