Energy Benchmarking: a Tool developed for EBRD For Assessing Energy Efficiency Performance and Carbo

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Energy Benchmarking a Tool developed for EBRD
For Assessing Energy Efficiency Performance and
Carbon Credit OpportunitiesMario
LazzeriBusiness Development Manager DAppolonia
S.p.A.

• 10 CEI SUMMIT ECONOMIC FORUM
• NOVEMBER 21, 2007 SOFIA

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PROJECT CONTEXT AND BACKGROUND

• EBRD Energy Efficiency Team (EET) rates all
  projects based on their energy efficiency
  potential
• E/2 most energy intensive (i.e. iron and steel,
  cement, etc.),
• E/1 moderately energy intensive (food, drink,
  etc.)
• E/0 limited energy efficiency increase potential
• E/2 projects are subject of detailed on-site
  energy audits
• Energy Benchmarking would provide EBRD with an
  efficient and cost effective method of assessing
  energy efficiency and carbon credit opportunities

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ENERGY BENCHMARKING

• Energy Benchmarking allows the comparison
  between
• the actual energy consumption in a given plant
• AND
• appropriate and relevant energy values that
  could be taken as references

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Specific Energy Consumption (SEC)

• SEC is the consumption of energy per unit of
  output
• SEC for the Whole Industry SECPlant
• Example Energy consumption for hl of beer
• SEC of single Industrial Process Stage SECStage
• Example Energy consumption per ton of rolled
  steel in a HRM
• SEC takes into account thermal energy and
  electric energy

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3 QUESTIONS TO BE ADDRESSED

• Is the PLANT consuming more energy than what
  should be consumed? Which is the potential for
  energy saving?
• Is the PLANT consuming more energy than the
  peers? How is the PLANT ranked in an energy
  efficiency classification?
• Where the energy inefficiency derives from?

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ASSUMPTIONS REQUIREMENTS

• Reliable screening with minimal data requirement
• Benchmark values adjustment to achieve the most
  appropriate reference for each considered
  industry and for the Banks Countries of Operation
• Elaboration of a living software
• Microsoft Office environment
• stand-alone and user-friendly system
• specifically tailored for the EBRD IT system
• connected to existing EBRD databases
• updating automatically the input data

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APPROACH

• Bottom-up development of the general methodology
  starting from the analysis of specific industrial
  sectors of interest for EBRD breweries, milk,
  edible oil and fruit juice industries
• Organization of Benchmarking as an on-going
  activity (creation of an energy performances
  database)
• Multi aspect Energy Efficiency assessment
  consumption, management, technology
• Estimation of possible energy saving
  interventions and CO2 emission reductions
• Two tools a questionnaire (client data
  collection) and a software database (client
  data evaluation and storage)

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QUESTION 1 Is the PLANT consuming more energy
than what should be consumed? Which is the
potential for energy saving?

• Energy Efficiency Index EEI
• this index compares the specific energy
  consumption (SEC) at a given site with reference
  benchmarks
• EEI SECPlant (Given Plant) / SECPlant
  (Benchmark)
• SECPlant(Benchmark) must be adjusted based on
  some specific features of the investigated plant
• parameters that have been considered in the
  process of adjustment are listed in the
  following
• plant size
• packaging mix
• process stages
• utilization rate.

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EEIAlgorithms and Calculation
Size
1. Formulas of Regression
SEC Adjusted for Size
Packaging Mix
2. Formulas for Packaging Mix Adjustment
SEC Adjusted for Packaging Mix
Process Stages
3. Breakdown of Energy Consumptions by Process
Stages
SEC Adjusted for Process Stages
Utilisation Rate
4. Formulas for UR Adjustment
SEC Adjusted for UR
Outputs from Software
Inputs from EBRD Client
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SEC over SIZE

• SAVE 2000, Energy Benchmarking in
  Breweries, prepared for European Commission DG
  TREN

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The total energy saving is split on selected fuel
mix
Fuel , electrical, CO2 and economic savings are
estimated based on provided input
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QUESTION 2 Is the PLANT consuming more energy
than the peers? How is the PLANT ranked in an EE
classification?

• Energy Performance Indicator EPI
• allows a comparison between a selected EBRD
  Client performance and the set of data
  representing the Banks database (self-updating)
• The Energy Performance Indicator (EPI) is
  obtained through a statistical calculations

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EPI CALCULATION

• Database of plants a in the considered sector

Different regressions (linear, power,
polynomial), Selection of the best fitting
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Filter deselects some plants
And allows some other plants
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It is possible to choose the statistical
approach simple trendline or stochastic frontier
The function of selected equation is displayed
It is possible to select the most adequate
trendline function
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EPI CALCULATION

• Delta (Consumption of a given sample element)
  (Trendline consumption for the same size)
• Delta/Trendline Consumption (difference ) for
  each sample point

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EPI CALCULATION

• Distribution of Delta/Trend Consumption in the
  Database

The integral of the distribution gives the
cumulate density F(x)
The A value value shows the EE ranking (44 of
peers are more virtuous than the given industry)
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EPI is the percentage of samples plants better
than the Clients one
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Trend line Formula
Allowed plants constitute the sample population
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Question 3 Where the energy inefficiency
derives from?

• 2 Qualitative Factors
• Technology Factor
• equipment technology for motors, boilers,
  transformers and cooling systems
• age based assessment
• nominal and operational load efficiency
  assessment based on international standards
• energy efficient technologies installed
• process technology
• possible specific process technologies are
  proposed
• Management Factor
• it is a cross-cutting qualitative indicator of
  the Clients performance in energy use management
• the adopted approach has been taken from the
  Building Research Energy Conservation Support
  Unit (BRECSU)
• it can provide useful indications on plants
  management attitude towards possible energy
  efficiency programs
• is based on a simple assessment matrix structured
  in order to provide a performance evaluation that
  can be visualized as a chart
• each type of chart is associated to a diagnosis
  on the plants situation

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MANAGEMENT FACTOR ASSESSMENT MATRIX
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MANAGEMENT FACTOR POSSIBLE SHAPES

• The high balanced shape is expression of an
  excellent performance, because the scores of all
  management fields are good. The problem might be
  to maintain a so high standard.
• The low balanced shape indicates a very low score
  in all analyzed management fields. The balanced
  results may be a symptom of not still completed
  orderly progress or the stagnation of the energy
  management system.
• The U-shaped curve may indicate that your energy
  management expectations have been raised, making
  an effort in Policy and Investment, but you are
  still vulnerable in all other fields, which have
  not yet reached the same high level.
• The N-shaped curve highlight that achievement in
  the centre (mainly Information and Motivation) is
  likely to be wasted for the lacking of a good
  energy management Policy and adequate Investment.
  

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MANAGEMENT FACTOR POSSIBLE SHEAPES

• The Trough shape indicates there is one
  management field, which is strongly underscored
  with respect to all the others. Underachievement
  in this management field may hold back success in
  the others.
• A single field score very high with respect to
  the others identifies the Peak shape. It means
  that there is a very strong effort in one
  management area, which could be wasted by lack of
  progress in all the other management fields.
• The Unbalanced shape is defined by some score
  very high or very low with respect to the average
  score. The more imbalances are present in the
  energy management the harder it is to perform
  well.

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It is possible to analyze all equipment under
several efficiency criteria
For TF Clients main equipments efficiency are
compared to benchmark levels
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Here it is possible to see the installation year
of the various process stages technologies
Or it is possible to analyze single process
stages characteristics
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CONCLUSIONS

• Compare Clients specific energy performances
  with appropriate and adjusted reference Benchmark
  values
• Rank the individual site against peers from an
  energy point of view
• Assess both the efficiency levels of energy
  monitoring and management system in the selected
  plant and the technology level of the process
• Provide an assessment of the achievable CO2
  emission reductions
• Suggest possible actions to improve energy
  efficiency