Abstract
This article presents an application of the Particle Swarm Optimization (PSO) on the optimization of the power flow in an IEEE system with 14 nodes, which has some nodes with distributed generation. In first place, the mathematical model used for the optimization of the electricity generation costs is defined. Afterwards, this model is applied in a study case with the IEEE system with 14 nodes and distributed generation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Carpentier, J.: Contribution a l’étude du dispatching économique. Bulletin de la Société Française des Electriciens 3, 431–447 (1962)
Frank, S., Rebennack, S.: A Primer on Optimal Power Flow: Theory, Formulation, and Practical Examples, Golden (2012)
Momoh, J.A., Adapa, R., El-Hawary, M.E.: A review of selected optimal power flow literature to 1993. I. Nonlinear and quadratic programming approaches. IEEE Trans. Power Syst. 14(1), 96–104 (1999)
Schutte, J.F.: Particle Swarms in Sizing and Global Optimization. University of Pretoria (2001)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. IV, 1942–1948 (1995)
Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of IEEE International Conference on Evolutionary Computation (1998)
Umapathy, P., Venkataseshaiah, C., Senthil Arumugam, M.: Particle Swarm Optimization with various inertia weight variants for optimal power flow solution. Discrete Dyn. Nat. Soc. 2010, 15 (2010)
Electric Power Systems Analysis & Nature-Inspires Optimization Algorithms. http://www.al-roomi.org/power-flow. Accessed 10 Apr 2017
Montoya, D.: Formulación del Despacho Económico en el Mercado de Energía con Alta Penetración de Energía Eólica. Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional Unidad Guadalajara (2016)
Abido, M.: Optimal power flow using tabu search algorithm. Electric Power Compon. Syst. 30, 469–483 (2002)
Kherfane, R., Younes, M., Kherfane, N., Khodja, F.: Solving economic dispatch problem using hybrid GA-MGA. Energy Procedia 50, 937–944 (2014)
Yuryevich, J., Wong, K.: Evolutionary programming based optimal power flow algorithm. IEEE Trans. Power Syst. 14, 1245–1250 (1999)
Ashish, S., Chaturvedi, D., Saxena, A.: Optimal power flow solution: a GAFuzzy system approach. Int. J. Emerg. Electr. Power Syst. 5(2) (2006)
Paranjothi, S.R., Anburaja, K.: Optimal power flow using refined genetic algorithm. Electr. Power Compon. Syst. 30(10) (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Gómez, J.D., Gaitan, L.F., Rivas Trujillo, E. (2017). Particle Swarm Optimization Applied to the Economic Dispatch in a Power System with Distributed Generation, Study Case: IEEE 14 Nodes System. In: Figueroa-García, J., López-Santana, E., Villa-Ramírez, J., Ferro-Escobar, R. (eds) Applied Computer Sciences in Engineering. WEA 2017. Communications in Computer and Information Science, vol 742. Springer, Cham. https://doi.org/10.1007/978-3-319-66963-2_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-66963-2_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66962-5
Online ISBN: 978-3-319-66963-2
eBook Packages: Computer ScienceComputer Science (R0)