The paper presents a methodology which can be used to improve the static adequacy of high-voltage (HV) transmission systems under contingency. In this case the most suitable actions to be taken for bringing the power system back to acceptable operation conditions are identified by means of a power system management software. The proposed software combines a micro-genetic algorithm (mu GA) optimization procedure with a load-flow program based on the fringing Current correction (FCC) method. The foreseen control actions consist in transformer tap setting, insertion and/or regulation (if variable) of shunt reactor and capacitor banks, change of network configuration, power re-dispatching and load shedding. The performance of the proposed procedure is tested with respect to the main parameters both of electrical power systems and of genetic algorithms (GAs). An application to existing HV transmission systems is presented and discussed in order to evaluate its possible use ill a System Control Center. (C) 2008 Elsevier B.V. All rights reserved.
Improving high-voltage transmission system adequacy under contingency by genetic algorithms / Gatta, Fabio Massimo; Geri, Alberto; Lauria, Stefano; Maccioni, Marco. - In: ELECTRIC POWER SYSTEMS RESEARCH. - ISSN 0378-7796. - STAMPA. - 79:1(2009), pp. 201-209. [10.1016/j.epsr.2008.05.013]
Improving high-voltage transmission system adequacy under contingency by genetic algorithms
GATTA, Fabio Massimo;GERI, Alberto;LAURIA, Stefano;MACCIONI, Marco
2009
Abstract
The paper presents a methodology which can be used to improve the static adequacy of high-voltage (HV) transmission systems under contingency. In this case the most suitable actions to be taken for bringing the power system back to acceptable operation conditions are identified by means of a power system management software. The proposed software combines a micro-genetic algorithm (mu GA) optimization procedure with a load-flow program based on the fringing Current correction (FCC) method. The foreseen control actions consist in transformer tap setting, insertion and/or regulation (if variable) of shunt reactor and capacitor banks, change of network configuration, power re-dispatching and load shedding. The performance of the proposed procedure is tested with respect to the main parameters both of electrical power systems and of genetic algorithms (GAs). An application to existing HV transmission systems is presented and discussed in order to evaluate its possible use ill a System Control Center. (C) 2008 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.