Primary Author: Mr Bruno N. Rodrigues
Co-author(s): Ms Clemence R. Dawed; Mr Antoine de Chillaz; Mr Bastien Durand; Mr Sebastien Binet
Audience Focus: Advanced
Application Type: Application
Venue: 2013 AACE International Annual Meeting, Washington, DC, USA
Abstract: Between 2006 and 2008, global escalation of prices in Europe generated high costs that had not been anticipated.
A methodology for forecasting thermal power plants escalation cost has been developed by the company’s cost estimate team since then. This study will present the methodology used for forecasting combined cycle gas turbine escalation costs, and can be adapted to other industrial projects.
Engineering equipment (combustion turbine, heat recovery steam generator, steam turbine) costs are mainly related to market demand. That is why an equipment producer price index does not reflect the market escalation price and a Business Intelligence approach is recommended.
In order to forecast other escalation costs (balance of plant, civil engineering and labor), price indexes can be forecasted using time series modeling software applications. This paper offers a comparison of results obtained using common time series modeling techniques. This approach enables estimators to provide consistent escalation costs including quantitative accuracy range based on past volatility.
A more precise approach using economist results or based on market indicators is also presented.
Co-author(s): Ms Clemence R. Dawed; Mr Antoine de Chillaz; Mr Bastien Durand; Mr Sebastien Binet
Audience Focus: Advanced
Application Type: Application
Venue: 2013 AACE International Annual Meeting, Washington, DC, USA
Abstract: Between 2006 and 2008, global escalation of prices in Europe generated high costs that had not been anticipated.
A methodology for forecasting thermal power plants escalation cost has been developed by the company’s cost estimate team since then. This study will present the methodology used for forecasting combined cycle gas turbine escalation costs, and can be adapted to other industrial projects.
Engineering equipment (combustion turbine, heat recovery steam generator, steam turbine) costs are mainly related to market demand. That is why an equipment producer price index does not reflect the market escalation price and a Business Intelligence approach is recommended.
In order to forecast other escalation costs (balance of plant, civil engineering and labor), price indexes can be forecasted using time series modeling software applications. This paper offers a comparison of results obtained using common time series modeling techniques. This approach enables estimators to provide consistent escalation costs including quantitative accuracy range based on past volatility.
A more precise approach using economist results or based on market indicators is also presented.