Title :
Transmission network expansion planning under an improved genetic algorithm
Author :
da Silva, E.L. ; Gil, H.A. ; Areiza, J.M.
Author_Institution :
Univ. Fed. de Santa Catarina, Brazil
Abstract :
This paper describes the application of an improved genetic algorithm (IGA) to deal with the solution of the transmission network expansion planning (TNEP) problem. Genetic algorithms (GAs) have demonstrated the ability to deal with nonconvex, nonlinear, integer-mixed optimization problems, like the TNEP problem, better than a number of mathematical methodologies. Some special features have been added to the basic genetic algorithm (GA) to improve its performance in solving the TNEP problem for three real-life, large-scale transmission systems. Results obtained reveal that GAs represent a promising approach for dealing with such a problem. In this paper, the theoretical issues of GA applied to this problem are emphasized
Keywords :
genetic algorithms; power transmission planning; transmission network calculations; computational performance; improved genetic algorithm; nonconvex nonlinear integer-mixed optimization problems; transmission network expansion planning; Circuits; Costs; Gas insulated transmission lines; Genetic algorithms; Heuristic algorithms; Instruction sets; Investments; Large-scale systems; Optimization methods; Power generation;
Conference_Titel :
Power Industry Computer Applications, 1999. PICA '99. Proceedings of the 21st 1999 IEEE International Conference
Conference_Location :
Santa Clara, CA
Print_ISBN :
0-7803-5478-8
DOI :
10.1109/PICA.1999.779513