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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

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


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ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
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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.

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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.

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IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  2/2015 - 14

Design and Implementation of PV based Energy Harvester for WSN Node with MAIC algorithm

RAJENDRAN, H. See more information about RAJENDRAN, H. on SCOPUS See more information about RAJENDRAN, H. on IEEExplore See more information about RAJENDRAN, H. on Web of Science, RAMABADRAN, R. See more information about  RAMABADRAN, R. on SCOPUS See more information about  RAMABADRAN, R. on SCOPUS See more information about RAMABADRAN, R. on Web of Science, SANKARARAJAN, R. See more information about SANKARARAJAN, R. on SCOPUS See more information about SANKARARAJAN, R. on SCOPUS See more information about SANKARARAJAN, R. on Web of Science
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Download PDF pdficon (975 KB) | Citation | Downloads: 613 | Views: 2,122

Author keywords
DC-DC power converters, energy harvesting photovoltaic cells, solar energy, wireless sensor networks

References keywords
power(19), energy(11), tracking(8), solar(7), point(7), maximum(7), systems(6), system(6), sensor(6), harvesting(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-05-31
Volume 15, Issue 2, Year 2015, On page(s): 109 - 116
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.02014
Web of Science Accession Number: 000356808900014
SCOPUS ID: 84979846389

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Wireless sensor networks (WSNs) are hardly in need of an additional source of power other than the normally used batteries, to increase the lifetime considerably. In this paper, mathematical modeling of photovoltaic energy harvesting (PVEH) system for the WSN is presented. The system comprises of the solar PV panel, boost converter as maximum power point tracker with moving averaged incremental conductance (MAIC) maximum power point (MPP) algorithm, Ni-MH battery for energy storage, compensator, buck regulator and the mathematically modeled WSN mote. MAIC algorithm is proposed to avoid the effect of drastic variations in input irradiance, in locking the MPP point. WSN mote is modeled in both active and sleep state based on the power consumption. To maintain the voltage stability, proper compensator has been designed for the proposed system. The performance of the system is tested for dynamic variations of environmental conditions using MATLAB simulation. The proposed system has 50 to 60 percent improved conversion efficiency when compared to the conventional direct coupling method. The parameters of the photovoltaic panel model have been validated through experimentation. Also the practical verification of the operation of MPPT circuit has been performed.

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

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[2] C. Alippi, C. Galperti, "An adaptive system for optimal solar energy harvesting in wireless sensor network nodes," IEEE Trans Circ Syst, vol.55, no.6, pp. 1742-1750, 2008.
[CrossRef] [Web of Science Times Cited 170] [SCOPUS Times Cited 230]

[3] C. Y. Chen, P. H. Chou, "Duracap: a supercapacitor-based, power-bootstrapping, maximum power point tracking energy-harvesting system," in Proc. 2010 ACM/IEEE International Symposium on Low-Power Electronics and Design (ISLPED), Austin, USA, 2010, pp. 313 - 318.

[4] D. Brunelli, C. Moser, L. Thiele, L. Benini, "Design of a solar-harvesting circuit for batteryless embedded system," IEEE Trans Circ Syst, vol. 56, no. 11, pp. 2519-2528, 2009.
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[CrossRef] [SCOPUS Times Cited 436]

[7] S. J. Chiang, H. J. Shieh, M. C. Chen, "Modeling and control of pv charger system with sepic converter," IEEE Transactions on Industrial Electronics, vol. 56, no.11, pp. 4344-4353, 2009.
[CrossRef] [Web of Science Times Cited 132] [SCOPUS Times Cited 183]

[8] K. Hoonki, M. Young-Jae, C. H. Jeong, K. Kyu-Young, K. Chulwoo, K. Soo-Won, "A 1-mW solar-energy-harvesting circuit using an adaptive mppt with a sar and a counter," IEEE Transactions on Circuits And Systems—II: Express Briefs, vol.60, no.6, pp. 331-335, 2013.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 16]

[9] N. Femia, G. Petrone, G. Spagnuolo, M. Vitelli, "Optimization of perturb and observe maximum power point tracking method," IEEE Trans.Power Electron., vol.20, no.4, pp.963-973, 2005.
[CrossRef] [Web of Science Times Cited 1040] [SCOPUS Times Cited 1488]

[10] W. Wu, N. Pongratananukul, W. Qiu, K. Rustom, T. Kasparis, I. Batarseh, "DSP-based multiple peak power tracking for expandable power system," in Proc. 18th Annu. IEEE Appl. Power Electron. Conf. Expo., Florida vol.1, 2003, pp. 525-530.

[11] M. A. Masoum, H. Dehbonei, E. F. Fuchs, "Theoretical and experimental analyses of photovoltaic systems with voltage and current-based maximum power-point tracking," IEEE Trans. Energy Convers., vol. 17, no. 4, pp. 514-522, 2002.

[12] El. Khateb, N. A. Rahim, J. Selvaraj, M. N. Uddin, "Fuzzy logic controller based sepic converter of maximum power point tracking," in Proc. 2012 IEEE Industry Applications Society Annual Meeting (IAS), Las Vegas, 2012, pp. 1-9.
[CrossRef] [SCOPUS Times Cited 7]

[13] L. Whei-Min, H. Chih-Ming, C. Chiung-Hsing, "Neural-network-based mppt control of a stand-alone hybrid power generation system," IEEE Trans.Power Electron., vol. 26, no.12, pp. 3571-3581, 2011.
[CrossRef] [Web of Science Times Cited 108] [SCOPUS Times Cited 136]

[14] T. Esram, P. L. Chapman, "Comparison of photovoltaic array maximum power point tracking techniques," IEEE Transactions on Energy Conversion., vol. 22, no.2, pp. 439-449, 2007.
[CrossRef] [Web of Science Times Cited 1797] [SCOPUS Times Cited 2601]

[15] V. Salas, A. Barrado, A. Lazaro, "Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems," Solar Energy Materials & Solar Cells, vol. 90, pp. 1555-1578, 2006.
[CrossRef] [Web of Science Times Cited 498] [SCOPUS Times Cited 677]

[16] I. Houssamo, F. Locment, M. Sechilariu, "Experimental analysis of impact of mppt methods on energy efficiency for photovoltaic power systems," Int J Electr Power Energy Syst, vol. 46, pp. 98-107, 2013.
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[17] M. M. Algazar, H. AL-monier, H. A. EL-halim, M. El Kotb Salem, "Maximum power point tracking using fuzzy logic control," Journal of Electrical Power and Energy Systems, vol. 39, pp. 21-28, 2012.
[CrossRef] [Web of Science Times Cited 103] [SCOPUS Times Cited 142]

[18] Q. Mei, M. Shan, L. Liu, J. M. Guerrero, "A novel improved variable step-size incremental-resistance mppt method for pv systems," IEEE Transactions on Industrial Electronics, vol. 58, no.6, pp. 2427-2434, 2011.
[CrossRef] [Web of Science Times Cited 247] [SCOPUS Times Cited 317]

[19] G. Walker, "Evaluating mppt converter topologies using a matlab pv model," J. Electrical & Electronics Engineering, IEAust, vol. 21, no.1, pp. 49-56, 2001.

[20] Olivier tremblay, A. Louis Dessaint, "Experimental validation of a Battery dynamic Model for EV applications," World Electric Vehicle Journal, vol.3, pp.1-10, 2009.

[21] K. C. Wu, "Switch-mode power converters design and analysis", pp.245-247, Elsevier Academic Press, 2006.

[22] R. Ramaprabha, B. L. Mathur, "Development of an improved model of spv cell for partially shaded solar photovoltaic arrays," European Journal of Scientific Research, vol. 47, no.1, pp. 22-134, 2010

References Weight

Web of Science® Citations for all references: 4,340 TCR
SCOPUS® Citations for all references: 6,819 TCR

Web of Science® Average Citations per reference: 197 ACR
SCOPUS® Average Citations per reference: 310 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 2017-12-10 11:58 in 104 seconds.

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

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