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Interactions and Implications of Renewable and Climate Change Policy on UK Energy Scenarios

Interactions and Implications of Renewable and Climate Change Policy on UK Energy Scenarios. Dr. Gabrial Anandarajah, Dr. Neil Strachan King’s College London IEW2009 - Venice - 17 th June 2009 gabrial.anandarajah@kcl.ac.uk , neil.strachan@kcl.ac.uk. Content. Introduction UK MARKAL model

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Interactions and Implications of Renewable and Climate Change Policy on UK Energy Scenarios

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  1. Interactions and Implications of Renewable and Climate Change Policy on UK Energy Scenarios Dr. Gabrial Anandarajah, Dr. Neil Strachan King’s College London IEW2009 - Venice - 17th June 2009 gabrial.anandarajah@kcl.ac.uk, neil.strachan@kcl.ac.uk

  2. Content • Introduction • UK MARKAL model • Scenario definition • Selected results • Conclusions

  3. Introduction • UK Government has set the target of 80% CO2 reduction at 1990 level by 2050 • EU renewable directive: • 20% renewables in EU’s final energy consumption • UK’s contribution to this should be to increase the share of renewables to 15% by 2020 • Two major renewable policies in UK • Renewable Obligations (RO) • A certain percentage of all electricity generation should be from renewables • Renewable Transport Fuel Obligations (RTFO) • A certain percentage of sales (road transport fuels) are made up of bio-fuels • This paper analyses interaction and implications of renewable and climate change policies on UK energy scenarios

  4. UK MARKAL Model • An elastic demand version of the UK MARKAL (MED) model has been used to analyse the Low Carbon Scenarios in UK • What is MARKAL? • MARKAL (acronym for MARKetALlocation) is a widely-applied, perfect foresight, technology detailed linear programming (LP) optimisation model • MARKAL’s objective function is to minimise discounted total energy system cost • It is an integrated energy system model • Standard MARKAL model • Fixed energy service demand (exogenous demand) • MARKAL (MED) model • Energy service demand changes along the stepped linear representation of demand function (endogenous demand curve). Own price elasticity: (D/D0) = (P/P0)-E • Maximises total societal welfare (producer + consumer surpluses)

  5. Assumptions & Calibration Notes • Calibrated in its base year (2000) to DUKES data within 1% of actual resource supplies, energy consumption, electricity output, installed technology capacity and CO2 emissions • All existing policy measures as of EWP 2007 are implemented • Other than EU-ETS (€20/t-CO2) no carbon price is included • Resource price in line with higher revisions from IEA, BERR • 10% global discount rate and technology specific 'hurdle' rates on future transport technology and on building conservation and efficiency options are applied. • The hurdle rates apply only to capital costs and thus effectively increases the investment barriers to these efficiency technology. Set at 15%, 20% and 25%. These hurdle rates represent information unavailability, non price determinants for purchases and market imperfections • Elasticity values: taken from different literatures.

  6. Scenarios • Reference Scenario (RS): • No CO2 constraint and RO and RTFO are kept at level of 15% and 5% respectively from 2015 • Low Carbon Scenario (LCS): • CO2 emission is constrained to 26% in 2020 and 80% in 2050 • Renewable Policy Scenario (RPS): • the RO has been increased by 5% in each successive runs to 50% starting from the Reference Case values of 15% from 2020. • The RTFO has been increased from 5% to 20% with steps of 5% in each successive run. • All other conditions are same as in RS • Low Carbon Renewable Scenario (LCRS): • combinations of LCS and RPS

  7. CO2 Emissions • If new policies/measures are not taken, base case CO2 emissions in 2050 would be 584 MtCO2: 6% higher than 2000 levels and 1% lower than 1990 levels. • Existing policies and technologies would bring down emissions in 2020 to about 500 MtCO2 - a 15% reduction. • Decarbonisation is foremost in the power sector till the middle or end of the projection period • Then major efforts switch to the residential/transport sector/service sectors

  8. Sectoral CO2 emissions in RPS • When the RO is increased, CO2 emission decreases • RO can reduce the CO2 emissions by 26% and 20% in 2020 and 2050 respectively • When RTFO is increased, transport sector CO2 emissions is further reduced from 134 MtCO2 to 112 MtCO2 in 2020. • RO and RTFO together can reduce CO2 emission by 30% in 2020 Sectoral CO2 emissions at 5% RTFO Sectoral CO2 emissions at 20% RTFO

  9. Electricity generation mix (RS, LCS, RPS) • Till the middle, end-use sector decarbonisation is mainly by efficiency improvements and demand reduction • During the latter period, end-use sectors’ decarbonisation is mainly by electrification • When the RO is increased, end-use sectors’ demand for expensive electricity decreases in 2050

  10. Electricity generation mix in LRPS • RO increases the share of wind and coal generation in 2020 and reduces gas and coal-CCS generation • RTFO further increases the electricity generation from coal in 2020

  11. Decarbonisation of End-use Sectors • The residential sector is decarbonised by shifting to electricity (from gas) as well as technology switching from boilers to heat pumps for space heating and hot water heating. • The transport sector is decarbonised by fuel switching: hybrid, hybrid plug-in (diesel and petrol), ethanol, bio-diesl, hydrogen and battery operated vehicles. • The service sector is decarbonised by shifting to electricity. • Besides efficiency and fuel switching (and technology shifting), the elasticity (demand reduction) is also plays a major role in reducing CO2 emissions by reducing energy service demand (5% - 25% by scenario and by ESD)

  12. Bio-fuel demand • In the Reference Scenario: • 11 PJ and 14 PJ of biomass is selected for residential and services sector heating while transport sector consumes 70 PJ of biomass in 2020 to meet the RTFO of 5%. • In 2050, transport sector biomass consumption is to meet the RTFO target • In RPS, the transport sector demands 175, 262 and 349 PJ of bio-fuels at the RTFO levels of 10%, 15% and 20%, respectively. • When the CO2 emission is constrained in LCS: • bio-fuel is critical in transport sector • about half of the transport fuel consumption is bio-fuel • In LCRS, • The share of bio-fuel increases in 2020 to meet the RTFO targets (20%) • No significant change in the share of bio-fuel in 2050

  13. EU Renewable Directive • Table above shows the share of renewable in final energy demand • The LCS didn’t meet the EU renewable directive • EU renewable directive can be met: • -at 35% and 20% of RO and RTFO respectively • -or at 40% and 15% of RO and RTFO respectively • -these scenario will also reduce the 2020 emissions by 30%

  14. Economic implications • Marginal carbon price varies from £165 to £183/t-CO2 across the scenarios in 2050. • Demand reduction levels are in the range of 0-5% in 2020 and 5%-25% in 2050 across the scenarios. • Societal welfare losses (change in consumer + producer surplus) are up to £7 billion in 2020 and £40 billion in 2050 in 2000 prices. • Incremental cost that is the difference in total discounted system cost to meet the EU directive is only a couple of billion pounds in 2000 prices. • But cost of implementing the RTFO policy will relatively be high and challenging.

  15. Conclusions • RO will increase the electricity prices leading to less electricity demand from end-use sectors. • Power sector decarbonisation occurs early and it is critical • There are trade-off in sectoral emissions between power and transport when the RTFO is increased. • LCS will not meet the EU renewable directive • Renewable policies (RO and RTFO) can meet the EU renewable directive and short-term climate change target, but not long term • Great challenge in implementing RTFO is ensuring production of bio-fuel sustainably with minimum environmental impacts. • Engineering challenge is electricity grid with increased share of intermittent sources at high RO.

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