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Long-term energy system modelling with improved resolution to address short-term implications

IEA-ETSAP
IEA-ETSAP

Long-term energy system modelling with improved resolution to address short-term implications Dr. Xiufeng Yue, University College Cork

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Long-term energy planning towards 100% renewable
electricity in Ireland with considerations in short
term constraints
Xiufeng Yue, Brian O Gallachoir, James Glynn
ETSAP Workshop (Dec 17, 2020)
University College Cork, Ireland
Introduction
Background
• Many studies proposing 100% renewable energy system(Jacobson et al., 2017)
• 100% Energy system(Lund and Connolly, 2012) and optimal pathways(Yue et al., 2020) projected for Ireland
• Long-term energy systems pathways overlook short-term constraints
➢ Stylized Temporal Resolution (Seasons, Day/Night/Peak)
➢ Soft-link has convergence/optimality Issues
Method
We model power sector of Ireland using TIMES model with improved temporal, technical and spatial details
Research Question
• Pathways of a power system consistent with system-wide 100% renewable energy by 2050
➢ Electricity output, curtailment, hydrogen, storage, etc.
• Impact of increased number of timeslices
• Impact of adding unit commitment features (ramp rate, cycling costs)
TIMES-Ireland Power Sector Model
Temporal Resolution
Timeslices
• 16TS (4 Seasons - Day/Night/Peak/Evening)
• 576TS (12 months – Weekday/Weekend – 24 hours)
ELC Demand Profile
• Real time historical Hourly Data
Availability factor
• Wind and solar – Historical data
• Wave – based on hourly buoy data and power matrix
24 Hours
Technical Details
• Dispatchable power plants modelled by individual turbines instead of by process capacity
• Unit Commitment Features Considered
Spatial Resolution
Connection costs of onshore wind based on GIS
• Wind farms regionalized based on connection costs
• Connection cost data of potential wind farm sites based
on 1938 GIS parcels
• Modelling wind farms individually increases model size
exponentially
• Connection costs modelled step-wise
Locations of existing dispatchable plants in Ireland

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Long-term energy system modelling with improved resolution to address short-term implications

  • 1. Long-term energy planning towards 100% renewable electricity in Ireland with considerations in short term constraints Xiufeng Yue, Brian O Gallachoir, James Glynn ETSAP Workshop (Dec 17, 2020) University College Cork, Ireland
  • 2. Introduction Background • Many studies proposing 100% renewable energy system(Jacobson et al., 2017) • 100% Energy system(Lund and Connolly, 2012) and optimal pathways(Yue et al., 2020) projected for Ireland • Long-term energy systems pathways overlook short-term constraints ➢ Stylized Temporal Resolution (Seasons, Day/Night/Peak) ➢ Soft-link has convergence/optimality Issues Method We model power sector of Ireland using TIMES model with improved temporal, technical and spatial details Research Question • Pathways of a power system consistent with system-wide 100% renewable energy by 2050 ➢ Electricity output, curtailment, hydrogen, storage, etc. • Impact of increased number of timeslices • Impact of adding unit commitment features (ramp rate, cycling costs)
  • 4. Temporal Resolution Timeslices • 16TS (4 Seasons - Day/Night/Peak/Evening) • 576TS (12 months – Weekday/Weekend – 24 hours) ELC Demand Profile • Real time historical Hourly Data Availability factor • Wind and solar – Historical data • Wave – based on hourly buoy data and power matrix 24 Hours
  • 5. Technical Details • Dispatchable power plants modelled by individual turbines instead of by process capacity • Unit Commitment Features Considered
  • 6. Spatial Resolution Connection costs of onshore wind based on GIS • Wind farms regionalized based on connection costs • Connection cost data of potential wind farm sites based on 1938 GIS parcels • Modelling wind farms individually increases model size exponentially • Connection costs modelled step-wise Locations of existing dispatchable plants in Ireland
  • 7. Scenarios Intermittency: 70% VRES limit by 2030 and 100% by 2050 RE% target: 70% renewables by 2030 No Coal from 2030 (Climate Action Plan) 100% renewable by 2050 Electricity Demand: linearly forecasted based on Generation Capacity Statement (305PJ by 2050) Hydrogen Demand: Based on previous analysis (Yue et al., 2020) with TIMES 1.0 under assumption of no bioenergy import & 100% renewable Demand profile assumed uniform (65PJ by 2050) 576 time slices 12Months,WD/WN,24Hours 16 time slices 4 seasons, Day/Evening/Peak/Night Demand/AF Aggregated from 576TS model No constraint on RE% 576TS 16TS No constraint on RE% Unit Commitment Features 576TS-UC 16TS-UC 100% RE by 2050 576TS-RE 16TS-RE 100% RE by 2050 Unit Commitment Features 576TS-UC-RE 16TS-UC-RE
  • 8. No Policy Constraint Electricity production Pathway 100% Renewable Target Unit Commitment: Impact on dispatchable generation ~1% Adding time slices: dispatchable generation 12% in 2050 Unit Commitment Impact ~1% Adding time slices: 37% increase in dispatchable H2 power plants Pathway Changes from Unit Commitment Changes from adding time slices Pathway Changes from Unit Commitment Changes from adding time slices
  • 9. Hydrogen storage + H2 power plants contribute to system flexibility Increasing temporal resolution shifts towards lower VRES and higher dispatchable generation Electricity production Pathway Electricity Production from Hydrogen when VRES is low and demand is high Hydrogen Produced when VRES is high
  • 10. Wind Production In each time slice, actual and available output of onshore wind compared No curtailment found in the results
  • 11. Energy Storage Hydrogen Storage 16TS: Mainly capture day/night variation from solar 576TS: Better captures variation from wind/ocean
  • 12. Impacts from Unit Commitment Applying Unit Commitment results in less variation in dispatchable generation Unit Commitment Cost accounts for~10% of O&M costs of dispatchable power plants
  • 13. Conclusions Policy Insights • 100% renewable energy is feasible for Ireland with current resource potentials (which is more conservative than JRC estimates) • Wind & Ocean will play a significant role • H2 generation could play an important role under 100% renewable Modelling Insights Impact of increasing temporal resolution 16TS => 576TS • Moderate on generation mix (10% difference on dispatchable/VRES ratio) • Significant on energy storage requirements. . • Better captures effect from unit commitment features of dispatchable power plants • Solution Time increases from <1 minute to ~8 hours, may not be feasible for models with large number of processes/regions
  • 14. Questions? Xiufeng Yue xiufeng.yue@ucc.ie University College Cork, Ireland www.marei.ie/project/chimera The authors also acknowledge funding support of the CHIMERA project funded by the National Natural Science Foundation of China (NSFC) under the SFI- NSFC Partnership Programme Grant Number 17/NSFC/5181.