1,218 research outputs found
The Influence of the Increasing Penetration of Photovoltaic Generation on Integrated Transmission-Distribution Power Systems
No full textPower system simulations should be adapted to be applicable to the trends that are currently evoked by the energy transition. This transition is pushing our power system from a traditional hierarchical system to a modern interactive system. In order to keep the supply and transport of energy safe and reliant, we need to change the way we perform power system simulations. This requires a comprehensive framework in which both transmission and distribution systems are simultaneously analyzed. This chapter describes how transmission and distribution networks are modeled together as an integrated network and used to do steady-state operation analysis in order to assess the interaction of these two networks. Furthermore, we investigate the influence of the increasing amount of imbalance at distribution level on the transmission network that is evoked by the increase of highly variable resources and loads at distribution level. This influence is not taken into account in traditional power system simulations as power networks are analyzed on its own. We show that the hybrid network representation is a powerful tool to analyze modern power systems and that the effects of increased PV penetration under normal operating conditions are limitedGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Numerical Analysi
A Multilabel Approach Using Binary Relevance and One-versus-Rest Least Squares Twin Support Vector Machine for Scene Classification
No full text
Direct acyclic graph based multi-class twin support vector machine for pattern classification
No full textPrediction of Defective Software Modules Using Class Imbalance Learning
No full textSoftware defect predictors are useful to maintain the high quality of software products effectively. The early prediction of defective software modules can help the software developers to allocate the available resources to deliver high quality software products. The objective of software defect prediction system is to find as many defective software modules as possible without affecting the overall performance. The learning process of a software defect predictor is difficult due to the imbalanced distribution of software modules between defective and nondefective classes. Misclassification cost of defective software modules generally incurs much higher cost than the misclassification of nondefective one. Therefore, on considering the misclassification cost issue, we have developed a software defect prediction system using Weighted Least Squares Twin Support Vector Machine (WLSTSVM). This system assigns higher misclassification cost to the data samples of defective classes and lower cost to the data samples of nondefective classes. The experiments on eight software defect prediction datasets have proved the validity of the proposed defect prediction system. The significance of the results has been tested via statistical analysis performed by using nonparametric Wilcoxon signed rank test
SYNTHESIS AND CHARACTERIZATION OF COPPER COMPLEX OF SCHIFF BASE
No full text<p>Schiff base metal complexes have been studied extensively because of their wide range of applications in different scientific areas and their chemical and physical properties. Many of them are centred on the catalytic activity of Schiff base complexes in a large number of homogeneous and heterogeneous reactions. By this paper we throw light on the IR, UV studies of synthesised copper complex of schiff base.</p>
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