Techno-economic and environmental risk assessment of gas turbines for use with flared associated gases.

Investing in the economic use of associated gas for power generation using gas turbines would require a model for evaluating the effect of gas turbine degradation on the divestment time of the redundant units of engines. The Techno-Economic and Environmental Risk Assessment (TERA) framework is adopted for a broad and multidimensional analysis of the problem. Due to the limited availability of the associated gas, the fleet composition is optimised to obtain the maximum power, economic returns and best divestment time. The performance, emission, creep life, economic returns and risk associated with the optimised fleets are all analysed. Four different study engines are considered an aero-derivative, an aero-derivative with intercool, a single shaft, and a reheat engine. Turbomatch, Hephaestus, and Genetic Algorithm in Matlab are among the tools used. As expected, results show that engine degradation extends the divestment time. For example, at the 2ᵑᵈ year of the project; 0, 1, 2, 3, 3 are the respective number of units of engines divested in the pessimistic degraded, medium degraded, optimistic degraded, clean (optimised) and baseline fleets of the aero-derivative engine. An increase of 1.0% and 1.6% respectively in the power and NPV of the optimised clean aero-derivative fleet as against the baseline are achieved. The economic performance of the fleets show the optimised fleet (clean) of the aero-derivative intercooled engine having the highest NPV of $3.24b and the pessimistic degraded fleet of the (43.3MW) aero-derivative engine having the least NPV of $2.39b. Degradation reduced the NPV of the project for the degraded fleets. As an example, a reduction by 4.0%, 9.1% and 15.8% for the optimistic, medium and pessimistic degraded fleets of the 43.3MW aero-derivative engine is observed. The novel technical contribution of this research is the development of a model and methodology for evaluating the effect of degradation on divestment time, which serves as a guide to associated gas investors. Other contributions are the development of models for best divestment time evaluation, improvement of the economic performance of different fleets of different gas turbine cycles and the assessment of the impact of engine degradation on the economic use of associated gas. The results of the optimised divestment time, fleet compositions, power and improved economic returns from the project are also a big contribution to knowledge. This research has proposed a model that can be used for the profitable economic utilisation of associated gas.