Archive
2020, Volume 9
2019, Volume 8
2018, Volume 7
2017, Volume 6
2016, Volume 5
2015, Volume 4
2014, Volume 3
2013, Volume 2
2012, Volume 1




Volume 3, Issue 6-2, December 2014, Page: 15-20
Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit
Pragya Nema, Engg Department, LNCT, Indore, India
Shraddha Gajbhiye, Electrical Engg Department, SVITS, Indore, India
Received: Nov. 5, 2014;       Accepted: Nov. 10, 2014;       Published: Nov. 12, 2014
DOI: 10.11648/j.ijepe.s.2014030602.13      View  3732      Downloads  354
Abstract
Economic Dispatch(ED) is one of the main problem of power system operation and control which determines the optimal real power settings of generating units with an objective of minimizing the total fuel cost, subjected to limits on generator real power output & transmission losses. In all practical cases, the fuel cost of generator can be represented as a quadratic function of real power generation. This paper describe and Introduce a new nature Inspired Artificial Intelligence method called Firefly Algorithm(FA). The Firefly Algorithm is a stochastic Meta heuristic approach based on the idealized behavior of the flashing characteristics of fireflies. The aim is to minimize the generating unit’s combined fuel cost having quadratic cost characteristics subjected to limits on generator real power output & transmission losses. This paper presents an application of the FA to ED with valve point loading for different Test Case system. The obtained solution quality and computation efficiency is compared to another artificial intelligence technique, called Genetic algorithm (GA) . The simulation results show that the proposed algorithm outperforms previous artificial intelligence method.
Keywords
Economic Dispatch, Firefly Algorithm, Genetic Algorithm
To cite this article
Pragya Nema, Shraddha Gajbhiye, Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit, International Journal of Energy and Power Engineering. Special Issue: Distributed Energy Generation and Smart Grid. Vol. 3, No. 6-2, 2014, pp. 15-20. doi: 10.11648/j.ijepe.s.2014030602.13
Reference
[1]
Serena H. Chen, Anthony J. Jakeman, John P. Norton, Artificial Intelligence techniques: An introduction to their use for modelling environmental systems. Mathematics and Computers in Simulation 78 (2008) 379–400, Jan 2008
[2]
T. Baeck, D. B. Fogel and Z. Michalewicz, “Handbook of Evolutionary Computation”, Taylor & Francis, 1997.
[3]
X. S. Yang, “Nature-Inspired Metaheuristic Algorithms”, Luniver Press, 2008.
[4]
X. S. Yang, “Engineering Optimization: An Introduction with Metaheuristic Applications”, Wiley & Sons, New Jersey, 2010.
[5]
X. S. Yang, “Firefly algorithms for multimodal optimization”, Stochastic Algorithms:Foundations and Appplications (Eds O. Watanabe and T. eugmann), SAGA 2009, LectureNotes in Computer Science, 5792, Springer-Verlag, Berlin, pp. 169-178, 2009.
[6]
D. C. Walters and G. B. Sheble, “Genetic algorithm solution of economic dispatch with the valve-point loading”, IEEE Trans. on Power Systems, Vol. 8, No. 3, pp. 1325-1332, Aug. 1993
[7]
S. N. Singh, S. C. Srivastava “A Genetic Algorithm and its Applications in Power System Problems”. Proceedings of tenth National Power System Conference NPSC, 1998, vol 1 pp. 289-296.
[8]
S. Lukasik and S. Zak, “Firefly algorithm for continuous constrained optimization tasks,” in Proceedings of the International Conference on Computer and Computational Intelligence (ICCCI ’09), N.T. Nguyen, R. Kowalczyk, and S.-M. Chen, Eds., vol. 5796 of LNAI, pp. 97–106, Springer, Wroclaw,Poland, October 2009.
[9]
X. S. Yang, Nature-Inspired Meta-Heuristic Algorithms, Luniver Press, Beckington, UK, 2008.
[10]
S. Lukasik and S. Zak, “Firefly algorithm for con-tinuous constrained optimization tasks,” in Proceedings of the International Conference on Computer and Computational Intelligence (ICCCI ’09), N. T. Nguyen, R. Kowalczyk, and S.-M. Chen, Eds., vol. 5796 of LNAI, pp. 97–106, Springer, Wroclaw, Poland, October 2009.
[11]
X. S. Yang, “Firefly algorithm, stochastic test functions and design optimisation,” International Journal of Bio-Inspired Computation, vol. 2, no. 2, pp. 78–84, 2010.
[12]
X. S. Yang, “Firefly algorithm, Levy flights and global optimization,” in Research and Development in Intelligent Systems XXVI, pp. 209–218, Springer, London, UK, 2010.
[13]
Y. Liu and K. M. Passino, “Swarm Intelligence: A Survey”, International Conference of Swarm Intelligence, 2005.
[14]
P. H. Chen and H.C. Chang, Large-Scale Economic Dispatch by Genetic Algorithm, IEEE Transactions on Power Systems, Vol. 10, No.4, pp. 1919–1926, Nov. 1995.
[15]
Z. L. Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator constraints”, IEEE Trans. on Power Systems, Vol. 18, No. 3, pp. 1187-1195, Aug. 2003.
[16]
Pereira-Neto A, Unsihuay C, Saavedra OR. Efficient evolutionary strategy optimisation procedure to solve the nonconvex economic dispatch problem with generator constraints. IEEE Proc Gener Transm Distrib 2005;152(5):653–60.
[17]
Fan JY, Zhang L. Real-time economic dispatch with line flow and emission constraints using quadratic programming. IEEE Trans Power Syst 1998;13(2):320–5.
[18]
Jayabarathi T, Sadasivam G, Ramachandran V. Evolutionary programming based economic dispatch of generators with prohibited operating zones. Elect Power Syst Res 1999;52(3):261–6.
[19]
Pereira-Neto A, Unsihuay C, Saavedra OR. Efficient evolutionary strategy optimisation procedure to solve the nonconvex economic dispatch problem with generator constraints. IEEE Proc Gener Transm Distrib 2005;152(5):653–60.
[20]
Roa-Sepulveda CA, Pavez-Lazo BJ. A solution to the optimal power flow using simulated annealing. Electr Power Energy Syst 2003;25(1):47–57.
[21]
Da Silva IN, Nepomuceno L, Bastos TM. An efficient Hopfield network to solve economic dispatch problems with transmission system representation. Electr Power Energy Syst 2004;26(9):733–8.
[22]
Lin WM, Chen FS, Tsay MT. An improved tabu search for economic dispatch with multiple minima. IEEE Trans Power Syst 2002;17(1):108–12.
[23]
Khamsawang S, Boonseng C, Pothiya S. Solving the economic dispatch problem with tabu search algorithm. In: IEEE International Conference on Industrial Technology 2002, Bangkok, Thailand. p.274–8.
[24]
T. Apostolopoulos and A. Vlachos. Application of the Firefly Algorithm for solving the EELD problem:International Journal of Combianatorics 2011.
[25]
Hardiansyah. Solving Economic Dispatch Problem with Valve-Point Effect using a Modified ABC Algorithm: International Journal of Electrical and Computer Engineering 2013.
Browse journals by subject