Post on 30-Jul-2020
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The role of CCS in UK's power sector decarbonisation using high spatial and temporal resolution modelling
Praveen Bainsa, Clara F. Heubergera,b, Niall Mac Dowella,b,*a Centre for Environmental Policy, b Centre for Process Systems Engineering
• Electricity demand• Reserve requirements• Inertia requirements • Emission target
min { CAPEX + mode-specific OPEX }
• System capacities design• Power dispatch• Reserve and inertia provision • Carbon emissions by technology • Flexibility of power generating units• Detailed capital and operational costs
References[1] Heuberger, C.; Rubin, E.S.; Staffel, I.; Shah, N. and Mac Dowell, N. (2017) “Power capacity expansion planning considering endogenous technological learning”, Applied Energy: Vol 204, pp 831-845. http://dx.doi.org/10.1016/j.apenergy.2017.07.075[2] Strbac, G.; Kirschen, D. and Moreno, R. (2016), “Reliability Standards for the Operation and Planning of Future Electricity Networks”, Foundations and Trends in Electric Energy Systems: Vol. 1, No. 3, pp 143–219. DOI: 10.1561/3100000001. [3] Pfenninger, S. and Staffel, I. Renewables.ninja. www.renewables.ninja
Fig. 1: Zonal design and representative transmission network for Great Britain [2]
System-wide constraints
Tech.-wise constraints
Integer scheduling
Objective
System design
The maps above illustrate the new capabilities of ESONE. We see an immediate increase in power imported from the south, and see increased power flowing from Scotland to England as offshore wind comes online. In terms of CCS, we see CCGT-CCS and BECCS built by the end of 2050, mostly in southern Scotland and across England, but they are hardly utilised. They mainly function as low carbon backup for a mostly renewable fleet, and provide ancillary services to the grid.
Motivation Typical energy system capacity expansion models consider resources aggregated at the national scale. But how do we capture the nuance of energy factors that are highly site-specific?
What type of power technologies should be built?
When should they be built?
ESONE: Spatially-explicit electricity system optimisation
We built a mixed-integer linear program (MILP) which simultaneously optimises the electricity system design and operation.
ESONE Capabilities: when and where does CCS come into play?
AcknowledgementsWe thank the IEA Greenhouse Gas R&D Programme (IEAGHG) and MESMERISE-CCS by the Engineering and Physical Sciences Research Council (EPSRC) under grant EP/M001369/1 for the funding of this work. We acknowledge financial support of the UK CCS Research Centre. The UKCCSRC is funded by the EPSRC as part of the RCUK Energy Programme.
Mathematical Description:
Where should they be built?
How should they be operated?
*Corresponding author, Tel.: +44 (0)20 7594 9298; E-mail: niall@imperial.ac.uk
• Transmission between zonesTransmission
Annual Capacity Installed (GW) Annual Power Generated (TWh) Annual Power Flow (TWh)
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Resource availability was determined using average of multiple points within each zone
Used k-means clustering to calculate 10 representative days + peak demand day for each zone
chosen day
centroid
Data Preparation
Fig. 2: Example of a cluster of time dependent input data for a single zone [3]
• Continue to validate ESONE model and finalise base case.• Investigate the impact of regional electric vehicle growth rates, charging
patterns and infrastructure installed• Explore the value of tidal energy in an emissions-constrained energy system
Future Work
Fig. 3: A snapshot of the total installed capacity (right) and average annual capacity utilisation rate (left) for each 5-year time step over the entire optimisation time horizon. Carbon emissions are exogenously constrained on production (do not include imported electricity).
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