International Journal of Research in Science & Technology

1-7

Authors: S..L.S.Durga, M.V.V.N.Revathi, M.J.P.Nayana, Md.Aaquila Fathima and K.Murali

This project addresses the problem of clock synchronization between a base station (BS) and a mobile station (MS). A conventional technique for clock synchronization is that the MS clock is derived from the downlink signal originated from a base station. In cellular systems, a base station and mobile stations need to be synchronized before data exchange. Since the base station clock reference is more accurate, a mobile station typically derives its clock reference from the base station. But the carrier frequency offset due to Doppler shift may have harmful effects on the local clock derivation. This project proposes a joint clock and frequency synchronization technique between a base station and a mobile station, which is effective even with Doppler shift. We derive the joint estimation algorithm by analyzing the phase and the amplitude distortion caused by the sampling frequency offset and the carrier frequency offset. Simulation results showing the effectiveness of the proposed algorithm will also be presented.

8-12

Authors: A.Vineela and L. Sudha Rani

The Internet of Things (IoT), also referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already had on education, science, communication, business, government, and humanity. Clearly, the Internet is one of the most important and a powerful creation in all of human history. This paper discussesIOT architecture, IOT applications and limitations of IOT.

19-25

Authors: Mrs. Sangita B. Patil and Mr. Bapu K. Patil

The energy is a vital input for the social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also increasing. The increasing use of natural and renewable energy sources is needed to take the burden of our current dependency on fossil fuels. Development and analysis of renewable energy models helps utility in energy forecasting, planning, research and policy making. The wind power is a clean, inexhaustible, and almost a free source of energy. But the integration of wind parks with the power grid has resulted in many challenges for the utility in terms of commitment and control of power plants. As wind speed and wind direction fluctuate frequently, the accurate long-term and short-term forecasting of wind speed is important for ascertaining the wind power generation availability. To deal with wind speed forecasting, many methods have been developed such as physical method, which use lots of physical considerations to reach the best forecasting precision and other is the statistical method, which specializes in finding the relationship of the measured power data. Wind speed can be predicted by using time series analysis, artificial neural network, Kalman Filter method, linear prediction method, spatial correlation models and wavelet, also by using the support vector machines. In this paper, the SVM is used for day ahead prediction of wind speed using historical data of wind park. In this paper Support Vector Machine (SVM) results are compared with feedforward Backpropagation neural network. It is observed that the Mean Absolute Percentage Error (MAPE) by SVM method is around 7% and correlation coefficient is close to 1. This justifies the ability of SVM for wind speed prediction task than Backpropagation algorithm.

36-44

Authors: Suresh Kumar and Sunil Kumar Goyal

This paper presents particle swarm optimization (PSO) based approach for solving optimal reactive power dispatch for minimizing power losses. The control variables are bus voltage magnitudes (continuous type), transformer tap settings (discrete type) and reactive power generation of capacitor banks (discrete type). The algorithm solution of PSO is tested on a standard IEEE 30 Bus system. The intention is to minimize power losses by optimizing the reactive power dispatch with optimal setting of control variables without violating inequality constraints and satisfying equality constraint. The detailed results for different cases have been listed