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JCR Impact Factor: 0.700
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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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A Proposed Signal Reconstruction Algorithm over Bandlimited Channels for Wireless Communications, ASHOUR, A., KHALAF, A., HUSSEIN, A., HAMED, H., RAMADAN, A.
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2024-Jun-20
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.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  2/2015 - 14

 HIGHLY CITED PAPER 

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: 1,526 | Views: 6,297

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

Abstract
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Full text preview
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

[1] A. Hande, T. Polk, W. Walker, D. Bhatia, "Indoor solar energy harvesting for sensor network router nodes," J. Microprocessors & Microsystems, vol. 31, no.6, pp.420-432, 2007.
[CrossRef] [Web of Science Times Cited 132] [SCOPUS Times Cited 176]


[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 262] [SCOPUS Times Cited 355]


[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.
[CrossRef] [Web of Science Times Cited 184] [SCOPUS Times Cited 243]


[5] C. Park, P. H. Chou, "Ambimax: autonomous energy harvesting platform for multi-supply wireless sensor nodes," in Proc. 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks conference, California, 2006, pp. 168-177.
[CrossRef] [SCOPUS Times Cited 414]


[6] X. Jiang, J. Polastre, D. Culler, "Perpetual environmentally powered sensor networks," in Proc. 4th International Symposium on Information Processing in Sensor Networks, Los Angeles, 2005, pp.463-468.
[CrossRef] [SCOPUS Times Cited 635]


[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 239] [SCOPUS Times Cited 356]


[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 39] [SCOPUS Times Cited 43]


[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 1915] [SCOPUS Times Cited 2617]


[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.
[CrossRef] [SCOPUS Times Cited 140]


[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.
[CrossRef]


[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 11]


[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 213] [SCOPUS Times Cited 312]


[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 3225] [SCOPUS Times Cited 4498]


[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 772] [SCOPUS Times Cited 1072]


[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.
[CrossRef] [Web of Science Times Cited 86] [SCOPUS Times Cited 109]


[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 219] [SCOPUS Times Cited 293]


[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 459] [SCOPUS Times Cited 618]


[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: 7,745 TCR
SCOPUS® Citations for all references: 11,892 TCR

Web of Science® Average Citations per reference: 352 ACR
SCOPUS® Average Citations per reference: 541 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 2024-11-29 17:22 in 123 seconds.




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


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