Abstract
This article offers an enriched biogeography-based optimization (EBBO) technique to crack the economic power dispatch (EPD) problem of coal-fired generating units. The considered EPD involves the complex limitations including valve point loading effects, transmission line losses, and ramp rate limits. The geographical smattering of biological species is the vital scope of this algorithm. The proposed EBBO describes the arousal, enhanced migration of species from one environment to another. The algorithm has two main steps specifically, migration and mutation. These steps are involved in searching the global optimum solution. The EBBO’s efficiency has been verified on 13 and 40 generating test systems. The proposed technique produces superior results when compared with the conventional biogeography-based optimization (BBO) and other prevailing techniques. Also, it gives the quality and promising results for solving the EPD problems. Further, it can be applied for practical power system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
El-Keib, A., Ma, H., Hart, J.L.: Environmentally constrained economic dispatch using the Lagrangian relaxation method. IEEE Trans. Power Syst. 9(4), 1723–1729 (1994)
Sinha, N., Chakrabarti, R., Chattopadhyay, P.K.: Evolutionary programming techniques for economic load dispatch. IEEE Trans. Evolut Comput. 7(1), 83–94 (2003)
Liang, Z.X., Glover, J.D.: A zoom feature for a dynamic programming solution to economic dispatch including transmission losses. IEEE Trans. Power Syst. 7(5), 544–549 (1992)
Chowdhury, B.H., Rahman, S.: A review of recent advances in economic dispatch. IEEE Trans. Power Syst. 5(4), 1248–1259 (1990)
Wang, J., Huang, W., Ma, G., Chen, S.: An improved partheno genetic algorithm for multi-objective economic dispatch in cascaded hydropower systems. Int. J Electr. Power. 67, 591–597 (2015)
Basu, M.: Modified particle swarm optimization for nonconvex economic dispatch problems. Int. J. Electr. Power. 69, 304–312 (2015)
Rahman, T.K.A., Suliman, S.I., Musirin, I.: Artificial immune-based optimization technique for solving economic dispatch in power system. Neural Nets. 3931, 338–345 (2006)
Jayabarathi, T., Sadasivam, G., Ramachandran, V.: Evolutionary programming based economic dispatch of generators with prohibited operating zones. Elect. Power Syst. Res. 52, 261–266 (1999)
Yegireddy, N.K., Panda, S., Kumar Rout, U., Bonthu, R.K.: Selection of control parameters of differential evolution algorithm for economic load dispatch problem. Comput. Intell. Data Min. 3, 251–260 (2015)
Secui, C.D.: A method based on the ant colony optimization algorithm for dynamic economic dispatch with valve-point effects. Int Trans. Electr. Energy 25(2), 262–287 (2015)
Vijay, R.: Intelligent bacterial foraging optimization technique to economic load dispatch problem. Int. J. Soft Comput. Eng. 2, 55–59 (2012)
Simon, D.: Biogeography-based optimization. IEEE Trans. Evolut. Comput. 12(6), 702–713 (2008)
Roy, P.K., Ghoshal, S.P., Thakur, S.S.: Biogeography-based optimization for economic load dispatch problems. Electr. Power Compon. Syst. 38(2), 166–181 (2009)
Wang, G.G., Gandomi, A.H., Alavi, A.H.: An effective krill herd algorithm with migration operator in biogeography-based optimization. Appl. Math. Model. 38(9), 2454–2462 (2014)
Ma, H.: An analysis of the equilibrium of migration models for biogeography-based optimization. Inf. Sci. 180(18), 3444–3464 (2010)
Bhattacharya, A., Chattopadhyay, P.K.: Biogeography-based optimization for different economic load dispatch problems. IEEE Trans. Power Syst. 25(2), 1064–1077 (2010)
Dakuo, H., Fuli, W., Zhizhong, M.: A hybrid genetic algorithm approach based on differential evolution for economic dispatch with valve-point effect. Electr. Power Energy Syst. 30, 31–38 (2008)
He, D.K., Wang, F.L., Mao, Z.Z.: Hybrid particle swarm optimization algorithm for non-linear, genetic algorithm for economic dispatch with valve-point effect. Elect. Power Syst. Res. 78, 626–633 (2008)
Chaturvedi, K.T., Pandit, M., Srivastava, L.: Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch. IEEE Trans. Power Syst. 23(3), 1079 (2008)
Coelho, L.D.S., Mariani, V.C.: Particle swarm approach based on quantum mechanics and harmonic oscillator potential well for economic load dispatch with valve-point effects. Energ. Convers Manag. 49, 3080–3085 (2008)
Alsumait, J.S., Al-Othman, A.K., Sykulski, J.K.: Application of pattern search method to power system valve-point economic load dispatch. Electr. Power Energy Syst. 29, 720–730 (2007)
Aruldoss Albert Victoire, T., Ebenezer Jeyakumar, A.: Hybrid PSO-SQP for economic dispatch with valve-point effect. Electr. Power Syst. Res. 71(1), 51–59 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Vijay Raviprabhakaran, Ravichandran, C.S. (2016). Enriched Biogeography-Based Optimization Algorithm to Solve Economic Power Dispatch Problem. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 437. Springer, Singapore. https://doi.org/10.1007/978-981-10-0451-3_78
Download citation
DOI: https://doi.org/10.1007/978-981-10-0451-3_78
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0450-6
Online ISBN: 978-981-10-0451-3
eBook Packages: EngineeringEngineering (R0)