Techno-economic operation optimization of a HRSG in combined cycle power plants based on evolutionary algorithms: A case study of Yazd, Iran

Document Type: Research Paper

Authors

1 Department of Applied Mathematics, Islamic Azad University South Tehran Branch, Tehran, Iran

2 Department of Energy Engineering, Sharif University of technology (SUT), Tehran, Iran

10.22059/ees.2019.34618

Abstract

In this research study, energy, exergy and economic analyses is performed for a combined cycle power plant (CCPP) with a supplementary firing system. The purpose of this analyses is to evaluate the economic feasibility of a CCPP by applying an optimization techniques based on Evolutionary algorithms. Actually, the evolutionary algorithms of Firefly, PSO and NSGA-II are applied to minimize the cost function and to optimally adjust the operating design variables of a CCPP. The input parameters are measured in real case study (i.e., Yazd city, Iran) and they are used to model and optimize the system performance. The cost objective function is formed from several parts: Operating cost, capital cost and exergy destruction cost. In following of optimization procedure, a thermo-economic method is employed to compare the impact of operating parameters from an economic standpoint by COMFAR III (Computer Model for Feasibility Analysis and Reporting) software. The economic analysis consists of determination of NPV, sensitivity analysis and calculation of break-even point. The results showed that the optimization results are economically more feasible than the base case. In addition, among different optimization techniques, Firefly algorithm improves the economic justification of CCPP. At the end, the results of sensitivity analysis show that by decreasing the operation costs, fixed assets and sales revenue by 40%, the IRR increases by 6.7%, 42.8% and decreases by 41.4%, respectively. Furthermore, the lowest sensitivity of IRR is related to operation cost, while the highest sensitivity of IRR is corresponding to variations of fixed assets.

Keywords


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