how costs affect deployment of low carbon technologies - analysis with jrc-eu-times
TRANSCRIPT
Joint Research Centrethe European Commission's
in-house science service
How costs affect
deployment of low
carbon technologies -
analysis with JRC-EU-
TIMES
Wouter Nijs
Institute for Energy and Transport -
Energy Technology Policy Outlook Unit
• Energy research and innovation R&I are key for achieving a low-carbon transition and a fundamental building block of the Energy Union.
• Objective of this research Provide insights for better targeting of R&I efforts by exploring the impact of techno-economic assumptions of low carbon energy supply technologies (in PPT: focus on RES-e and CCS)
Introduction and rationale
Model landscape JRC IET - Energy Technology
Policy Outlook Unit (ETPO)
Energy System Optimisation
(JRC-EU-TIMES)
Asset Optimisation Price Taker Models
(SPIRIT)
Energy Services Demand (GEM-E3)
Power System Unit Commitment
(Dispa-SET)
Weather / Demand Statistical Models
3
Land use & forestry(LUISA, CBM,
GFTM)
Regional Holistic Global Equilibrium
(RHOMOLO)
IET model
Other JRC
Hydrology(LISFLOOD)
Global Energy (TIMES-TIAM)
BIO-MASS2
WATER-FLEX3
ERIBE-LAND1
1) Project IET/IES/IPTS2) Project IET/IES/IPTS3) Proposal IET/IES (tbd)
JRC T
IMES T
RAD
E
• Technology rich bottom up energy system optimisation (partial equilibrium) model based on the TIMES model generator of the IEA for EU28, CH, IS, NO + Western Balkans
• Designed for analysing the role of energy technologies and their innovation for meeting Europe's energy and climate change related policy objectives
• Model owned and operated by the JRC
• Model horizon: 2010-2050 (2075)Available at: http://publications.jrc.ec.europa.eu/repository/handle/111111111/30469
JRC-EU-TIMES in a nutshell
Objective• Minimise total energy system costs
Constraints• Demand and supply balances by
country and sector• Capacity limits• Renewable and emission targets• …
Energy service demands
Resource availabilitiesand costs
Sectoral costs and price
proxies (by country, energy
carrier, technology)
Supply and demand
technologies
Emissions
Techno-economic
assumptions
Modelling approach
Material and energy flows
Aligned t
o late
st
EU
Energ
y R
efe
rence
Scenari
os
Policies(GHG and
energy target, subs.)
ETRI
JRC-EU-TIMES model extensions
Improved RES-e potentials
Other improvementsModel coupling
Recalibration and model updates
Coupling with other JRC models
Updated biomass potentialUpdated solar potential with explicit representation of land use Updated wind potential
Such as• Monte Carlo runs• Include retrofit options• Include biogas blending
New base year 2010+ Explicit representation of insulation options in buildings
Bioenergy in the JRC-EU-TIMES
Potentials• Agriculture (CAPRI)• Roundwood and forestry
residues (EFISCEN + now: CBM GFTM)
• Waste (Eurostat statistics linked to population and GDP)
Scenarios• Differ in land use, agricultural
practices, and protected areas.
Source: "The JRC-EU-TIMES model. Bioenergy potentials for EU and neighbouring countries."
Model resultBiomass demand is high and almost insensitive under a 80% CO2
reduction target and the assumption of carbon neutrality.
2050 potentials (PJ)
Assumptions on energy and climate targets
• Investing 12 B€ per year in PV R&D could be cost-effective if this reduces PV cost to 450-500 €/kW, cet. paribus
• PV cost is vital for PV deployment and for the energy system cost in a cost optimal low carbon energy system
How do costs affect PV deployment in EU28 ?
SET Plan Conference 2015
Every 100€/kW PV cost reduction adds 30GW in
2030
and 85GW in 2050
A bigger exercise: 50 scenarios !
The case of Geothermal: CAPEX evolution and share in power production
No CCS leads to double Geothermal generation
Geothermal power production in 2050 (TWh)
Most countries still well below 50% of the economic potential that is based on 100 EUR/MWh LCOE
Further demonstration of the outputs
• Electricity production in TWh
• Installed capacity in GW
• CAPEX requirements in EUR billion
• Energy related CO2 emissions in Mt
for scenarios: CAP, NOCCS, NOPEC + technology sensitivities
Conclusions (1)
• Technology interactions, sensitivities and possible future investments are valuable outputs for targeting of R&I efforts
• Capital intensive technologies are more sensitive
• Technology interactions and competition are crucial, even in a low carbon energy system
• Key technologies exist for cross technology sensitivity within the power sector: CCS, Bio-CCS and geothermal.
• Without CCS, the indirect use of power (Power2Gas) from variable RES becomes important
• Breakthrough levels have been defined for ocean and CSP
Conclusions (2)
• Using savings in the total energy system cost as a proxy for a possible R&I budget is powerful although partial:
• Ceteris paribus (other techs don't move)
• No link between R&I and technology improvement.
• When results of JRC-EU-TIMES were deviating from isolated cost analysis, the cause was often different commodity prices
• Uncovered but on the wish list:
• Extend analysis to demand technologies and storage
• Combinations to overcome single technology sensitivity.
Thank you for your attention!
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