BRISKEEBehaviouralresponsetoinvestmentrisksin

energyefficiency

FinalBRISKEEConferenceandeceeeannualpolicyseminarWednesday,29November2017,Brussels

Resultsfromthetechno-economicandmacro-economicmodelling

MichaelHartner(TUWien),RainerWalzandMathiasPfaff(FraunhoferISI)

This project has received funding from the European Union’s Horizon 2020 research and innovation

programme under grant agreement No 649875. This presentation only reflects the authors' views and

EASME is not responsible for any use that may be made of the information it contains.

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Approach:

Meso Level – t e c h n o e c o n o m i c m o d e l l i n g o f h o u s e h o l d ´ s i n v e s t m e n t i n e n e r g y e f f i c i e n c y u n t i l 2 0 3 0

Results analysis – investments and spendings for macro models

Scenario definition and quantification

Current policy Intensified measures Actor related measures

Implementation and sensitivity analysis on discount rates

Model Invert/EE-Lab Model FORECAST

Analysis of survey results Heating/thermal retrofitting Appliances

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RESULTS FOR HEATING AND THERMAL RETROFITTING Model used: Invert/EE-Lab (www.invert.at)

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What mat ters for investments in heat ing systems and thermal re furb ishment

AverageLikertscalevaluepercountry

5– Veryimportant

4– Important

3– Neitherimportantnorunimportant

2– Notveryimportant

1– Playednorole

Technicalperformance

Increaseinpropertyvalue

Recomm.byprofessionals

Recomm.byfriendsandfamily

Energycosts

Financialsupportmeasures

Investmentcosts

4.22

4.16

4.10Indoorcomfort

4.05

3.78Environmentalfriendliness

3.50

3.46

3.08

3.78

AverageIncomeofrespondentshigher lower

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•  Discount rates have a significant impact on modelling results

•  Difference in final energy demand in 2030 is between 5% and 15% between low discounts rates of 2% versus a 20% discount rate scenario

•  Lowering discount rates can significantly increase thermal renovation activities

•  But impact is limited by investment cycles and other policies (e.g. standards)

Hea t ing – impac t o f d i scoun t ra tes on therma l renova t ion – example Be lg ium

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Scenar ios for heat ing and cool ing in BRISKEE

Scenario name Explanation

1) Current-policy scenario

Policies which have been decided or already implemented.

-  Renewable Energy Directive -  Energy Efficiency Directive, -  Directive on Energy Performance of buildings -  Ecodesign Directive -  National policies (Mure Database

2) Intensified-measures

National policy approaches are the same but intensified

-  Higher subsidies for renewable heating systems and retrofitting -  Higher standards for thermal performance of buildings

3) Actor-related measures

Policy measures affecting the discount rate of low income agents

-  Discount rates of low income agents are reduced to the level of median income

-  reduction of discount rates between 2% and 5%

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•  Final energy demand is expected to decrease in all 3 scenarios (17% in Current policy scenario) - reductions of space heating demand

•  Intensified-measures lead to -22% reduction of final energy demand compared to 2012, actor related scenario: -23%

•  Also the share of renewables increase - 34% compared to 32% in intensified-measures scenario (heat pumps and solar thermal), still high shares of natural gas

Heat ing and Cool ing – F ina l energy demand for EU28 in 3 scenar ios

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Heat ing and Cool ing – Investments for EU28 in 3 scenar ios

•  Significantly more investments in thermal retrofitting and heating systems when low interest rates are assumed for low income households. (+9% more than in the intensified scenario)

•  Annual expenditures on energy carriers decrease by -18.6% in the intensified vs. -21.6% in the actor related scenario compared to base year 2012

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RESULTS FOR APPLIANCES

Model used: FORECAST (www.forecast.eu)

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What mat ters for investments in appl iances accord ing to the BRISKEE survey

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Scenar ios for appl iances in BRISKEE

Scenario name Explanation

1) Current-policy scenario

Policies which have been decided or already implemented.

-  Ecodesign Directive -  Additional national labelling measures -  Adopted for refrigerators, , dishwashers, stoves and lighting

individually -  Average efficiencies for TV, desktop computers, AC

2) Intensified-measures

National policy approaches are the same but intensified

-  Higher minimum standards -  Labels are rescaled -  More efficient devices are available earlier

3) Actor-related measures

Policy measures affecting the discount rate of agents

-  Lower discount rate (from 20% to 2%) -  Environmentally concious consumer group introduced -  Subsidies for very efficient appliances (important for low income

according to survey)

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App l iances - F ina l energy demand for EU-28 in 3 scenar ios

0

100

200

300

400

500

600

700

Curren

t

Intensified

Actor-related

Curren

t

Intensified

Actor-related

Curren

t

Intensified

Actor-related

2012 2020 2030

Finalene

rgyde

mand(TWh)

Whitegoods Lighting Cooking ICT New&Others

•  Slight increase in final energy demand in current policy scenario

•  Significant decrease in the intensified policy scenario in particular for energy consumption of white goods

•  Actor related measures for low income agents only lead to small effects

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§  Investments increase in all scenarios, for intensified and actor related scenario more than doubled

§  More appliances are purchased per household compared to base year in particular in currently low income countries

§  More energy efficient appliances are expected to be significantly more expensive – also an explanation for less effect of monetary actor related measures

§  Energy expenditures are expected to decrease by -10% compared to the current policy scenario

Appl iances - Investment for EU-28 in 3 scenar ios

0

50,000

100,000

150,000

200,000

250,000

2012 2020 2030MioEURp.a.

Investmenttoappliances

Current Intensified Actor-related

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•  It is crucial to include non-monetary decision criteria to model investments in energy efficiency measures and consider the technical lifetime of buildings and heating systems for scenarios on heat demand

•  The meaning and effect of implicit discount rates depend on the implemented decision algorithm which vary substantially across models

•  In total final energy demand of the residential sector is expected to decrease until 2030 for all calculated scenarios. -6% in the intensified and -8% in the actor-related scenario – mainly triggered through reductions of space heating demand

•  Shares of renewables in heating and cooling increase significantly in scenarios with lower discount rates. In particular the deployment of solar thermal systems and heat pumps increases. Natural gas still shows high market shares until 2030.

•  Policy measures addressing the investment behavior of agents can significantly increase the share of renewable energy carriers in the building stock. Policy costs?

Summary and key f ind ings I

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•  The final energy demand for appliances remains approximately constant. Energy demand for lighting strongly decreases in all scenarios. Energy demand for ICT increases strongly – early measures

•  Ecodesign proves to be the most effective instrument for appliances while improved labelling also contributes to more energy conscious purchase behaviour.

•  A programme subsidising the purchase of very efficient white goods appliances for low-income households in all EU member states only leads to minor savings in the model. Highly efficient appliances need to become significantly cheaper to reach a major market uptake.

Summary and key f ind ings I I

BRISKEEBehaviouralresponsetoinvestmentrisksin

energyefficiency

FinalBRISKEEConferenceandeceeeannualpolicyseminarWednesday,29November2017,Brussels

ResultsfromWP4:MacroeconomicEffects

RainerWalzandMatthiasPfaff,FraunhoferISI

This project has received funding from the European Union’s Horizon 2020 research and innovation

programme under grant agreement No 649875. This presentation only reflects the authors' views and

EASME is not responsible for any use that may be made of the information it contains.

Seite 17

Ob ject ive of WP 4 and in tegrat ion in to overa l l model l ing approach

MacrolevelMesolevelMicrolevelHousehold-level

decisionsmakingonenergyefficiency

Technologydiffusionandenergydemandinresidentialsector

Overallimpactsoftechnologydiffusionand

demandchanges

Bottom-upenergymodels

Allocationofimpulses

Macroeconomicmodeling

Investmentsinenergyefficiencytechnologies

Energycostreductions

Subsidies

Netchangeininvestmentsand

intermediatedeliveries

Netchangeinconsumption

Netchangeinenergyefficiencytechnology

exports

NetchangeinGDP

Netchangeinemployment

Netchangeinsectorialcompositionofeconomy

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Descr ip t ion of macroeconomic mechanisms

Effects resulting from investments (positive impulses) -  Increased production and employment in these sectors and upstream sectors -  Enhanced chances of domestic producers to increase their technology exports

Effects resulting from energy cost reduction (negative impulses) -  Reduced production and employment in energy sectors and upstream sectors

Effects resulting from compensation of impulse differences -  conservative assumption: if investment impulse is higher than cost saving impulse,

there is a compensating reduction in consumption

Macroeconomic income effects -  Changes in production of investment and consumption goods lead to

changes in income (inducement of multiplier effects), which also effects further structural changes of the economy

Changes in structural composition of economy lead to -  changes in overall import -  changes in overall labour intensity of an economy

stru

ctur

al e

ffect

s

of im

puls

es

indu

ced

mac

ro-

econ

omic

effe

cts

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Impulses on the EU28 leve l (Mi l l ion € 2005)

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ASTRA EC – Model overv iew and impulses

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Resul ts for the EU28, 2012-2030 Relat ive GDP and employment change

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

0.16%

0.18%

D2 D3 D2 D3

GDP EmploymentFTE

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Resul ts for the EU28 Development o f GDP and employment

D2

D3

D2D3

-0.10%

0.00%

0.10%

0.20%

0.30%

0.40%

0.50%

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

GDP Employment

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-0.40% -0.30% -0.20% -0.10% 0.00% 0.10% 0.20% 0.30% 0.40%

Agriculture

Energy

Metals

Minerals

Chemicals

Metal_Products

Industrial_Machines

Computers

Electronics

Vehicles

Food

Textiles

Paper

Plastics

Other_Manufacturing

Construction

Trade

Services

D2 D3

EU28 2012-2030 Relat ive employment changes on sector leve l

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-0.40% -0.20% 0.00% 0.20% 0.40% 0.60% 0.80% 1.00% 1.20%

ATBEDKESFIFRUKDEELIEITNLPTSEBGCYCZEEHULVLTMTPLROSISKLUHR

EU28

D2 D3

Count ry leve l 2012-2030 Re la t i ve GDP changes

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-0.12% -0.09% -0.06% -0.03% 0.00% 0.03% 0.06% 0.09% 0.12%

ATBEDKESFIFRUKDEELIEITNLPTSEBGCYCZEEHULVLTMTPLROSISKLUHR

EU28

D2 D3

Country leve l 2012-2030 Relat ive employment changes

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I n terpretat ion

Positive effects are robust: results show lower limit of positive effects

-  conservative assumption with regard to Keynesian effects (impulse compensation)

-  positive effects of investment continue after 2030, negative effects of compensation occur before 2030: consumption compensation will turn positive

effects on GDP stronger than on employment -  increased energy efficiency triggers sectors related to manufacturing -  impulse compensation also reduces consumption related to service sectors -  labour intensity in service sector higher than in manufacturing

country differences can be explained by -  different structure of impulses for country -  different structural composition of the economy -  differences in labour intensity and import intensities of value chains

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Out look research: enhancing analys is by feedbacks between micro and macro leve l

spillover from changing IDR to overall macroeconomic consumption behaviour?

feedback from macroeconomic effects to environmental behaviour?

Source: Fraunhofer ISI, adapted from Bamberg&Möser 2007 and Klöckner 2013

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THANKS FOR YOUR ATTENTION! - QUESTIONS AND DISCUSSION F O R M O R E I N F O R M AT I O N P L E A S E V I S I T O U R W E B S I T E W W W. B R I S K E E - C H E E TA H . E U / B R I S K E E / W P 2 – D E L I V E R A B L E S O N M I C R O - L E V E L + S U R V E Y W P 3 – D E L I V E R A B L E S O N M E S O - L E V E L M O D E L L I N G W P 4 – D E L I V E R A B L E S O N M A C R O - L E V E L M O D E L L I N G W P 5 – D E L I V E R A B L E S O N P O L I C Y R E C O M M E N D AT I O N S

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For more in format ion p lease check our websi te

www.briskee.eu

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Impulses f rom energy models

Impulses Model variable/sector affected

Investment and exports in energy efficient heating technologies and insulation

Investment sectors, constructions

Investment in energy efficient appliances electronics and computing equipment

Reduced energy expenditures due to heating technologies and insulation

energy sector

Reduced energy expenditures due to efficient appliances

energy sector

Consumption changes due to changes in disposable income

Consumption (final goods and service sectors)

Subsidies Consumption, government expenditures

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EU as lead suppl ier on wor ld market

Success factors for lead supplier position

-  demand advantage (EU = D2, D3 scenario)

-  transfer and export advantage (EU = positive RXA)

-  technological advantage (EU = positive RPA)

-  system advantage -  regulatory advantage

(EU = D2, D3 scenario)

Source: Fraunhofer ISI

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France Germany

Italy Poland

Romania Spain

Sweden

UK

Geographica l focus: EU-28 Survey in 8 countr ies

75% of EU energy consumption

76% of EU population

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Microlevel–EnergyefficiencytechnologyadoptioninhouseholdsMulti-countryhouseholdsurveyoneffectsoftime&riskpreferencesonEETadoptionMicro-econometricanalysis

Macrolevel–MacroeconomiceffectsofenergypolicyTranslationofresultsfromenergymodellingintoinputtomacroeconomicmodelling(ASTRA)

Mesolevel–EnergyefficiencypolicyandhouseholdinvestmentbehaviorIntegrationofempiricalfindingsintomodelsforresidentialbuildings(Invert/EE-Lab),appliances(FORECAST)

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Scope:

•  Temporal scope: Annual energy demand projections until 2030

•  Sectoral scope: Energy demand for residential buildings (Invert/EE-Lab) and residential appliances (FORECAST)

•  Geographic scope: EU 28 (at the level of individual member states)

•  Economic perspective: Energy costs and investments.

•  Supply and efficiency options: Heating systems, appliances, investments in thermal refurbishment, energy carriers

WP3 – Energy demand model l ing - In t ro

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Large appliances (white goods): refrigerators, freezers, washing machines, dryers, dishwashers Information and Communication Technologies ICT: televisions, desktop computers, computer screens, routers, laptop computers, set-top boxes Lighting Cooking New & Others: energy using devices not covered in the previous points, including small appliances, such as tablet computers, toasters and phones

Energy uses in FORECAST-Resident ia l

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Overv iew FORECAST-Resident ia l

Policy

Labelling

EcodesignTechnologicalparameters

(t=t0,…,tn)•  Lifetime•  Operationpower•  Operationtime•  Stand-bytime•  Stand-bypower

Ownershiprate

Population

Economicparameters(t=t0,…,tn)

Behaviouralparameters(t=t0,…,tn)

•  Accesstoinformation•  Computationalcapacity

InvestmentDecision

Marketshareperefficiencylevel

Energycost

Investmentcost

Marketdiscountrate

Behaviouraldiscountrate

Accessibleoptions

FinancialIncentives

Energy demand by scenario

…

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-  Building stock model based on annual heating and cooling demand calculations for aggregated (>1000 building segments per country)

-  Development of thermal condition of buildings and of heating systems is based on a nested logit approach – main drivers are cost related but additional parameters influence the decisions in the model (e.g. importance of comfort, factor for sustainability, information awareness)

-  Decision makers are implemented as agents (e.g. Owner occupier, housing association, low income owner) and distributed over the building stock in the model.

-  Each agent can be associated with a distinct discount rate (e.g. low income have higher discount rates in the initial set up of the model). We have to be careful when comparing this discount rate with references in the literature because we add other factors which are often summarized in the discount rate

Heat ing and Cool ing in the res ident ia l sector - INVERT/EE-Lab

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Heat ing and Cool ing in the res ident ia l sector - INVERT/EE-Lab

Simulationresults

• Installationofheating,refurbishmentoptions,DHWsystems(#,kW,m²)

• Renovationofbuildings(number,m²,…)• Energydemandandconsumption• CO2-emissions• Investments,policyprogramandrunningcosts

Adoptedbuildingstockdatabase

Energymodule

Investment-decisionmodule

ServicelifetimemoduleWeibull

distribution

Kernel

Quasi-steady-stateenergybalance

approach

Nestedlogitmodel

Logisticgrowthmodel

Diffusionrestrictions

Technology databases

Buildingstockdatabase(t=t0,dynamicinputfort1 …tn)

Database:Refurbishment bundles

Technology combinations

Spaceheatingtechn.

ShadingsystemsVentilationsystems

Buildingshellcomponents

Heatdistr.systemsDHWtechnologies

Building stock database

Exogenouslydefinedscenario-specific

datasets

Growthofbuildingstock

Optionsforthermalrenov.andSH-technol.

Energypricesandcost-resource-potential-

curves

Policies

Diffusionrestrictions

Preferencesforheatingsystems,traditions,

inertia,...

t=t0

Climatedata

Buildingusageanduserbehavior

t=t 1

t=t 2…t n

#16

DataflowwithinsimulationCalibrationonanindividuallevelCalibrationonagloballevel

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Technolog ica l scope: Di f ferent purchase pr ice categor ies

„Low cost“ „Medium cost“ „High cost“

lighting White goods

Thermal retrofit and heating

Seite 40

•  Intensified measures also lead to higher shares of renewables

•  Share of fossil fuels decreases to less than 50% - strong reductions of fuel oil and coal, still high shares of natural gas

•  Lower discount rates of low income agents significantly increases the shares of renewables to 34% compared to 32% compared to intensified-measures scenario

•  Strong increase of solar thermal and heat pumps

•  Heat pumps vs. Direct electric heating

Heat ing and Cool ing – Energy carr ier mix in EU 28 in 3 scenar ios

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Heat ing and Cool ing – the ro le o f d iscount ra tes -  Discount rates (r) influence the value of future cash flow in investment appraisals -  High impact on thermal renovation investment decision because of long lifetime of measures (>20

years and up to more than 50 years) -  Also high impact on investments in heating systems. High discount rates make investments in

efficient and renewable heating technologies less likely -  Example: Heat pumps versus direct electric heating

𝑁𝑃𝑉↓𝑟𝑒𝑛𝑜𝑣𝑎𝑡𝑖𝑜𝑛 =−𝐼+∑𝑛=1↑𝑁▒(𝑄↓𝑜𝑙𝑑 − 𝑄↓𝑛𝑒𝑤 )∙p_heat/(1+𝑟)↑𝑛   

𝑁𝑃𝐶↓ℎ𝑒𝑎𝑡𝑖𝑛𝑔 𝑠𝑦𝑠𝑡𝑒𝑚 =𝐼+∑𝑛=1↑𝑁▒Q∙ p_electricity∙ 1/𝜂 /(1+𝑟)↑𝑛   

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App l iances - Energy costs in the EU-28

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

2012 2020 2030

MioEURp.a.

Current Intensified Actor-related

Seite 43

Scenar ios for heat ing and cool ing in - INVERT/EE-Lab

Scenario name ExplanationCurrent-policy scenario The “Current-policy scenario” considers targets and measures

concerning RES-H/C and energy efficiency which have been decided or already implemented. On the European level, the relevant policy implications are particularly set by the Renewable Energy Directive, the Energy Efficiency Directive, the Directive on Energy Performance of buildings, and the Ecodesign Directive.

Intensified-measures scenario The intensified measures scenario assumes that the policies which are implemented currently are intensified; however, the policy approaches remain the same. For example, a country that currently relies on minimum efficiency standards would continue to use this approach; however, the standards would be defined in a more ambitious way. Monetary subsidies for thermal renovation and renewable heating systems are increased in all member states

New actor-related measures scenario The new actor-related measures scenario assumes that energy efficiency policy is complemented by new policy measures affecting the discount rate of low income agents. The discount rates of low income agents are reduced to the level of median income building occupants – reduction of discount rates between 2% and 5% depending on initial assumptions in member states

Seite 44

Scenar ios for heat ing and cool ing in - INVERT/EE-Lab

Scenario name ExplanationCurrent-policy scenario The “Current-policy scenario” considers targets and measures

concerning RES-H/C and energy efficiency which have been decided or already implemented. On the European level, the relevant policy implications are particularly set by the Renewable Energy Directive, the Energy Efficiency Directive, the Directive on Energy Performance of buildings, and the Ecodesign Directive.

Intensified-measures scenario The intensified measures scenario assumes that the policies which are implemented currently are intensified; however, the policy approaches remain the same. For example, a country that currently relies on minimum efficiency standards would continue to use this approach; however, the standards would be defined in a more ambitious way. Monetary subsidies for thermal renovation and renewable heating systems are increased in all member states

New actor-related measures scenario The new actor-related measures scenario assumes that energy efficiency policy is complemented by new policy measures affecting the discount rate of low income agents. The discount rates of low income agents are reduced to the level of median income building occupants – reduction of discount rates between 2% and 5% depending on initial assumptions in member states