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JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Nov 2018
Next issue: Feb 2019
Avg review time: 79 days


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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A Proposal of a Novel Method for Generating Discrete Analog Uniform Noise, PEJIC, D., GAZIVODA, N., LICINA, B., UREKAR, M., SOVILJ, P., VUJICIC, B.
Issue 3/2018


Improving Voltage Profile and Optimal Scheduling of Vehicle to Grid Energy based on a New Method, NAZARLOO, A., FEYZI, M. R., SABAHI, M., BANNAE SHARIFIAN, M. B.
Issue 1/2018


Implementation of High Speed Tangent Sigmoid Transfer Function Approximations for Artificial Neural Network Applications on FPGA, KOYUNCU, I.
Issue 3/2018


Low Complexity V-BLAST MIMO-OFDM Detector by Successive Iterations Reduction, AHMED, K., ABUELENIN, S., SOLIMAN, H., AL-BARBARY, K.
Issue 1/2015


Underwater Image Enhancement by Adaptive Gray World and Differential Gray-Levels Histogram Equalization, WONG, S.-L., PARAMESRAN, R., TAGUCHI, A.
Issue 2/2018


Measurement of Soil Resistivity in Order to Determine the Buried Walls Trajectory, MUNTEANU, M. S., CZUMBIL, L., MICU, D. D., BRAICU, S. F., NEMETI, S., PISLARU, M.
Issue 1/2017



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.

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.

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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  1/2018 - 11

Software Solution for a Renewable Energy Microgrid Emulator

LAZAR, E. See more information about LAZAR, E. on SCOPUS See more information about LAZAR, E. on IEEExplore See more information about LAZAR, E. on Web of Science, PETREUS, D. See more information about  PETREUS, D. on SCOPUS See more information about  PETREUS, D. on SCOPUS See more information about PETREUS, D. on Web of Science, ETZ, R. See more information about  ETZ, R. on SCOPUS See more information about  ETZ, R. on SCOPUS See more information about ETZ, R. on Web of Science, PATARAU, T. See more information about PATARAU, T. on SCOPUS See more information about PATARAU, T. on SCOPUS See more information about PATARAU, T. 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 (2,443 KB) | Citation | Downloads: 212 | Views: 604

Author keywords
energy management, graphical user interfaces, microgrids, renewable energy sources, SCADA systems

References keywords
energy(28), renewable(11), microgrid(9), management(8), system(6), power(6), optimization(5), real(4), microgrids(4), japenergy(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 89 - 94
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01011
Web of Science Accession Number: 000426449500011
SCOPUS ID: 85043242060

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The paper presents a software solution and communication network used to implement and test management algorithms for different microgrid configurations. The results obtained are represented in a Graphical User Interface (GUI). Data is transferred between the devices and a central processing unit that has a communication protocol interpreter implemented using an RS-485 network. After being interpreted, the raw data containing useful information for the management algorithm is converted in numerical or Boolean values. These values are stored and used by the management algorithms implemented for cost optimization. A microgrid emulator is used for the proof of concept. The software solution and communication network together with the data interpreter can be easily used for other microgrid structures with or without modifications, depending on the number and types of equipment used. In the presented case the microgrid management control algorithm tries to keep the state of charge of the batteries between two values by using efficiently the available resources depicted by: solar energy, geothermal energy, and energy obtained from biomass. The microgrid setup has emulators for the geothermal and biomass generators and a photovoltaic system with storage capability and two inverters, a grid forming capable and a grid follower.

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

[1] S. M. Dawouda, X. Lin, M. I. Okbaa, "Hybrid renewable microgrid optimization techniques: A review," Renewable and Sustainable Energy Reviews, Vol. 82, Part. 3, pp. 2039-2052, 2018.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 11]

[2] A. G. Lupu, A. Dumencu, M. V. Atanasiu, C. E. Panaite, Gh. Dumitrascu, A. Popescu, "SWOT analysis of the renewable energy sources in Romania – case study: solar energy", 7th International Conference on Advanced Concepts in Mechanical Engineering, IOP Conf. Series: Materials Science and Engineering Vol. 147, pp. 1-10, 2016.
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[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 12]

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[CrossRef] [Web of Science Times Cited 97] [SCOPUS Times Cited 115]

[5] E. Mengelkamp, J. Garttner, K. Rock, S. Kessler, L. Orsini, C. Weinhardt, "Designing microgrid energy markets: A case study: The Brooklyn Microgrid", Applied Energy, Vol. 210, pp. 870-880, 2017.
[CrossRef] [Web of Science Times Cited 41] [SCOPUS Times Cited 72]

[6] M. Smaoui, L. Krichen, "Control, energy management and performance evaluation of desalination unit based renewable energies using a graphical user interface", Energy, Vol. 114, pp. 1187-1206, 2016.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 18]

[7] I. Gonzalez, A. J. Calderon, J. M. Anduj, "Novel remote monitoring platform for RES-hydrogen based smart microgrid", Energy Conversion and Management, Vol. 148, pp. 489-505, 2017.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 8]

[8] M. E. Khodayar, "Rural electrification and expansion planning of off-grid microgrids", The Electricity Journal, Vol. 30, pp. 65-74, 2017.
[CrossRef] [SCOPUS Times Cited 10]

[9] T. Adefarati, R. C. Bansal, "Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources", Applied Energy, Vol. 206, pp. 911-933, 2017.
[CrossRef] [SCOPUS Times Cited 17]

[10] H. Morais, P. Kadar, P. Faria, Z. A. Vale, H. M. Khodr, "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming", Renewable Energy, Vol. 35, pp. 151-156, 2010.
[CrossRef] [Web of Science Times Cited 230] [SCOPUS Times Cited 292]

[11] H. Ren, W. Gao, "A MILP model for integrated plan and evaluation of distributed energy systems", Applied Energy, Vol. 87, pp. 1001-1014, 2010.
[CrossRef] [Web of Science Times Cited 197] [SCOPUS Times Cited 239]

[12] P. Garciaa, J. P. Torreglosa, L. M. Fernandez, F. Juradoc, R. Langella, A. Testa, "Energy management system based on techno-economic optimization for microgrids", Electric Power Systems Research, Vol. 131, pp. 49-59, 2016.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 13]

[13] E. Lazar, D. Petreus, R. Etz, T. Patarau, "Minimization of operational cost for an Islanded Microgrid using a real coded Genetic Algorithm and a Mixed Integer Linear Programming method", 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP), Brasov, Romania, 25-27, May, pp. 693-698, 2017.
[CrossRef] [SCOPUS Times Cited 3]

[14] X. Lu, K. Zhou, S. Yang, "Multi-objective optimal dispatch of microgrid containing electric vehicles", Journal of Cleaner Production, Vol. 165, pp. 1572-1581, 2017.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 17]

[15] M. S. Fakhar, S. A. R. Kashif, M. A. Saqib, T. Hassan, "Non cascaded short-term hydro-thermal scheduling using fully-informed particle swarm optimization", Electrical Power and Energy Systems, Vol. 73, pp. 983-990, 2015.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 17]

[16] C. Roldan-Blay, G. Escriva-Escriva, C.Roldan-Porta, C. Alvarez-Bel, "An optimisation algorithm for distributed energy resources management in micro-scale energy hubs", Energy, Vol.132, 126-135, 2017.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 15]

[17] M. Marzband, A. Sumper, A. Ruiz-Alvarez, J. L. Dominguez-Garcia, B. Tomoiaga, "Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets", Applied Energy, vol. 106, pp. 365-376, 2013.
[CrossRef] [Web of Science Times Cited 113] [SCOPUS Times Cited 115]

[18] R. Etz, D. Petreus, T. Patarau, E. Lazar, "An islanded renewable energy microgrid emulator for geothermal, biogas, photovoltaic and lead acid battery storage", 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), Edinburgh, UK, pp. 2109–2114, 19–21 June 2017.
[CrossRef] [SCOPUS Times Cited 4]

[19] M. Marzband, E. Yousefnejad, A. Sumper, J. Luis Dominguez-Garcia, "Real time experimental implementation of optimum energy management system in standalone Microgrid by using multi-layer ant colony optimization", Electrical Power and Energy System, Vol. 75, pp. 265-274, 2016.
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[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 17]

References Weight

Web of Science® Citations for all references: 866 TCR
SCOPUS® Citations for all references: 1,088 TCR

Web of Science® Average Citations per reference: 41 ACR
SCOPUS® Average Citations per reference: 52 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 2019-02-14 14:15 in 140 seconds.

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