MURE Database and Simulation Tool for Energy Efficiency Measures

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MURE Database and Simulation Tool for Energy
Efficiency Measures

• EU and eceee expert seminar on measurement and
  verification in the European Commissions
  Proposal for a Directive on Energy Efficiency and
  Energy Services
• Brussels 21/09/2004
• Wolfgang Eichhammer, Fraunhofer ISI

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MURE a brief reminder

• A comprehensive database of RUE measures, for
  each EU member state, for the EU, and for all
  end-use sectors (Household, Transport, Industry
  and Tertiary)
• A simulation tool, allowing to build and run RUE
  scenarios to calculate potential costs and
  impacts associated to RUE policies and measures
• www.mure2.com

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Path of Analysis 2004
Level 1
Level 2
Level 3
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Case 2 Several measures on one target,
follow-up indicator for package of measures
M1 M2 M3
Impact
Target
I1
T1
Example M1 minimum efficiency standards for
boilers M2 thermal insulation standard (for
building shell) M3 subsidies for condensing
boilers T1 new houses I1 emissions or
specific consumption per dwelling or m2
Measure
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PMs maps in the residential sector

• Heating before EEAP (1990-1999) / after EEAP
  (2000-2004)
• Captive electricity White Goods before EEAP
  (1990-1999) / after EEAP (2000-2004)
• Captive electricity Brown Goods before EEAP
  (1990-1999) / after EEAP (2000-2004)
• Distributed renewables before EEAP (1990-1999) /
  after EEAP (2000-2004)
• 6 files per country
• Quality of evaluation (13)

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Level 1 Evaluation measure impact 1990-2000 with
Odyssee Impact Indicators (PJ) (EU-level)
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Evaluation measure impact 1990-2000 with Odyssee
Impact Indicators (Mt CO2) (EU-level)
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Level 2 Evaluation measure impact EU 1990-1999
with impacts specified in MURE descriptions
semi-quantitative estimates (by instrument) ( of
energy/CO2 savings)
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Objective of MURE simulations (Level 3)
To allow the User to simulate, starting from a
given year, the impact of a given energy Policy
Scenario with respect to a Reference Scenario.

• To this end we define
• The reference year, as the year from which starts
  the impact simulation exercise
• The reference scenario, as the energy demand
  trend taking into account the main energy
  consumption drivers (i.e. the households growth
  rate) and the (residual) impact of the energy
  saving measures issued before the reference year
• The policy scenario, as the energy demand
  development taking into account additional energy
  saving measures issued (or even planned) after
  the reference year.

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The Impact Evaluation of PMs

• The impact evaluation can be carried out on both
• Backcasting (1990-2000)
• and
• Forecasting (2000 2025)
• exercises

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Impact simulation methodology

• General data set up
• Measures analysis and parametrisation
• Run and discussion of results
• Possible further measures parametrisation and
  data calibration

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Impact simulation methodologyMeasures analysis
and parametrisation

• Grouping the measures by homogeneous category
  (financial, fiscal, ordinances, informative,
  etc.)
• Sorting the measures by issuing date
• Setting of the simulation criteria (measures
  parameterisation)
• Selection of the type of intervention to be
  simulated (insulation, boiler substitution, )
• Simulation of the measure relative gain (
  saving)
• Definition of the measures penetration rate (i.e.
  the rate of penetration in the involved dwelling
  stock)

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MURE HOUSEHOLD CASE STUDIES Back-casting
Scenario Germany
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MURE HOUSEHOLD CASE STUDIES Forecasting
Scenario Germany
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Advantages/disadvantages of the three evaluation
paths

• Evaluation with Odyssee impact indicators (Level
  1) comprise still social factors/trends (i.e.
  yield often net effect between factors increasing
  energy consumption and policy measures) but have
  a full coverage of targets to be monitored. Link
  between indicator and measure impact sometimes
  weak depending on data availability
• Bottom-up evaluation from MURE measure
  description semi-quantitative estimates (Level
  2) In general based on in-depth evaluation of
  measure hence more careful evaluation measure
  impact. Yields larger savings as social
  factors/trends are not often taken into account
  in the evaluations ("gross impact of measure").
  Incomplete coverage although some of the gaps can
  be closed with fairly easy estimates of the
  impact derived from the measure descriptions.
  Overlaps between measures are not fully
  eliminated (in-depth work of ECN on measure
  overlap). Information based in general on
  national evaluations, hence on not fully
  comparable assumptions.
• Systematic evaluation of measures with the MURE
  simulation tool (Level 3)provides evaluation of
  most types of measures based on a careful
  simulation of measure impacts. Homogeneous
  treatment of measures accross countries. Data
  requirements quite high (depending on the
  required precision)