Assessing the effectiveness of policies using experiments by CHEETAH - - PowerPoint PPT Presentation

Andreas Müller, Technische Universität Wien – Energy Economics Group CHEETAH help us understanding why and how households make energy efficiency investments. The project provides empirical evidence of consumer decision-making linked to energy modelling and policy.

Assessing the effectiveness of policies using experiments

by CHEETAH project (CHanging Energy Efficiency Technology Adoption in Households)

Macro level: Translation of results from energy modelling into input to macroeconomic modelling

Meso level: Models for residential buildings (Invert/EE-Lab), appliances (FORECAST) and agent-based (EMLab-Consumer)

Analyse the effects of energy efficiency policies and household energy efficiency investments on residential energy demand for all EU member states until 2030. Pre-Analysis

Micro level – Survey

Household survey in 8 EU member states (online, ~2000 participants per country, representative samples) - Micro-econometric analysis.

Methodological approach

CHEETAH

CHEETAH survey

• Sample of 18,000 households
• Main focus on policy items and hypothetical

adoption in choice experiments

• data on socio-demographics, housing,

environmental attitudes and technology-specific items

The core of our empirical research: Large representative household surveys

Italy UK Spain Poland Germany Romania Sweden France

75% of EU energy consumption 76% of EU population

CHEETAH

Meso level: Modelling structure

Survey

INVERT/EE-Lab

(Buildings)

FORECAST

(Appliances)

EMLab-Consumer

Modelling ABM ,

Empirical basis for decision making process; how this is influenced by policies

Heating: Invert/EE-Lab & EMLab-Consumer Appliances: FORECAST & EMLab-Consumer

CHEETAH

Outline

Selected results

• Possible range of saving due to thermostats
• Impact of settings of policy framework

Summary of findings

CHEETAH

I) Thermostats

• The survey doesn’t deliver values for the savings [%] per

building due to thermostats.

• Assumption: Savings rate Smax up to 10% (depending on building)

(with sensitivity for 0% and 20%)

• We don’t get the information on how often households think

about whether or not to install such a device.

• Assumption: 10% of households (without thermostats) look into

whether or not to install thermostats (with a sensitivity of 5%)

CHEETAH

I) Thermostats

• In a base scenario, thermostats could the final energy demand by

3 – 5% (up to 10 % with Smax=20%) in 2030

• Significant, but way less than effect of refurbishment which

reduces demand by 25-30% in the same scenario

27% 27% 27% 27% 27% 27% 16% 16% 16% 16% 16% 16% 3% 3% 3% 3% 3% 3% 11% 11% 11% 11% 11% 11% 17% 17% 18% 17% 18% 18% 13% 13% 13% 13% 13% 13% 5% 5% 5% 5% 5% 5% 7% 7% 7% 7% 8% 7% 500 1000 1500 2000 2500 3000 cheetah_smart_thermos_0_10 cheetah_smart_thermos_0_20 cheetah_smart_thermos_10_10 cheetah_smart_thermos_10_20 cheetah_smart_thermos_20_10 cheetah_smart_thermos_20_20 2030

Final energy demand (TWh) gas fuel oil coal District heating Electricity biomass ambient heat solar thermal

20% 20% 10% 10% 0% 0% Annual share considering to install 5% Upper limit of energy savings: Smax 10% 5% 10% 5% 10%

Energy consumption for space heating and domestic hot water preparation, EU-28, 2030 impact of smart thermostat technology

CHEETAH

II) Heating systems

• Impact of framework settings in subsidy-issuing system and

differentiated subsidy levels for different income groups on the European energy consumption for space heating and domestic hot water preparation

45% 28% 29% 28% 32% 33% 32% 15% 16% 16% 16% 16% 17% 17% 4% 3% 3% 3% 3% 3% 3% 10% 11% 11% 11% 11% 11% 11% 11% 17% 17% 17% 15% 15% 15% 12% 13% 13% 13% 14% 14% 14% 2% 6% 5% 6% 4% 4% 4% 0% 6% 6% 6% 5% 5% 5% 500 1000 1500 2000 2500 3000 3500 4000

Scenario H9 Scenario H9 Scenario H11 Scenario H12 Scenario H10 Scenario H13 Scenario H14 2012 2030 Final energy demand (TWh)

gas fuel oil coal District heating Electricity biomass ambient heat solar thermal

Only subsidies for low income households (using default subsidy level)

High trust in subsidy-issuing system Low trust in subsidy-issuing system

Subsidies for low income households: 150% of default value, 50% for other households Default settings for subsidies, equal subsidies for all households Only subsidies for low income households (using default subsidy level) Subsidies for low income households: 150% of default value, 50% for other households Default settings for subsidies, equal subsidies for all households

CHEETAH

Summary of important findings

• Thermostats:
• We see an impact, but not overwhelmingly high.
• The effects on overall energy consumption of increased penetration

rate of thermostats is diminishing. Once mostly buildings with a low energy demand install thermostats, the impact of additional penetration is modest.

• Heating systems:
• Institutional settings of support mechanism is important. The two

framed and tested rebate schemes in the survey lead to a difference in final energy consumption of 3% in 2030.

CHEETAH

Contact

Andreas Müller, Energy Economics Group TU Wien, Austria mueller@eeg.tuwien.ac.at

www.briskee-cheetah.eu

CHEETAH