Title :
Automatic Load Shedding Calculated with genetic algorithms - DAC-CMAG
Author :
Guichon, M. ; Melo, M. ; Nieto, A.C. ; Vignolo, M. ; Yedrzejewski, N.
Author_Institution :
Dept. of Tech. Studies, Network Oper. Montevideo in UTE, Montevideo, Uruguay
Abstract :
This paper presents an optimization tool based on Genetic Algorithms, DAC-CMAG (Automatic Load Shedding Calculated Through Genetic Algorithms), developed in Matlab and applied to the calculation of load shedding in Electric Power Systems. This application calculates the optimal load shed necessary to eliminate overloading of any series element of an electrical network. It includes a module that runs DC load flow to calculate the power flow for each branch or transformer and verifies there are no current violations in any equipment. The results are analyzed using this tool applied to the calculation of optimum load shed required for the worst contingencies in the 500kV power system of Uruguay.
Keywords :
genetic algorithms; load flow; load shedding; mathematics computing; DAC-CMAG; DC load flow; Matlab; Uruguay; automatic load shedding; electric power system; genetic algorithm; optimization tool; power flow; power system; voltage 500 kV; Genetic algorithms; Load flow; Load modeling; Power system stability; Sociology; Statistics; Substations; DC load flow; Genetic Algorithm; load shedding;
Conference_Titel :
Transmission and Distribution: Latin America Conference and Exposition (T&D-LA), 2012 Sixth IEEE/PES
Conference_Location :
Montevideo
Print_ISBN :
978-1-4673-2672-8
DOI :
10.1109/TDC-LA.2012.6319121