ACTIVE POWER LOSS REDUCTION BY SYNTHESIZED ALGORITHM
DOI:
https://doi.org/10.29121/granthaalayah.v6.i5.2018.1436Keywords:
Particle Swarm Optimization, Genetic Algorithm, Harmony Search, Optimal Reactive Power, Transmission LossAbstract [English]
In this paper, Synthesized Algorithm (SA) proposed to solve the optimal reactive power problem. Proposed Synthesized Algorithm (SA) is a combination of three well known evolutionary algorithms, namely Differential Evolution (DE) algorithm, Particle Swarm Optimization (PSO) algorithm, and Harmony Search (HS) algorithm. It merges the general operators of each algorithm recursively. This achieves both good exploration and exploitation in SA without altering their individual properties. In order to evaluate the performance of the proposed SA, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results show’s that Synthesized Algorithm (SA) successfully reduces the real power loss and voltage profiles are within the limits.
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
R. Thangaraj, M. Pant, A. Abraham, and P. Bouvry, “Particle Swarm Optimization: Hybridization perspectives and experimental illustrations”, Appl. Math. and Comput., vol. 217, pp. 5208-5226, 2011.
X.H. Shi, Y.C. Liang, and L.M. Wang, “An improved GA and novel PSO-GA-based hybrid algorithm”, Inf. Process. Lett., vol. 93, pp. 255-261, 2005. DOI: https://doi.org/10.1016/j.ipl.2004.11.003
N. Holden, A.A. Freitas, “A hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data.”Swarm Intell. Symp. SIS 2005, pp.100-107, 2005.
A.A.A. Esmin, G.T. Torres, and G.B. Alvarenga, “Hybrid Evolutionary Algorithm Based on PSO and GA mutation”, In proc. of the Sixth Int. Conf. on Hybrid Intell. Syst., pp.57, 2006. DOI: https://doi.org/10.1109/HIS.2006.264940
H. Li, and H. Li, “A Novel Hybrid Particle Swarm Optimization Algorithm Combined with Harmony Search for High Dimensional Optimization Problems”, The Int. Conf. on Intell. Pervasive Comput., pp. 94-97, 2007. DOI: https://doi.org/10.1109/IPC.2007.22
i. Cionei, E. Kyriakides, “Hybrid Ant Colony-Genetic Algorithm (GAAPI) for Global Continuous Optimization”, IEEE Trans. On Syst., Man, and Cybern. - Part B.
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.