| dc.description.abstract | Combining gas-fired power plants equipped with CO2 capture systems is an efficient and cost-effective method for reducing carbon dioxide emissions from flue gases, thereby mitigating greenhouse gas emissions and combating global warming and climate change. The use of amine-based solvents for CO2 removal from exhaust gas is a well-established and effective process.
In this study, a base case scenario was modeled in Aspen HYSYS employing input data from previous studies on the integration of CO2 capture plant and NGCC (Natural Gas Combined Cycle). The base case simulation design included setting key parameters such as turbine inlet temperature (1500 °C), power generation of the combined cycle (400 MW),75 °C as the minimum temperature approach in the evaporator (ΔTmin), CO2 removal efficiency (90%), minimum temperature approach in the lean/rich heat exchanger (10 °C), and flue gas inlet temperature to the absorber (40 °C). The Enhanced Detailed Factor (EDF) and net present value (NPV) techniques as well as Aspen In-Plant Cost Estimator software, were employed to guess the total cost of the base case model, considering CAPEX, OPEX, and income from power sales. The cost evaluation revealed a net present value of €289 million over project lifetime (a 25-year), with a 16-year payback period following project implementation. Sensitivity analysis was conducted to optimize costs, using the power law method to estimate equipment costs when their sizes were changed. Parameters such as ΔTmin in lean/rich heat exchanger, and the evaporator's minimum temperature approach were adjusted to maximize the project's NPV. The other parameter was the exhaust gas recirculation (EGR) ratio. EGR is the portion of the heat recovery steam generators exhaust gas, which is recirculated back to the gas turbine inlet
The cost-optimized parameters identified from the sensitivity analysis included a zero EGR ratio, ΔTmin of 20 °C in lean/rich heat exchangers, and ΔTmin of 65 °C in evaporators. Also a python code was written to perform this automatic sensitivity calculation by calling HYSYS from Python.
The primary objective of this study was to use the Aspen HYSYS software to calculate cost and estimate cost optimum process parameters of a gas-based power plant which is integrated with an MEA-based CO2 capture system. This work is innovative in its inclusion of a sensitivity analysis on the EGR ratio and the evaporator's minimum temperature approach with this integrated model, which has not been previously addressed in similar studies. | |
