Abstract
Many methods to estimate the cut-off value in order to determine the actual groups from a dendrogram given via hierarchical clustering methods have been proposed in the litetarure. However, in most of the cases, the determination of this value is critical and based on heuristics. In this context, a new method based on Pareto-optimality and on the hierarchical clustering method called Data Mine of Code Repositories (DAMICORE) to determine the most promising groups in a given dendrogram is proposed. This method is called Pareto-Efficient Set Algorithm (PESA). In order to validate the proposed method, PESA was applied find the most promising groups for the preventive control selection problem in the context of voltage stability assessment in electrical power systems. PESA was able to design a set of controllers to eliminate all critical contingencies and was successfully tested in a reduced south-southeast Brazilian system composed of 107 buses.
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References
Granville, S., Mello, J.C.O., Melo, A.C.G.: Application of interior point methods to power flow unsolvability. IEEE Transactions on Power Systems 11, 1096–1103 (1996)
Bedrinana, M., Castro, C., Bedoya, D.: Maximization of voltage stability margin by optimal reactive compensation. In: 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, pp. 1–7, July 2008
Greene, S., Dobson, I., Alvarado, F.: Sensitivity of the loading margin to voltage collapse with respect to arbitrary parameters. IEEE Transactions on Power Systems 12(1), 262–272 (1997)
Zhao, J., Chiang, H.-D., Li, H., Zhang, B.: A novel preventive control approach for mitigating voltage collapse. In: Power Engineering Society General Meeting, p. 6. IEEE (2006)
Mansour, M., Alberto, L., Ramos, R.: Look-ahead based method for selection of preventive control for voltage stability analysis, pp. 469–473, March 2012
Chiang, H.-D., Wang, C.-S., Flueck, A.: Look-ahead voltage and load margin contingency selection functions for large-scale power systems. IEEE Transactions on Power Systems 12(1), 173–180 (1997)
Mansour, M.R., Alberto, L.F.C., Ramos, R.A., Delbem, A.C.B.: Identifying groups of preventive controls for a set of critical contingencies in the context of voltage stability. In: ISCAS, pp. 453–456 (2013)
Sanches, A., Cardoso, J., Delbem, A.: Identifying merge-beneficial software kernels for hardware implementation. In: International Conference on Reconfigurable Computing and FPGAs (ReConFig), November 30 to December 2, 2011, pp. 74–79 (2011)
Figueira, J., Greco, S., Ehrgott, M.: Multiple criteria decision analysis: state of the art surveys. International Series in Operations Research & Management Science. Springer (2005). http://books.google.co.in/books?id=YqmvlTiMNqYC
Chauhan, A., Vaish, R.: Hard coating material selection using multi-criteria decision making. Materials & Design 44, 240–245 (2013)
Pedro, L.R., Takahashi, R.H.C.: Modeling decision-maker preferences through utility function level sets. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds.) EMO 2011. LNCS, vol. 6576, pp. 550–563. Springer, Heidelberg (2011)
Pareto, V.: Manual of political economy (manuale di economia politica). Kelley, New York. Translated by Ann S. Schwier and Alfred N. Page
Morse, J.N.: Reducing the size of the nondominated set: Pruning by clustering. Computers & OR 7(1–2), 55–66 (1980)
Mattson, C.A., Mullur, A.A., Messac, A.: Smart Pareto filter: obtaining a minimal representation of multiobjective design space. Engineering Optimization 36(6), 721–740 (2004)
Veerappa, V., Letier, E.: Understanding clusters of optimal solutions in multi-objective decision problems. In: Proceedings of the 2011 IEEE 19th International Requirements Engineering Conference, ser. RE 2011, pp. 89–98. IEEE Computer Society, Washington, DC (2011)
ONS. Submódulo 23.3: Diretrizes e critérios para estudos elétricos, November 2011. http://www.ons.org.br/procedimentos/index.aspx
Cilibrasi, R., Vitányi, P.M.B.: Clustering by compression. IEEE Transactions on Information Theory 51, 1523–1545 (2005)
Felsenstein, J.: Inferring Phylogenies, 2nd edn. Sinauer Associates, September 2003
Newman, M.: Networks: An Introduction. Oxford University Press Inc., New York (2010)
Alves, W.F.: Proposition of test-systems to power systems analysis, Ph.D. dissertation, Universidade Federal de Fluminense, Niteroi, RJ (2007). http://www.sistemas-teste.com.br/ (in Portuguese)
Chiang, H.-D., Flueck, A., Shah, K., Balu, N.: Cpflow: a practical tool for tracing power system steady-state stationary behavior due to load and generation variations. IEEE Transactions on Power Systems 10(2), 623–634 (1995)
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Mansour, M.R., Delbem, A.C.B., Alberto, L.F.C., Ramos, R.A. (2015). Integrating Hierarchical Clustering and Pareto-Efficiency to Preventive Controls Selection in Voltage Stability Assessment. In: Gaspar-Cunha, A., Henggeler Antunes, C., Coello, C. (eds) Evolutionary Multi-Criterion Optimization. EMO 2015. Lecture Notes in Computer Science(), vol 9019. Springer, Cham. https://doi.org/10.1007/978-3-319-15892-1_33
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