ENRICHED BLACK HOLE ALGORITHM FOR DIMINUTION OF REAL POWER LOSS
DOI:
https://doi.org/10.29121/granthaalayah.v5.i9.2017.2228Keywords:
Optimal Reactive Power, Transmission Loss, Enriched Black HoleAbstract [English]
This paper presents an Enriched Black Hole (EBH) algorithm for solving reactive power flow problem. The Black Hole Algorithm starts with a preliminary population of contestant and for all iteration of the black hole algorithm, the most excellent candidate is favored to be the black hole, which followed by pulling further candidates around it, called stars. If a star move very close to the black hole, it will be consumed by the black hole and is vanished undyingly. In such a case, a new star - candidate solution is arbitrarily created and placed in the exploration space and starts a new search. Black hole algorithm is feeble to carry out global search completely in the large size problem spaces. So the enhancement in the amalgamation process in black hole algorithm has to be done. In this work, black hole algorithm will be enhanced, using stars gravities information. For this aim, a kind of gravitational force between stars is defined and the movement of stars to the black hole is adjusted during the penetration of solution space. In order to evaluate the projected Enriched Black Hole (EBH) algorithm, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results reveal about the Enriched performance of the projected algorithm in plummeting the real power loss.
Downloads
References
O.Alsac,and B. Scott, “Optimal load flow with steady state security”,IEEE Transaction. PAS -1973, pp. 745-751. DOI: https://doi.org/10.1109/TPAS.1974.293972
Lee K Y ,Paru Y M , Oritz J L –A united approach to optimal real and reactive power dispatch , IEEE Transactions on power Apparatus and systems 1985: PAS-104 : 1147-1153 DOI: https://doi.org/10.1109/TPAS.1985.323466
A.Monticelli , M .V.F Pereira ,and S. Granville , “Security constrained optimal power flow with post contingency corrective rescheduling” , IEEE Transactions on Power Systems :PWRS-2, No. 1, pp.175-182.,1987. DOI: https://doi.org/10.1109/TPWRS.1987.4335095
Deeb N ,Shahidehpur S.M ,Linear reactive power optimization in a large power network using the decomposition approach. IEEE Transactions on power system 1990: 5(2) : 428-435 DOI: https://doi.org/10.1109/59.54549
E. Hobson ,’Network consrained reactive power control using linear programming, ‘ IEEE Transactions on power systems PAS -99 (4) ,pp 868=877, 1980 DOI: https://doi.org/10.1109/TPAS.1980.319715
K.Y Lee ,Y.M Park , and J.L Oritz, “Fuel –cost optimization for both real and reactive power dispatches” , IEE Proc; 131C,(3), pp.85-93. DOI: https://doi.org/10.1049/ip-c.1984.0012
M.K. Mangoli, and K.Y. Lee, “Optimal real and reactive power control using linear programming” , Electr.Power Syst.Res, Vol.26, pp.1-10,1993. DOI: https://doi.org/10.1016/0378-7796(93)90063-K
K.Anburaja, “Optimal power flow using refined genetic algorithm”, Electr.Power Compon.Syst , Vol. 30, 1055-1063,2002. DOI: https://doi.org/10.1080/15325000290085343
D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal power flow for security enhancement”, IEE proc-Generation.Transmission and. Distribution; 152, 6 November 2005. DOI: https://doi.org/10.1049/ip-gtd:20045234
Abdolreza Hatamlou “Black hole: A new heuristic optimization approach for data clustering”, Information Sciences 222 (2013) 175–184.
L. Kaper, E. Heuvel, P. Woudt, R. Giacconi, “Black hole research past and future, in: Black Holes in Binaries and Galactic Nuclei: Diagnostics, Demography and Formation”, Springer, Berlin/Heidelberg, 2001, pp. 3–15.
C. Pickover, “Black Holes: A Traveler’s Guid”e, John Wiley & Sons, 1998.
J. Zhang, K. Liu, Y. Tan, X. He, “Random black hole particle swarm optimization and its application”, in: 2008 IEEE International Conference Neural Networks and Signal Processing, ICNNSP, 2008, pp. 359–365.
A. A. Heidari * , R. A. Abbaspour, “Improved Black Hole Algorithm for Efficient Low Observable UCAV Path Planning in Constrained Aerospace”, ACSIJ Advances in Computer Science: an International Journal, Vol. 3, Issue 3, No.9 , May 2014 ISSN : 2322-5157.
Hatamlou, A., “Black hole: A new heuristic optimization approach for data clustering”, Information Sciences 222, 2013, pp.175-184. DOI: https://doi.org/10.1016/j.ins.2012.08.023
Chaohua Dai, Weirong Chen, Yunfang Zhu, and Xuexia Zhang, “Seeker optimization algorithm for optimal reactive power dispatch,” IEEE Trans. Power Systems, Vol. 24, No. 3, August 2009, pp. 1218-1231. DOI: https://doi.org/10.1109/TPWRS.2009.2021226
J. R. Gomes and 0. R. Saavedra, “Optimal reactive power dispatch using evolutionary computation: Extended algorithms,” IEE Proc.-Gener. Transm. Distrib.. Vol. 146, No. 6. Nov. 1999. DOI: https://doi.org/10.1049/ip-gtd:19990683
IEEE, “The IEEE 30-bus test system and the IEEE 118-test system”, (1993),
http://www.ee.washington.edu/trsearch/pstca/.
Jiangtao Cao, Fuli Wang and Ping Li, “An Improved Biogeography-based Optimization Algorithm for Optimal Reactive Power Flow” International Journal of Control and Automation Vol.7, No.3 (2014), pp.161-176.
Downloads
Published
How to Cite
Issue
Section
License
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.