Optimal Power Flow Solution using Efficient Sine Cosine Optimization Algorithm

Optimal Power Flow Solution using Efficient Sine Cosine Optimization Algorithm

Автор: Abdelmoumene Messaoudi, Mohamed Belkacemi

Журнал: International Journal of Intelligent Systems and Applications @ijisa

Статья в выпуске: 2 vol.12, 2020 года.

Бесплатный доступ

The problem encountered in most metaheuristic methods is the choice of the good control parameters of the algorithm. That is the objective of this work by using an efficient sine cosine algorithm (ESCA) in optimal power flow problem. The sine-cosine algorithm (SCA) is a modern method applied in numerical optimization problems. It consists of search randomly the best vector of control variables from the initial group of elements and oscillates to converge to the global optimum or diverge from it, functioning with a simple formulation based on sine and cosine mathematical functions with few setting parameters. In the proposed efficient sine cosine Algorithm (ESCA) the best values of setting parameters are chosen to give the best optimum solution with fast convergence. This technique improves the quality of the solution by exploring more search domain than the SCA method. The modified algorithm has been applied to the classical IEEE 30-Bus network with various objective functions and constraints. To make the comparison of ESCA and different recent algorithms, present results show the importance of ESCA to give the best and effective solution to the multi-objective optimal power flow problem.

Еще

Optimal power flow (OPF), load flow (LF), sine cosine Algorithm (SCA), efficient SCA (ESCA), fuel cost, real power losses

Короткий адрес: https://sciup.org/15017493

IDR: 15017493   |   DOI: 10.5815/ijisa.2020.02.04

Список литературы Optimal Power Flow Solution using Efficient Sine Cosine Optimization Algorithm

  • O. Alsac, B. Stott,” Optimal load flow with steady state security”, IEEE Transactions on Power Apparatus and Systems, vol 93 n° 3 pp. 745–751, May 1974.
  • Lee K, Park Y, Ortiz J.” A united approach to optimal real and reactive power dispatch” IEEE Transactions on Power Apparatus and Systems, vol. 104 n°5 pp.1147-1153 , May 1985.
  • F. Capitanescu,M.Glavic, D.Ernst,L.Wehenkel,"Interior point based algorithms for the solution of optimal power flow problems", Electric Power Systems Research vol. 77 pp. 508-51, April 2007.
  • L.L.Lai,J.T.Ma, R. Yokoma, M. Zhao, ”Improved genetic algorithms for optimal power flow under both normal and contingent operation states”, Electrical Power & Energy System, Vol. 19, No. 5, pp. 287-292, June 1997
  • A.G.Bakirtzis,P.N.Biskas, “Optimal power flow by enhanced genetic algorithm”, IEEE transactions on power systems”,vol.17,n°2, pp.229-236, May 2002.
  • A. Bakirtzis, V. Petridis, and S.kazarlis,”Genetic Algorithm solution to the economic dispatch problem”, Proc.Inst.Elect.Eng., Vol. 141, pp. 377-382, July 1994.
  • Sailaja Kumari M, Maheswarapu S. “Enhanced genetic algorithm based computation technique for multi-objective optimal power flow”, Int J Electr Power Energy Syst; vol. 32(6):7 pp. 36–42, July 2010.
  • Abdel-Fattah Attia , Yusuf A. Al-Turki and Abdullah M. Abusorrah” Optimal power flow using adapted genetic algorithm with adjusting population size” Elect. Power Compon. Syst., Vol. 40, No. 11, pp. 1285–1299, August 2012.
  • Yuryevich J, Wong KP,” Evolutionary programming based optimal power flow algorithm”, IEEE transactions on power systems, Vol.14, No.4, ,pp. 1245-1250, Nov.1999.
  • W. Ongsakul, T. Tantimaporn,” Optimal power flow by improved evolutionary programming”, Elect. Power Compon. Syst., Vol. 34, No.1, pp. 79-95, Feb. 2006.
  • M.A. Abido. ,”Optimal power flow using particle swarm optimization”, Int J Electr Power Energy Syst.,24 pp.563-571, October 2002.
  • Kim JY, Mun KJ, Kim HS, Park JH. “Optimal power system operation using parallel processing system and PSO algorithm”, Int J Electr Power Energy Syst; vol.33(8):14 pp.57–61, October 2011.
  • A.A. Abou El Ela, M.A. Abido, S.R. Spea, ”optimal power flow using differential evolution algorithm”,Electric Power Systems Research, vol.80 pp.878–885, July 2010.
  • T. Niknam, M. r. Narimani, M. Jabbari, A.R. Malekpour, “A modified shuffle frog leaping algorithm for multi-objective optimal power flow”, Energy, vol.36(11) pp.6420–6432, November 2011.
  • Duman S, Güvenç U, Sönmez Y, Yörükeren N. “Optimal power flow using gravitational search algorithm”, Energy Convers Manage, vol.59, pp.86–95, July 2012.
  • Bhattacharya A, Roy PK. “Solution of multi-objective optimal power flow using gravitational search algorithm”, IET Gener Transm Distrib; vol. 6(8) pp.751–763, August, 2012.
  • Bhattacharya, A.; Chattopadhyay, P.K. “Application of biogeography-based optimization to solve different optimal power flow problems”, IET Gener. Trans. Distrib., vol.5, pp.70–80, Jan. 2011.
  • Sivasubramani S, Swarup KS. “Multi-objective harmony search algorithm for optimal power flow problem”, Int J. Electr Power Energy Syst, vol.33(3), pp.745–752, March 2011.
  • N. Sinsuphan, U. Leeton, T. Kulworawanichpong, “Optimal power flow solution using improved harmony search method”, Appl. Soft Comput; vol.13(5), pp. 2364–2374, M ay2013.
  • Arul R, Ravi G, Velusami S. “Solving optimal power flow problems using chaotic self adaptive differential harmony search algorithm”. Electr Power Compon Syst; vol.41(8), pp.782–805, April 2013.
  • M.R. Adaryani, A. Karami, “Artificial bee colony algorithm for solving multi-objective optimal power flow problem”, Int. J. Electr. Power Energy Syst. vol.53 pp.219–230, December 2013.
  • H.R. E. Bouchekara& M. A. Abido,” Optimal power flow using differential search algorithm”, Electric Power Components and Systems, vol.42, pp.1683–1699, October 2014.
  • K. Abaci , V. Yamacli, “ Differential search algorithm for solving multi-objective optimal power flow problem”, Int J. Electrical Power and Energy Systems, vol.79,pp.1-10, July 2016.
  • H.R.E.H. Bouchekara, M.A. Abido, M. Boucherma, “Optimal power flow using teaching-learning-based optimization technique”, Electr. Power Syst. Res. vol. 114 pp.49–59, September 2014.
  • P.K. Roy, C. Paul, “Optimal power flow using krill herd algorithm”, Int. Trans. Electr. Energy Syst., vol.25(8) pp.1397–1419, August 2015.
  • H.R. El-Hana Bouchekara, M.A. Abido, A.E. Chaib, “Optimal power flow using an improved electromagnetism-like mechanism method”, Electr. Power Compon. Syst. vol. 44 pp. 434-449, 2016.
  • H.R.E.H. Bouchekara, A.E. Chaib, M.A. Abido, R.A. El-Sehiemy, “Optimal power flow using an improved colliding bodies optimization algorithm”, Appl. Soft Comput. vol.42, pp.119–131, May 2016.
  • Bouchekara HR. “Optimal power flow using black-hole-based optimization approach”,Appl Soft Comput; vol.24, pp.879–888,2014.
  • M. Younes, F. Khodja, R. L.Kherfane,” Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration”, Energy vol.67, pp.595-606, April 2014.
  • Attia A. El-Fergany & Hany M. Hasanien;” Single and multi-objective optimal power flow using grey wolf optimizer and differential evolution algorithms,” Electric Power Components and Systems, vol.43(13),pp.1548–1559, July 2015.
  • W. Warid, H. Hizam, N. Mariun and N. I. Abdul-Wahab,”Optimal power flow using the jaya algorithm”, Energies, vol.9, pp.678-696, August 2016.
  • A. A. Mohamed, , Y. S. Mohamed, A. A.M. El-Gaafary.,A. M. Hemeida “Optimal power flow using moth swarm algorithm”, Electric Power Systems Research vol.142,pp. 190–206, January 2017.
  • C .Shilaja, K . Ravi, “Multi-objective optimal power flow problem using enhanced flower pollination algorithm”; Gazi University Journal of Science, vol.30(1),pp.79-91, January 2017.
  • A. Bhattacharya & P. K. Chattopadhyay,” Solution of economic power dispatch problems using oppositional biogeography-based optimization”, Electric Power Components and Systems, vol.38, pp. 1139–1160, July 2010.
  • P.K. Roy, D. Mandal, “Quasi-oppositional biogeography-based optimization for multi-objective optimal power flow”. Electr Power Compon Syst, vol.40, pp. 236–256, December 2011.
  • W. Warid, H. Hizam, N. Mariun, N. I. Abdul Wahab,”, A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution”, Applied Soft Computing , vol. 65, pp. 360–373, April 2018.
  • J. Radosavljevic, D. Klimenta, M. Jevtic, N. Arsic, “Optimal power flow using a hybrid optimization algorithm of particle swarm optimization and gravitational search algorithm”, Electr. Power Compon. Syst. vol.43 (17),pp. 1958-1970, August 2015.
  • S. S. Reddy” Optimal power flow using hybrid differential evolution and harmony search algorithm”,International Journal of Machine Learning and Cybernetics. vol.10, pp 1077–1091, May 2019.
  • P. P. Biswas, P.N. Suganthan , R. Mallipeddi , G. A.J. Amaratunga,” Optimal power flow solutions using differential evolution algorithm integrated with effective constraint handling techniques” Engineering Applications of Artificial Intelligence, vol.68 pp. 81–100, February 2018.
  • Seyed ali Mirjalili, “SCA: A sine cosine Algorithm for solving optimization problems”; Knowledge-Based Systems , Vol. 96 , pp.120-133, March 2016.
  • Abdel-Fattah Attia, R. A. El Sehiemy, H. M. Hasanien,” Optimal power flow solution in power systems using a novel Sine-Cosine algorithm”, Electrical Power and Energy Systems vol. 99 pp.331–343, July 2018.
Еще
Статья научная
QR-код для установки приложения SciUp Наведите камеру и скачайте бесплатное приложение SciUp