Title :
Genetic Algorithm based Methodology for Optimisation of innovative Switchgear Design
Author_Institution :
High Voltage Lab., ETH Zurich, Zurich
Abstract :
Life Cycle Cost (LCC) analysis of substations is an important instrument to improve substations and to improve innovative layouts. The LCC calculation methods used today provide good results for ascertained plants. However, because of the high number of possible variation the classic LCC method cannot be used as sensitivity analysis to carry out design trends. The present paper shows the application of a genetic algorithm to optimize substation life cycle cost, to determine cost sensitive component parameters and to derive design trends from the results. The Genetic Algorithm (GA) with its elements of selection, variation, crossover and mutation is described. A simulation example is given.
Keywords :
genetic algorithms; life cycle costing; sensitivity analysis; substations; switchgear; LCC analysis; genetic algorithm; life cycle cost; optimisation; sensitivity analysis; substation layout; switchgear design; Algorithm design and analysis; Cost function; Design optimization; Equations; Genetic algorithms; Genetic mutations; Isolation technology; Sensitivity analysis; Substations; Switchgear; Genetic Algorithm; Life cycle cost analysis; sensitivity analysis;
Conference_Titel :
Electrical Insulation, 2008. ISEI 2008. Conference Record of the 2008 IEEE International Symposium on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-2091-9
Electronic_ISBN :
1089-084X
DOI :
10.1109/ELINSL.2008.4570367
