(576c) Flexible Operation of CO2 Capture Processes at Different Plant Scales

The transition of energy systems to meet CO₂ mitigation targets has led to an increased integration of intermittent renewable energy. To balance the intermittency, fossil fuel-fired power plant with CO₂ capture and storage (CCS) will need to operate flexibly (Mac Dowell and Staffell, 2016). By coordinating the balance between electricity supply and CO₂ emission reduction targets, the economic and technical performance of power plants with CCS could potentially improve. The system-wide benefit of flexible CCS are clear, e.g., total system cost is reduced, and power system resilience and operability are improved.

The profitability of the system can be maximised with flexible operation by ramping the CO₂ capture process up and down in accordance to electricity demand. In additional to this load following approach, other flexible operation strategies include systems that bypass CO₂ capture, vent flue gas, store rich/lean solvent and optimisation of the steam cycle design. Techno-economic studies demonstrate the economic value of flexible CCS operation. However, further research needs to evaluate the impact of process disturbances on the technical performance and plant operability during flexible operation. Dynamic process modelling and pilot plant studies will be essential in assessing the feasibility of flexible operation in CO₂ capture plants.

The process dynamics of a CO₂ capture plant is a function of plant size or scale. We need to better understand the effect of plant scale, also identifying the key characteristics that impact process operability and flexibility. This study will investigate the feasibility of flexible operation for post-combustion CO₂ capture at three different plant scales:

• UKCCSRC PACT CO₂ capture pilot plant (1 t_CO2/day capture capacity);
• Brindisi CO₂ capture plant (60 t_CO2/day capture capacity);
• Technology Centre Mongstad (TCM) CO₂ capture plant (80 t_CO2/day capture capacity).

A combination of pilot plant performance assessment and dynamic modelling have been employed to identify key factors that can limit the flexibility of a CO₂ capture plant. Dynamic models of these three CO₂ capture plants were developed in gCCS (by Process Systems Enterprise) and validated against steady state and dynamic plant data.

The UKCCSRC PACT pilot plant (Sheffield, UK) results demonstrates CO₂ capture of ~1 t_CO2/day from flue gas with CO₂ concentration of 12–13 vol% (similar to coal flue gas). The PACT pilot plant datasets presented in this paper demonstrates three dynamic operation scenarios: (a) partial load stripping, (ii) capture plant ramping, and (iii) reboiler steam decoupling (Bui et al., 2018). The Brindisi pilot plant (Brindisi, Italy) represents a “mid-scale” plant in this study, which captures 60 t_CO2/day from flue gas exiting a coal-fired power plant with a CO₂ concentration of 10–13 vol%. To study the dynamics of the Brindisi plant, step changes in the following process parameters were modelled (based on data from Enaasen et al. (2014)): steam flow rate, solvent flow rate and flue gas flow rate. The largest plant of three is the Technology Centre Mongstad (TCM) CO₂ capture plant (Mongstad, Norway), designed to capture CO₂ from two flue gas sources:

• Combined heat and power (CHP) plant: capture capacity of 80 tonnes CO₂/day from flue gas of CO₂ concentration 3.5–4 mol%.
• Residual fluid catalytic cracker (RFCC) unit: capture capacity of 275 tonnes CO₂/day from flue gas of CO₂ concentration 12–13 mol%.

The CHP configuration was used for a flexible operation test campaign at the TCM plant in July 2017. Using MEA solvent, three dynamic scenarios were implemented: (i) effect of steam flow rate, (ii) time varying solvent regeneration, and (iii) variable ramp rates.

In the development of flexible operation strategies, an important consideration is plant flexibility, which depends on: (i) the achievable minimum load, and (ii) ramp rate capabilities. Conventional combined cycle gas turbine (CCGT) power plants have ramp rates that range between 2–8 %P_n/min (percentage of the nominal load per min), whereas the ramp rate of gas turbines is between 8–15 %P_n (Hentschel et al., 2016). Although the power plant ramp rate limits are relatively well understood, there is a lack reliable data on ramp rate limits for CO₂ capture processes. In comparison to large or commercial scale CO₂ capture plants, small scale plants tend to have fast dynamics (Bui et al., 2016). Therefore, the scale of a CO₂ capture plant will likely have a significant impact on achievable ramp rate limits.

A comprehensive analysis of the experimental data from three CO2 capture plants combined with dynamic model evaluation has provided invaluable insight into the process dynamics. The effect of plant scale is shown to be an important factor in the flexibility of a plant as it impacts the plant response time and feasible operating range for process parameters. Based on the pilot plant and modelling analysis, we identify the key process considerations that demonstrate the greatest influence on process dynamics. Important process parameters during flexible operation include the liquid-to-gas (L/G) ratio and lean loading (function of the reboiler temperature and L/G ratio) as both directly impact CO2 absorption performance. The factors that dictate the solvent circulation rate of the system include the solvent inventory volume, liquid flow rate, also the volume of individual equipment and pipes (determines residence time). Minimising the solvent inventory or increasing solvent flow rate can provide faster solvent circulation times. The most crucial factor is the process control system, which can limit plant flexibility (e.g., restricts ramping capabilities) if not optimised for dynamic operation. The findings from this study will be essential for future design of robust flexible operation strategies and effective dynamic process control. Furthermore, we can begin to establish a correlation or function that describes the dynamic performance of a CO₂ capture process based on characteristics that describe plant scale (e.g., solvent inventory, plant volume).

References

Bui, M., Gunawan, I., Verheyen, V., Feron, P. & Meuleman, E. (2016). Flexible operation of CSIRO's post-combustion CO₂ capture pilot plant at the AGL Loy Yang power station. International Journal of Greenhouse Gas Control, 48, Part 2 (Flexible operation of carbon capture plants), 188–203.

Bui, M., Tait, P., Lucquiaud, M. & Mac Dowell, N. (2018). Dynamic operation and modelling of amine-based CO2 capture at pilot scale. International Journal of Greenhouse Gas Control, 79, 134–153.

Enaasen, N., Zangrilli, L., Mangiaracina, A., Mejdell, T., Kvamsdal, H. M. & Hillestad, M. (2014). Validation of a dynamic model of the Brindisi pilot plant. Energy Procedia, 63, 1040-1054.

Hentschel, J., Babić, U. a. & Spliethoff, H. (2016). A parametric approach for the valuation of power plant flexibility options. Energy Reports, 2, 40–47.

Mac Dowell, N. & Staffell, I. (2016). The role of flexible CCS in the UK's future energy system. International Journal of Greenhouse Gas Control, 48, Part 2 (Flexible operation of carbon capture plants), 327–344.