Dimensionless exergo-economic and emission parameters for biogas fueled gas turbine optimization

• Main Authors: Barzegaravval, Hasan, Hosseini, Seyed Ehsan, Abdul Wahid, Mazlan, Saat, Aminuddin
• Format: Article
• Published: Elsevier Ltd 2020
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/86794/; http://dx.doi.org/10.1016/j.jclepro.2020.121153O
• Institution: Universiti Teknologi Malaysia

ptimization of energy system is a favored method to mitigate emission and manage fuel resources. However, optimization results interpretation and optimal point selection is a challenging area, and mostly a subjective decision. In addition, optimization, even with cost objectives, are carried out by technical teams which normally differ from project decision makers. To provide a solution, at first a framework for optimization is defined with general optimal correlations as goals of optimization. This framework is devised to prepare results understandable and helpful to decision makers. Then two important parameters named cr (ratio of product to fuel cost) and CR (ratio of annualized fixed to current cost) are employed to represent the system performance and design variables in optimal points of pareto front. Finally, a set of correlation functions is evaluated to correlate the optimal design variables to design parameters. In addition, an emission parameter is introduced in terms of cr and CR. The results revealed that cr-CR can successfully represent the system characteristics and lead to smooth functionality between newly defined star design variables and cr. The method is implemented on a biogas fueled gas turbine. Sensitivity of minimum cr to fuel composition variations is examined and results illustrate that at this point, implementing 50% methane content for a system which is designed optimally for pure methane, causes 2% reduction in efficiency and increases the cost of product. However, in comparison to system optimally designed for 50% methane, efficiency drop is less than 1% and product cost does not change significantly. Analyzing (emission per product) and cr suggests that CR < 0.8 is suitable for optimal design selection. The proposed method here helps to tradeoff between cost and emission reduction in early phase of the project which boost energy efficiency applications.