Abstract
In this work we present a particular encoding and fitness evaluation strategy for a genetic approach in the context of searching in graphs. In particular, we search for a spanning tree in the universe of directed graphs under certain constraints related to the topology of the graphs considered. The algorithm was also implemented and tested as a new topological approach to electrical power network observability analysis and was revealed as a valid technique to manage observability analysis when the system is unobservable. The algorithm was tested on benchmark systems as well as on networks of realistic dimensions.
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
Preview
Unable to display preview. Download preview PDF.
References
Schweppe, F.C., Wildes, J.: Power system static-state estimation, part i: exact model. IEEE Transactions on Power Apparatus and Systems PAS-89(1), 120–125 (1970)
Schweppe, F.C., Rom, D.B.: Power system static-state estimation, part ii: approximate model. IEEE Transactions on Power Apparatus and Systems PAS-89(1), 125–130 (1970)
Schweppe, F.C.: Power system static-state estimation, part iii: implementation. IEEE Transactions on Power Apparatus and Systems PAS-89(1), 130–135 (1970)
Monticelli, A., Wu, F.F.: Network observability identification of observable islands and measurement placement. IEEE Transactions on Power Apparatus and Systems PAS-104(5), 1035–1041 (1985)
Monticelli, A., Wu, F.F.: Network observability theory. IEEE Transactions on Power Apparatus and Systems PAS-104(5), 1042–4048 (1985)
Krumpholz, G., Clements, K., Davis, P.: Power system observability: a practical algorithm using network topology. IEEE Transactions on Power Apparatus and Systems PAS-99(4), 1534–1542 (1980)
Clements, K., Krumpholz, G., Davis, P.: Power system state estimation with measurement deficiency: an algorithm that determines the maximal observable subnetwork. IEEE Transactions on Power Apparatus and Systems PAS-101(9), 3044–3052 (1982)
Nucera, R.R., Gilles, M.L.: Observability analysis a new topological algorithm. IEEE Transactions on Power Systems 6(2), 466–473 (1991)
Mori, H., Tanaka, H.: A genetic approach to power system topological observability. In: IEEE Proceedings of International Symposium on Circuits and Systems 1991, ISCAS 1991, vol. 2, pp. 1141–1144 (1991)
Mori, H.: A ga-based method for optimizing topological observability index in electric power networks. In: IEEE Proceedings of the First Conference on Evolutionary Computation 1994. IEEE World Congress on Computational Intelligence, vol. 2, pp. 565–568 (1994)
Vazquez-Rodriguez, S., Duro, R.: A genetic baseed technique for the determination of power system topological observability. International Scientific Journal of Computing 2(2)
Vazquez-Rodriguez, S., Faiña, A., Neira-Dueñas, B.: An evolutionary technique with fast convergence for power system topological observability analysis. In: Proceedings IEEE World Congress on Computational Intelligence, WCCI 2006, pp. 3086–3090 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vazquez-Rodriguez, S., Duro, R.J. (2009). A Strategy for Evolutionary Spanning Tree Construction within Constrained Graphs with Application to Electrical Networks. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Bioinspired Applications in Artificial and Natural Computation. IWINAC 2009. Lecture Notes in Computer Science, vol 5602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02267-8_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-02267-8_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02266-1
Online ISBN: 978-3-642-02267-8
eBook Packages: Computer ScienceComputer Science (R0)