Vol. 2 No. 2 (2003): Revista UIS Ingenierías
Articles

Static planning of the expansion of transmission systems: comparison of genetic algorithms, search tabu and truncated enumeration

Paola Baratto Callejas
Universidad Industrial de Santander
Bio
Camilo Táutiva Mancera
Universidad Industrial de Santander
Bio
Gerardo Latorre Bayona
Universidad Industrial de Santander
Bio

Published 2003-12-03

Keywords

  • Transmission Systems Expansion,
  • long-term planning,
  • heuristic models

How to Cite

Baratto Callejas, P., Táutiva Mancera, C., & Latorre Bayona, G. (2003). Static planning of the expansion of transmission systems: comparison of genetic algorithms, search tabu and truncated enumeration. Revista UIS Ingenierías, 2(2), 113–119. Retrieved from https://revistas.uis.edu.co/index.php/revistauisingenierias/article/view/2314

Abstract

This work comprises the study and comparative analysis of three methods of planning the expansion of electric energy transport systems, applied to three systems of different size and complexity: Colombian, Southern Brazil and North-northeast Brazil. Criteria for the application of these methods to the Colombian system are established.

The comparison of the results was made taking into account the cost of investment, cost of operation and cost of energy not supplied; The latter grouped in the operating cost. Because software available for Tabu Search (B1) and Genetic Algorithms (AG) does not provide operating costs, it was necessary to evaluate the solutions in coverage mode using the Truncated Enumeration (ET) software to obtain those costs. BT presented the best performance for the Colombian system; However, ET and AG presented close solutions.

This study showed that the solution is sensitive to the control parameters that guide the search within each method. Therefore, it is important to select them appropriately to obtain good quality solutions. In addition, it can be said that algorithms need not be handled independently. Consequently, it is possible to obtain very satisfactory results if the algorithms are integrated, taking advantage of the potentialities of each one of them. However, ET has an advantage over other methods, since it allows to consider different scenarios of demand and / or generation, in addition to actual costs

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References

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