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Volume-4 Issue-10: Published on April 15, 2017
Volume-4 Issue-10: Published on April 15, 2017

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S. No

Volume-4 Issue-10, April 2017, ISSN: 2319–6386 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.

Page No.



Purvi Kapoor, Manish Kr. Singh, Shashikant

Paper Title:

A Review on Distributed Generation Definitions and DG Impacts on Distribution System

Abstract: Rapidly growing the power consumption and decrease in generating and transmission capacities have set the trend towards the Distributed Generation (DG) sources. Still there is not a univer sal definition of DG. This paper discusses the different definitions proposed in the literature. For DG system to become a major part of the current power scenario it needs to be connected with the existing grid system. This integration will cause some technical, operational and economic impacts on distribution systems. This paper also summarizes these different impacts of DG on distribution system.

Keywords:  Distributed Generation, Impacts of DG, Islanding, Economic Impacts of DG, Power Quality, Voltage Regulation, Islanding, Dispatched Operation


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4.          Gas Research Institute, Distributed Power Generation: A Strategy for a Competitive Energy Industry, Gas Research Institute, Chicago, USA 1998

5.          D. Sharma, R. Bartels, Distributed electricity generation in competitive energy markets: a case study in Australia, in: The Energy Journal Special issue: Distributed Resources: Toward a New Paradigm of the Electricity Business, The International Association for Energy Economics, Clevland, Ohio, USA, 1998, pp. 17–40

6.          J. Cardell, R. Tabors, Operation and control in a competitive market: distributed generation in a restructured industry, in: The Energy Journal Special Issue: Distributed Resources: Toward a New Paradigm of the Electricity Business, The International Association for Energy Economics, Clevland, Ohio, USA, 1998, pp. 111–135.

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Micro cogeneration towards decentralized energy systems, Berlin: Springer, pp. 197-218, 2006. 

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Purwono Hendrad, Harry Budi Santoso, Zainal A Hasibuan

Paper Title:

Use Clustering  Data of Student  High School for Placement in Personalization E-Learning  on Higher Education

Abstract: Personalize the e-learning begins after students interact with the system by utilizing the functions and features to collect data and process it so that the resulting information from students who used to organize further activities. In another study, the educational background of the student (and types of SMA) also affects the success in education at the university. In this study developed a personalized e-learning design of the early, which is when the new students will interact with the system. The system will be a kind of student placement test. The case studies used subjects Program Building which is one of the core subjects in the study program Engineering Informatics. As the methods used Knowledge Data Discovery (KDD) using background data combined with a high school student math scores on the National Exam as an ingredient on the stage of Data Mining. This study will measure the extent of the student's educational background above can be used as a system of placement of students in personalized e-learning.

Keywords: high school background, data mining, placement, personalized e-learning.


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7.       Zainal A. Hasibuan, Harry Budi Santoso Mira Suryani, "Personalisasi Konten Pembelajaran Berdasarkan Pendekatan Tipe Belajar Triple-Factor Dalam Student Centered E-Learning Environment," in KNSI , Makasar, 2014.

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9.       Zainal A Hasibuan, Heru Suhartanto Sfenrianto, "An Automatic Approach for Identifying Triple-Factor in e-Learning Process," International Journal of Computer Theory and Engineering, vol. 5, no. 2, pp. 371-376, April 2013.

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