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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


    
 

  2/2017 - 7

Conceptual Design of an Online Estimation System for Stigmergic Collaboration and Nodal Intelligence on Distributed DC Systems

DOORSAMY, W. See more information about DOORSAMY, W. on SCOPUS See more information about DOORSAMY, W. on IEEExplore See more information about DOORSAMY, W. on Web of Science, CRONJE, W. See more information about CRONJE, W. on SCOPUS See more information about CRONJE, W. on SCOPUS See more information about CRONJE, W. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,487 KB) | Citation | Downloads: 207 | Views: 544

Author keywords
autonomous agents, distributed energy systems, microgrid, recursive estimation, state estimation

References keywords
power(16), microgrids(9), systems(8), energy(8), electronics(8), system(4), optimization(4), impedance(4), control(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 47 - 54
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02007
Web of Science Accession Number: 000405378100007
SCOPUS ID: 85020099701

Abstract
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Full text preview
The secondary level control of stand-alone distributed energy systems requires accurate online state information for effective coordination of its components. State estimation is possible through several techniques depending on the system's architecture and control philosophy. A conceptual design of an online state estimation system to provide nodal autonomy on DC systems is presented. The proposed estimation system uses local measurements - at each node - to obtain an aggregation of the system's state required for nodal self-control without the need for external communication with other nodes or a central controller. The recursive least-squares technique is used in conjunction with stigmergic collaboration to implement the state estimation system. Numerical results are obtained using a Matlab/Simulink model and experimentally validated in a laboratory setting. Results indicate that the proposed system provides accurate estimation and fast updating during both quasi-static and transient states.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 1,196 TCR
SCOPUS® Citations for all references: 1,885 TCR

Web of Science® Average Citations per reference: 43 ACR
SCOPUS® Average Citations per reference: 67 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-12-15 20:57 in 180 seconds.




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