Title :
Parameter Estimation through a Genetic Algorithm
Author :
Meza, Edwin Benito Mitacc ; De Souza, Julio Cesar Stacchini ; Filho, Milton Brown Do Coutto
Author_Institution :
Fluminense Fed. Univ., Niteroi, Brazil
Abstract :
Network parameter errors may come from many different sources, such as: imprecise data provided by manufacturers, poor estimation of transmission line lengths, changes in the transmission network design which are not adequately updated in the corresponding database, etc. Network parameter data are used by almost all power system analysis tools, from real time monitoring to long term planning. Parameter errors may contaminate the obtained results and compromise decision making processes. This work proposes a methodology that combines genetic algorithms and power system state estimation to correct single or multiple network parameter errors. Simulations with the IEEE 14-bus test system are performed to illustrate the proposed method.
Keywords :
genetic algorithms; power system analysis computing; power system planning; genetic algorithm; long term planning; parameter estimation; power system analysis tools; power system state estimation; real time monitoring; Databases; Error correction; Genetic algorithms; Manufacturing; Parameter estimation; Power system analysis computing; Power system planning; Power system simulation; Power transmission lines; Real time systems; Genetic Algorithms; Optimization; Parameter Estimation;
Conference_Titel :
Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on
Conference_Location :
Curitiba
Print_ISBN :
978-1-4244-5097-8
DOI :
10.1109/ISAP.2009.5352894