Abstract:
The growing desire for sponsors of power generation projects to share risk with the
lenders has promoted the use of computational tools, simulating and evaluating from a
techno-economic viewpoint long-term, high-risk projects. Such models need to include
reliable engine diagnostics, life cycle costing and risk analysis technique.
This work consisted in designing a Decision Support System (DSS) for the assessment
of power generation projects using industrial gas turbines in combined cycle. The
software, programmed in Visual Basic in Excel in a windows-frame, runs an external
application named Pythia, which has been developed by the Department of Propulsion,
Power; Energy and Automotive Engineering at Cranfield University. It can perform gas
turbine performance simulations, including off-design conditions, with or without
degradation effects providing thus reliable engine diagnostics.
Steam cycle models including different heat recovery steam generator configurations
have been developed to simulate steam turbine design and off-design performance.
Plant performance simulation takes into account off-design conditions, part-load
governing strategies and degradation effects.
Besides a robust economic mode and a life cycle costing model including maintenance planning assessments offer a wide range of possible operating and economic scenarios.
The degree of uncertainty relating to technical and economic factors is assessed using
normal distributions, and the level of risk is then evaluated using a risk analysis, technique based upon the Monte Carlo method.
The DSS provides all sorts of charts and techno-economic figures in order to support the
decision making through an effective user-friendly window-oriented interface.
