Artificial intelligence based dynamic transmission network expansion planning

Author

Simo, A. ; Kilyeni, St ; Barbulescu, C.

Author_Institution

Power Syst. Dept., Politeh. Univ. Timisoara, Timisoara, Romania

fYear

2015

fDate

25-27 June 2015

Firstpage

54

Lastpage

60

Abstract

The paper is focusing on dynamic transmission network expansion planning (TNEP). The TNEP problem has been approached from the retrospective and prospective point of view. To achieve this goal, the authors are developing two software-tools in Matlab environment. Power flow computing is performed using conventional methods. Optimal power flow and network expansion are performed using artificial intelligence methods. Within this field, two techniques have been tackled: particle swarm optimization (PSO) and genetic algorithms (GA). The case study refers to well-known IEEE 24 RTS test power system.

Keywords

genetic algorithms; load flow; particle swarm optimisation; planning (artificial intelligence); power engineering computing; software tools; transmission networks; GA; IEEE 24 RTS test power system; Matlab environment; PSO; artificial intelligence based dynamic transmission network expansion planning; dynamic TNEP; genetic algorithms; optimal power flow; particle swarm optimization; power flow computing; software-tools; Genetic algorithms; Optimization; Planning; Power system dynamics; Sociology; Statistics; artificial intellingence; dynamic expansion planning; optimization; retrospectiv approach; software-tool; transmission network;

fLanguage

English

Publisher

ieee

Conference_Titel

Human System Interactions (HSI), 2015 8th International Conference on

Conference_Location

Warsaw

Type

conf

DOI

10.1109/HSI.2015.7170643

Filename

7170643