mure database and simulation tool for energy efficiency measures eu and eceee expert seminar on...
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MURE Database and Simulation Tool MURE Database and Simulation Tool for Energy Efficiency Measuresfor Energy Efficiency Measures
EU and eceee expert seminar on measurement and EU and eceee expert seminar on measurement and verification in the European Commission’s Proposal for verification in the European Commission’s Proposal for a Directive on Energy Efficiency and Energy Servicesa Directive on Energy Efficiency and Energy Services
Brussels 21/09/2004 Brussels 21/09/2004 Wolfgang Eichhammer, Fraunhofer ISIWolfgang Eichhammer, Fraunhofer ISI
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 measureswww.mure2.com
Path of Analysis 2004
1
Packages of measures + associ-ated energy indicators
Analysis of measures with MURE simulation tool
Analysis of impacts specified in MURE measure descriptions
Analysis of impacts specified in MURE measure descriptions
Analysis of measures with MURE simulation tool
Backcasting (1990-2000) Forecasting (2000-2010-2020)
Energy savings (ex-post) Energy savings (ex-ante)
ENERDA-TAFhG-ISI
ISIS FhG-ISI
FhG-ISI
Level 1
Level 1
Level 2
Level 2
Level 3
Level 3
Case 2 : Several measures on one target, follow-up indicator for package of measures
Measure
Target ImpactM1
M2
M3
T1 I1
Example : M1 : minimum efficiency standards for boilersM2 : thermal insulation standard (for building shell)M3 : subsidies for condensing boilersT1 : new housesI1 : emissions or specific consumption per dwelling
or m2
Example : M1 : minimum efficiency standards for boilersM2 : thermal insulation standard (for building shell)M3 : subsidies for condensing boilersT1 : new housesI1 : emissions or specific consumption per dwelling
or m2
P&Ms 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 countryQuality of evaluation (1…3)
Level 1: Evaluation measure impact 1990-2000 with Odyssee Impact
Indicators (PJ) (EU-level)
PJ
8,67
50,91
22,83
12,667,72
2,76 2,32 2,62 3,16 3,16
40,97
20,89
0,28
19,80
0
10
20
30
40
50
60
70
80
90
100
Heatin
g
New d
welling
s
Existin
g dw
elling
s
Electri
c app
lianc
es -
white
good
s
Refrig
erat
ors
Freez
ers
Was
hing
mac
hines
Electri
c tum
ble d
riers
Combin
ed w
ashe
r drie
rs
Electri
c dish
washe
rs
Light
ing
Electri
c app
lianc
es -
brow
n go
ods TV
Other
s
Distrib
uted
rene
wables
/CHP
Solar t
herm
al PV
Distrib
uted
CHP
372 364
Evaluation measure impact 1990-2000 with Odyssee Impact Indicators
(Mt CO2) (EU-level)Mt CO2
0,61
5,67
2,541,41
0,860,31 0,26 0,29 0,35 0,35
2,99
1,46
0,03
1,50
0
2
4
6
8
10
12
14
16
18
20
Heatin
g
New d
welling
s
Existin
g dw
elling
s
Electri
c app
lianc
es -
white
good
s
Refrig
erat
ors
Freez
ers
Was
hing
mac
hines
Electri
c tum
ble d
riers
Combin
ed w
ashe
r drie
rs
Electri
c dish
washe
rs
Light
ing
Electri
c app
lianc
es -
brow
n go
ods TV
Other
s
Distrib
uted
rene
wables
/CHP
Solar t
herm
al PV
Distrib
uted
CHP
26.1 25.5
Level 2: Evaluation measure impact EU 1990-1999 with impacts specified in MURE
descriptions + semi-quantitative estimates (by instrument) (% of energy/CO2 savings)
0
5
10
15
20
25
30
35
40
45
50
legislative/normative legislative/information fiscal/tariffs financial information/education VA
(%)
Energy (%)
CO2 (%)
Objective of MURE simulations (Level 3)
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.
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.
The Impact Evaluation of P&Ms
The impact evaluation can be carried out on both
Backcasting (1990-2000)and
Forecasting (2000 – 2025)exercises
Impact simulation methodology
General data set upMeasures analysis and parametrisationRun and discussion of resultsPossible further measures parametrisation and data calibration
Impact simulation methodology:Measures 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)
MURE HOUSEHOLD CASE STUDIES: Back-casting Scenario Germany
Germany: Unitary Energy Consumption - Household Back-Casting Scenario
1,75
1,80
1,85
1,90
1,95
2,00
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
toe
/dw
Reference Energy Labelling
Main Financial Policies Thermal Insulation Ordenance
Heating Installation Ordenance Policy
Observed
MURE HOUSEHOLD CASE STUDIES: Forecasting Scenario Germany
Germany: Total Energy Consumption Data - Forecast scenario
45,00
47,00
49,00
51,00
53,00
55,00
57,00
59,00
61,00
Mto
e
Reference New Labelling Scheme
Renewable energy source act + oth. Building Rehabilitation Prog.
New Building Codes
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)