Techno-Economic, Environmental and Risk Analysis (TERA) for Power Generation -Market Growth

Gas turbines (GTs) are extensively used in many power generation applications. This project has close coupled advanced, economic diagnostics with the technology of prime movers using a Genetic Algorithm (GA) to optimise the economic performance of fleets of GTs for electricity production. The investigation has included comparative assessment of traditional and novel GT options, including the design and off-design performance of the engines. The originality of the work lies in the concurrent technical and economic optimisation of a fleet of GTs based on a GA using current and novel engine cycles in a wide range of climatic conditions. The project has developed an effective model for optimising operational strategies for off-design conditions capable of optimising the economic performance of existing fleets of GT engines to meet power requirement while minimising environmental impact. It has also developed an approach able to simulate engine operating conditions with attendant costs under different scenarios based on the Techno-Economic, Environmental, and Risk Analysis (TERA) philosophy which allows for a broad and multidimensional analysis of the problem. By integrating the TERA model with in-house performance simulation software (Turbomatch) it has been possible to simulate the engine performances at design point and off-design conditions and maximise total power output at minimum cost to aid equipment selection and plant operation strategies for new plant. This study simulated and accounted for the time value of money during the operational life of the power plant. The model includes a life cycle cost assessment including: capital cost, maintenance and operating costs, fuel cost and emission taxes. Using the Net Present Value (NPV) technique the model was able to make techno-economic comparisons between various modes of operation and variations in power demand. Peak load operation requires GTs to operate at high firing temperatures with consequent reduction in component’ useful life. The techno-economic analysis found the optimum condition between both operating condition and corresponding strategies and thus includes a comparative lifing model, which performs stress and thermal analyses, and estimates the component’s minimum creep life using the Larson Miller method. A fleet of GT engine operating in a warm coastal environment have been modelled and investigated in this study. The results showed that the combined effect of the operating environment and the power demand can have significant impact on the blade creep life. The ability to predict this impact will aid GT users in the decision making process associated with GT operation. The project has developed an emissions model which identifies the GT engine with smallest impact on global warming and lowest cost of ownership (including governmental taxation policies) and which will meet a variety of emission legislation.