Solomon Aforkoghene Aromada i doktorgradsprogrammet Prosess, energi og automatiseringsteknikk ved Fakultet for teknologi, naturvitenskap og maritime fag (TNM), forsvarer sin avhandling «Cost Estimation Methods for CO2 Capture Processes».
Prøveforelesning og disputas holdes for alle interesserte ved campus Porsgrunn 12. oktober i Auditorium A-271. Arrangementet kan også følges digitalt på Zoom. (lenke kommer.)
Tittel på prøveforelesning: «Carbon capture and storage today and in the future – in Norway and globally».
Sammendrag på engelsk
Estimates of CO2 capture and storage technologies are essential for making policies, and for making important decisions like funding of research and projects, as well as investment in industrial deployment of a carbon capture technology. Capital cost estimates of CO2 capture and other chemical plants can be improved by applying detailed factors and sub-factors as provided by the Enhanced Detailed Factor (EDF) method. The EDF method is robust and suitable for capital cost estimation of new plants, modification projects or retrofit plants, and large and small plants. The EDF method’s installation factors are sensitive to differences in equipment costs compared to the Lang Factor method, and some percentage of delivered equipment cost and the Bare Erected Cost methods. Nevertheless, due to the details involved in the EDF method, it is relatively time intensive, and it requires more work to implement. This becomes challenging when there is a need for several iterative calculations. An example is an iterative cost estimation process where each iteration involves process simulations, equipment sizing, capital cost, operating cost, and other economic analysis. This is the case for sensitivity analysis and cost optimisation studies which are very important in techno-economic analysis of CO2 capture processes.
The Iterative Detailed Factor (IDF) scheme was developed as a simple tool for fast and accurate implementation of the EDF method for CO2 capture processes’ cost optimisation and sensitivity studies. The IDF scheme was implemented by means of the spreadsheets incorporated in Aspen HYSYS application. The models for equipment dimensioning, capital cost and operating cost, as well as other key performance indicators were developed inside the Aspen HYSYS spreadsheets. It is based on estimating new equipment costs using the Power Law when subsequent simulations iterations are performed after the initial one. When a process parameter is varied, new cost estimates based on EDF installation factors and subfactors can be automatically obtained immediately after simulations have converged. The IDF scheme enables the use of the EDF method with all its advantages to obtain very fast CO2 capture cost estimates during sensitivity analysis and cost optimisation of CO2 capture processes. Several CO² capture plants’ cost optimisation studies and sensitivity analyses were conducted using this IDF scheme during this PhD project.