Time filter

Source Type

Kulkarni D.B.,Gogte Institute of Technology | Udupi G.R.,V D R Institute Of Technology
IEEE Transactions on Power Delivery

Electrical distribution system suffers from various problems, such as reactive power burden, unbalanced loading, voltage regulation, and harmonic distortion. Though DSTATCOMS are ideal solutions for these systems, they can be costly and have complexity compared to other reactive power compensation solutions. Phasewise-balanced reactive power compensations are required for fast-changing loads needing dynamic power factor correcting devices leading to terminal voltage stabilization. Static var compensators (SVCs) are preferred for these loads due to low cost and simple control strategy. These SVCs, while correcting power factor, inherently create harmonics due to the nonsinusoidal currents caused by the operation of thyristor-controlled reactors. This paper proposes minimizing the harmonics injected into the distribution systems with the operation of TSC-TCR-type SVC used in conjunction with fast-changing loads at the LV distribution level. The fuzzy logic system and ANNare used to solve this nonlinear problem, giving optimum triggering delay angles used to trigger thyristors in TCR. The scheme is attractive and can be used at SVC installations in distribution systems for steady-state reactive power compensation. © 2010 IEEE. Source

Joshi D.R.,Gogte Institute of Technology | Joshi D.R.,Basaveshwar Engineering College | Jangamshetti S.H.,Basaveshwar Engineering College
IEEE Transactions on Energy Conversion

Anovel analyticalmethod is proposed to find the reliability, the average failure rate, and the operation and maintenance costs (OMCs) of wind turbine generator based on the site wind data. The failure rate function is developed using wind turbine failure frequency distribution, published by Renewable Energy Information System on Internet,Germany.The presentedmethodworks computationally fast and does not require large wind data input, which is a requirement of many existing, commercially available simulation methods. The annually increasing OMCs, computed by this method, give better financial assessment of the wind power projects. The method presented is implemented on an Indian wind site. OMCs are obtained for 20 years. Results match the actual field data, for the survey period, barring their warranty period. It is hoped that the proposed method helps financial investors and equity holders for a better financial assessment of the wind power projects at planning stage. © 2009 IEEE. Source

Amarnath H.K.,Gogte Institute of Technology | Prabhakaran P.,M. S. University of Baroda
International Journal of Green Energy

Fossil fuels are the chief contributors to urban air pollution and major source of green house gases and are considered to be the prime cause behind the global climate change. Biofuels are renewable, can supplement fossil fuels, reduce green house gases, and mitigate their adverse effects on the climate resulting from global warming. In the present study, biodiesel produced from karanja oil is evaluated as alternative fuel in a diesel engine. The experiments are conducted on a single-cylinder, four-stroke, direct-injection CI engine and the experimental parameters include the percentage of karanja biodiesel in the blend, engine load, injection pressure, and compression ratio. Comparative measures of brake thermal efficiency, brake-specific fuel consumption, smoke opacity, and HC, CO, and NOX emissions are presented and discussed. Results show that the performance of the engine fuelled with karanja biodiesel and its blends with diesel fuel is generally comparable to that when the engine is fuelled with pure diesel. At higher compression ratios, the engine gives lesser emission and better performance. Genetic algorithm optimization technique was used to optimize the parameters. With respect to maximum efficiency and minimum emissions, the optimum values of load, compression ratio, injection pressure, and blend were 6 kg, 18, 247 bar, and B95, respectively. Copyright © Taylor & Francis Group, LLC. Source

Sondur V.V.,Gogte Institute of Technology | Sondur V.B.,Gogte Institute of Technology | Ayachit N.H.,Alagappa Chettiar College of Engineering And Technology
Digital Signal Processing: A Review Journal

A modification to the weighted least-squares algorithm is proposed to minimize the relative error in the response of a digital differentiator (DD) and is applied to the design of fifth-order DD. Simulation results are given to demonstrate the performance of the method for both even and odd length DDs. The design procedure to satisfy prescribed specifications is also discussed. © 2009 Elsevier Inc. All rights reserved. Source

Rodd S.F.,Gogte Institute of Technology | Kulkarni U.P.,SDMCET | Yardi A.R.,Walchand College
Evolving Systems

A recent trend in database performance tuning is towards self tuning for some of the important benefits like efficient use of resources, improved performance and low cost of ownership that the auto-tuning offers. Most modern database management systems (DBMS) have introduced several dynamically tunable parameters that enable the implementation of self tuning systems. An appropriate mix of various tuning parameters results in significant performance enhancement either in terms of response time of the queries or the overall throughput. The choice and extent of tuning of the available tuning parameters must be based on the impact of these parameters on the performance and also on the amount and type of workload the DBMS is subjected to. The tedious task of manual tuning and also non-availability of expert database administrators (DBAs), it is desirable to have a self tuning database system that not only relieves the DBA of the tedious task of manual tuning, but it also eliminates the need for an expert DBA. Thus, it reduces the total cost of ownership of the entire software system. A self tuning system also adapts well to the dynamic workload changes and also user loads during peak hours ensuring acceptable application response times. In this paper, a novel technique that combines learning ability of the artificial neural network and the ability of the fuzzy system to deal with imprecise inputs are employed to estimate the extent of tuning required. Furthermore, the estimated values are moderated based on knowledgebase built using experimental findings. The experimental results show significant performance improvement as compared to built in self tuning feature of the DBMS. © 2013 Springer-Verlag Berlin Heidelberg. Source

Discover hidden collaborations