IIEC-Africa
ENERGY EFFICIENCY METRICS
Ian Househam IIEC-Africa 011 482 5990
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Overview of South Africa’s Energy
Efficiency Strategy
• Energy Efficiency Strategy set sectoral and economy-wide energy efficiency targets to be achieved by 2015
• Targets are expressed as a percentage reduction in final energy demand relative to the ‘business as usual’ projection
◊ Economy-wide: 12%
◊ Industry and mining: 15%
◊ Power generation (parasitic): 15%
◊ Commercial / public: 15%
◊ Residential: 10%
◊ Transport: 9%
• Interpret these as percentage reductions in final energy demand attributable to improvements in energy efficiency
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Development of a system for
monitoring energy efficiency
‘Wish list’ of data needed to perform monitoring under idealised approach Assessment of actual data currently available Stakeholder consultation Recommendations to fill data gaps Review of the theoretical background to energy efficiency monitoring, and formulation of an idealised methodology for the South African
context
Review of international best practice, and assessment of applicability in the South African context
Modified methodology to work with imperfect data Recommendations on institutional arrangements for energy efficiency monitoring: activities; staffing and resourcing levels; powers and
responsibilities.
Methodology handbook
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Approaches to monitoring energy efficiency
• Project-based approaches:
◊ observe the impacts of individual energy efficiency policies, programmes and projects
◊ infer that the aggregate change in energy efficiency is equal to the combined impacts of these policies, programmes and
projects
• Indicators-based approaches:
◊ observe directly the aggregate change in energy efficiency
◊ infer that this change is due to a range of factors that may or
may not include specific energy efficiency policies, programmes and projects
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Approaches to monitoring energy efficiency
n / a ‘Decomposition’
method-ologies as used by e.g. Netherlands, Canada and
New Zealand Top-down
Approach mandated in the EU Draft Directive on Energy
End-Use Efficiency and Energy Services
‘Odex’ index approach, developed under the EU
Odyssee programme Bottom-up
Project-based Indicators-based
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Limitation of project-based approach
ENERGY EFFICIENCY Policies, programmes and projects designed to bring about improvements in energy efficiency Other unidentified or unquantified factors tending to improve energy efficiency Factors, both identified and unidentified, tending to cause a worsening of energy efficiency Project-based approach to monitoring looks only at these factors
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What is energy efficiency?
At least three possible definitions:
• Theoretical minimum energy requirement for performing task
÷ energy actually used
• Current best practice energy requirement for performing task ÷ energy actually used
• Useful output obtained ÷ energy used
The first definition is technically the most ‘correct’, but also probably the least useful
The reciprocal of the final definition is more commonly called ‘energy intensity’
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Energy intensity as an indicator of
energy efficiency
• At the micro-level, physical energy intensity (e.g. MJ / tonne of product) is a very good indicator of energy efficiency
• At the macro-level, economic energy intensity (e.g. TJ / $ of GDP) may be a very poor indicator of energy efficiency
To what extent does a fall in energy intensity
indicate an improvement in energy efficiency?
“There is no unequivocal quantitative measure of ‘energy efficiency’. Instead, one must rely on a series of indicators relevant to the context…”
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Bottom-up versus top-down
CHANGES IN MICRO-LEVEL PHYSICAL ENERGY INTENSITY INDICATORS CHANGE IN MACRO-LEVEL ECONOMIC ENERGY INTENSITY INDICATOR AGGREGATION DECOMPOSITION ECONOMY-WIDE CHANGE IN ENERGY EFFICIENCY ECONOMY-WIDE CHANGE IN ENERGY EFFICIENCY ACTIVITY-LEVEL EFFECTS STRUCTURAL EFFECTS
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Illustrative example
350 € / item 900 € / tonne Year t 300 € / item 1000 € / tonne Year 0 Value added perunit of output -5.0% -12.5% % change -1.9 GJ / item 7 GJ / t Year t -2 GJ / item 8 GJ / t Year 0 Physical energy intensity +58 GJ +102 GJ -44 GJ change 538 GJ (6.10 MJ/ €) 342 GJ 196 GJ Year t 480 GJ (7.27 MJ/ €) 240 GJ 240 GJ Year 0 Energy consumption €88,200 180 items 28 tonnes Year t €66,000 120 items 30 tonnes Year 0 Output Sector total Industry B Industry A
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Log-mean Divisia decomposition
• LMD decomposition is arithmetically the ideal approach as it yields no residual component
• The arithmetic looks complicated…
…but is straightfoward to perform in a computer spreadsheet
(
)
∑
× = ∆ j t j j t F E E Y Y P ,0 , 0 , ln(
)
∑
× = ∆ j j t j t j j I I E E F I 0 , , , 0 , , ln(
)
∑
× = ∆ j j t j t j j S S E E F S 0 , , , 0 , , lnIIEC-Africa
Indicators required for decomposition
analysis
• Decomposition analysis requires:
◊ Energy consumption indicator
◊ Activity-level indicator
for every sector / sub-sector upon which the analysis is performed
• Analysis must be performed on every sector for which an energy efficiency target has been set
• Analysis at the level of industrial sub-sectors and individual industries provides a clearer picture of second- and third-order structural effects
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Challenges (1)
Industrial sector
• Widespread misunderstanding of energy efficiency targets, which may lead to a reluctance to share data needed for effective monitoring
• Detailed data on GDP disaggregated by sub-sector currently only available every 4-5 years
Residential sector
• Almost complete absence of detailed data
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Challenges (2)
Commercial / public sector
• Energy consumption data disaggregated by sub-sector is not currently available
• Choice of an appropriate activity-level indicator:
◊ GDP / value-added ?
◊ Floor-area ?
◊ Number of employees ?
Transport sector
• Energy consumption data not disaggregated into passenger versus freight
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‘Driving force’ indicators of energy
efficiency
• Not sufficient only to answer the quantitative question of
whether the targets have been / are being met
• Need also to address the question of why targets are (or are not) being met – what are the driving forces ?
• ‘Driving force’ indicators:
◊ Turnover of stock of energy-using equipment (including buildings)
◊ Awareness of energy costs
◊ Understanding of opportunities for improving energy efficiency
◊ Energy efficiency as a criterion in purchasing decisions (total cost of ownership)
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Economy-wide analysis
2000-2001
0.67% -23433.6 65097.846 -9807.05 47951.766 -134786 8110.219 Intensity effect -16188.9 6024.895 261.15957 -18210.9 -4264.06 Structural effect 105941.6 4461.1539 101480.4 Activity effect 0.108721 0.5407053 0.31686 0.033713 2001 0.105848 0.5393828 0.318841 0.035928 2000 Share of GDP 0.0058692 2.644572 0.3156433 11.57994 2.635854 2001 0.0043945 2.762418 0.2013389 12.12657 2.335398 2000 Intensity 224967.07 3320810 224947.5 106648.83 2922201 67012.81 Weight 44560644 787760 85646 425946 249610 26558 2001 43685699 764051 80873 412116 243611 27451 2000 Activity 66319 261536 3321415 226497 134447 2890468 70003 2001 191977 3324655 223405 82975 2954166 64109 2000 Energy Totals Residential Sub-totals Transport Commerce Industry Ag & fishIIEC-Africa
