The European Commissions science and knowledge service

Joint Research Centre

Economic models for energy systems

IAEA Technical Meeting TM-52285

Amsterdam, 23rd June 2016

Andreas ZUCKER Institute for Energy and Transport

Energy Technology Policy Outlook Unit

2

Content

Energy and power system models

The role of storage

Economics of storage

Conclusion

3

The JRC develops models for the energy system and interlinked sectors

3

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

Land use & forestry (LUISA, CBM,

GFTM)

Regional Holistic Global Equilibrium

(RHOMOLO)

IET model Other JRC

Hydrology (LISFLOOD)

Global Energy (TIMES-TIAM)

Model landscape

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Objective Minimise total energy system costs

Constraints Demand and supply balances:

Transport, industry, buildings, agriculture - primary energy (RES, fossils), refineries and electricity

Impacts of high variable RES-e Flexible use possible excess RES-e:

curtailment, Power2gas and storage Reduced operation dispatch. power

Energy services demands

(pkm, tkm, PJ, Mt)

Resources and costs

Technology costs (O&M, investments)

Supply and demand

technologies

Emissions (t CO2) and

prices

Technologies

The JRC-EU-TIMES model optimises the energy system over long time periods

Material and energy flows

Alig

ned

to la

test

EU

En

ergy

Ref

eren

ce

Sce

nari

os

Policies (GHG and energy

target, subs.)

ETRI

JRC-EU-TIMES model logic

5

JRC-EU-TIMES captures the time dimension in time slices and sub-periods

SP SU FA WI

SP

Day

SP

Nig

ht

SP

Peak

SU

Day

SU

Nig

ht

SU

Pea

k

FA D

ay

FA N

ight

FA P

eak

WI

Day

WI

Nig

ht

WI

Peak

Period 3 Period 9 BY

Seasons

Part of the day

Model horizon

Milestone years

2 subperiods in the power sector

Excess Variable Renewable-E

One timeslice

Demand

2010 2015 2060

Period 8

2050

Period 4

2020 2005

Period 2

Variable Ren-E

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Nuclear power plants are explicitly represented in the JRC-EU-TIMES model

Existing nuclear plants and known new build projects represented at reactor level (differentiated techno-economic parameters)

Development of nuclear fleet, including investment and retirement based on economic merit and in competition with other energy sources

Maximum lifetime provided as boundary condition for each reactor

Additional new nuclear capacity part of generic projects on country level

No investments in Member States with nuclear phase (BE, DE) or decision not to use nuclear (AT, CY, DK, EE, EL, IE, LV, LU, MT, PT)

Currently 2 scenarios for new build:

Restricted to projects already known today

No restrictions in "pro-nuclear" MS

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NPP model logic and basic principles

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Different scenarios for the maximum lifetime of the existing nuclear fleet

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Fixed end of life for all reactors in BE, DE, CH, NL, UK

Fixed end of life selected reactors in Sweden and France (reflecting announcements by utilities and government)

Generic lifetime assumption for all other reactors

Investment costs for plant lifetime extension (e.g. grand carnage in FR EUR 55 bn for post Fukushima upgrades + PLEX)

0

20

40

60

80

100

120

140

160

2010 2015 2020 2025 2030 2035 2040 2045 2050

[GW

]

Remaining installed nuclear capacity

Remaining Capacity(40 yrs scenario)

Remaining Capacity(50 yrs scenario)

Remaining Capacity(60 yrs scenario)

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Nuclear remains in the mix in scenarios with ambitious carbon goals JRC-EU-TIMES output electricity generated from nuclear energy in 2040

Scenario assumptions

Carbon: -80% in 2050 (relative to 1990)

Energy efficiency: Primary energy limit of 1319 Mtoe in 2050 (as in EE27 scenario of COM(2014) 520)

Existing nuclear fleet 40 years basic lifetime plus 20 years lifetime extension

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Dispa-SET 2.0 is a state of the art unit commitment and dispatch model

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Objective Minimise variable system costs Constraints Hourly demand balances

(power and reserve) Ramping constraints, minimum up

and down times Storage balances (PHS,CAES) NTC based market coupling Curtailment of wind, PV and load

shedding (optional)

Wind, PV Generation (MWh/h)

Commodity Prices

(EUR/t)

Power Demand (MWh/h)

Variable costs/prices (EUR/MWh)

Plant output (MWh/h)

Emissions (t CO2)

Plant data (MW, eff,)

Formulated as a tight and compact mixed integer program (MIP) Implemented in GAMS, solved with CPLEX

Plant on/off status

(binary)

Dispa-SET model logic

10 10 29 June, 2016

Rolling optimization over a shorter periods of time One day of overlap to avoid end-of-period effects Advantage: Successive problems with dimension of Nvar x 48 instead

of one problem with dimension Nvar x 8760

Dispa-SET optimises the hourly power plant dispatch on a rolling horizon Optimisation horizon

11 11

Dispa-SET helps identifying the flexibility needs of a power system

Insufficient ramping capability

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Content

Energy and power system models

The role of storage

Economics of storage

Conclusion

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Decisions in the power system need to be taken on very different time scales Power system scheduling along different time horizons

1 week 1 year 1 day

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Storage technologies can provide flexibility on different time scales Typical storage technologies for different time horizons

1 week 1 year 1 day

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System interconnection

Flexible thermal power plants (Coal, gas nuclear, biomass)

Introduction Storage is competing with other options for providing flexibility

1 week 1 year 1 day

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Content

Energy and power system models

The role of storage

Economics of storage

Conclusion

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Assess the profitability of power storage from the investor's point of view

Investor value

System Value

Assess benefit of adding storage to the generation system

Maximise profit resulting from (possible) storage revenue streams

Minimise total costs of operating the power system

The value of storage depends on the point of view taken in the assessment Type of study Process Mathematical formulation

JRC report "Assessing Storage Value in Electricity Markets" in collaboration with EdF (JRC 83688) comprehensive review of studies

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Different mathematical tools are used for investor and system studies

Dispatch (MWh/h)

Revenues (EUR/h)

Maximise revenues (LP, NLP or MIP)

Power Prices

Residual demand (MWh/h)

Commodity Prices

(EUR/t)

Variable costs/prices (EUR/MWh)

Plant output

(MWh/h)

Minimise variable costs

(LP or MIP)

Storage dispatch model

(Investor view)

Power market model

(System View)

Input Output

19

Recent system studies cast doubts on need for large scale storage in mid term

Agora Energiewende

Etude PEPS

Other flexibility options less expensive if RES-E capacity between 40%-60% (2030 horizon)

Storage can add system value for 90% RES-E system (2050 horizon)

No significant increase of storage need by 2030 (+1 1.5 GW) if PV below 30 GW

Largest value driver is "capacity value" i.e. avoided investments in gas turbines

Germany 2030-50

France 2030

Study Time horizon Key findings

ADEME 100% RES-E

36 GW needed for a 100% RES- system, thereof 17 GW of seasonal storage (e.g. power 2 gas)

Only 15 GW needed for 80% RES-E system, thereof no seasonal storage

France 2050

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Increasing PV share requires solution for distribution grids (e.g. over voltages)

First commercialisation of products (e.g. Tesla Power Wall) & different forms of incentives

Consumer discount rate below utility discount rates

Counterproductive from grid operator point of view (less revenue, same costs)

Need to coordinate dispatch in case of further growth?

Potential to reduce battery CAPEX Economics for self-consumer under

different regulatory schemes Implications on distribution grid

sizing and operation

Barriers Key questions

RET TRANS GEN TRAD DIST END

PV self-consumption plus storage increasingly competing with grid

Drivers

21

Self-sufficiency of 30% in absence of batteries increases to 70% if 7 kWh battery deployed

Size and costs increase sharply when trying to increase self-sufficiency beyond 70%

Cost also increase when undersizing the battery due to fixed costs (installation, cables)

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Required capacity and costs as a function of self-sufficiency rate1

1) Own analysis, based on real household consumption and PV production profiles for Belgium

Ongoing JRC Study on self-consumption shows that self-sufficiency is not a given

Prosumers will likely not abandon the power grid, but they will underutilize it

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Retail prices consist of energy costs, grid costs, RES-E surcharge and taxes

PV remunerated with FIT Storing (and self-consuming)

economically attractive if costs lower than (opportunity costs) of lost FIT

Profitable in DE if battery lifetime is 15 yrs, not profitable if lifetime is 10 yrs

Studies show that buyers of home batteries not only motivated by economic motives1

Battery costs vs total retail price for DE

1) ISEA RWTH 2015 Wissenschaftliches Mess- und Evaluierungsprogramm Solarstromspeicher Jahresbericht 2015

There might be no economic incentive for storing solar PV energy

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Conclusion

Long term energy system studies require a number of different modelling tools

Nuclear energy remains one of several options for a low-carbon energy systems

Low carbon energy systems require flexibility

Storage is one flexibility options but competing with alternatives

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LinkedIn: Joint Research Centre

YouTube: EU Science Hub

Stay in touch

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Backup

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Supply and demand are balanced in real time keeping stable grid frequency Grid frequency and reserve power injection during one minute

Supply > demand Frequency > 50 Hz Negative reserve 'injected'

Reserve power

Grid frequency

Frequency control used for real time system control

Activated by transmission system operators

Deviation >1h lead to transactions on intraday markets

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Retail Trans-mission Gene-ration Trade

Distri-bution

Power Arbitrage

Reserve Power

End User

Portfolio Optimisation

(PV) Self-consumption

Voltage control

Congestion relief

Capacity Firming

Investment deferral

Uninterrupted power sup.

Demand aggregation

Capacity markets? Imbalance penalties?

Nodal pricing? Regulatory challenges

Grid tariff structure

But possible storage use cases only exist within a regulatory environment Electricity value chain

28

Retail Trans-mission Gene-ration Trade

Distrib-ution

Power Arbitrage

Reserve Power

Regulated Deregulated

End User

Portfolio Optimisation

(PV) Self-consumption

Voltage control

Congestion relief

Investment deferral

Uninterrupted power sup.

Demand aggregation

Typical use cases for large scale storage

Typical use cases for distributed storage

Capacity Firming

Storage can deliver services along the entire electricity value chain Electricity value chain

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Technology rich (300+) bottom-up energy system optimisation (partial equilibrium) model based on the TIMES model generator of the IEA

Designed for analysing the role of energy technologies and their innovation for meeting Europe's energy and climate change related policy objectives

Model fully owned and operated by the JRC

Model validation with Commission Services and external modelling experts

JRC-EU-TIMES in a nutshell

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Available at: http://publications.jrc.ec.europa.eu/repository/handle/111111111/30469

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Dispa-SET 2.0 in a nutshell

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Unit commitment and dispatch model of the European power system

Optimises short-term scheduling of power stations in large-scale power systems

Assess system adequacy and flexibility needs of power systems with growing share of renewable energy generation

Assess feasibility of power sector solutions generated by the JRC-EU-TIMES model

Validated for Belgium (report published 12/2014)

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Basic technical assumptions for new nuclear power plants in JRC-EU-TIMES

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Assumptions following from European Utility Requirements1

New build reactors will have a technical lifetime of 60 years

Maximum availability factor is set at 92%

Option to "correct" at MS level taking into account a non-base load operation due to a very high share of nuclear generation (e.g. FR)

Model might not make use of the full availability in very high RES-E scenario

CAPEX due at begin of five year period between payment of CAPEX and begin of commercial operation approximation of interests during construction

WACC of 9% (real) for power sector aligned to PRIMES

1) www.europeanutilityrequirements.org document drafted by the European utilities

http://www.europeanutilityrequirements.org/

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Costs for new nuclear reactors from JRC (ETRI) or other sources

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Unit Specific overnight CAPEX Year 2010 2020 2030 2050 GEN III LWR (ETRI)

EUR2013 /kW

4500 4350 4100 3750

Modular LWR (ETRI)

EUR2013 /kW

6300 5750 5350 5300

GEN III LWR (PRIMES)

EUR2010 /kW

/ 4350 4212 3949

Unit Fixed OPEX GEN III LWR (ETRI)

EUR2013 /kW

95 91 78 60

Modular LWR (ETRI)

EUR2013 /kW

126 115 107 106

GEN III LWR (PRIMES)

EUR2010 /kW

/ / / /

Economic models for energy systemsContentThe JRC develops models for the energy system and interlinked sectorsThe JRC-EU-TIMES model optimises the energy system over long time periodsJRC-EU-TIMES captures the time dimension in time slices and sub-periodsNuclear power plants are explicitly represented in the JRC-EU-TIMES modelDifferent scenarios for the maximum lifetime of the existing nuclear fleetNuclear remains in the mix in scenarios with ambitious carbon goalsDispa-SET 2.0 is a state of the art unit commitment and dispatch modelDispa-SET optimises the hourly power plant dispatch on a rolling horizonDispa-SET helps identifying the flexibility needs of a power systemContentDecisions in the power system need to be taken on very different time scalesStorage technologies can provide flexibility on different time scalesStorage is competing with other options for providing flexibilityContentThe value of storage depends on the point of view taken in the assessmentDifferent mathematical tools are used for investor and system studiesRecent system studies cast doubts on need for large scale storage in mid termPV self-consumption plus storage increasingly competing with gridOngoing JRC Study on self-consumption shows that self-sufficiency is not a givenThere might be no economic incentive for storing solar PV energyConclusionStay in touchBackupSupply and demand are balanced in real time keeping stable grid frequencyBut possible storage use cases only exist within a regulatory environmentStorage can deliver services along the entire electricity value chain JRC-EU-TIMES in a nutshellDispa-SET 2.0 in a nutshellBasic technical assumptions for new nuclear power plants in JRC-EU-TIMESCosts for new nuclear reactors from JRC (ETRI) or other sources