Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30178
Optimal Economic Load Dispatch Using Genetic Algorithms

Authors: Vijay Kumar, Jagdev Singh, Yaduvir Singh, Sanjay Sood

Abstract:

In a practical power system, the power plants are not located at the same distance from the center of loads and their fuel costs are different. Also, under normal operating conditions, the generation capacity is more than the total load demand and losses. Thus, there are many options for scheduling generation. In an interconnected power system, the objective is to find the real and reactive power scheduling of each power plant in such a way as to minimize the operating cost. This means that the generator’s real and reactive powers are allowed to vary within certain limits so as to meet a particular load demand with minimum fuel cost. This is called optimal power flow problem. In this paper, Economic Load Dispatch (ELD) of real power generation is considered. Economic Load Dispatch (ELD) is the scheduling of generators to minimize total operating cost of generator units subjected to equality constraint of power balance within the minimum and maximum operating limits of the generating units. In this paper, genetic algorithms are considered. ELD solutions are found by solving the conventional load flow equations while at the same time minimizing the fuel costs.

Keywords: ELD, Equality constraints, Genetic algorithms, Strings.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107031

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3114

References:


[1] Holand, J. H, “Adaptation in natural and Artificial Systems.” The University of Michigan press, Ann Arbor, USA, 1975, ch.5.
[2] C. L. Chiang, “Genetic-based algorithm for power economic load dispatch,” IET Generation, Transmission and Distribution, vol. 1, no. 2, 2007, pp. 261–269
[3] Hesham, Alfares & Mohammad Nazeeruddin, “Electric load forecasting: literature survey and classification of Methods,” International Journal of Systems Science, volume 33,2002, pp 23-34
[4] K. Senthil & K. Manikandan “Improved Tabu Search Algorithm to Economic Emission Dispatch with Transmission Line Constraint”, International Journal of Computer Science & Communication, Vol. 1, July 2010, pp. 145-149
[5] D. M. Himmelblau, “Applied Non Linear Programming” McGraw– Hill, New York, 1972, ch.6-7.
[6] D. E. Goldber, “Genetic Algorithm in Search, Optimization and Machine Learning”, Addison Wesley Publishing Company, Ind. USA, 1989.
[7] H. Altun and T. Yalcinoz, “Implementing soft computing techniques to solve economic dispatch problem in power systems,” Expert Systems with Applications, vol. 35, no. 4, 2008, pp. 1668–1678
[8] Belkacem Mahdad, Tarek Bouktir and Kamel Srairi, “Optimal power Flow of the Algerian Network using Genetic Algorithm/Fuzzy Rules,” Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, IEEE July 2008, pp. 1-8, 20-24
[9] L. d. S. Coelho, V. C. Mariani,“Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units”, International Journal of Chaos, Solitons and Fractals (Elsevier), Aug. 2009, pp 2376–2383.
[10] M. Rahli, “Applied Linear and Nonlinear Programming to Economic Dispatch”, Ph.D. Thesis, Electrical Institute, USTO, Oran, Algeria, 1996.
[11] L. D. S. Coelho, C. S. Lee, “Solving economic load dispatch problems in power systems using chaotic and Gaussian particle swarm optimization approaches, “Electrical Power and Energy Systems (Elsevier), 2008, pp.297-307.
[12] A. Lakshmi Devi and O. Vamsi Krishna, “Combined Economic & Emission Dispatch Using Evolutionary Algorithms-A Case Study”, ARPN Journal of Engineering and Applied Sciences, Vol.3, Dec. 2008,pp.28-35
[13] J. S. A. Sumait, A. K. A. Othman, J. K. Sykulski,“Application of pattern search method to power system valve-point economic load dispatch, Electrical Power and Energy Systems (Elsevier),Vol.29,2007,pp.720– 730.
[14] M. Kondalu, G. S. Reddy, J. Amarnath, “A Modified Particle Swarm Optimization To Solve The Economic Dispatch Problem of Thermal Generators of a Power System” International Journal of Engineering Science and Technology, Vol. 2, 2010, pp.6140-6148.
[15] J. S. Alsumait, J. K. Sykulski, and A. K. Al-Othman, “A hybrid GA-PSSQP method to solve power system valve-point economic dispatch problems,” Applied Energy, vol. 87, no. 5, 2010, pp. 1773–1781.
[16] R. Ouiddir, M. Rahli & L. A. Koridak, “Economic Dispatch using a Genetic Algorithm: Application to Western Algeria’s Electrical Power Network,” Journal of Information Science& Engineering, 2005, pp 659- 668.
[17] I. G. Damousis, A. G. Bakirtzis, and P. S. Dokopoulos, “Networkconstrained economic dispatch using real-coded genetic algorithm,” IEEE Trans. on Power Systems, Vol. 18, Feb. 2003, pp. 198-205.
[18] J. Tippayachai, W. Ongsakul, and I. Ngamroo, “Parallel micro genetic algorithm for constrained economic dispatch,” IEEE Trans. on Power Systems, vol. 17,Aug.2002, pp. 790-797.
[19] M. S. Osman, Mahmoud A. A. Sinna, A. A. Mousa, “A combined genetic algorithm-fuzzy logic controller (GA–FLC) in nonlinear programming”, International Journal of Applied Mathematics and Computation, Vol.170, 2005, pp.821–840.
[20] A. Soundarrajan, Dr. S. Sumathi, C. Sundar, “Particle Swarm Optimization Based LFC and AVR of Autonomous Power Generating System” International Journal of Computer Science, 2009, pp.148-156.
[21] S. C. Swain, S. Panda, A. K. Mohanty, C. Ardil, “Application of Computational Intelligence Techniques for Economic Load Dispatch” World Academy of Science, Engineering and Technology, 2010, pp 63- 69.
[22] A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas, and V. Petridis, “Optimal power flow by enhanced genetic algorithm”, IEEE Trans. on Power Syst., vol. 17, May 2002, pp. 229-236.
[23] J. Nanda, L. Hari, and M. L. Kothari, “Economic emission load dispatch with line flow constraints using a classical technique,” IET Generation, Transmission and Distribution, vol. 141, no. 1, 1994, pp. 1–10.
[24] Y. C. Chang, J. K. Lin, M. H. Chuang, “Optimal chiller loading by genetic algorithm for reducing energy consumption”, Energy and Buildings (Elsevier), Vo.37, 2005, pp.147-155.
[25] Samir Sayah, Khaled Zehar, “Using Evolutionary Computation to Solve the Economic Load Dispatch Problem”, Leonardo Journal of Sciences, Vol. 12, January 2008, pp. 67-78.
[26] Y. S. Brar, J. S. Dhillon and D. P. Kothari, “Interactive fuzzy satisfying multiobjective generation scheduling”, Asian Journal of Information Technology, Vol. 3, no. 11, 2004, pp. 973-982.
[27] C. C. Hsu, C. Y. Chen, “Regional load forecasting in Taiwan: applications of artificial neural networks,” Energy Conversion and Management (Elsevier), Vol.44, 2003, pp.1941–1949.
[28] Y. Labbi, D. B. Attous, “A Hybrid GA–PS Method to Solve the Economic Load Dispatch Problem”, Journal of Theoretical and Applied Information Technology, 2005 pp.61-68.
[29] Mimoun Younes Mostafa Rahli, “Economic Power Dispatch Using The Combinational of Two Genetic Algorithms”, Journal of Electrical & Electronics Engineering,” Vol.6, 2006, pp 175-181.
[30] B. Milosevic and M. Begovic, “Nondominated sorting genetic algorithm for optimal phasor measurement placement,” IEEE Trans. on Power Syst., Vol. 18, Feb. 2003, pp. 69-75.
[31] M. Younes, M. Rahli and A. Koridak.”Dispatching Economic par Intelligence Artificially”, Proceeding ICEL’2005, U.S.T. Oran, Algeria, Vol.02, 13-15 November 2005, pp.16-21.
[32] J. B. Park, Y. W. Jeong, H. H. Kim and J. R. Shin, “An Improved Particle Swarm Optimization for Economic Dispatch with Valve-Point Effect”, International Journal of Innovations in Energy Systems and Power, Vol. 1,Nov.2006, pp.1-7.
[33] Y.-G. Wu, C.-Y. Ho, and D.-Y. Wang, “A diploid genetic approach to short-term scheduling of hydro-thermal system,” IEEE Trans. on Power Systems, vol. 14, 2002, pp. 1268-1274.
[34] M. Sudhakaran, P. Ajay, D. V. Raj, “Integrating genetic algorithms and tabu search for unit commitment problem”, International Journal of Engineering, Science and Technology, Vol. 2, 2010, pp. 57-69.
[35] S. M. V. Pandian and K. Thanushkodi, “Solving Economic Load Dispatch Problem Considering Transmission Losses by a Hybrid EPEPSO Algorithm for Solving both Smooth and Non-Smooth Cost Function”, International Journal of Computer and Electrical Engineering, Vol. 2, June 2010, pp.1793-8163.
[36] X. Xia, A. M. Elaiw, “Optimal dynamic economic dispatch of generation: A review”, Electric Power Systems Research, (Elsevier), 2010, pp.975–986.
[37] Z. X. Liang and J. D. Glover, “A zoom feature for a dynamic programming solution to economic dispatch including transmission losses,” IEEE Transactions on Power Systems, vol. 7, no. 2, 1992, pp. 544–550.
[38] J. Nanda, L. Hari, and M. L. Kothari, “Economic emission load dispatch with line flow constraints using a classical technique,” IET Generation, Transmission and Distribution, vol. 141, no. 1, 1994, pp. 1–10.
[39] P. G. Lowery, “Generating unit commitment by dynamic programming,” IEEE Transactions on Power Apparatus and Systems, vol. 85, no. 5, 1996, pp. 422–426.
[40] K. S. Swarup and S. Yamashiro, “Unit commitment solution methodology using genetic algorithm,” IEEE Transactions on Power Systems, vol. 17, no. 1, 2002, pp. 87–91.
[41] J. S. Al-Sumait, A. K. AL-Othman, and J. K. Sykulski, “Application of pattern search method to power system valve-point economic load dispatch,” International Journal of Electrical Power and Energy Systems, vol. 29, no. 10, 2007, pp. 720–730
[42] Dr. Chanan Singh, J O Kim, “Optimal Service Restoration and Reconfiguration of Network Using Genetic-Tabu Algorithm”, Electric Power Systems Research, Vol. 71, 2004, pp 145-162.
[43] Gaganpreet Chawla, Mohinder S. Sachdev and G. Ramakrishna, “Artificial Neural Network Applications for Power System Protection”, Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering, Saskatoon, Canada, 2005, pp. 1954-1957.
[44] Kuljit Kaur, Hardeep Singh, “A Metrics Based Approach to Evaluate Design of Software Components”, Proceedings of 3rd IEEE International Conference on Global Software Engineering, Bangalore, India, 2008 pp. 269-272.
[45] C. L. Chiang, “Genetic-based algorithm for power economic load dispatch,” IET Generation, Transmission and Distribution, vol. 1, no. 2, 2007, pp. 261–269.
[46] Z. L. Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator constraints,” IEEE Transactions on Power Systems, vol. 18, no. 3, 2003, pp. 1187–1195.
[47] J. B. Park, K. S. Lee, J. R. Shin, and K. Y. Lee, “A particle swarm optimization for economic dispatch with nonsmooth cost functions,” IEEE Transactions on Power Systems, vol. 20, no. 1, 2005, pp. 34–42.
[48] Zayegh, A. and Kalam, A “Modelling and Simulation: Keys to Technological Advances”, Victoria University of Technology, Vol 2, ISBN 1 86272 4229 and 186272 4237, 1993.
[49] J. Cai, X. Ma, L. Li, and P. Haipeng, “Chaotic particle swarm soptimization for economic dispatch considering the generator constraints,” Energy Conversion and Management, vol. 48, no. 2, 2007, pp. 645–653.
[50] A. I. Selvakumar and K. Thanushkodi, “A new particle swarm optimization solution to nonconvex economic dispatch problems,” IEEE Transactions on Power Systems, vol. 22, no. 1, 2007, pp. 42–51.
[51] D. Liu and Y. Cai, “Taguchi method for solving the economic dispatch problem with nonsmooth cost functions,” IET Generation, Transmission and Distribution, vol. 1, no. 5, 2007, pp. 793–803.
[52] H. Altun and T. Yalcinoz, “Implementing soft computing techniques to solve economic dispatch problem in power systems,” Expert Systems with Applications, vol. 35, no. 4, 2008, pp. 1668–1678.
[53] K. T. Chaturvedi, M. Pandit, and L. Srivastava, “Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch,” IEEE Transactions on Power Systems, vol. 23, no. 3, 2008, pp. 1079–1087.
[54] A. Bhattacharya and P. K. Chattopadhyay, “Solving complex economic load dispatch problems using biogeography-based optimization,” Expert Systems with Applications, vol. 37, no. 5, 2010, pp. 3605–3615.