Simulation and Impact of different Optimization Parameters on CO2 Capture Cost

The influence of different process parameters/factors on CO2 capture cost, in a standard amine based CO2 capture process was studied through process simulation and cost estimation. The most influential factor was found to be the CO2 capture efficiency. This led to investigation of routes for capturing more than 85% of CO2. The routes are by merely increasing the solvent flow or by increasing the absorber packing height. The cost-efficient route was found to be by increasing the packing height of the absorber. This resulted in 20% less cost compared to capturing 90% CO2 by increasing only the solvent flow. The cost optimum absorber packing height was 12 m (12 stages). The cost optimum temperature difference in the lean/rich heat exchanger was 5 °C. A case with a combination of the two cost optimum parameters achieved a 4% decrease in capture cost compared to the base case. The results highlight the significance of performing cost optimization of CO2 capture processes.publishedVersio

A Techno-Economic Model for Benchmarking the Production Cost of Lithium-Ion Battery Cells

In response to the increasing expansion of the electric vehicles (EVs) market and demand, billions of dollars are invested into the battery industry to increase the number and production volume of battery cell manufacturing plants across the world, evident in Giga-battery factories. On the other side, despite the increase in the battery cell raw material prices, the total production cost of battery cells requires reaching a specific value to grow cost-competitive with internal combustion vehicles. Further, obtaining a high-quality battery at the end of the production line requires integrating numerous complex processes. Thus, developing a cost model that simultaneously includes the physical and chemical characteristics of battery cells, commodities prices, process parameters, and economic aspects of a battery production plant is essential in identifying the cost-intensive areas of battery production. Moreover, such a model is helpful in finding the minimum efficient scale for the battery production plant which complies with the emergence of Giga-battery plants. In this regard, a process-based cost model (PBCM) is developed to investigate the final cost for producing ten state-of-the-art battery cell chemistries on large scales in nine locations. For a case study plant of 5.3 GWh.year−1 that produces prismatic NMC111-G battery cells, location can alter the total cost of battery cell production by approximately 47 US$/kWh, which is dominated by the labor cost. This difference could decrease by approximately 31% at the minimum efficient scale of the battery production plant, which is 7.8 GWh.year−1 for the case study in this work. Finally, a comprehensive sensitivity analysis is conducted to investigate the final prices of battery cell chemistries due to the changes in commodities prices, economic factors of the plant, battery cell production parameters, and production volume. The outcomes of this work can support policy designers and battery industry leaders in managing production technology and location

Simulation and cost estimation of CO2 capture processes using different solvents/blends

There has been a growing trend toward removing CO2 emissions from the industry with different methods. One of the most mature methods for carbon capture is to absorb CO2 in an amine-based (MEA) post-combustion technology. Shortcomings of MEA make other solvents and their blends more interesting in CO2 removal plants. The work in this master thesis is absorption-desorption CO2 capture process simulated in Aspen HYSYS for different solvents/blends than MEA. Moreover, cost estimation methods for simulated cases have been performed to provide a complete cost estimation package. The data for cost estimation is provided with Aspen In-Plant Cost Estimator program. A base case simulation model consisting of a simplified carbon capture unit including a 10-stage absorber, 6-stage desorption column, 85% CO2 removal efficiency and minimum approach temperature for the lean/rich heat exchanger of 10 °C has undergone different solvents/blends of MEA, MDEA and PZ. The results indicate that adding 5 – 10 wt.% of piperazine to base case (30 wt.%) could offer a blend of solvents with lower regeneration energy than base case. Also, this matter was accurate for adding 5 – 20 wt.% MDEA to base case. Optimization of suggested range of blends has been performed in term of regeneration energy. Optimized concentrations could be as 30% MEA + 5% PZ (wt.%) and 30% MEA + 15% MDEA (wt.%) where lead into 4.9% and 7.5% lower regeneration energy than base case with 3.77 [MJ/kg CO2]. These blends, also, have been simulated for vapor recompression configuration. Lean, rich and cyclic loadings for suggested blends in both standard and VR configurations have been discussed. Aspen In-Plant Cost Estimator, applying Enhanced Detail Factor (EDF) method, was used for the cost estimation of processes. based on conducted cost estimations, plant with suggested blends presents cost savings rather than standard base case. Hopefully, the results in this thesis contribute to perform cost optimization more efficiently