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JCR Impact Factor: 0.700
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SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Aug 2024
Next issue: Nov 2024
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PUBLISHER

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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Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

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  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
 
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Download PDF pdficon (1,487 KB) | Citation | Downloads: 1,037 | Views: 2,690

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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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.


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