The increasing demand for energy, the continuous reduction in existing sources of fossil fuels and the growing concern regarding environment pollution, have pushed mankind to explore new technologies for the production of electrical energy using clean, renewable sources, such as solar energy, wind energy, etc. Among the non-conventional, renewable energy sources, solar energy affords great potential for conversion into electric power, able to ensure an important part of the electrical energy needs of the planet. This paper deals with the design and execution of a solar tracker system dedicated to the PV conversion panels. The proposed single axis solar tracker device ensures the optimization of the conversion of solar energy into electricity by properly orienting the PV panel in accordance with the real position of the sun. The operation of the experimental model of the device is based on a Stepper motor intelligently controlled by a dedicated drive unit that moves a mini PV panel according to the signals received from two simple but efficient light sensors. In this paper mechanism of building an efficient solar tracking system with the help of Labview software is discussed and also discussed about the control strategy of the stepper motor. From the study it is found that the motor will move the solar array according to the light intensity of the sun.

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Summary Recent research indicates that future power networks will witness a major enhancement in renewable energy–based distributed generation (DG). The impact of DG and distribution management system (DMS) action can be directly and easily implemented in the distribution networks for the improvement of its voltage security states. In the first phase of this paper, the voltage security state of the distribution network is identified using combined Kohonen's self‐organizing feature map (SOFM) and learning vector quantization (LVQ) algorithm. Two indicators namely voltage stability index (VSI) and distribution system stability indicator (DSSI) are used in this paper for verification of classification result. To ensure voltage security, it is essential to improve the voltage profile of the system. In the next phase, genetic algorithm (GA) and spider monkey optimization (SMO) techniques have been applied to find the optimal location and size of DG for voltage security state improvement of the reconfigured distribution system. Accurate allocation of DG can help in demand side management (DSM) for providing better service to the consumers in real time in smart grid scenario. This methodology has been tested on IEEE 33 bus, IEEE 69 bus, and Indian 85 bus practical radial distribution system. Result shows that the proposed methodology can successfully and appropriately identify the voltage security states of power system by combined SOFM and LVQ algorithms, and utilization of suitable amount of DGs at best locations as obtained from SMO algorithm can improve the operating states of distribution network in terms of voltage security.

Social Networks such as Twitter, Facebook play a remarkable growth in recent years. The ratio of tweets or messages in the form of URLs increases day by day. As the number of URL increases, the probability of fabrication also gets increased using their HTML content as well as by the usage of tiny URLs. It is important to classify the URLs by means of some modern techniques. Conditional redirection method is used here by which the URLs get classified and also the target page that the user needs is achieved. Learning methods also introduced to differentiate the URLs and there by the fabrication is not possible. Also the classifiers will efficiently detect the suspicious URLs using link analysis algorithm.

Complexity of modern power network and Large disturbance results voltage collapse. So, voltage security analysis is important in power system. Indicators are helpful in voltage stability analysis, as they give information about the state of the system. In this paper a new indicator namely Distribution System Stability Indicator (DSSI) has been formulated using the information of Phasor Measurement Unit (PMU).The proposed indicator (DSSI) is tested on standard IEEE 33 bus radial distribution system. The suggested indicator is also applicable to the equivalent two bus system of a multi-bus power system. The proposed indicator is calculated for different contingent conditions at different system load configurations. The result of DSSI is verified with the standard indicator (VSI) which proves applicability of the proposed indicator. The bus voltages of all the buses at base loading and at maximum loading are evaluated for base data and for tripping of most critical line.