(538d) Evaluation of Novel CO2 Capture Process Configurations with Combined Cycle Gas Turbine Plants | AIChE

(538d) Evaluation of Novel CO2 Capture Process Configurations with Combined Cycle Gas Turbine Plants


As per the Energy Information Administration (EIA), the world energy consumption is expected to increase by almost 50% between 2018 and 2050 [1]. Approximately, 70% of the global energy is generated by the thermoelectric powerplants which burn fossil fuels emitting huge quantities of Carbon dioxide (CO2) into the atmosphere currently estimated at 36.8 Gt/yr. Presently, post-combustion CO2 capture from a combined cycle gas turbine, considered to be a back-up plant when moving to renewable sources, using chemical solvent is the preferred option due to its technological maturity and commercial availability [2]. There are various promising chemical solvents that can be used to capture CO2 from flue gas in the absorption process such as Ammonia, Ionic Liquids, Amines, water-lean solvents with high absorption capacity and low regeneration energy. However, they come with many drawbacks that need to be investigated, considering complete techno-economic evaluations that are able to capture the trade-offs at the system level. For example, ammonia faces the challenges of ammonia slip due to its low volatility and moderate reaction kinetics amplifying the capital costs of the process. Ionic Liquids also possess superior characteristics such as low volatility, high thermal stability and energy efficient solvent recovery, however its major drawback is its high viscosity which limits mass transfer of CO2 in ILs resulting in slower reaction kinetics [3].

In this work, we have performed techno-economic evaluations of various process configurations of MEA and MDEA/PZ blend CO2 capture plant attached to CCGT plant. We have developed and validated rate-based model of the integrated CO2 capture process in ASPEN plus V10 with Electrolyte Non-Random Two Liquid (ENRTL) method to determine the fundamental liquid properties and Redlich Kwong (RK) Equation of State to determine the fundamental vapor properties. We have ensured that all the detailed configurations and solvent blends are examined using detailed cost analysis without leaning towards reduction of energy penalty as the sole indicators as reported in the literature. Process Configurations have the potential to improve the CO2 loading capacity and decrease the reboiler duty. The various process configurations described in detail in the literature include Absorber Inter Cooling (AIC), Rich Solvent Recycle (RSR), Rich Solvent Preheating (RSP), Rich Solvent Split (RSS), Solvent Split Flow (SSF), Rich Solvent Flash (RSF), Lean Vapor Compression (LVC), Rich Vapor Compression (RVC), Multi Pressure Stripper (MPS) and Inter Heated Stripper (IHS) [4-8].

The results of the simulations of attaching 750MW Natural Gas Combined Cycle (NGCC) Power Plant to various individual and combined process configurations considering the optimal operating parameters from the sensitivity analyses are shown in Table 1. The results of the sensitivity analysis show that 2 bar is the optimum stripper pressure and 90% is the optimum degree of capture for CO2 removal. In addition, it demonstrated that for MEA; 30wt% and for MDEA/PZ; 35wt%/15wt% are the optimum ratios while 0.25 for MEA and 0.10 for MDEA/PZ are the optimum lean loadings resulting in minimum energy requirement. The results shown in table 1 highlight that RSF and RSP for MEA and RVC, RSF and RSP for MDEA/PZ had no positive effect in reducing the regeneration energy requirement while the combination of AIC+RSS+LVC had the maximum positive effect as it resulted in the lowest regeneration energy resulting in 22.1% and 21.7% energy savings for MEA and MDEA/PZ process respectively.

In this talk, we are going to present the techno-economic evaluations of the various solvents and process configurations, similar to the one shown in Table 2 for MEA. It shows that RVC and IHS had higher Levelized Cost of Capture and Compression (LCCC) than the base case indicating no positive effect on cost reduction while the combination of AIC+RSS+LVC had the maximum positive effect on cost reduction (55.1$/tCO2), being the best combination for MEA process in terms of energy and cost savings.

In conclusion, implementing process configuration combinations along with replacing MEA with MDEA/PZ can significantly reduce the high regeneration energy requirement. Moreover, the results show that considering one of the KPI such as reboiler duty might lead to misleading results as the overall performance of having more capex lead to higher cost.


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