A generalized framework for evaluating the performance of CO2 capture processes Colin Alie1 , Peter Douglas, Eric Croiset Department of Chemical Engineering University of Waterloo Waterloo, Ontario, Canada N2L 3G1
Nomenclature Variables CCA cost of CO2 avoided, $/tonne CO2 CEI
CO2 emissions intensity, tonne CO2 /MWhe
CoE
cost of electricity, $/MWhe
FOM fixed operating and maintenance cost, $/year VOMCO2 CO2 capture variable operating and maintenance costs (excluding fuel), $/tonne CO2 VOMe generator variable operating and maintenance costs (excluding fuel), $/MWhe Subscripts cap
pertaining to case with CO2 capture
ref
pertaining to reference case
1 Introduction Different CO2 capture processes are usually compared on the basis of CCC (Cost of CO2 Capture) (e.g., Mariz et al.[1], David Singh [2]): ´ ! Ã annualized + FOM fuel cost per capital cost unit mass + VOMCO2 + CCC = mass CO2 recovered per year CO2 recovered ³
1 Corresponding
Author:
[email protected], +1 416-879-3036
1
(1)
or, more often as of late, CCA (Cost of CO2 Avoided) (e.g., Paitoon et al. [3], Guillermo OrdoricaGarcia [4], Rao and Rubin [5]):
CCA =
(CoE)cap − (CoE)ref (CEI)ref − (CEI)cap
(2)
with cost of electricity given by:
CoE =
³
´ annualized + FOM ³ ´ capital cost cost per +VOMe + fuel unit energy annual energy output
(3)
and CEI (CO2 Emissions Intensity) expressed as: CEI =
CO2 emissions rate net plant output
(4)
In reviewing the literature, two fundamental problems have been observed with the use of Equations 1 through 4: 1. It is assumed that power plants operate at their MCR (Maximum Continuous Rating) and are nearly fully committed. A sampling of the generator capability disclosure reports in the Ontario electricity market revealed the following truths: why these two cases only?
• power output from coal units can vary substantially from hour to hour • coal units that are nominally identical can have substantially different loads Also, in a deregulated, competitive market, a unit’s power output is an indeterminate function of its marginal cost of operation relative to that of all other generators and its technical operating characteristics. Therefore, for a new plant or a heavily-modified existing unit, predicting the utilization is very difficult. 2. It is assumed that the CO2 recovery factor of a plant can be known in advance. The fraction of CO2 recovered in any one time period is strongly dependent upon market forces. When electricity demand is high, the value of producing electricity will be greater than the value of capturing CO2 and CO2 recovery should decrease. And, after prolonged periods of high-CO2 emissions, the value of capturing CO2 will be greater than the value of producing electricity and CO2 recovery will increase. It is, however, impossible to immediately predict when or how often these conditions will persist. The implication of these two problems is that the CCC and CCA may fail as a metric for evaluating the performance of CO2 capture processes. It is proposed that the aforementioned problems can be avoided by explicitly considering the operation of the electricity system. When this is the case: • No assumptions have to be made regarding the utilization of new processes. The dynamic performance of all power plants is simulated and the utilization is an output of the model and not an input.
2
• The reference case is the entire electricity system. It has been shown that considerable bias can be introduced into techno-economic studies of CO2 capture processes through the selection of the reference plant [6, 4].
2 Modelling
include a compete description of Figure 1.
i.e. 24 buss grid, mix of generation types To test the merits of the new approach, a case study is performed using ‘Area A’ from the IEEE etc. ect. Reliability Test System 1996 [7] as the basis. This represents an electricity system of reasonable diagram willl not size with a mix of generation technologies and fuels. The busexplain diagram and(chem. a briefeng. description of understand this system is presented in Figure 1.
move all figures to the end of the paper.
• 24-bus grid – 10 supply nodes – 17 demand nodes • mix of generation types – conventional steam – combustion turbine – nuclear – hydro • mix of fuels – #2 and #6 fuel oil – coal – uranium
Figure 1: IEEE Reliability Test System 1996 [7] Three scenarios are evaluated: 1. No changes to the configuration of the electricity system. 2. MEA (monoethanolamine)-based CO2 capture process installed at 350 MWe coal-fired generator (code-named Avery) with CO2 recovery fixed at 85%. 3
3. MEA-based CO2 capture process installed at 350 MWe coal-fired generator with variable CO2 recovery fixed. For each scenario, the operation of the electricity system is simulated. To meet demand in each hour, the generators are dispatched in such a way that total generation cost is minimized while maintaining CO2 emissions at or below the imposed limit. Several simplifying assumptions are made: • The economic dispatch is taken as a proxy for the system operation. In reality, there will be differences between the generation schedule and the actual system behaviour. • Only real Ipower flows considered and second-order of the and cosine think that you are should insert a section in the Modelling approximations section that describes howsine you solved the model i.e. include the model equations or references to them; how you solved them i.e GAMS terms in the AC power flow equation are used. discuss the Objective Function and constraints as well as the model for the CO2 capture • MinimumYou up-should and down-time constrains are ignored. process.
A relationship between the power plant de-rate associated with CO2 capture andthe fraction of CO2 recovered is obtained using Aspen Plus® .2
3 Results Figure 2 shows the sensitivity of generation cost and the marginal value of CO2 to the extent of CO2 mitigation. The BAU (Business As Usual) emissions correspond to the quantity of CO2 emitted prior to the existence of a CO2 emissions limit. From Figure 2(a) it is observed that Average generation cost / $/MWh
no CO2 capture CO2 capture 10.5 fixed flexible CO2 capture 10.0 9.5 9.0
200.0 Marginal CO2 cost / $/tonne CO2
11.0
no CO2 capture fixed CO2 capture flexible CO2 capture
150.0
100.0
8.5
You should describe in detail what each Figure is. Explain what the Y-axis is.
8.0
What is happening at % CO2 = 0% and 10% and 35%.
7.5 0.00
0.40 0.05 0.10 0.15 0.20 0.25 0.30 0.35that I think you CO2 reduction, fraction of BAU emissions
50.0
0.0
0.10 0.15 on 0.20each 0.30 0.35 0.25scenario. should0.00 have0.05 a sub-section
0.40
CO2 reduction, fraction of BAU emissions
(a) Sensitivity of generation cost to CO2 mitiga(b) Sensitivity of marginal CO2 value to CO2 mitAlso I think that you should include the Figures that were on the poster that tion target igation target showed the operation of the generating station with CCS on it in each of the the 3 scenarios.
Figure 2: Sensitivity of average cost of electricity and marginal value of CO2 to CO2 emission reduction limit • It was possible to reduce CO2 emissions by up to 20% by simply rescheduling power generation among existing units. With one CO2 fixed-capture process installed, it is possible to reduce CO2 emissions by up to 34%; with a flexible-capture process, a reduction of 36% is doable. • Without CO2 capture, even small reductions in CO2 emissions cause a noticeable increase in the cost of power generation. 2 See
[8] for a detailed description of the process models. Due to space restrictions, it is not possible to include the precise formulation of the scheduling model. Please contact the corresponding author for more detailed information.
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• With CO2 capture, it is possible to achieve a significant reduction in CO2 emissions with a negligible increase in the average cost of electricity generation. The optimal value of the dual variable of the CO2 emissions constraint represents the marginal value of CO2 for a particular scenario. Figure 2(b) shows the sensitivity of the marginal value of CO2 to the CO2 mitigation target. Given what was observed in Figure 2(a), it should come as no surprise that the shadow price of CO2 in the no-capture scenario increases dramatically faster as greater CO2 emission reductions are enforced versus the cases where CO2 capture is an option. To borrow an analogy from chemistry, CO2 capture buffers generation and CO2 cost against changes in CO2 emission limits. Ultimately, as the system approaches its minimum emissions intensity, the costs increase asymptotically. Having CO2 capture within the system allows greater emission reductions to occur prior to this cost explosion.
Average generation cost / $/MWh
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.00
0.10 0.20 0.30 0.05 0.15 0.25 CO2 reduction target, fraction of BAU emissions
0.35
Marginal CO2 cost difference / $/tonne CO2
Figure 3 attempts to demonstrate the benefit of variable CO2 recovery in terms of the cost of electricity and the marginal value of CO2 experienced by the system. In Figure 3(a), the difference in average generation cost between the fixed- and flexible-capture scenarios is plotted as a function of reduction in CO2 emissions:
(a) Sensitivity of generation cost difference to CO2 mitigation target
30.0 25.0 20.0 15.0 10.0 5.0 0.0 −5.0 0.00
0.10 0.20 0.30 0.05 0.15 0.25 CO2 reduction, fraction of BAU emissions
0.35
(b) Sensitivity of marginal CO2 value difference to CO2 mitigation target
Figure 3: Benefit of flexible CO2 capture in regards to average cost of electricity and marginal value of CO2 • Initially, the flexible-capture case provides electricity at a slightly lower average cost. In the fixed-capture case, the marginal cost of power generation at the Avery coal-fired generating station increases and its capacity decreases because it is constrained to always capturing 85% of the CO2 that it generates. So while the fraction of its capacity that is asked to produce does not markedly change, this amounts to less overall power and at a greater price. This contrasts with the flexible-capture scenario where the same coal unit is dispatched but does not capture CO2 and thus produces power more cheaply. • As the CO2 emission limit increases, the difference between average generation cost of the two scenarios decreases. In the flexible-capture case, an increasing fraction of the CO2 emissions at the Avery coal-fired unit is captured bringing the average generation cost of this unit more closely aligned with that observed in the fixed-capture case. In the fixed-capture case, because the CO2 emissions constraint does not become binding until a reduction of 13% is required, the generation cost is essentially constant.
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• The difference between average generation cost of the two scenarios experiences a minimum at a reduction target of 0.17. The flexible-capture case is always strictly lower-cost then the fixed-capture case, as is expected. • After this minimum, the difference between average generation cost of the two scenarios increases quickly, first linearly and then exponentially, with increasing CO2 mitigation requirements. From this point, low-cost but high CO2 -intensity generation is shunned for more CO2 -friendly power. As was seen in Figure 2(a), every scenario ultimately experiences a rapid rise in average generation cost when the CO2 emission reduction target becomes stringent enough. The flexible-capture case fares better because it has the ability to capture the full quantity of CO2 emissions that are produced from the Avery coal-fired unit whereas the fixed-capture case is limited to capturing only 85% of the CO2 that is produced. Figure 3(b) shows the difference between the marginal value of CO2 between the two scenarios as a function of CO2 emission mitigation target. • Below a reduction target of 0.17, the difference between the two scenarios is negligible. • Above a CO2 mitigation reduction target of 0.17, the absolute difference in the marginal value of CO2 becomes significant and tends to increase as the CO2 mitigation target increases.
4 Conclusions This paper discusses the potential benefits of an approach for evaluating the performance of CO2 capture that explicitly considers the operation of the electricity system. The approach allows for CCA to be calculated without needing to a priori set parameters for power plant utilization or the Reference = paperof in Energy Conversion and Management fraction CO2 recovered. Reference= Energy Conversion and Management
List of References [1] Mariz, C., Ward, L., Ganong, G., and Hargrave, R. Cost of CO2 recovery and transmission for EOR from boiler stack gas. In Riemer, P. and Wokaun, A., editors, Greenhouse Gas Control Technologies: Proceedings of the 4th International Conference on Greenhouse Gas Control Technologies. Elsevier Science Ltd., April 1999. 1 [2] Singh, D. J. Simulation of CO2 capture strategies for an existing coal fired power plant - MEA scrubbing versus O2 /CO2 recycle combustion. Master’s thesis, University of Waterloo, 2001. 1 [3] Tontiwachwuthikul, P., Chan, C., Kritpiphat, W., DeMontigny, D., Skoropad, D., Gelowitz, D., Aroonwilas, A., Mourits, F., Wilson, M., and Ward, L. Large scale carbon dioxide production from coal-fired power stations for enhanced oil recovery: a new economic feasibility study. Journal of Canadian Petroleum Technology, 37(11):48–55, November 1998. 2 [4] Ordorica-Garcia, J. G. Evaluation of combined-cycle power plants for CO2 avoidance. Master’s thesis, University of Waterloo, Waterloo, Ontario, Canada, 2003. 2, 3
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[5] Rao, A. B. and Rubin, E. S. A technical, economic, and environmental assessment of aminebased CO2 capture technology for power plant greehouse gas control. Environmental Science and Technology, 36(20):4467–4475, 2002. 2 [6] Rubin, E. S. and Rao, A. B. Uncertainties in CO2 capture and sequestration costs. In Gale, J. and Kaya, Y., editors, Greenhouse Gas Control Technologies: Proceedings of the 6th International Conference on Greenhouse Gas Control Technologies, volume 2, pages 1119– 1124. Elsevier Science Ltd., October 2002. 3 [7] Grigg, C., Wong, P., Albrecht, P., ad M. Bhavaraju, R. A., Billinton, R., Chen, Q., Fong, C., Haddad, S., Kuruganty, S., Li, W., Mukerji, R., Patton, D., Rau, N., Reppen, D., Schneider, A., Shahidehpour, M., and Singh, C. The IEEE reliability test system — 1996. IEEE Transactions on Power Systems, 14(3):1010–1021, August 1999. 3 [8] Alie, C. CO2 capture with MEA: integrating the absorption process and steam cycle of an existing coal-fired power plant. Master’s thesis, University of Waterloo, Waterloo, Ontario, Canada, 2004. 4
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