Genetic Algorithm based Methodology for Optimisation of innovative Switchgear Design

Author

Hinow, M.

Author_Institution

High Voltage Lab., ETH Zurich, Zurich

fYear

2008

fDate

9-12 June 2008

Firstpage

437

Lastpage

440

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Insulation, 2008. ISEI 2008. Conference Record of the 2008 IEEE International Symposium on

Conference_Location

Vancouver, BC

ISSN

1089-084X

Print_ISBN

978-1-4244-2091-9

Electronic_ISBN

1089-084X

Type

conf

DOI

10.1109/ELINSL.2008.4570367

Filename

4570367