Overview of CCS plant flexibility modelling

Transcription

1 Workshop on operating flexibility of power plants with CCS Imperial College London November 11 12, 2009

2 Outline 1 Motivation 2 3

3 Outline 1 Motivation 2 3

4 Novel process concept to be evaluated. Absorber Stripper Compressor Blower Reboiler HP IP LP Boiler Condenser FWP-A FWP-B FWP-C FWP-D FWP-E FWP-F FWP-G

5 Cost of CO 2 avoided oft-used performance metric. Cost of CO 2 avoided CCA = (CoE) cap (CoE) ref (CEI) ref (CEI) cap where Cost of Electricity can be expressed as: annualized capital cost + FOM CoE = + VOM e + fuel cost per annual energy output unit energy Need a method to predict unit utilization: annual energy output fuel cost per unit energy CO 2 emissions intensity Need to assess benefit of operating flexibility

6 Process modelling + electricity system simulation. Three-step process: 1 Modelling and simulation of generating unit with CCS 2 Simulation of electricity system 3

7 Outline Motivation 1 Motivation 2 3

8 Outline Motivation 1 Motivation 2 3

9 Develop process model of generating unit with CCS. Exple workflow: Blower Stripper Absorber Reboiler Compressor 1 develop model of boiler and ste cycle from heat design balance at 50%, 75%, and 100% load HP IP LP 2 design PCC process to recover 85% of CO 2 at nominal load Boiler FWP A FWP B FWP C FWP D FWP E FWP F FWP G Condensor 3 integrate PCC process and generating unit models 4 characterize part-load performance of integrated unit

10 Objective is to find Pareto frontier of integrated unit. Stripper Absorber Compressor interested in the relationship between: Blower Reboiler HP IP LP 1 heat input to boiler ( q) 2 CO 2 recovery (x CO2 ) 3 net unit power output (E net) E net = f ` q, x CO2,... Boiler FWP A FWP B FWP C FWP D FWP E FWP F FWP G Condensor only interested in the best performance (i.e., Pareto frontier) Find E net for feasible combinations of q and x CO2.

11 Pareto frontier for generating unit with CCS. Enet / MWe x load CO 2 recovery Developed model describing Pareto frontier using linear regression: q = f `E net, x CO2

12 Summary of data requirements for novel process. Key unit pareters: Boiler Stripper Absorber Compressor Blower Reboiler HP IP LP FWP B FWP A FWP C FWP D FWP E FWP F FWP G Condensor incremental heat rate minimum and maximum power output start-up heat input rp rates minimum up- and downtimes fuel cost Initial assumption is that CO 2 capture process dynics are fast.

13 Outline Motivation 1 Motivation 2 3

14 ACME ACME ACME ACME ACME ACME ACME ACME ACME ACME ACME ACME Motivation Analysis is electricity system-specific. Aston (17) 400 Astor (18) Attlee (21) Aubrey (22) Austen (23) Grigg et al. The IEEE Reliability Test System 1996, IEEE Transactions on Power Systems, 14(3): , August Asser (16) Arthur (15) Arnold (14) Avery (24) Attar Attila (19) (20) Arne (13) Anna (11) Archer (12) Adler (3) Ali (9) Allen (10) Alber (6) Agricola (4) Aiken (5) Alger (8) Legend #6 fuel oil conventional ste #2 fuel oil combustion turbine hydroelectric w/ reservoir coal fired conventional ste Exple workflow: 1 Incorporate novel process into electricity system. 2 Simulate system operation. 3 Analyze simulation results. Abel (1) Ads (2) Alder (7) thermal nuclear

15 Motivation Novel process added to electricity system Astor (18) Attlee (21) Aubrey (22) Aston (17) Austen (23) Asser (16) Attar (19) Attila (20) Arthur (15) Arnold (14) Avery (24) Arne (13) Anna (11) Archer (12) Legend Adler (3) Ali (9) Allen (10) Alber (6) Agricola (4) oil fired conventional ste natural gas combustion turbine hydroelectric w/ reservoir MEA (monoethanoline)-based PCC (Post-Combustion Capture) added to e coal-fired unit at Austen plant load and CO 2 recovery are flexible Aiken (5) Alger (8) coal fired conventional ste Abel (1) Ads (2) Alder (7) thermal nuclear ine based CO2 capture

16 Motivation Electricity system operation simulated Aston (17) 155 Asser (16) Astor (18) Attlee (21) Aubrey (22) Austen (23) Attar Attila (19) (20) Electricity demand / MWh Arthur (15) Arnold (14) Avery (24) Arne (13) Anna (11) Archer (12) Legend Adler (3) Ali (9) Allen (10) Alber (6) Agricola (4) Aiken (5) Alger (8) Abel (1) Ads (2) Alder (7) oil fired conventional ste natural gas combustion turbine hydroelectric w/ reservoir coal fired conventional ste thermal nuclear ine based CO2 capture Mon Tue Wed Thu Fri Time of Day Sat Sun Mon c COLIN ALIE, 2009 For each time period, select units that will satisfy: demand reserve requirement physical constraints on equipment such that overall benefit is maximized

17 Outline Motivation 1 Motivation 2 3

18 Cost of CO 2 avoided estimate is easily had. Cost of CO 2 avoided CCA = (CoE) cap (CoE) ref (CEI) ref (CEI) cap where Cost of Electricity can be expressed as: annualized capital cost + FOM CoE = + VOM e + fuel cost per annual energy output unit energy Simulation directly provides: Cost of Electricity CO 2 Emissions Intensity so estimate of Cost of CO 2 Avoided is readily obtained, if desired.

19 At $40/tonne, flexible case delivers least power base fixed flexible Real power output / MWe pm pm 2 Time of day pm 4 pm 6 pm 8 10 pm 12

20 Flexible case commits more to reserve markets. Reserve power / MWe base flexible pm pm 2 Time of day pm 4 pm 6 pm 8 10 pm 12

21 Overall utilization similar: base vs flexible. Real power committed / MWe pm pm 2 Time of day base fixed flexible pm 4 pm 6 pm 8 pm Utilization is similar between base case and flexible case. However, flexible case has better economics as costs are lower Cost of CO 2 avoided wouldn t reflect this

22 Outline 1 Motivation 2 3

23 Summary and future work Able to quantify benefits from operating flexibility. Operating flexibility shifted capacity from energy market to reserve markets. Assessment of dynic performance needs to be included! Sensitivity analysis.

24 Acknowledgements National Sciences and Engineering Research Council (Canada) Eric Croiset, Peter Douglas, Ali Ekel University of Waterloo Paul Grah Energy Technology Division, CSIRO