Abstract
The Economic Load Dispatch problem (ELD) decides the minimum economic cost of production in a given power system, while keeping the environmental constraints and the load demand to an acceptable level without compromising on the generator ratings. Analysis on this application have been made using multi-modal Bacteria Foraging Optimization(BFO) algorithm, where the bacterial motion is incorporated as a search algorithm in finding the optimum values for economic generation. An improvisation on this algorithm is the co-operative bacteria foraging optimization using serial decomposition (CBFO-s) and CBFO-hybrid that combines BFO and CBFO-s. The search space decomposition and stochastic analysis ensures greater precision and accuracy in cost functions compared to conventional methods of Lagrange’s multipliers and Particle Swarm Optimization (PSO). This paper illustrates these points with the ELD problem as a reference.
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References
Parti, S.C., Kothari, D.P., Gupta, P.V.: Economic Thermal Power Dispatch. Institution for Engineers, (India) Journal 64, 123–132 (1983)
Yalanoz, T., Altun, H.: Environmentally constrained Economic Dispatch via. G.A. with arithmetic crossover. In: 6th Africon Conference in Africa, October 2-4, vol. 2, pp. 923–928 (2002)
Rahman, T.K.A., Yasim, Z.M.: Artificial Immune-Based Foraging for Solving Economic Dispatch in Power system. In: National Power and Energy Conference, vol. 1, pp. 31–35 (2004)
Da Silva, I.N., Nepomuceno, L.: An Efficient Neural Approach to Economic Load Dispatch in Power systems. In: Power Engineering Society Summer Meeting, vol. 2, pp. 1269–1274 (2001)
Kumaran, G., Mouly, V.S.R.K.: Using Evolutionary Computation to solve the Economic Load Dispatch Problem. In: Congress on Evolutionary Computation, vol. 1, pp. 296–301 (2001)
Praveena, P., Vaisakh, K.: A Bacterial Foraging PSO-DE Algorithm for Solving Dynamic Economic Load Dispatch Problem with Security Constraints. In: Joint International Conference on Power Electronics, Drives and Energy Systems (PEDES), pp. 1–7 (2010)
Supriyono, H., Tokhi, M.O.: Bacterial Foraging Algorithm with Adaptable Chemotactic step Size. In: Second International Conference on Computational Intelligence, Communication Systems and Networks, pp. 72–77 (2010)
Munoz, M.A., Halgamuge, S.K.: Simplifying the Bacteria Foraging Optimization Algorithm. In: IEEE Conference on Evolutionary Computation, pp. 1–7 (2010)
Panigrahi, B.K., Yadav, S.Y.: A clonal algorithm to solve Economic Load Dispatch. Electric Power Systems Research 77, 1381–1389 (2007)
Panigrahi, B.K., Ravikumar Pandi, V.: An Adaptive Particle Swarm Optimization Approach for Static and Dynamic Economic Load Dispatch. International Journal on Energy Conversion and Management 49, 1407–1415 (2008)
Raj, P.A.D.V.: Performance Evaluation of Swarm Intelligence based Power system Optimization Techniques, ch. 2 (November 29, 2010)
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Rathinam, A., Phukan, R. (2012). Solution to Economic Load Dispatch Problem Based on BFO,CBFO-S and CBFO-H Algorithms and Its Advantages over the PSO. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_37
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DOI: https://doi.org/10.1007/978-3-642-35380-2_37
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