Electrical Switching and Other Properties of Chalcogenide Glasses

Abstract | Electrical switching which has applications in areas such as information storage, power control, etc is a scientifically interesting and technologically important phenomenon exhibited by glassy chalcogenide semiconductors. The phase change memories based on electrical switching appear to be the most promising next generation non-volatile memories, due to many attributes which include high endurance in write/read operations, shorter write/read time, high scalability, multi-bit capability, lower cost and a compatibility with complementary metal oxide semiconductor technology.Studies on the electrical switching behavior of chalcogenide glasses help us in identifying newer glasses which could be used for phase change memory applications. In particular, studies on the composition dependence of electrical switching parameters and investigations on the correlation between switching behavior with other material properties are necessary for the selection of proper compositions which make good memory materials.In this review, an attempt has been made to summarize the dependence of the electrical switching behavior of chalcogenide glasses with other material properties such as network topological effects, glass transition & crystallization temperature, activation energy for crystallization, thermal diffusivity, electrical resistivity and others.

Fuzzy logic based TCSC supplementary controller for damping of inter area oscillations in power system

This paper describes an application of a FACTS supplementary controller for damping of inter area oscillations in power systems. A fuzzy logic controller is designed to regulate a thyristor controlled series capacitor (TCSC) in a multimachine environment to produce additional damping in the system. Simultaneous application of the excitation controller and proposed controller is also investigated. Simulation studies have been done with different types of disturbances and the results are shown to be consistent with the expected performance of the supplementary controller.

Beat frequency oscillations in the output voltage of high voltage DC power supplies under pulsed loading

High voltage power supplies for radar applications are investigated, which are subjected to pulsed load (125 kHz and 10% duty cycle) with stringent specifications (<0.01% regulation, efficiency>85%, droop<0.5 V/micro-sec.). As good regulation and stable operation requires the converter to be switched at much higher frequency than the pulse load frequency, transformer poses serious problems of insulation failure and higher losses. Few converter topologies are proposed to tackle these problems. A study is made regarding the beat frequency oscillations that may exist with pulsed loading. It is illustrated with respect to the proposed converter topologies. Methods are proposed to eliminate or minimize these oscillations.

Decentralized peak power control based on short-term forecast using modified Kalman filter

This paper proposes a method of short term load forecasting with limited data, applicable even at 11 kV substation levels where total power demand is relatively low and somewhat random and weather data are usually not available as in most developing countries. Kalman filtering technique has been modified and used to forecast daily and hourly load. Planning generation and interstate energy exchange schedule at load dispatch centre and decentralized Demand Side Management at substation level are intended to be carried out with the help of this short term load forecasting technique especially to achieve peak power control without enforcing load-shedding.

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.

Structural, thermal and electrical characterization of NdLiMo2O8 electroceramics, using impedance spectroscopy

We report electrical property of a polycrystalline NdLiMo2O8 ceramics using complex impedance analysis. The material shows temperature dependent electrical relaxation phenomena. The d.c. conductivity shows typical Arrhenius behavior, when observed as a function of temperature. The a.c. conductivity is found to obey Jonscher's universal power law. The material was prepared in powder form by a standard solid-state reaction technique. Material formation and crystallinity have been confirmed by X-ray diffraction studies. Impedance measurements have been performed over a range of temperatures and frequencies. The results have been analyzed in the complex plane formalism and suitable equivalent circuits have been proposed in different regions. The role of bulk and grain boundary effect in the overall electrical conduction process is discussed with proper justification. (C) 2011 Elsevier Ltd. All rights reserved.

New Insights into Optimal Discrete Rate Adaptation for Average Power Constrained Single and Multi-Node Systems

The throughput-optimal discrete-rate adaptation policy, when nodes are subject to constraints on the average power and bit error rate, is governed by a power control parameter, for which a closed-form characterization has remained an open problem. The parameter is essential in determining the rate adaptation thresholds and the transmit rate and power at any time, and ensuring adherence to the power constraint. We derive novel insightful bounds and approximations that characterize the power control parameter and the throughput in closed-form. The results are comprehensive as they apply to the general class of Nakagami-m (m >= 1) fading channels, which includes Rayleigh fading, uncoded and coded modulation, and single and multi-node systems with selection. The results are appealing as they are provably tight in the asymptotic large average power regime, and are designed and verified to be accurate even for smaller average powers.

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

A robust three phase power flow algorithm for radial distribution systems

An efficient load flow solution technique is required as a part of the distribution automation (DA) system for taking various control and operations decisions. This paper presents an efficient and robust three phase power flow algorithm for application to radial distribution networks. This method exploits the radial nature of the network and uses forward and backward propagation to calculate branch currents and node voltages. The proposed method has been tested to analyse several practical distribution networks of various voltage levels and also having high R/X ratio. The results for a practical distribution feeder are presented for illustration purposes. The application of the proposed method is also extended to find optimum location for reactive power compensation and network reconfiguration for planning and day-to-day operation of distribution networks.

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static Var compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system.

A neural network based power system stabilizer suitable for on-line training-a practical case study for EGAT system

This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS