DocumentCode :
3345143
Title :
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
Link To Document :
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