Studies On Preparation And Characterization Of Hts Current Leads Using Multifilamentary Ag And Ag-Alloy Sheathed (Bi,Pb)-2223 Superconducting Tapes

The application vistas of superconductors have widened very much since the discovery of high TC superconductors (HTS) as many of the applications can be realised at 77 K rather than going down to 4.2 K, the liquid He temperature. One such application is the HTS current lead which is used to connect a superconducting system with a room temperature power source. Minimising heat leak to the cryogenic environment is the main advantage of introducing current leads into superconducting systems. The properties of HTSS likes zero resistance (avoiding joule heating) and very low thermal conductivity (minimized conductive heat transfer) make them ideal candidates to be used as current leads. There are two forms of HTS current leads. (i) bulk form (tube or rod) prepared either from YBCO or BSCCO and (ii) tape form prepared from Bi-2223 multifilamentary tapes. The tape form of current leads has many advantages with respect to the mechanical and thermal stability related criteria. Crucial information on various aspects of HTS current lead development are not available in the literature as those are kept proprietary by various companies around the world. The present work has been undertaken to tailor the properties of multifilamentary tapes for the current lead application and to optimise the processing parameters of the same for enhanced critical current density and field tolerance. Also it is the aim of the present investigation is to prepare prototype current leads engineered for operation in conduction cooled mode and test them for operational stability

Fabrication and characterisation of polymer optical fibers for smart sensing and optical amplification

The thesis presented the fabrication and characterisation of polymer optical fibers in their applications as optical amplifier and smart sensors.Optical polymers such as PMMA are found to be a very good host material due to their ability to incorporate very high concentration of optical gain media like fluorescent dyes and rare earth compounds. High power and high gain optical amplification in organic dye-doped polymer optical fibers is possible due to extremely large emission cross sections of oyes. Dye doped (Rhodamine 6G) optical fibers were fabricated by using indigenously developed polymer optical fiber drawing tower. Loss characterization of drawn dye doped fibers was carried out using side illumination technique. The advantage of the above technique is that it is a nondestructive method and can also be used for studying the uniformity in fiber diameter and doping. Sensitivity of the undoped polymer fibers to temperature and microbending were also studied in its application in smart sensors.Optical amplification studies using the dye doped polymer optical fibers were carried out and found that an amplification of l8dB could be achieved using a very short fiber of length lOcm. Studies were carried out in fibers with different dye concentrations and diameter and it was observed that gain stability was achieved at relatively high dye concentrations irrespective of the fiber diameter.Due to their large diameter, large numerical aperture, flexibility and geometrical versatility of polymer optical fibers it has a wide range of applications in the field of optical sensing. Just as in the case of conventional silica based fiber optic sensors, sensing techniques like evanescent wave, grating and other intensity modulation schemes can also be efficiently utilized in the case of POF based sensors. Since polymer optical fibers have very low Young's modulus when compared to glass fibers, it can be utilized for sensing mechanical stress and strain efficiently in comparison with its counterpart. Fiber optic sensors have proved themselves as efficient and reliable devices to sense various parameters like aging, crack formation, weathering in civil structures. A similar type of study was carried out to find the setting characteristics of cement paste used for constructing civil structures. It was found that the measurements made by using fiber optic sensors are far more superior than that carried out by conventional methods. More over,POF based sensors were found to have more sensitivity as well.

A Numerically efficient power optimization scheme for coded OFDM systems in achieving minimum frame error rate

Coded OFDM is a transmission technique that is used in many practical communication systems. In a coded OFDM system, source data are coded, interleaved and multiplexed for transmission over many frequency sub-channels. In a conventional coded OFDM system, the transmission power of each subcarrier is the same regardless of the channel condition. However, some subcarrier can suffer deep fading with multi-paths and the power allocated to the faded subcarrier is likely to be wasted. In this paper, we compute the FER and BER bounds of a coded OFDM system given as convex functions for a given channel coder, inter-leaver and channel response. The power optimization is shown to be a convex optimization problem that can be solved numerically with great efficiency. With the proposed power optimization scheme, near-optimum power allocation for a given coded OFDM system and channel response to minimize FER or BER under a constant transmission power constraint is obtained

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Optimized operations of Distributed Renewable Energy Sources in Smart Grid

The renewable energy sources (RES) will play a vital role in the future power needs in view of the increasing demand of electrical energy and depletion of fossil fuel with its environmental impact. The main constraints of renewable energy (RE) generation are high capital investment, fluctuation in generation and requirement of vast land area. Distributed RE generation on roof top of buildings will overcome these issues to some extent. Any system will be feasible only if it is economically viable and reliable. Economic viability depends on the availability of RE and requirement of energy in specific locations. This work is directed to examine the economic viability of the system at desired location and demand.