Artificial intelligence based TNEP. Part 1: Mathematical models

Author

Cristian, Dan ; Barbulescu, C. ; Kilyeni, St ; Pop, Oana ; Solomonese, Florin

Author_Institution

Power Syst. Dept., “Politeh.” Univ. of Timisoara, Timisoara, Romania

fYear

2013

fDate

23-25 May 2013

Firstpage

391

Lastpage

394

Abstract

The paper is focusing on transmission network expansion planning (TNEP) problem solved using artificial intelligence techniques. It is divided into two parts. The 1^st part is dedicated to the particle swarm optimization (PSO) and genetic algorithm (GA) concepts and mechanisms. The mathematical models and the associated software tool are also presented. Practical considerations are discussed. The 2^nd part is focusing on case studies. 13 buses test power system, developed by the authors and IEEE 24 RTS have been used. The research work is going to be used in case of the Romanian power system (over 1000 buses).

Keywords

IEEE standards; artificial intelligence; genetic algorithms; mathematical analysis; particle swarm optimisation; power engineering computing; power transmission planning; power transmission reliability; GA; IEEE 24 RTS; PSO; Romanian power system; TNEP problem; artificial intelligence techniques; buses test power system; genetic algorithm; mathematical models; particle swarm optimization; software tool; transmission network expansion planning; Genetic algorithms; Mathematical model; Particle swarm optimization; Planning; Power systems; Sociology; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Applied Computational Intelligence and Informatics (SACI), 2013 IEEE 8th International Symposium on

Conference_Location

Timisoara

Print_ISBN

978-1-4673-6397-6

Type

conf

DOI

10.1109/SACI.2013.6609005

Filename

6609005