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Reseach Article

Application of Fruit Fly Algorithm for Security Constrained Optimal Power Flow Problem

by S. Sakthivel, K. Kavipriya, P. Poovarasi, B. Prema
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 162 - Number 12
Year of Publication: 2017
Authors: S. Sakthivel, K. Kavipriya, P. Poovarasi, B. Prema
10.5120/ijca2017913420

S. Sakthivel, K. Kavipriya, P. Poovarasi, B. Prema . Application of Fruit Fly Algorithm for Security Constrained Optimal Power Flow Problem. International Journal of Computer Applications. 162, 12 ( Mar 2017), 16-21. DOI=10.5120/ijca2017913420

@article{ 10.5120/ijca2017913420,
author = { S. Sakthivel, K. Kavipriya, P. Poovarasi, B. Prema },
title = { Application of Fruit Fly Algorithm for Security Constrained Optimal Power Flow Problem },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 162 },
number = { 12 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume162/number12/27295-2017913420/ },
doi = { 10.5120/ijca2017913420 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:08:50.815348+05:30
%A S. Sakthivel
%A K. Kavipriya
%A P. Poovarasi
%A B. Prema
%T Application of Fruit Fly Algorithm for Security Constrained Optimal Power Flow Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 162
%N 12
%P 16-21
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Optimal power flow (OPF) is a major task in power system economics and operation. In OPF power real power outputs from the generators of a power system are so adjusted that the total production cost is minimum. Security constraint OPF (SC-OPF) is minimizing the cost keeping line flows within their respective limits for security reasons. Real power output from generators, generator bus voltage magnitudes, var outputs from shunt compensators and transformer tap settings are controlled for optimizing the total fuel cost in this OPF problem. This proposed work considers the bio inspired fruit fly algorithm (FFA) for optimally selecting the values for control variables. The proposed algorithm is simple, with less number of parameters and easy to implement. The performance of this algorithm in OPF task is tested on IEEE 30 bus test system. Numerical results are compared to literature results and found to be improved.

References
  1. Dommel, Hermann W., and William F. Tinney. "Optimal power flow solutions." IEEE Transactions on power apparatus and systems 10 (1968): 1866-1876.
  2. Deb, Kalyanmoy. Optimization for engineering design: Algorithms and examples. PHI Learning Pvt. Ltd., 2012.
  3. Venkatesh, P., R. Gnanadass, and Narayana Prasad Padhy. "Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints." IEEE Transactions on Power systems 18.2 (2003): 688-697.
  4. AlRashidi, M. R., and M. E. El-Hawary. "Hybrid particle swarm optimization approach for solving the discrete OPF problem considering the valve loading effects." IEEE transactions on power systems 22.4 (2007): 2030-2038.
  5. Varadarajan, M., and K. Shanty Swarup. "Solving multi-objective optimal power flow using differential evolution." IET Generation, Transmission & Distribution 2.5 (2008): 720-730.
  6. Babu, AV Naresh, and Sirigiri Sivanagaraju. "Optimal power flow with FACTS device using two step initialization based algorithm for security enhancement considering credible contingencies." Advances in Power Conversion and Energy Technologies (APCET), 2012 International Conference on. IEEE, 2012.
  7. Abido, M. A. "Optimal power flow using particle swarm optimization." International Journal of Electrical Power & Energy Systems 24.7 (2002): 563-571.
  8. Erol, Osman K., and Ibrahim Eksin. "A new optimization method: big bang–big crunch." Advances in Engineering Software 37.2 (2006): 106-111.
  9. Yang, Xin-She. "Multiobjective firefly algorithm for continuous optimization." Engineering with Computers 29.2 (2013): 175-184.
  10. Yang, Xin-She, and Suash Deb. "Cuckoo search via Lévy flights." Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on. IEEE, 2009.
  11. Pan, Wen-Tsao. "A new fruit fly optimization algorithm: taking the financial distress model as an example." Knowledge-Based Systems 26 (2012): 69-74.
  12. Abido, M. A. "Optimal power flow using tabu search algorithm." Electric Power Components and Systems 30.5 (2002): 469-483.
  13. Ghasemi, Mojtaba, et al. "An improved teaching–learning-based optimization algorithm using Lévy mutation strategy for non-smooth optimal power flow." International Journal of Electrical Power & Energy Systems 65 (2015): 375-384.
  14. Rao, CV Gopala Krishna, and G. Yesuratnam. "Big-Bang and Big-Crunch (BB-BC) and FireFly Optimization (FFO): Application and Comparison to Optimal Power flow with Continuous and Discrete Control Variables." International Journal on Electrical Engineering and Informatics 4.4 (2012): 575.
Index Terms

Computer Science
Information Sciences

Keywords

Optimal power flow security constraint optimal power flow bio inspired algorithm line flow limit.