Deciding Optimal Location of DPFC in Transmission Line Using Artificial Algae Algorithm
Abstract
In this paper, the application of artificial algae algorithm (AAA) in optimal placement distributed power flow controller (DPFC) with MCFC in transmission networks has been proposed The proposed method is tested on IEEE 14- bus system and the results are discussed. The biggest advantage of DPFC is that it can control the active and reactive power flow and bus voltages, simultaneously. In this paper, the optimal placement of one DPFC in IEEE-14 bus system and then optimal placement of two DPFCs in IEEE-14 bus system has been proposed. Optimal placement of DPFC in power system by AAA leads to increased stability and capacity of the power transmission in lines. The proposed model has been simulated in Matlab/Simulink and the performance results are tabulated.
Keywords:
artifical algae algorithm, DPFC, MCFCDownloads
References
S. V. Ravi Kumar, S. S. N. Raju, “Loss Minimization by incorporation of UPFC in Load Flow Studies”, International Journal of Electrical and Power Engineering, Vol. 1, No. 3, pp. 321-327, 2007
A. M. Vural, M. Tumay, “Mathematical modelling and analysis of a unified power flow controller: A comparison of two approaches in power flow studies and effects of UPFC location”, Electrical Power and Energy Systems, Vol. 29, pp. 617-629, 2007 DOI: https://doi.org/10.1016/j.ijepes.2006.09.005
B. V. Rao, G. V. N. Kumar, M. R. Priya, P. V. S. Sobhan, “Implementation of Static VAR Compensator for Improvement of Power System Stability”, 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, Trivandrum, India, December 28-29, 2009 DOI: https://doi.org/10.1109/ACT.2009.117
M. D. Reddy, K. D. Babu, “Optimal placement of SVC using fuzzy and PSO algorithm”, International Journal of Engineering Research and Applications, Vol. 3, No. 1, pp. 485-490, 2013
V. K. Shende, P. Jagtap, “Optimal Location and sizing of SVC by PSO technique for Voltage Stability Enhancement and Power loss minimization”, International journal of Engineering Trends and Technology, Vol. 4, No. 6, pp. 2278-2282, 2013
R. S. Rao, V. S. Rao, “A generalized approach for determination of optimal location and performance analysis of FACTs devices”, International Journal of Electrical Power & Energy Systems, Vol. 73, pp. 711-724, 2015 DOI: https://doi.org/10.1016/j.ijepes.2015.06.004
B. Bhattacharyya, V. K. Gupta, S. Kumar, “UPFC with series and shunt FACTS controllers for the economic operation of a power system”, Ain Shams Engineering Journal, Vo. 5, No. 3, pp. 775-787, 2014 DOI: https://doi.org/10.1016/j.asej.2014.03.013
N. Karuppiah, V. Malathi, G. Selvalakshmi, “Optimal Placement and Sizing of Multi-type Facts Devices Using PSO and HSA”, in: Lecture Notes in Computer Science, Vol. 8947, Springer, 2014 DOI: https://doi.org/10.1007/978-3-319-20294-5_26
S. Frank I. Steponavice, S. Rebennack, “Optimal power flow: a bibliographic survey II Nondeterministic and hybrid methods”, Energy Systems, Vol. 3, No. 3, pp. 259-289, 2012 DOI: https://doi.org/10.1007/s12667-012-0057-x
S. Akumalla, S. Peddakotla, S. R. A. Kuppa, “A Modified Cuckoo Search Algorithm for Improving Voltage Profile and to Diminish Power Losses by Locating Multi-type FACTS Devices”, Journal of Control, Automation and Electrical Systems, Vol. 27, No. 1, pp. 93-104, 2016 DOI: https://doi.org/10.1007/s40313-015-0219-x
S. Dutta, P. K. Roy, D. Nandi, “Optimal location of UPFC controller in transmission network using hybrid chemical reaction optimization algorithm”, International Journal of Electrical Power & Energy Systems, Vol. 64, pp. 194-211, 2015 DOI: https://doi.org/10.1016/j.ijepes.2014.07.038
S. A. Taher, M. K. Amooshahi, “New approach for optimal UPFC placement using hybrid immune algorithm in electric power systems”, International Journal of Electrical Power & Energy Systems, Vol. 43, No. 1, pp. 899-909, 2012 DOI: https://doi.org/10.1016/j.ijepes.2012.05.064
J. Chakravorty, J. Saraswat, V. Bhatia, “Modeling a Distributed Power Flow Controller with a PEM Fuel Cell for Power Quality Improvement”, Engineering, Technology & Applied Science Research, Vol. 8, No. 1, pp. 2585-2589, 2018 DOI: https://doi.org/10.48084/etasr.1807
S. Ali, G. Tezel, E. Yel, “Artificial Algae Algorithm (AAA) for nonlinear global optimization”, Applied Soft Computing, Vol. 31, pp. 153-171, 2015 DOI: https://doi.org/10.1016/j.asoc.2015.03.003
S. A. Uymaz, G. Tezel, E. Yel, “Artificial Algae Algorithm with multi-light source for numerical optimization and application”, Biosystems, Vol. 138, pp. 25-38, 2015 DOI: https://doi.org/10.1016/j.biosystems.2015.11.004
M. P. Aghababa, M. E. Akbari, A. M. Shotorbani, “An Efficient Modified Shuffled Frog Leaping Optimization Algorithm”, International Journal of Computer Applications, Vol. 32, pp. 26-30, 2011
Downloads
How to Cite
License
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
