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JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Aug 2018
Next issue: Nov 2018
Avg review time: 80 days


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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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 »


    
 

  4/2014 - 4

Incentive Driven Distributed Generation Planning with Renewable Energy Resources

KAUR, S. See more information about KAUR, S. on SCOPUS See more information about KAUR, S. on IEEExplore See more information about KAUR, S. on Web of Science, KUMBHAR, G. B. See more information about KUMBHAR, G. B. on SCOPUS See more information about KUMBHAR, G. B. on SCOPUS See more information about KUMBHAR, G. B. 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 (837 KB) | Citation | Downloads: 470 | Views: 1,990

Author keywords
distributed power generation, heuristic algorithms, optimization, power generation planning, sustainable development

References keywords
power(10), energy(10), planning(9), optimization(9), generation(9), distributed(9), distribution(8), systems(6), system(6), search(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 21 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04004
Web of Science Accession Number: 000348772500004
SCOPUS ID: 84921651204

Abstract
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Renewable DGs may not be economically viable due to the stochastic generation and huge capital investment, but are an inevitable choice for sustainable energy development and future planning. An appropriate incentive scheme for clean Distributed Generation (DG) technologies is able to address this issue in an economical manner and is considered in proposed distributed generation planning model. The proposed model minimizes the annualized cost with Emission Offset Incentive (EOI) and the penalty for Green-house Gas (GHG) emissions. A meta-heuristic approach with dynamic tuning of control parameters is adopted to improve the success and the convergence rate of optimal solutions. The algorithm provides the optimal solution in terms of type, size, and location of DG. The proposed technique is implemented on IEEE 33-bus system. Proposed model helps the Distribution Network Operators (DNOs) to decide the proper DG technology from an economic prospective for eco-friendly energy planning.


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

[1] A. Keane, L. F. Ochoa, C. Borges, G. Ault, A. Alarcon, R. Currie, F. Pilo, C. Dent, G. P. Harrison, "State of the art techniques and challenges ahead for DG planning and optimization," IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 1493-1502, May 2013.
[CrossRef] [Web of Science Times Cited 131] [SCOPUS Times Cited 146]


[2] P. S. Georgilakis, N. D. Hatziargyriou, "Optimal distributed generation placement in power distribution Network: Models, methods and future", IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 3420-3428, 2013.
[CrossRef] [Web of Science Times Cited 271] [SCOPUS Times Cited 326]


[3] W. El-Khattam, K. Bhattacharya, Y. Hegazy, M. M. A. Salama, "Optimal investment planning for distributed generation in a competitive electricity market," IEEE Transactions on Power Systems, vol. 19, no. 3, pp. 1674-1684, 2004.
[CrossRef] [Web of Science Times Cited 227] [SCOPUS Times Cited 353]


[4] A. Zangeneh, S. Jadid, A. R. Kian, "Promotion strategy of clean technologies in distributed generation expansion planning," Renewable Energy, vol. 34, no. 12, pp. 2765-2773, 2009.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 65]


[5] W. S. Tan, M.Y. Hassan, H. A. Rahman, M. P. Abdullah, F. Hussin, "Multi-distributed generation planning using hybrid partical swarm optimization - gravitational search algorithm inclusing voltage rise issue," Generation, Transmission & Distribution, IET, vol. 7, no. 9, pp. 929-942, 2013.
[CrossRef] [Web of Science Times Cited 44]


[6] T. Niknam, S. I. Taheri, J. Agahei, S. Tabatabaei, M. Nayeripour, "A modified mating optimization algorithm for multiobjective placement of renewable energy resources," Applied Energy, vol. 88, no. 12, pp. 4817-4830, 2011.
[CrossRef] [Web of Science Times Cited 91] [SCOPUS Times Cited 102]


[7] M. A. Abdullah, A. P. Agalgaonkar, K. M. Muttaqi, "Quantification of emission reduction from electicity network with the integration of renewable resources," in Proc. IEEE Power and Energy Society General Meeting, 2011 , pp. 1-7.
[CrossRef] [SCOPUS Times Cited 6]


[8] A. Soroudi, M. Eshan, H. Zareipour, "A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy sources," Renewable Energy, vol. 36, no. 1, pp. 179-188, 2011.
[CrossRef] [Web of Science Times Cited 58] [SCOPUS Times Cited 73]


[9] R. Ebrahimi, M. Eshan, H. Nouri, "A profit-centric strategy for distributed generation planning considering time varying voltage dependent load demand," International Journal of Electrical Power & Energy Systems, vol. 44, no. 1, pp. 168-178, 2013.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 13]


[10] G. P. Harrison, A. Piccolo, P. Siano, A. R. Wallace, "Hybrid GA and OPF evaluation of network capacity for distributed generation connections," Electric Power System Research., vol. 78, no. 3, pp. 392-398, 2008.
[CrossRef] [Web of Science Times Cited 120] [SCOPUS Times Cited 153]


[11] Y.M. Atwa, E. F. E. Saadany, M. M. A. Salama, R. Seethapathi, "Optimal renewable resources mix for distribution system energy loss minimization," IEEE Transactions on Power Systems, vol. 25, no. 1, pp. 360-370, 2010.
[CrossRef] [Web of Science Times Cited 478] [SCOPUS Times Cited 605]


[12] P. Siano, L.F. Ochoa, G.P. Harrison, A. Piccolo, "Assessing the strategic benefits of distributed generation ownership for DNOs," Generation, Transmission & Distribution, IET, vol. 3, no. 3, pp. 225-236, March 2009.
[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 79]


[13] Z. W. Geem, J. H. Kim, G. V. Loganathan, "A New Heuristic Optimization Algorithm: Harmony Search," SIMULATION, vol. 76, no. 2, pp. 60-68, 2001.
[CrossRef] [SCOPUS Times Cited 2721]


[14] K. S. Lee, Z. W. Geem, S. Lee, K. Bae, "The harmony search heuristic algorithm for discrete structural optimization," Engineering Optimization, vol. 37, no. 7, pp. 663-684, 2005.
[CrossRef] [Web of Science Times Cited 191] [SCOPUS Times Cited 223]


[15] S. Das, A. Mukhopadhyay, A. Roy, A. Abraham, B. K. Panigrahi, "Exploratory Power of the Harmony Search Algorithm: Analysis and Improvements for Global Numerical Optimization," IEEE Transactions on System Man and Cybernetics, Part B: Cybernetics, vol. 41, no. 1, pp. 89-106, 2011.
[CrossRef] [Web of Science Times Cited 117] [SCOPUS Times Cited 161]


[16] M. Mahdavi, M. Fesanghary, E. Damangir, "An improved harmony search algorithm for solving optimization problems," Applied Mathematics and Computation, vol. 188, no. 2, pp. 1567-1579, 2007.
[CrossRef] [Web of Science Times Cited 712] [SCOPUS Times Cited 1076]


[17] K. Nekooei, M. M. Farsangi, H. Nezamabadi-Pour, K. Y. Lee, "An Improved Multi-Objective Harmony Search for Optimal Placement of DGs in Distribution Systems," IEEE Transactions on Smart Grid, vol. 4, no. 1, pp. 557-567, 2013.
[CrossRef] [Web of Science Times Cited 96] [SCOPUS Times Cited 110]


[18] K. Zou, A. P. Agalgaonkar, K. M. Muttaqi, S. Perera, "Distribution System Planning With Incorporating DG Reactive Capability and System Uncertainties," IEEE Transactions on Sustainable Energy, vol. 3, no. 1, pp. 112-123, 2012.
[CrossRef] [Web of Science Times Cited 145] [SCOPUS Times Cited 190]


[19] N. Jain, S. N. Singh, S. C. Srivastava, "A Generalized Approach for DG Planning and Viability Analysis Under Market Scenario," IEEE Transactions on Industrial Electronics, vol. 60, pp. 5075-5085, 2013.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 52]


[20] D. Olivera, P. Feltrin, "Investigation of the relationship between load and load factors for a Brazillian electric utility," in Proc. Electric utility Transmission and distribution conference and exposition, Latin America, 2006, pp. 1-6
[CrossRef]


[21] N. Jain, S.N. Singh, S. C. Srivastava, "Planning and impact evaluation of distributed generators in Indian context using Multi-Objective Particle Swarm Optimization," in Proc. IEEE Power and Energy Society General Meeting, 2011, pp. 1-8.
[CrossRef] [SCOPUS Times Cited 17]


[22] L. R. A. Deepa, N. Praveen, "Impact of Climate change and adaptation to green technology in India," in Proc. Recent Advances in Space Technology Services and Climate Change (RSTSCC), 2010, pp. 460-465.
[CrossRef] [SCOPUS Times Cited 1]


[23] A. M. Jain, B. E. Kushare, "Techno-economics of solar wind hybrid system in Indian context: A case study," in Proc IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007, pp. 39-44.



References Weight

Web of Science® Citations for all references: 2,860 TCR
SCOPUS® Citations for all references: 6,472 TCR

Web of Science® Average Citations per reference: 119 ACR
SCOPUS® Average Citations per reference: 270 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 2018-09-24 06:11 in 165 seconds.




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Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

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


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