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Tytuł artykułu

Hybrid of lamda and bee colony optimization for solving economic dispatch

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Optymalizacja ekonomii rozsyłu enegii z wykorzystaniem metod rojowych i metody lamda.
Języki publikacji
EN
Abstrakty
EN
This paper proposes the method to solve the economic dispatch problem with hybrid of lamda and bee colony optimization (HLBCO). The fundamental constraints of economic dispatch problem are the load demand and power loss into consideration. The generation cost function considering smooth cost function characteristic. To verify the performance of the proposed HLBCO algorithm, it is operated by the simulation on the MATLAB program and tested the two case studies. The simulation results indicate that the HLBCO can provide a better solution than the others in terms of quality solution, computational and convergence efficiently.
PL
W artykule zapropponowano metode optymalizacji rozsyłu energii prze wykorzystanie hybrydy dwóch metod: lamda i algorytmów rojowych HLBCO. Symulacja przeprowadzona nakilku przykładach dowodzi że zaproponowany algorytm lepiej rozwiązuje prtoblemy ekonomicznego rozsyłu biorąc pod uwagę jakość I skuteczność.
Rocznik
Strony
220--223
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
autor
  • Faculty of Engineering, Rajamangala University of Technology Lanna, Lampang, Thailand
autor
  • Faculty of Engineering, Rajamangala University of Technology Lanna, Lampang, Thailand
Bibliografia
  • [1] A. J. Wood, B. F. Wollenberg, “Power Generation, Operation, and Control,” 2nd edition, Wiley, New York, 1996.
  • [2] K. P. Wong and C. C. Fung, “Simulated annealing based economic dispatch algorithm,” IEE Proceeding., vol. 140, No.6 Nov. 1993 .pp. 50951 -5.
  • [3] K. K. Vishwakarma, H. M. Dubey, M. Pandit and B.K. Panigrahi, “Simulated annealing approach for solving economic load dispatch problems with valve point loading effects,” International Journal of Engineering, Science and Technology, Vol. 4, No. 4, 2012, pp. 60-72.
  • [4] J. C. Lee, W. M. Lin, G. C. Liao and T. P. Tsao, “Quantum genetic algorithm for dynamic economic dispatch with valvepoint effects and including wind power system,” Electrical Power and Energy Systems 33 (2011), pp. 189–197.
  • [5] N. Javidtash, A. Davodi, M. Hakimzadeh and A. Roozb, “Genetic Algorithm for Solving Non-Convex Economic Dispatch Problem,” International Journal of Mathematical, Computational, Statistical, Natural and Physical Engineering Vol:8, No:5, 2014, pp.866-869.
  • [6] W. M. Lin, F. S. Cheng, and M. T. Tsay, "An improved tabu search for economic dispatch with multiple minima," IEEE Trans. Power System, vol. 17, Feb. 2002. pp. 112-108.
  • [7] S. Pothiya, I. Ngamroo and W. Kongprawechnon, “Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints,” Energy Conversion and Management 49, 2008. pp.506–516.
  • [8] C. C. Kuo, “A Novel Coding Scheme for Practical Economic Dispatch by Modified Particle Swarm Approach,” IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 23, NO. 4, NOVEMBER 2008, pp. 1825-1835.
  • [9] A. Jaini, I. Musirin, N. Aminudin, M. M. Othman and T. K. A Rahman, “Particle Swarm Optimization (PSO) Technique in Economic Power Dispatch Problems,” in Proceeding of PEOCO2010, 23-24 June 2010, pp. 308-312.
  • [10] J. Sharma and A. Mahor, “ Particle Swarm Optimization Approach For Economic Load Dispatch: A Review,” International Journal of Engineering Research and Applications, Vol. 3, Issue 1, January-February 2013, pp.013- 022.
  • [11] R. Rahmani, M. F. Othman, R. A. Yusof and M. Khalid, “Solving Economic Dispatch Problem Using Particle Swarm Optimization by an Evolutionary Technique for Initializing Particles,” Journal of Theoretical and Applied Information Technology, Vol, 46, No.2, pp. 526-536.
  • [12] R Gopalakrishnan and A. Krishnan, “An efficient technique to solve combined economic and emission dispatch problem using modified Ant colony optimization,” Sadhana, Vol. 38, Issue 4, August 2013, pp. 545–556.
  • [13] P. J. Vasovala, C. Y. Jani, Ghanchi. H. Ghanchi and P. H. K. Bhavsar, “Application of Ant colony Optimization technique in Economic Load Dispatch Problem for IEEE-14 Bus System,” International Journal for Scientific Research & Development| Vol. 2, Issue 02, 2014, pp. 990-994.
  • [14] F. Khodja, M. Younes, M laouer, R. L. Kherfane and N. Kherfane, “A New Approach ACO for Solving the Compromise Economic and Emission with the Wind Energy,” Energy Procedia 50 (2014), 2014, pp.893-906.
  • [15] R. Effatnejad, H. Aliyari, H. Tadayyoni and A. Abdollahshirazi, “ Noval Optimization Based on the Ant Colony for Economic Dispatch,” International Journal on Technical and Physical Problems of Engineering, Vol. 5, Issue 15, pp. 75-80.
  • [16] N. A. Rahmat and I. Musirin, “ Differential Evolution Immunized Ant Colony Optimization Technique in Solving Economic Load Dispatch Problem,” Engineering, Vol.5, No. 1B, 2013 pp. 157 162.
  • [17] S. K. Nayak, K.R. Krishnanand, B.K.Panigrahi and P.K.Rout, “Application of Artificial Bee Colony to Economic Load Dispatch Problem with Ramp Rate Limits and Prohibited Operating Zones,” in Proceeding of World Congress on Nature & Biologically Inspired Computing, 9-11 Dec. 2009, pp. 1237 – 1242.
  • [18] A. Gupta and K. T. Chaturvedi, “Artificial Bee Colony Optimization For Economic Load Dispatch,” International Journal of Advance Computer, Electronics, Electrical, Mechanical and Civil Engineering Research & Technology, Vol. - 01, No. -01, August, 2013, pp. 28-32.
  • [19] G. R. Ankasala, “Artificial Bee Colony Optimisation for Economc Load Dispatch of a Modern Power system,” International Journal of Scientific & Engineering Research, Volume 3, Issue 1, January-2012, pp.1-6.
  • [20] C. Koodalsamy and S. P. Simon,” Fuzzi_ed arti_cial bee colony algorithm for nonsmooth and nonconvex multiobjective economic dispatch problem,” Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 21, Issue 1, 2013, pp. 1995-2014.
  • [21] C. Chokpanyasuwant, S. Anantasate, S. Pothiya,We Pattaraprakom, and P. Bhasaputra, “Honey Bee Colony Optimization to solve Economic Dispatch Problem with Generator Constraints,” in Proceeding of ECTI-CON 2009, 6-9 May 2009, pp. 200 – 203.
  • [22] M. Younes and M. Maamar,” Improvement of the ACO metaheuristic by using the method Artificial Bees Colony (ABC),” PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review) R. 88 NR 5b/2012, pp. 174-178.
  • [23] F. S. Abu-Mouti and M. E. El-Hawary, “Optimal Dynamic Economic Dispatch Including Renewable Energy Source using Artificial Bee Colony Algorithm,” in Proceeding of Systems Conference (SysCon), 19-22 March 2012, pp. 1-6.
  • [24] Hardiansyah, “Solving Economic Dispatch Problem with Valve- Point Effect using a Modified ABC Algorithm,” International Journal of Electrical and Computer Engineering, Vol. 3, No. 3, June 2013, pp. 377-385.
  • [25] D. Karaboga, B. Gorkemli, C. Ozturk and N. Karaboga, “A comprehensive survey: artificial bee colony (ABC) algorithm and applications,” Artificial Intelligence Review, Volume 42, Issue 1, 2014, pp. 21-57.
  • [26] C.Kumar and T.Alwarsamy, “Solution of Economic Dispatch Problem using Differential Evolution Algorithm,” International Journal of Soft Computing and Engineering, Volume-1, Issue- 6, January 2012, pp. 236-241.ograph – Directions for use, Welch Allyn Ltd Navan, Republic of Ireland, CD ref 102731, DIR 80015344, ver. C
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-32a2fa2a-eccb-4860-a2d7-1a79a9019c2d
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