National Workshops Bottom up example – Energy labelling for white appliances
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Transcript of National Workshops Bottom up example – Energy labelling for white appliances
Contract number: EIE/06/128/SI2.445841 Project duration: November 06 - April 2009
National WorkshopsBottom up example – Energy labelling for white appliances
Pascal LARSONNEURRobert ANGIOLETTI
22nd January, 2007
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Harmonised bottom-up evaluation method for cold appliances and washing machines
Type of EEI activities covered
Sector Residential
Energy end-use White goods Cold appliances
Washing machines
Efficient solution A class appliances
A+ and A++ for cold appliances
< 0,17 kWh/kg for washing machines
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Types of EEI facilitating measures
• Regulation: Minimum Equipment Energy Performance Standards
• Information: Focused information campaignsLabellingTraining and EducationMetering and informative billing
• Financial instruments for energy savings:Cash rebatesTax rebates and other taxes reducing energy end-use
consumptionThird-party financingLoans
• Voluntary agreements:Industrial companies (appliance manufacturers)Commercial (appliance trade) or industrial organisations
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Formula for unitary gross annual energy savings
Cold appliances
The energy label provides data on the annual unit consumption
Unit gross annual energy savings of cold appliances= ( [annual energy consumption] *BL - [annual energy consumption]* BAT )* F
Where:BL = baseline In case of normal replacement, the baseline should be, either the second best energy class appliances (currently A+ ), which is a very conservative option, or the average of the A+ to C appliances on offer In case of early replacement: average stock appliance
BAT (best available technology): the best energy class on the market (currently A++)
F: correction factor reflecting the ratio of the consumption under the standard test conditions and the measured consumption in real life
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Energy label annual unit consumption
Energy efficiency class Energy Efficiency Index (%) A++ 30 A+ 42 A 55 B 75 C 90 D 100 E* 110 F* 125 G* 155**
Cold appliances
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Formula for unitary gross annual energy savings
Washing machines
The energy label displays the standard cycle consumptionIt is therefore necessary to estimate the average number of cycles per year
Unit gross annual energy savings of washing machines = ( [CC*AC]*BL - [CC*AC]*BAT )* F
Where: CC: Cycle Consumption as stated on the energy label
AC: Annual number of Cycles for the average household
BL = baseline, depending on the level of effort In case of normal replacement: second best energy class appliances (currently A ); In case of early replacement: average stock appliance;
BAT (best available technology): the best energy class on the market (currently A+)
F: correction factor reflecting the ratio of the consumption under the standard test conditions and the measured consumption in real life
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Energy efficiency class Energy Efficiency Index (kWh/kg) A 0.19 B 0.23 C 0.27 D 0.31 E 0.35 F 0.39 G 0.43*
Washing machines
Energy label annual unit consumption
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Baseline
• Two approaches must be used: Consumers willing to purchase a more efficient appliance than they would have done without the EEI promotion measure. The measure may encourage early replacement.
• In the first case, a market modelling approach should define the baseline, since the savings refer to the appliance that would have been purchased if the measure was not implemented.
• Level 1: EU 27 not efficient appliances average unit consumption• Level 2: country not efficient appliances average unit consumption
• In the latter case, a stock modelling approach should define the baseline: the savings are estimated with reference to an appliance that would have normally been kept in the stock, still functioning, if the measure not was applied (level 3).
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Market modelling
Class A+ A B C D EEI UCEEI 42 55 75 90 100 N 0 38,1 41,9 10 10 71 439,2
N+1 0 46 38,5 6,8 8,7 69 424,5N+2 1 54,3 36,7 8 0 65 400N+3 3 61,5 35,5 0 0 62 379,7N+4 5 67,7 27,3 0 0 60 368N+5 7 72,6 20,4 0 0 58 357,9N+6 9 76,1 14,9 0 0 57 349,5
Market share (%), average EEI, average UC (kWh/y)
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Stock UC of year N for saturated markets
UCn = UCn-1 – S/V * (UCn-1 – UCsn)
Where UCn is the UC of the consumers' stock at the end of year NUCn-1 is the UC of the consumers' stock at the end of year N-1UCsn is the UC of the sales of year N, as calculated aboveS is the sales volume over one year (constant over the base period)V is the consumers' stock volume (constant over the base period)
Stock modelling (1)
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Stock UC of year N for non-saturated markets
Sold appliances are obviously not only intended for replacement but also for first purchase, thereby increasing the equipment rate.
The stock volume must therefore be calculated by estimating the ratio of sold appliances purchased for replacement and the ratio of first purchase.
The average stock UC at the end of year N becomes:
UCn = UCn-1 – Sn/Vn-1 . (UCn-1 – UCsn)
Where Sn is now the sales volume of year N and Vn-1 the stock volume at the end of year N-1.
Stock modelling (2)
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Considering rebound effect
• There could be a rebound effect in the purchase of bigger cold appliances, knowing they are energy efficient. However, no information is available (this could be the subject of a model survey in a set of countries).
• The same is the case whether consumers are washing more often
because they know that they purchased an energy-efficient washing machine.
• One direct rebound effect could also be linked to the fact that it is easier for larger washing machines (6, 7 or more kg of capacity) to achieve the threshold of 0.17 kWh/kg. So an EEI measure to promote energy-efficient washing machines could accelerate the shift towards bigger machines.
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Requirements for double counting
White goods are already included in the EU energy labelling scheme, and there is a minimum energy performance standard for cold appliances. Furthermore, the EcoDesign Directive is expected to lead to a new minimum energy performance standards for cold and wet appliances, and a revision of the EU energy label.
Therefore, double-couting with these measures is likely to be an issue. It will be smaller, if the method presented here is only applied to
facilitating measures that promote A++ cold appliances and very energy-efficient washing machines.
In any case, two general recommendations can be made: Try to evaluate the effect of the whole package of facilitating measures that promote energy-efficient cold appliances and washing machines; Try to cross-check the results with a top-down evaluation using regression analysis of the diffusion indicators for the overall market share
of the A++ cold appliances and the very energy-efficient washing machines, and/or for the average UC of all appliances sold in a Member State
market.
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Requirements for free-rider effect
Partial free-rider effect occurs for white appliances as a consequence of the self-sustained evolution of the market: higher demand for efficient appliances contributes to a larger and more competitive offer of best technologies.
Free-rider effect is therefore due to those consumers who would have purchased the most efficient appliances, even if the measure were not implemented.
A survey of participants will be needed to evaluate the share of free riders.
As the free-rider effect and the multiplier effect work into the opposite direction, they partly cancel out each other.
Furthermore, even with extensive surveys and evaluation efforts, the uncertainty for these effects can remain high.
For EEI measures or measure packages that have limited gross annual energy savings (e.g., below 20 million kWh/year), it may therefore be considered to neglect both correction factors.
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Requirements for savings lifetime
Energy savings lifetime
• Efficient cold appliances : 15 years • Efficient wet appliances : 12 years
Source : CWA CEN Workshop 27
Saving lifetimes of energy efficient improvement measures in bottom up calculations
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Total gross annual energy savings
Total gross annual energy savings
=
average annual energy savings per sold unit of equipment
*
number of sold equipment
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Total ESD annual energy savings
Total ESD annual energy savings
=total gross annual energy savings of all white appliances
* double-counting factor
*(1-free-rider coefficient + multiplier coefficient)
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Data collection (1)
Data needed in calculation for EU, national and measure specific values
Corresponding data sources
Data 1:
Standard cycle consumption of appliances on offer
Market survey (retailers: shop visits or online catalogue), based on the energy label
Data 2:
Correction factor: actual average cycle consumption
Measurement campaign (e.g. Remodece) or statistical survey
Data 3:
Consumer habits: number of cycles per year (for washing machines)
Market survey (consumers)
Data 4:
Voluntary agreements by manufacturers or retailers
CECED or national associations of manufacturers/retailers
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Data collection (2)
Data needed in calculation for EU, national and measure specific values
Corresponding data sources
Data 5:
Sales data: volume and breakdown by class
GfK
Data 6: Number of households National statistics
Data 7: Equipment ownership rate Stock volume (reference year) Global consumption for the end-use (total end-use impact)
Replacement ratio
National statistics, CECED or national associations of manufacturers/retailers
Data 8: Number of b.a.t. appliances sold under the scheme.
Number of purchases claiming financial benefit from the measure
Ex post data from participant monitoring and/or market survey (depending on type of facilitating measure)