ContentsAustralia............................................................................................................................................................................4

Overall Conclusions (page 9-10)....................................................................................................................................4

Overview of Methodology (pg. 15-22)..........................................................................................................................4

Stock (A measure of the physical extent of buildings) Model (i.e. the data!):...............................................................5

Energy Consumption Data (p17)...................................................................................................................................5

Normalisation for Hours of Operation p18....................................................................................................................6

Data Analysis and Model Construction (p19)................................................................................................................6

Model Validation (p20)..................................................................................................................................................6

Statistical Confidence (p20)...........................................................................................................................................7

Assumptions made in modelling...................................................................................................................................7

Japan.................................................................................................................................................................................8

Survey items of building energy consumption survey report........................................................................................8

Building specifications...................................................................................................................................................8

Equipment Specifications..............................................................................................................................................8

Operational Status.........................................................................................................................................................8

Various Energy Consumption........................................................................................................................................8

Analysis summary..........................................................................................................................................................9

Calculation of energy consumption...............................................................................................................................9

1. Display method of energy consumption per unit of manufacturing industry........................................................9

2. Display method of building energy consumption per unit.....................................................................................9

Application and perspective of this report..................................................................................................................10

Tables and graphs of this report..............................................................................................................................10

Take Advantage of this Report................................................................................................................................10

Germany..........................................................................................................................................................................11

Starting point and objective........................................................................................................................................11

Methodology...............................................................................................................................................................11

United States...................................................................................................................................................................13

Commercial Sector......................................................................................................................................................13

For the tables used to generate data:.........................................................................................................................13

Table 3.1.4. 2010 Commercial energy end use splits, by fuel type (quadrillion btu's).............................................13

Table 3.2.1. Total Commercial Floorspace and Number of Buildings by year..........................................................14

Table 3.2.8. 2003 Average Commercial Building Floorspace, by principly building type and vintage......................14

1

United Kingdom..............................................................................................................................................................15

The Building Types Studied.........................................................................................................................................15

System and Component Benchmarks..........................................................................................................................16

LIGHTING.................................................................................................................................................................16

FANS, PUMPS AND CONTROLS................................................................................................................................17

OFFICE EQUIPMENT................................................................................................................................................17

Method of calculating and determining indices..........................................................................................................18

Italy.................................................................................................................................................................................19

Data Gathering and Reporting.....................................................................................................................................19

Demands and Consumptions.......................................................................................................................................20

Climate Region Identification......................................................................................................................................20

Reliability of the analysis and procedure to discard unreliable data...........................................................................20

Total Mm2 vs heated and cooled ones. Estimations and calculations.....................................................................20

Calculation of Averages...........................................................................................................................................20

Total consumptions and demands calculation........................................................................................................21

Office Stock Summary.................................................................................................................................................21

Size of the Office Stock............................................................................................................................................21

Age of the office stock.............................................................................................................................................21

Type of Tenure........................................................................................................................................................21

Building type and construction................................................................................................................................21

Energy consumption and demand by end use.........................................................................................................22

Reference buildings.................................................................................................................................................22

Office Sector................................................................................................................................................................23

Office Building 1......................................................................................................................................................23

Office building 2......................................................................................................................................................23

Office building 3......................................................................................................................................................23

Sweden............................................................................................................................................................................24

Completed surveys......................................................................................................................................................24

District Heating........................................................................................................................................................24

Electricity Consumers: The Distribution of Use.......................................................................................................25

The lighting electricity use.......................................................................................................................................26

Fan Electricity Use...................................................................................................................................................26

PC and data center electricity use...........................................................................................................................27

Other electricity......................................................................................................................................................27

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Electricity consumption for cooling.........................................................................................................................27

Project Purpose...........................................................................................................................................................28

Scope.......................................................................................................................................................................28

Work Boundary.......................................................................................................................................................28

Method....................................................................................................................................................................... 29

Earlier work done in 2005.......................................................................................................................................29

Further development of the working model...........................................................................................................29

Sample.....................................................................................................................................................................29

Inventories..............................................................................................................................................................30

Protocol.......................................................................................................................................................................30

Quality Assurance....................................................................................................................................................30

Possible Re-survey...................................................................................................................................................30

Summary.................................................................................................................................................................30

Results for the property owner...............................................................................................................................31

Analysis....................................................................................................................................................................... 31

3

Australia Source: Baseline Energy Consumption and GHG Emissions In Commercial Buildings CBBS Part 1 - Report

Overall Conclusions (page 9-10)

This section has compiled and analysed an unprecedented amount of data on a wide range of buildings types across Australia, including over 1,700 individual office buildings, over 1,600 schools, almost 1000 retail buildings and tenancies, almost 400 tertiary education buildings and a similar number of hospitals. In total, some 15,800 data records relating to over 5,650 individuals buildings have been quality assured and compiled into the NRBuild model out of a total data set of nearly 20,000 records (the balance were discarded due to inadequate data quality).

Despite the large amount of data compiled and analysed for this study, overall the data sample falls short of that required for statistically significant resolution of all of the building types and data fields set out in the terms of reference. The analytical ‘frame’ for this study (13 historical time periods, 15 geographical areas, 15 building sub-types, 2 ownership categories, 5 fuels, and up to 25 end-uses) demands some 730,000 unique and statistically significant observations. To achieve a confidence level of 95% that each of these observations is within 10% of the mean, a sample size of some 9700 building records would be required for each year.

The data records are unevenly distributed by year, region and building type. Very little historical data was available on retail buildings, for example, and these are amongst the most energy intensive of the commercial buildings studied. Also, the data set was too small to draw statistically significant conclusions about energy use trends at the subnational level in most cases (although such conclusions are drawn where possible with respect to particular building types).

Overall then, a key conclusion is that additional data capture and analysis is required for a complete analysis the building types covered in the terms of reference.

Overview of Methodology (pg. 15-22)

The high-level steps that were involved in this project can be summarised as follows:

1. Create a stock model of the relevant building types, by state, region, year and ownership type (where feasible and relevant)

Backcast to 1999; forecast to 2020; validate model internally and externally.2. Capture and organise primary data on the energy performance of the relevant building types

Data search/request; data compilation; data quality assurance.3. Undertake statistical analysis of energy data sets

Create analytical ‘frame’ to match the required specifications (timeframe, spatial resolution, building sub-types, etc); regression analysis to establish trends through time for each sub-type; projections to 2020; compile sample size, standard deviations and other statistical indicators; end-use analysis;

4. Build an integrated stock and energy model Determine model functionality, user variables; integrate stock and energy/fuel intensities; calculate

key outputs (energy use, greenhouse gas emissions) by year, region, building type and sub type.5. Validate model

Top-down analysis of energy consumption by fuel and building type; comparisons with other external research reports, independent data sources.

6. Analyse and report findings.

4

Stock (A measure of the physical extent of buildings) Model (i.e. the data!):

A bespoke stock model was created for this project by BIS Shrapnel, a firm with specialised expertise in analysis and forecasting in the construction sector. A building classification structure was developed, drawing largely on that used by the Australian Bureau of Statistics (ABS), which is based on the concept of the primary function of buildings.

The primary metric used is floor space measured as ‘000m2 in terms of Net Lettable Area (NLA) or equivalent, except where otherwise specified. The data used to compile the estimate of commercial building stock is drawn from a wide array of different sources, with the different sources often not using a common definition of floor space. Adjustments have been made to some of the data provided in order that it approximates an NLA basis. There is considerable uncertainty surrounding floor area estimates in Australia.

Energy Consumption Data (p17)

A feature of this study is that compiles a large amount of quality-assured primary data on actual building energy performance (along with some secondary data sources, as described below) to create a model of energy use in this sector. Some 20,000 records, each with up to 50 data fields (that is, up to 1 million data points) were initially compiled. With the quality assurance process described below, this number was reduced to some 15,800 records (relating to 5,650 individual buildings) that are utilised by the model (see Table 3.1). The number of records exceeds the number of individual buildings as some records relate to the same building in multiple time periods, while other records relate to tenancies within the same building.

The sources of this data are described include:

Energy audit data from Exergy Australia Pty Ltd, pitt&sherry and Energetics Pty Ltd NABERS ratings data provided by the NSW Office of Environment and Heritage Data provided directly by building owners and managers, including for numerous universities Data on government building energy use compiled in the OSCAR database

Data provided directly by government departments and agencies

5

Public domain data from the public report of individual companies, institutions and industry associations.

Normalisation for Hours of Operation (p18)

Where the data included significant information on operating hours (offices, retail), fuel use and energy use fields were normalised to the average hours of operation revealed in the relevant data set. Energy consumption by fuel and end-use was, therefore, factored for the deviation between the mean values and the actual, reported values for operating hours (the factor is described in the model as an ‘hour/s of operation energy intensity factor’). Records containing no information about operating hours were assumed to have the mean value and, therefore, not normalised.

This normalisation process is important to be able to compare reported fuel and energy use intensity on a consistent basis with a building sub-type. As discussed further in Appendix D, however, the relationship between energy consumption and operating hours may not be linear, and in particular is less likely to be so as the value for hours of operation reaches extremes, due to the ‘fixed’ energy consumption of refrigeration, cool rooms, security lighting and other systems. Normalisations for other factors – such as climate – may also be relevant in certain circumstances.

Data Analysis and Model Construction (p19)

The energy data sets were analysed according to the analytical ‘frame’ required for this study; that is, by building type and sub-type, ownership type (offices), year (data records covered the period 1999 to 2012), state and territory, region (capital city vs regional, or balance of state, with ACT treated a ‘capital city’ only). This analytical frame requires around 730,000 statistically valid observations to be fully populated and therefore completely resolved.

For each combination of building type, ownership type, state, region and year, observations were calculated from the data sets regarding the intensity of use of individual fuels (electricity, gas, LPG, diesel and renewables, where revealed, or ‘total energy’, where fuel use is not revealed). Each observation is associated with the sample size (the number of separate records used) relied upon for that observation. A tool is provided within the model that enables the user to specify the minimum sample size per observation, with all values that fall below that sample size being eliminated from the analysis. This provides an initial tool for the model user to test and visualise the robustness of each analysis.

The next step was to construct time-series analyses, including backcasting to 1999 and forecasting to 2020. For each building sub-type, a regression analysis was performed on at least the average national energy intensity time series, as this provided the largest data sample. In some cases, there was sufficient information on fuel mix changes through time to also be able to perform regression analyses. We note that regression analyses could be performed on many other parameters within model. Generally, simple linear regressions provided adequate interpretation of data trends, although this varied greatly by building type and sub-type.

6

Model Validation (p20)

In summary, top-down data sources, such as ABARES’ Australian Energy Statistics and ABS publications such as Energy, Water and Environment Survey or EWES) are used to compare with bottom-up model estimates for energy consumption by fuel in the specified base year (FY2009). We stress that there are very significant limitations associated with such top-down analyses, and generally speaking top-down data will tend to over-estimate energy use in buildings, as the source data is reported energy consumption by ANZSIC classification. To varying degrees, the energy consumption reported may not relate to buildings. An attempt has been made to estimate the building related portions, and also to reconcile the different reporting bases for these two key top-down data sources.

Statistical Confidence (p20)

The analytical ‘frame’ for this study (13 historical time periods, 15 geographical areas, 15 building sub-types, 2 ownership categories, 5 fuels, and up to 25 end-uses) demands around 730,000 unique and valid statistical observations to be fully populated. This begs the question, how many (valid and complete) data records are required to achieve reasonable confidence in the results? We have calculated the minimum number of buildings records required, for each building type and year, using the standard deviation and mean of the current dataset.This is based on achieving a confidence level of 95% that each data point is within 10% of the mean.

In summary, a sample size of some 9700 building records is required each year, or around 126,000 records for the 13 years from 1999 to 2012, would be required to meet this confidence requirement. The terms of reference of this study called for a minimum sample of 1,000 buildings, with 400 end-use breakdowns. While in fact close to 16,000 valid records were compiled which represents around 13% of the sample required to meet the confidence requirements. However, these estimates were based on a number of assumptions, as discussed in Appendix E. In reality, a smaller sample may be judged sufficient. For example, we note that well over half of the required annual sample relates to schools (5227 records). From the large sample of school energy data compiled for this study, there appears to be limited variability in energy intensity between different schools within a state (but larger variability between states).

Therefore, it may suffice to compile a smaller data set for each state, but ensure that all states are covered (the current data set has no coverage of TAS, VIC, WA or SA). Also, annual data may not be required to establish valid time series trends; data points every three years may suffice.

Assumptions made in modelling

Only refer to GHG estimation and population growth, not directly relevent to the data extracted.

7

8

Japan Source: BEMA Digest volume 36 (This is translated so be forgiving with grammar)

Survey items of building energy consumption survey report

Survey, (one company) to target a subscription member companies about 900 buildings that management of the Nippon Building Energy Manager Technology Association is doing once a year. The survey items, company name and buildings that are related to the building in the name and income Hometown-completed year and renovation years, buildings use ratio, total floor area and building matters specific content such as related to matters and energy-saving measures related to air conditioning target area and rank and equipment specifications, needs to be changed as a basic is intended to investigate no item.

For energy consumption of electric power, oil, gas, water, power purchase power of the month [kWh / month], oil [ℓ / month], gas [m3 / month], in the consumption of water [m3 / month] In addition, in 1999 fiscal year version commonly used in-house power generation amount of power from [kWh / month] you are also investigated. In addition, the power value of the date of the annual maximum power of the year, are also investigating the operating period of cooling and heating.

Building specifications

1. Main applications: office, department stores, supermarkets, stores and restaurants, hotels, hospitals, schools,Apartment, other

2. Location: city, street, prefecture, county3. Total floor area: m24. air conditioning target area: m25. completed years and renovation date: AD6. Number of floors: the ground, underground

Equipment Specifications

1. cold heat source equipment type and capacity: boiler, refrigerator, generator, heat pump, heat storage tank, other

2. electrical equipment: transformers, motor capacity, in house power generation equipment3. Other amenities: water tank

Operational Status

1. electrical equipment: power contract, receiving voltage, maximum power2. air conditioning: set temperature, air conditioning period, air conditioning time3. energy saving measures implementation status4. building renovation and equipment update history

Various Energy Consumption

1. Power consumption (kWh): Monthly consumption of 2012 fiscal year and total.2. Consumption of oil (ℓ): 2012 year of kerosene, monthly consumption for each type of heavy oil, and the like, and

total.

9

3. Consumption of gas (cubic meters): Monthly consumption of2012 fiscal year and total.4. Water consumption (cubic meters): Monthly consumption of2012 fiscal year and total.5. District heating and cooling (MJ): 2012 year of cold water, hot water, consumption and total monthly for each

steam.

------------------------------

Analysis summary

Content analysis items are as follows:

1. The survey materials number: all the documents the number that have been submitted (the number ofall the documents that have been issued with each use

2. valid document number: what is unclear from all the documents, and the number ofnot applicable except for the Appendices Appendices.

3. total material number: total consumption in the effective material4. total floor space: the sum ofthe total floor area ofthe total number were submitted material5. effective total area: Sum oftotal floor area in the effective material6. flat Hitosh Vialue: total consumption (effective) ÷ total floor area (effective)7. simple average value: what is divided by the number ofvalid article in the sum ofthe total floor area ofeach

consumption ÷ building of each building8. average value ①: average value in the case ofthe power conversion counted was 9.83MJ / kWh9. average value ②: average value in the case ofthe power conversion counted was 9.76MJ / kWh10. standard deviation: I show the variation in the degree of consumption11. correlation coefficients: scale for knowing the depth ofthe relationship between the two variables12. least squares method: In this document, to predict the consumption by knowing the total floor area

Calculation of energy consumption

1. Display method of energy consumption per unit of manufacturing industry

In the manufacturing industry, "energy intensity" is the power consumption of the "per product" and "per product 1 kg" [kWh / number], [kWh / kg], consumption oil amount [kℓ / number], [kℓ / kg], consumption amount of gas [N ㎥ / piece] [N㎥ / k g], water consumption [kℓ (or kg) / number] [kℓ (or kg) / product kg] energy capacity and weight to consume such as often be listed, differences in equipment specifications remain. (eg, the pressure mature method a electric, B, etc. using gas) by correcting the, often to determine the energy consumption which, compared subject, in equipment group to produce a product dimensions, weight, etc., similar, staffing, often have similar well as the type of energy used, it not very large difference in the energy consumption between the plant This is due to the fact that link to and manufacturing cost.

2. Display method of building energy consumption per unit

In the building, cannot be displayed, such as per product there is no equivalent to the product of the manufacturing industry. In addition, because change significantly the configuration of the energy consumption for each building, simply lists the consumption of power, oil, gas and water The difference amount even if too large, it is difficult comparative evaluation of energy consumption. In this study, with each energy year (month) between consumption of power, oil and gas survey that has been submitted by each building, as consumption per unit floor area [meters] [kWh / m²-years] , [ℓ / ㎡-years], and that you are using, such as oil, coal, natural gas and nuclear as power generation

10

fuel in. power company that aggregated separately [MJ / m²-years], etc. "building applications" from large, power was converted to mature weight of these fuel "primary energy" was also shown together. In addition to consumption also oil and gas, and the amount of heat converted from units Hatsujuku amount of use oil and gas "primary energy" I have been shown together.

"Energy consumption of the building" is the power, oil and value that the sum was divided by the total floor area of the primary energy of the values calorie basis of gas [MJ / m²-years], I have done a comparative evaluation with this value . Heisei up to 10 fiscal version, had been with the [Mcal / ㎡-years], because it was moved to SI units from April 1999, is set to [MJ / m²-years], and display of the past in the data compared with the previous value unit [Mcal / ㎡-years] and I we have also shown.

Application and perspective of this report

This study, continuously investigated about the same items over the past 35 years, from the viewpoint of left to side to see the judgment of analytical data, has provided only that aggregate data. Therefore, a similar table it has become a list of the graph, the person other than areas of expertise that can effectively take advantage of these data, there is tended to have had a somewhat dull impression. We posted an excerpt of "2013 fiscal year version buildings energy consumption survey report" in this digest version. Also to the general public of everyone for the configuration of tables and graphs to help you understand the contents of these data will be outlined below.

Tables and graphs of this report

Table and graph showing the average value of the annual primary energy consumption per unit by building applications. By (4.1. See) which, it is possible to determine in which position the building it manages. 4.3 specifically. ~ 4.11. Shown by roughly in tables and graphs.

Take Advantage of this Report

1. Evaluation of primary energy consumption per unit.

Comparative evaluation of primary energy consumption per unit by the data in this report are possible. And the calculated value of the management to have ascorbyl, this report of building applications by the annual primary energy consumption and average value of the primary energy ｰ Hara unit by comparing the table of values of the simple average value, the management building to the evaluation of more than the average value or less Medicine.

"Low" when it becomes the evaluation, it is tentatively considered to have progressed energy saving than the average of the current, "many" for evaluation is considered that there is room for more energy saving, good Ri Detailed Analysis it means that it is necessary. Calculation and such as by application of energy consumption, it is necessary to perform a detailed diagnosis of the species. It requires a somewhat specialized knowledge of energy conservation for these techniques, (one company) Nippon Building Energy Manager Technology Association want the issue of energy conservation case ed of "building energy conservation comprehensive management approach" your reference wish.

2. Comparison of other data

In this report, analysis was carried out with the context of the consumption data and each item of water, change over time analysis, because the original units such as each species equipment has been posted, and compared with buildings that are managed I think that you are able to take advantage of as a reference such as the elimination of waste and improvement that it shall be.

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Germany Starting point and objective

In 2011, around 1,355 PJ or 15.5% of the total final energy consumption in Germany were accounted for by the sector of trade, commerce and services, which is also referred to as the tertiary sector (AGEB 2012). Up to now, the availability of energy statistics for this very heterogeneous sector is not sufficient. This makes the reporting obligations on energy consumption at the national and international level complicate and also limits the statistical basis for energy forecasts and decisions in the field of energy policy. In Germany, the Energy Concept from September 2010 and the decisions on a transformation of the energy system from June/July 2011, the so-called “Energiewende” (energy transition), led to an increasing demand on reliable statistical data for all energy consumption sectors. This is, because the progress made towards the overall targets and the current state of implementation the agreed action plan are evaluated at regular intervals. The corresponding monitoring process “Energy of the future” was approved by the German government on 19 October 2011. The new European Energy Efficiency Directive (2012/27/EU; EED) from 25 October 2012 also provides for annual as well as more comprehensive reporting obligations at three year intervals in Article 19.

In Germany, a regular survey on energy consumption in the tertiary sector has been carried out for 10 years. Within these surveys, the main consumption and structural data in the tertiary sector are collected by consumer group, energy carriers and end uses. This should further improve the energy statistics for this sector and satisfy the requirements for information about energy. In this study, the results for the 2006 to 2011 are presented. The results for 2011 are still preliminary due to some missing statistical data.

Another focus of the study is on the use of renewable energies in the tertiary sector. The large number and variety of technologies for using renewable energies mean that there are only partially reliable data about the amount of energy actually contributed. Through a more in-depth survey of the use of renewable energies in the tertiary sector, this study also aims at improving the data situation with regard to their use there.

Methodology

The basis for the determination of energy consumption in the tertiary sector is a broad survey which is conducted every two years. The size of the sample is approx. 2,000 workplaces. The results shown here are based on the surveys for the years 2006, 2008 and 2010. For the survey, the tertiary sector was divided into 14 groups, which are further subdivided into more detailed splits. For the extrapolation of energy consumption in the tertiary sector in Germany, at first the fuel and electricity consumption of the companies in the groups and splits were determined from the survey results and related to the number of employees documented in the questionnaire. Interpolations and extrapolations were made for years not covered by the original surveys (2007, 2009 and 2011). The averages of the specific electricity and fuel consumption derived from the survey were then extrapolated for Germany using the total number of employees in the individual groups and splits, which are available from the official statistics. For some consumer groups, other reference units for which the energy consumption is were used for the extrapolation.

For electricity, several components of energy consumption which were not documented in the survey were added to the consumption value determined from the survey (mainly electricity for street lighting, for shared installations in multi-purpose buildings and for supply and disposal functions). The energy consumption of agriculture and forestry and airports was also determined using data from secondary statistics.

Another element of the surveys is to collect information about energy consumption by energy uses within the individual groups. In order to gain additional information about energy-relevant details, energy audits were carried

12

out in 100 enterprises within the tertiary sector. These audits formed the main data basis for breaking down energy consumption in the tertiary sector by application. The electricity and fuel consumption were divided into the following end-uses: space heating, process heat, air-conditioning (AC), process cold, power, lighting, information and communication (ICT).

In order to gain more detailed information on the use of renewable energies in the tertiary sector, a special survey was carried out in two steps. To start with, 10,000 workplaces were contacted by telephone in order to find out how many enterprises actually use renewable energies. For a more detailed analysis, personal interviews were conducted in 300 selected workplaces. Technical data were requested on the existing installations (e.g. installed power, installation size) and the amounts of energy produced.

The second questioning was difficult since a certain number of the 1,600 out of 10,221 enterprises from the first round, who initially agreed to a second interview, finally refused the detailed questioning. As a result, less suitable enterprises had to be recruited, some of them even not part of the 10,000 sample. On the basis of the two stages of the special survey, values for the use of renewable energies per employee were derived which were typical for the technology and the branch structure involved. These then formed the basis, like in the main survey, for extrapolating the contribution of renewable energies in the tertiary sector via the number of employees in this sector and their group affiliation. On the basis of all the available results from the two main surveys and all stages of the special survey as well as other additional data sources such as the statistics of organizations and associations, studies etc., the extrapolation of the use of renewable energies in the tertiary sector was then made based on the number of employees.

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United States Source: Buildings Energy Data Book (2011)

Commercial Sector

Section 3.1 (Commercial, i.e. inclusive of offices) covers primary and site energy consumption in commercial buildings, as well as the delivered energy intensities of various building types and end uses. Commercial sector floor space is divided by the intended commercial activity, such as medical facility, office space, and retail space. Buildings owned and/or operated by Federal, state, or municipal governments are included in the commercial building sector and are categorized according to their primary purpose.

The main points from this chapter are summarized below:

Commercial buildings represent just under one-fifth of U.S. energy consumption, with office space, retail space, and educational facilities representing about half of commercial sector energy consumption.

The recession is evidenced by the sharp decrease in energy expenditures in the commercial building sector–a 10% drop. The value of new commercial construction also declined by 22%, the largest percentage drop in the last 30 years. The decline in economic activity had a positive effect on carbon dioxide emissions, which decreased 6%.

The top three end uses in the commercial sector are space heating, lighting, and space cooling, which represent close to half of commercial site energy consumption.

Commercial floor space and primary energy consumption grew by 58% and 69%, respectively, between 1980 and 2009. The Energy Information Administration (EIA) projects that they will continue to grow at slower rates between 2009 and 2035, 28% and 22%, respectively. Average energy prices, on the other hand, have been, and are expected to remain, relatively stable.

In aggregate, commercial buildings consumed 17.9 quads of primary energy in 2009, representing 46.0% of building energy consumption and 18.9% of U.S. energy consumption. (3.1.1) In comparison, the residential sector consumed 21.0 quads of primary energy, equal to 22.3% of U.S. energy consumption.

In 2003, the most recent year for which such data are available, office and retail buildings represented the greatest proportions of commercial floor space—17% and 16%,respectively—and 19% and 18%,respectively, of commercial sector energy consumption.

These statistics also indicate that the energy intensity of commercial buildings has remained relatively constant. Between 1980 and 2010, primary energy consumption per square foot increased by 8%. Between 2010 and 2035, EIA actually expects energy intensity to decrease by 6%. (3.1.3) Historical and projected building occupancy rates are currently unavailable, so it is not known how fluctuations in office and retail occupancy rates affect overall consumption and consumption per square foot.

For the tables used to generate data:

Table 3.1.4. 2010 Commercial energy end use splits, by fuel type (quadrillion btu's)

Notes: 1) Includes (0.43 quad) distillate fuel oil and (0.08 quad) residual fuel oil. 2) Kerosene (0.01 quad) and coal (0.06 quad) are assumed attributable to space heating. Motor gasoline (0.05 quad) assumed attributable to other end-uses. 3) Comprised of (0.11 quad) biomass, (0.03 quad) solar water heating, (less than 0.01 quad) solar PV, and (less than 0.01 quad) wind. 4) Site-to-source electricity conversion (due to generation and transmission losses) = 3.10. 5) Includes service station equipment, ATMs, telecommunications equipment, medical equipment, pumps, emergency

14

electric generators, combined heat and power in commercial buildings, and manufacturing performed in commercial buildings. 6) Energy adjustment EIA uses to relieve discrepancies between data sources. Energy attributable to the commercial buildings sector, but not directly to specific end-uses.

Sources: EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Summary Reference Case Tables, Tables A2, p. 3-5, Table A5, p. 11-12, and Table A17, p. 34-35; EIA, National Energy Modeling System (NEMS) for AEO 2012 Early Release, Jan. 2012; BTS/A.D. Little, Energy Consumption Characteristics of Commercial Building HVAC Systems, Volume II: Thermal Distribution, Auxiliary Equipment, and Ventilation, Oct. 1999, p. 1-2 and 5-25 - 5-26; EIA, AEO 1998, Dec. 1997, Table A5, p. 108-109 for 1995 ventilation; and DOE/Navigant Consulting, 2010 U.S. Lighting Market Characterization, Jan. 2012, Table 4.8, p. 34; EIA, Supplement to the AEO 2012 Early Release, Jan. 2012, Table 32.

Table 3.2.1. Total Commercial Floorspace and Number of Buildings by year

1) Based on PNNL calculations. 2) Percent built after Dec. 31, 2000. 3) Data is from previous year. 4) Data for 2000 and after excludes parking garages and commercial buildings on multi-building manufacturing facilities from the commercial building sector. 5) Data is from 1999. In 1999, commercial building floorspace = 67.3 billion square feet.

Sources: EIA, Annual Energy Outlook 1994, Jan. 1994, Table A5, p. 62 for 1990 floorspace; EIA, AEO 2003, Jan. 2003, Table A5, p. 127-128 for 2000 floorspace; EIA, Annual Energy Outlook 2012 Early Release, Jan. 2012, Summary Reference Case Tables, Table A5, p. 11-12 for 2008-2035 floorspace; EIA Commercial Building Characteristics 1989, June 1991, Table A4, p. 17 for 1990 number of buildings; EIA, Commercial Building Characteristics 1999, Aug. 2002, Table 3 for 1999 number of buildings and floorspace; and EIA, Buildings and Energy in the 1980s, June 1995, Table 2.1, p. 23 for number of buildings in 1980.

Table 3.2.8. 2003 Average Commercial Building Floorspace, by principly building type and vintage.

(Source: EIA, 2003 Commercial Buildings Energy Consumption Survey: Building Characteristics Tables, June 2006, Table B8, p. 63-69, and Table B9, p. 70-76.)

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United Kingdom Source: ECG Energy Use in Offices 19 (2000)

** Data here is oldest of the entire set. It is out dated and many recent documents will reference this despite its age.

The benchmarks are most appropriate for managed buildings with floor areas of 1500 m2 or more. They allow for actual hours of use including cleaning, weekend work and so on, and the wastage and inefficiency that inevitably occurs to some degree, even in the best regulated environments.

The Building Types Studied

Office Type DescriptionA simple building, often (but not always) relatively small and sometimes in converted residential accommodation.Typical size ranges from 100 m2 to 3000 m2. The domestic approach, with individual windows, lower illuminance levels, local light switches and heating controls helps to match the operation with the needs of occupants and tends to reduce electricity consumption in particular. There also tend to be few common facilities. Catering often consists of the odd sink, refrigerator and kettle.

Largely open-plan but with some cellular offices and special areas.Typical size ranges from 500m2 to 4000m2. This type is often purpose built, sometimes in converted industrial space. Illuminance levels, lighting power densities and hours of use are often higher than in cellular offices. There is more office equipment, vending machines etc, and more routine use of this equipment. Lights and shared equipment tend to be switched in larger groups, and to stay on for longer because it is more difficult to match supply to demand.

Largely purpose-built and often speculatively developed.Typical size ranges from 2000 m2 to 8000 m2. This type is similar in occupancy and planning to building type 2, but usually with a deeper floor plan, and tinted or shaded windows which reduce daylight still further. These buildings can often be more intensively used. The benchmarks are based on variable air volume (VAV) air-conditioning with aircooled water chillers; other systems often have similar overall consumption but a different composition of end use. (See Good Practice Guide (GPG) 71 ‘Selecting air conditioning systems. A guide for building clients and their advisors’.)

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A national or regional head office, or technical or administrative centre.Typical size ranges from 4000 m2 to 20 000 m2. This type is purpose-built or refurbished to high standards. Plant running hours are often longer to suit the diverse occupancy. These buildings include catering kitchens (serving hot lunches for about half the staff); air-conditioned rooms for mainframe computers and communications equipment; and sometimes extensive storage, parking and leisure facilities. These facilities may be found in offices of other types, and, if so, should be allowed for.

Low energy consumption is just one attribute of a carefully designed and well-managed building – comfort and productivity are others. Conversely, energy waste is an indicator of poor business management elsewhere. Maintenance organisations need to be carefully briefed and supervised if they are to manage energy effectively. If this is not reflected in contract conditions, systems may be run wastefully.

Variation in energy use between building types and end-uses reflects:

Differing occupancy, servicing and equipment in each of the four types Wide ranges in efficiency and utilisation for different systems.

There are nine principal end uses for energy in office buildings relating to building services or occupiers equipment.

End uses (building services):

Heating and hot water – by gas or oil Cooling – including chillers, packaged air conditioning equipment, condensers and cooling towers Fans, pumps and controls Humidification – though rare, is spreading in mechanically ventilated and air-conditioned buildings Lighting of the treated area. End uses (occupiers’ equipment): Office equipment – excluding vending machines, local kitchens or equipment in dedicated rooms (eg computer

suites and print rooms) Catering – including vending machines, kettles, dishwashers etc, and sometimes catering kitchens, shown in type

4 only Other electricity – including lifts, print rooms, and energy use outside the measured treated area, for instance by

plant room or exterior lighting Computer and communications rooms – including air-conditioning of their dedicated suites. Energy use depends

on the amount of equipment installed and can be substantial.

System and Component Benchmarks

LIGHTING

The annual EUI (Energy Use Indices) are the product of:

the installed power density in W/m2 the hours of use of the lighting the percentage utilisation.

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IPD (installed power densities) is estimated by:

adding up the wattage of all the lamps in an area adding control gear losses for discharge and fluorescent lighting (these typically add 20% to lamp rating, or 5% for

high-frequency ballasts, but check manufacturer's data) dividing the total by the floor area.

For offices with a repeating luminaire ceiling pattern, only a representative ceiling module needs to be assessed. The ‘hours of use’ is the annual period over which illumination (daylight or electric light) is needed in the offices, both for normal occupancy and for cleaning.

The ‘percentage utilisation’ is the time the electric lighting is on during those hours. It depends how much the lighting is off or dimmed, either by successful use of daylight, occupants selecting lower illuminance levels, or lights being off in unoccupied areas. The percentage tends to decrease with better manual and automatic controls.

IPD can also be defined as the product of the desktop illuminance level (in lux) and the illumination efficiency in W/m2 per 100 lux.

The good practice benchmark of 12 W/m2 is based on a level of 350-400 lux (often a good compromise between screen and paper-based tasks) at an efficiency of 3 W/m2 per 100 lux. This efficiency level is obtainable with good luminaires and high frequency fluorescent lighting, with a small allowance for decorative lighting. For 500 lux or an uplighting installation to 300-350 lux, an IPD of 15 W/m2 may be required. If your installation has an IPD well above 20 W/m2, replacement will often be cost-effective, particularly with long hours of use.

FANS, PUMPS AND CONTROLS

Air handling is one of the largest energy users in an air-conditioned office. Its EUI is the product of:

the amount of air handled – in litres/second per m2 of TFA. This typically varies between about 1 and 8 the average efficiency with which it is handled – called specific fan power (SFP) – in watts per litre/second (W/l-s) the annual hours run (hrs/yr).

For air-conditioning, SFP typically varies between 2 and 5 W per l/s. For energy-efficient systems a guideline of 1 W per l/s has been suggested, but this is difficult to attain except in simple systems or low speed operation.

OFFICE EQUIPMENT

Typically, desktop and associated IT equipment such as computer, printers, modems and faxes average about 160 W per work location.

The benchmarks in table 5 are the product of:

the load density in W/m2 the average hours per year (this includes for about 10% of the equipment being on permanently) the percentage of the floor area with IT equipment ie not including circulation space, meeting rooms, toilets,

stores etc.

Occupancy and equipment levels vary widely. Many small offices use less IT equipment less intensively, and their energy consumption will be lower. Some air-conditioned offices have high concentrations, though this is sometimes compensated for by liberal space standards in the building as a whole, particularly type 4.

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NOTE: the benchmarks do not include dealing rooms, which are highly variable and should be assessed separately. Computer and communications rooms are also very variable and in a separate category. See section 5.

Method of calculating and determining indices

1. Determine building type: Choose the most appropriate category for your office from the four generic types.

2. Calculating the energy cost index: From the bills you have paid find out the total annual costs and units consumed for each fossil fuel and for

electricity. You may need to make adjustments for estimated bills, missing data or periods of more or less than a full year.

Find out your floor area. Treated floor area will have to be measured, or estimated. Divide each cost in A by B to obtain your ECI's (Energy Cost Index) in annual fuel costs per unit area per fuel.

3. Checking unit energy costs: Obtain your annual cost and energy consumption of each fuel from A. If necessary, convert the annual units of each fuel consumed into kWh. For each fuel, divide annual cost by annual consumption to get the average unit cost per kWh.

4. Unit cost assessment: If the costs are very different from the average energy costs, then there is probably a mistake. If after

checking they are still high, then you may be able to purchase fuel more competitively unless your location or pattern of use is forcing up the unit rate (this should also be checked).

5. Choosing a benchmark: Choose good practice and typical ECI benchmarks for your office type.

6. Making the comparison: Comparison can be illustrated by histograms, which place the ECI for your building between the chosen

benchmarks. If your unit costs for any fuel are particularly high or low, you may need to correct the benchmarks to the rates you actually pay.

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Italy Source: D2.1a - Survey on the energy needs and architectural features of the EU Building Stock

"This document has been produced in the context of the iNSPiRe Project. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-201 3) under grant agreement n° 314461 . All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission has no liability in respect of this document, which is merely representing the authors view".

Data Gathering and Reporting

The data gathering exercise focused on published literature and various other sources with the aim of obtaining information about the current residential and office building stock. The types of information the survey focused on collecting included:

Number and floor area of residential buildings/dwellings and offices within the building stock; Typology ; Age distribution ; Typical type of construction, by age ; Façade types and glazing types ; Average floor area, geometry and number of floors ; U-value and thermal characteristic and performance of the buildings, by age ; Ownership and tenure i.e. number of social housing, owner occupied, private renting etc. ; Energy consumption and demand– total, space heating, domestic hot water, cooling, lighting, other ; Fuel and heating system types.

A wide variety of sources were consulted. The Office of Statistics for each country and the relevant Energy Agencies were contacted initially. Where available, data was extracted and analysed. The outputs from censuses were also invaluable in this study. Other sources of information included previous European Projects; such as TABULA, ENTRANZE, BPIE and Cost Effective etc., also Enerdata and Odyssee.

The reason for the limited availability is there is no systematic way of collecting the data for office buildings, particularly those built pre-2000.

Emporis provided some useful building-related information which was analysed to extract details about structural and façade types by age of office buildings across Europe.

Given the lack of data, “building experts” across Europe were identified, contacted and asked to participate in a telephone interview about the current building stock. The semi-structured interviews were conducted to gather further additional objective and subjective information. Most commercial organisations were not strongly motivated to assist in the research. The most positive response was generally from research and academic institutions which had a “track record” in researching this type of building.

More than 300 organisations/individuals were identified and contacted for information and invitation to a telephone interview. These organisations/individuals included Universities, Research Organisations, Property Agencies, National Statistics, Architects, Building Engineers, Chartered Surveyors, Consultancies, heating and sanitary installers, Energy

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Organisations, Construction, Government Institutes, Building Industry Association. Other contacts were identified by referrals from initial sources.

The information collected during the literature review has been presented in a database specifically created for the Inspire project. The database is in Microsoft Excel format.

It is important to note that the database and results presented in this report covers information collected from the literature only. There are gaps in the current database, which are mainly due to either the data was not found in the literature or data collected was considered to be untrustworthy and therefore not included.

Demands and Consumptions

The information was often reported in different formats. Sometimes specific energy consumption was given, other times a figure at national level was provided. In the latter case, the data was converted into specific energy by dividing by the total heated or cooled floor area.

The database contains energy demand and consumption for space heating, cooling and domestic hot water preparation, however it was more typical for consumption data to be found in literature than the demand data.

Climate Region Identification

Italy is identified as residing in a Mediterranean climatic zone.

Reliability of the analysis and procedure to discard unreliable data

For each variable and country, the aim was to collect data from at least four different sources. This was not always achieved, however sometimes more was found. All information gathered was checked and only “reasonable” data was included to the database. The data was further validated via the averaging methodology, as explained below.

Total Mm2 vs heated and cooled ones. Estimations and calculations

The database includes total floor areas and other relevant areas, such as heated or cooled area.

The residential heated floor area was sometimes reported in the literature. For countries where this was not known, proportions reported for “similar” or regional countries were taken as representative.

There was a lack of data about the cooled floor area. The proportions for buildings with cooling equipment were used as an indicator for both residential and office buildings.

The total floor areas also enabled a total figure at country, regional and EU-27 level to be calculated for the various energy consumption and demand aspects. See Figure 1 . The database sheets also include information relating to the proportions of total EU-27 inhabitants, floor area and relevant heating/cooling/lighting energy consumption/demand per country.

Calculation of Averages

The database calculates averages in two ways. The first is a simple average of the data collected. To improve the reliability of the average, the database calculates an “updated average”, which excludes data not within ± the standard deviation from the simple average. The averages reported for the individual countries, weighted for climatic regions and also weighted at EU-27 level. The database reports the total number of data points and how many were

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used to derive the new average for each country. Similar to the energy data the u-value data has been calculated at country level but also weighted at regional level to provide a more representative figure.

Total consumptions and demands calculation

The database calculates energy demand and consumption totals, at country-level, climatic region- level and finally at EU-27 level, using the “updated average” and total heated and cooled floor area, for example.

Office Stock Summary

The typologies seen in the office stock do vary across the EU-27 countries in a number of distinct ways:

Scale (linked to the population profile of each country) Age (linked to history and economic growth and public/private development). Energy used for space heating/cooling, hot water, lighting (linked to climate, each country’s history and

regulatory regime) Fuel used (linked to natural resources, industrialisation and geography)

However, the construction types of offices found within one country (and even for the same age range) are very heterogeneous. In saying that, it also believed that similar styles of construction are generally found throughout all EU-27 countries.

Size of the Office Stock

The literature review found data relating to the total floor area, however the heated and cooled floor areas were not always reported, and for many of the countries it is unlikely that these areas are known. For countries where data was not found, a 0.9 factor has been applied to the total floor area to convert the total area into a treated floor area. Not all offices have air-conditioning systems, and even those that do often do not have 100% of the floor area cooled. For countries where the cooled floor area was unknown, a 0.9x0.71 factor was applied to the total floor area.

The total office floor area in the EU-27 is approximately 1.251 billion m2. Of this, 0.987 billion m2 is estimated to be heated. The majority of the office floor area in Europe, 71%, lies in six ‘key’ countries; Spain, Italy, France, Germany, UK and Poland. This of course reflects the size of the population in these respective countries.

Age of the office stock

The literature review revealed that very little is known about the age of the current office stock, particularly those built pre-1980. However, what was evident was that although a large proportion of the office stock within the EU-27 countries dates from before 1980.

Type of Tenure

Most of the office stock in EU-27 is privately owned.

Building type and construction

The literature review revealed that the main material used in the structure of office buildings across the EU-27 is concrete. The older buildings, built pre-1960, were often built from masonry brick. The age distributions of the building in this database do not correlate perfectly with the distributions found in the literature review, mainly because more recently constructed building with detailed data is available in the database.

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The general construction types found across the EU-27 are the same in most countries. For example concrete structural frame office buildings with curtain wall facades - although they may have different number of floors or shapes, the outside of them look very similar whether you are in Germany, Italy, Hungary or UK.

The most important factor in retrofitting the office building stock however is the façade as this can have a major effect as it can cover significant areas of the building. Over the years there has been an increase in the amount of glazing and the use of non-structural infill panels.

The pre-1945 stock was typically constructed with brick structural walls and an exposed wall façade or concrete structure with concrete façade. The 1945-1964 stock has concrete structures with a brick or concrete façade. The first curtain walls also started to be seen during these years. Concrete structures continued to dominate the construction of office building into the 1970s and 1980s. During this time prefabricated sandwich walls were introduced.

The 1980s stock consisted of pre-fabricated elements, which were load bearing or in-fill only. Glass curtain walls and/or aluminium panels were fairly typical during the 1980s. The curtain wall façade seems to be the most typical type of construction, particularly those built after 1960.

Energy consumption and demand by end use

As expected, the space heating requirements are generally less in the warmer climates, whereas cooling is a higher. Specific space heating consumption is highest in the Southern Continental region (at 238 kWh/m2/year) and lowest in Southern Dry at 54kWh/m2/year. The EU-27 weighted average for space heating consumption is 161 kWh/m2/year and for 10 kWh/m2/year for DHW.

Specific space cooling consumption is highest in Southern Dry region (at 42 kWh/m 2/year) and lowest in the Oceanic region at 11 kWh/m2/year. The EU-27 weighted average for space cooling consumption is 22 kWh/m2/year.

Lighting energy consumption ranges between 25-71 kWh/m2/year, however, the average for Spain (71kWh/m2/year) does seem high. The EU-27 weighted average for lighting consumption is 39 kWh/m2/year.

Due to the lack of information found during the literature review, there are some uncertainties over the reliability of the data reported for some of the regions. None relate to Italy specifically.

Reference buildings

Not all the desired information related to the building stock was gathered from literature, mainly because the data was missing or unreliable. These “gaps” are being filled in using simulation work. Two different types of simulation of buildings are accounted for within the project:

Target buildings Reference buildings

Target buildings are meant as Virtual-Demo buildings, whose purpose is to allow calculating the effect of a number of renovation actions that cannot be verified otherwise on the three real demo buildings. As such, the target buildings are selected as “big fishes” within the actual building stock.

Reference buildings represent “average” buildings and are modelled/simulated to complement the gaps in the database, specifically for heating and cooling consumptions. The reference building models have been used to derive

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“average” heating and cooling consumption for the seven climate areas. The reference building models are based on the target building models in terms of building construction type and geometry.

The methodology used to derive the heating and cooling consumption for residential buildings was based on the available statistics for the different types of buildings and the heated/cooled area of that type: once ready the simulation models of each reference building, heating and cooling demands where simulated under a number of varying boundary conditions (such as infiltration rate, internal gains, ground coupling, etc.). The average heating and cooling demands per climatic regions –to be compared with literature information- were obtained by averaging over the building typologies described in this report (single family houses, multi-family houses in the residential sector and high-rise, low-rise office buildings).

Office Sector

Office Building 1

This category of buildings was built in pre 1970s and most typically during the 1950s and 1960’s, however small office buildings continued to be built from masonry. The main construction consists of walls and floor slabs made in situ. The structure consists of brick walls. Most buildings are constituted of usually 2 floors for an average total office of between 1800 and 3000 m2.

The lack of insulation in the facades and roofs contributes to a high heating demand. The heating generation is accomplished by fuel oil or gas boiler and distributed by radiators. The cooling demand depends on the location, so it is very variable.

The category office 1 is a low-rise masonry building, 2 floors with non-insulated, bearing brick walls. This category of buildings was built in pre 1970s and most typically during the 1950s and 1960s. The windows are double glazed and have internal shading. The roof consists of a flat concrete slab on wooden beams, with a bitumised surface.

Office building 2

The buildings in this category were mainly built between 1945 and 1970, although became most typical during the 1960s. There is little or no insulation in the buildings in this category. The number of floors in this category is between 2 and 7 floors, with an average total floor area of approximately 4000 m2.

The category office 2 is a five storey office building, plus basement with limited parking, building services, and storage space. Recreational rooms and sundeck on the roof are not part of the structural frame of the building. Precast concrete cladding panels on a concrete frame form the outer envelope of the building. The windows are double glazed and have internal shading. The typical period of construction is the 1960s.

Office building 3

The statistics showed that concrete structures dominate the stock and curtain walling is the most common type of façade. The majority of curtain walls incorporate glazing. This category is the most recent, with buildings built between 1960 and 1980. This category covers buildings with a concrete structure of reinforced cement.

Category office 3 is a five storey office building, plus basement with limited parking, building services, and storage space. Recreational rooms and sundeck on the roof are not part of the structural frame of the building. Window frames with aluminium panels form the outer envelope of the building, fitted between the concrete pillars and beams. Effectively each façade has three elements to the thermal envelope: concrete, aluminium, and glass. The windows are double glazed and have internal shading. The typical period of construction is the 1960s.

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Sweden Source: Improved Energy Statistics, Sweden, 2007 Study Report

Completed surveys

Overall, the inventory of 127 buildings completed. Of these, 123 pieces completed with quality assured results. Of the 127 surveyed buildings the 62 pieces from SCB's selection. In addition to the 127 inventoried buildings have 94 buildings existed in the work of the project, but been eliminated at an early stage of because they failed to meet the following criteria for buildings. The 123 inventory oriented and quality assured buildings with a total building area (BRAt) of 834,000 m2

Criteria for buildings within the category of office and administrative buildings can participate in "Step by Step STYLE" project:

The total area should be between 200 m2 and 30,000 m2. At least 80% of the building should be leased office area (1,2). Buildings should be included in the project should not have further supply of heat or electricity to other buildings

(3). A full year's media statistics with existing installations and tenants shall be provided, including tenants' electricity

use (4). Buildings should not have too many tenants with their own reading of electricity (Limit 12-15 pcs) (5).

1) If the surveyor at the time of inspection discovered that the proportion used / are leased as office was less than 80% but more than 50%, were carried out inspection anyway. 2) According to Statistics Sweden defines a building to the building category as at least 50% of the building employees turned to. 3) If the surveyor during the visit of the building discovered that further delivery after all is done has an estimate of how much energy the second building made and media statistics on the corresponding generating means reduced. 4) In SCB's statistics include both leased and non-leased premises. 5) The reason for this is that it takes very long time to collect data on all tenants' electricity use.

A prerequisite is that property owners, property managers and caretakers are interested in helping with viewing and production of statistics. (Within the framework of the project was offered the property owners help to obtain information about both their own and the tenants' energy use by proxy).

District Heating

District heating is dominant as a heating source for the inventoried office buildings, and represents 90% of the energy supplied to buildings for heating and domestic hot water. Other heat supply comes mainly from direct electricity (2.3%), oil boilers (2.2%), and the recovery from chillers (2.1%).

Of the 123 surveyed buildings are 117 pc connected to the district heating network. The 17 buildings exist direct electricity, and 24 are electric heater to heat the ventilation air. 7 buildings have electric boiler and 3 have water dispenser. Only one building has its own oil boiler. In a building uses city gas for heating. A building has outdoor air and a geothermal heat pump.

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29 of the 123 surveyed buildings are connected to district or cooling. There are relatively many presumably due to the inventoried buildings located in areas with access to remote or cooling, such as Stockholm. 91 buildings have comfort cooling of any kind while 57 buildings have process cooling. Water chillers occurs in 84 buildings and three urban water cooled.

The specific energy consumption for heating excluding cooling and power for climate cooling is on average 106 kWh per m2 per year, calculated for each building separately, based on building-specific data corresponding to those in Table 6, and distributed on the current building's total area (BRAt)

Specific annual energy use for heating office and administrative premises (excluding remote and närkyla and electricity for climate cooling) per m2 amounts, according to Statistics Sweden's energy statistics for premises 2004-119 ± 2 kWh per m2 per year (6).

Including cooling gives SCB statistics 128 ± 2 kWh per m2 per year (7) for office and administrative premises while the average for these inventoried buildings which amounts to 120 kWh per m2 per year.

6 and 7 Source: Statistics Sweden EN 16 SM 0503

The lower specific heating requirements of the inventoried buildings can be partly explained by the greater proportion of these are built after 1980 than in terms of facilities in the country as a whole. According to Statistics Sweden has buildings built after 1980 a specific energy of about 97-98 kWh per m2 per year depending on byggårs range, while those built before 1980 use 120-133 kWh per m2 per year, depending on byggårs range. The climate has of course also important, and the extent to which these inventoried buildings have a geographical distribution that corresponds office and administrative facilities in the country as a whole.

Electricity Consumers: The Distribution of Use

Lights and fans are the most significant electricity use areas in the surveyed office buildings. Together they constitute the entire 37.5% of electricity use in the inventoried buildings. In addition represents data centers and server rooms, PCs and chillers large electricity use areas. Of the total electricity consumption for office and administrative premises is 53% business electricity and 47% residential electricity.

Property electricity consumption is allocated to each building area just for office and administrative activities (share office of brat), while real estate electricity is allocated to each building's total area (BRAT). It should be noted that it is not clear who actually pay for the items in the table. It may for example be that the lighting is included in the property panel, but it does not therefore appear here. Miscellaneous This item is an amalgamation of another, identified use, and of that which has not been traced. (8,9,10)

8) All buildings do not have data center or server. If only the buildings that have data center or server is considered, the specific electricity consumption for this purpose will on average be 13.8 kWh / m2 per year of 112.6 kWh / m2 per year, ie 12.3%.9) If one disregards the electricity used for heating of any kind (this electric boiler, direct electricity, water heater, electric heating coil in the ventilation system or heat pump) is the specific electricity consumption 102 kWh / m2 per year.10) All buildings have not chillers. If one considers only those buildings that have chillers, the specific electricity consumption for this purpose to be an average of 15.0 kWh / m2 per year of 124.5 kWh / m2, ie 12.0%.

All the buildings have not all installations and facilities. A mean value must be used with care. The building has no elevator of course, is the use of electricity equal to zero in that case. Likewise, some buildings heating and others do

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not. For those who have electric heating value will be significantly higher, while for those who have no value will be zero. Only a few areas of electricity consumption occurs in all buildings. For most purposes, there will always be some building without that type of electricity. Some electricity consumption occurs in all buildings, while another found only in part. The results for the specific use of electricity in different applications is therefore equally sensitive to the percentage of the extremes are excluded, ie how many buildings are taken into account.

For lighting, fans and PC shows no significant difference in the specific use of electricity at different boundaries because this type of electricity is found in all buildings and shows a relatively even specific use.

For both data centers and server rooms and cooling equipment, for which electricity is more uneven, however, the value drops more. Below in Figure 9 illustrates this by the percentage deviation of the specific value displayed when internal percentiles P0,025 - P0,975 (5% excluded), P0,05 - P0,95 (10% excluded), and P0,1 - P0 , 9 (20% removed) is considered.

The lighting electricity use

Electricity consumption varies between 7 and 53 kWh per square meter per year. The mean value of the inventoried buildings is 23 kWh per square meter per year. Electricity consumption for each building is an estimate based on installed capacity and operating times.

Fluorescent lamps with conventional ballasts nearly half (46%) of the installed power for lighting in the inventoried buildings. The conventional operation means relatively high electricity consumption, with heavy losses in the diffuser. Fluorescent lamps for conventional operation (T8 tubes) has a diameter of 26 mm .Tidigare used T12 fluorescent tubes with a diameter of 38 mm, they may still occur in some buildings. For better energy has in recent years developed high frequency ballast (HF-ballast / ECGs), with minor losses. ECGs can be used for both T8 tubes (diameter 26 mm) and the newer slim T5 fluorescent lamps. T5 tubes are always powered with electronic ballasts and has a diameter of 16 mm. Fluorescent lamps with electronic ballasts, together for T8 and T5 is 27% of the installed power. In total, fluorescent 74% of the installed power for lighting, see also Table 10. Bulbs account for 12% of the lighting electricity use in the study.

The installed power for lighting has also been divided into various room types within the sector offices and management. Room types include individual offices, large room or landscape. They inventoried the buildings have been divided according to Figure 13 and Figure 14. As shown in both Figure 13 and Figure 14 represent the actual work rooms only less than half of the area offices and other spaces dominate. Other areas constitute corridors, stairwells and other public areas including heated garage (> 10degC).

For assessment of the lighting condition in different types of rooms the basis is about 270 000 m2 of individual offices and 50,000 m2 large room or office. The installed capacity in the various offices room types are quite similar, though slightly higher in individual offices. For other areas, the installed capacity lower. The effects shown in Figure 15 and Table 11.

Fan Electricity Use

The fans electricity consumption varies between 2 and 57 kWh/m2 per year for the inventoried buildings. The average is 17.9 kWh/m2 per year. Installed capacity for fans (19) amounts to a total of 3.9 W/m2. The fans then go about half a day on average.

The most common type of ventilation of the inventoried buildings are air handling units with constant flow ventilation, so-called CAV (75%). This is followed by air handling units with variable flows (VAV), and ventilation with both supply

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and exhaust fans (TF). Ventilation system with only exhaust fans (FF) or buildings with only natural ventilation are very few.

Supply Air Flow varies as shown in Figure 17 for all the studied buildings, where even such natural draft is represented in the figure. The mean is 1.48 liters / sec and m2, which provide good air circulation. As the room height average is 2.93 m, corresponding to an air change rate of 1.8 turnovers per hour when the fans are running.

Electricity consumption in relation to airflow Specific Fan Power (SFP) is for the inventoried buildings 2.75. SFP is then defined as the total electrical output for both supply and exhaust fans divided by the greater of the two flow rates [W / L, p-1].

19. This refers to operating at full speed for air handling units

PC and data center electricity use.

PC devices is one of the electricity use areas are found in all offices soch administrative buildings. Spread range is when two extreme cases are excluded, 1 to 35 kWh per m2 per year, see Figure 18. The two extreme cases is 134 respectively 830 kWh per m2 per year.

Average when all the buildings included is 15.5 kWh per m2 per year. Data centers and server rooms is present in most office and administrative premises, but it may also be that they have their server in another location. Spread The range for electricity use in data centers and server rooms is 0-85 kWh per m2 per year, see Figure 19. Average when all the buildings included is 10.9 kWh per m2 per year.

Specific electricity consumption for PCs, data centers and server rooms together amounts to 26.4 kWh per m2 per year for the inventoried buildings.

Other electricity

Property electricity besides fans consist primarily of electricity for chillers (10.6 kWh per m2 per year), electric heating and electricity for heat pumps (6.5 kWh per m2 per year), electricity for pumps (5.5 kWh per m2 per year) and electricity into circulation fans (2.6 kWh per m2 per year). Operational electricity besides lighting and computers are very small. Only the kitchen and pantry exceeds 2% of total use, while the other uses each represent less than 2% of electricity consumption. Together, other appliances for operation as specified in Table 9, approximately 7.4% (2.6 kWh per m2 per year) of the specific electricity consumption for the investigation office and administrative buildings.

Electricity consumption for cooling

Chillers specific electricity consumption for all inventoried buildings is averaging 10.6 kWh / m2 per year, which also includes buildings that have no electricity demand for cooling. These can be either remote or cooling, or no cooling at all.

Chillers specific electricity consumption in the inventoried buildings is the most significant electricity consumption for cooling in office and administrative premises. The amounts mentioned above 10.6 kWh per m2 per year. Also included electric Chiller Condenser electricity use increases the specific electricity consumption for cooling by 0.8 kWh per m2 per year.

Cooling occurs in 29 of the 123 inventoried buildings. While cooling causes electricity use even if it is not done within the building. In order to give a clear picture of the electricity used to cool the inventoried office and administrative buildings, even the electricity in the district cooling networks considered. If the district cooling adopted use 0.29 kWh

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of electricity per kWh of thermal cooling for the building (ie COP 20 = 3.5), this reasoning further 2.1 kWh per m2 per year on average for all buildings. This electricity is not included in the reported average value of all inventoried buildings at 109 kWh per m2 per year. (NB COP = Coefficient of Performance).

Project Purpose

The project aims to enhance national energy statistics for the local sector. This stage of the work is focused on building category offices and administrative premises. The work includes all energy used in the inventoried buildings, but has its main focus on electricity consumers distributions at various purposes (uses). The aim has been to regard the average specific values for the various purposes [kWh / area, year] for the whole group.

Scope

The scope of the project includes the following elements:

Further development of the working model for inventories Training of inspection official Support the identification of suitable buildings Inventories Main Inspection acumen with control inspections and quality assurance of inventories Analysis and Accounting Compilation of feedback to the property owner Project management with the compilation of the report

Work Boundary

The work covers the first year of inventory in the "Step by Step STYLE" project.

The first year's inventory refers only to office and administrative premises. The mission did not include making the selection of the premises, or inviting property owners to participate in the study. The Principal National Energy has been responsible for the selection and invitations, and this was done with help from Statistics Sweden (see also 5.2 Selection).

The inventories bounded aimed primarily determine the specific electricity use in office and administrative premises. This means:

1) that the premises with a small portion other activities, no accurate inventory of the specific electricity consumption in this small part, and

2) to other energy, so that energy for heating and cooling are of secondary interest. The latter is needed to make accurate assessments of building services such as electricity for the operation of chillers, fans, pumps and more.

The contact with the property owner is important in the work of "Step by Step STYLE" project, and as a service to property owners who took the time to participate in the study, a performance summary was provided. This results reversal is limited to presenting a selection of key indicators that describe the relevant individual building's electricity consumption and compared with the corresponding ratios for the average of the whole group inventoried buildings. The reversal does not contain any analysis of why the building possibly different from the crowd, nor any advice on appropriate actions to those with higher electricity consumption than the average.

Method

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Earlier work done in 2005

Within the framework of part of the "Step by Step STYLE" In 2005, following work carried out within the framework of the Agency's commitment to improving energy statistics for premises:

Further development of the working model Training of inspection official Selection of premises inventories

Further development of the working model

A further development of the working model and the development of certain key ratios, primarily for office and administration buildings were made in the spring of 2005. This work was presented in the report "Verification of key figures - Stepwise STYLE" (Report dated 2005-08-08).

As part of this mission, no significant changes in the model made. However, clarifications and suggestions on values added in several places in the model, for example in terms of lighting and effects for different types of light sources and boiler efficiencies.

Sample

Selection of premises for year 1 of the inventories in the "Step by Step STYLE" has been carried out by Statistics Sweden on Energy Agency's mission. SCB has drawn a selection of premises, whose owners have been invited to participate in the project. Energy Agency sent out a letter of invitation to the selected property owners. SCB's sample included 340 buildings (register contains a total of about 8000pcs). Of those obtained positive response from the owner of the 136 buildings.

Energy Agency's selection has been made so that the overwhelming majority of the buildings (80%) to be visited is located in the Mälardalen region, with the remaining buildings in northern Sweden (10%) and southern Sweden (10%). The reason for adding the vast majority of the number of buildings in the Mälardalen region was an effort to keep the project budget as low as possible.

During the project's initial phase was realized that all buildings notified to the project did not meet the criteria for the project, and that a further thinning of buildings thus was necessary. This was done by a short telephone interview with the current property owners. One reason for attrition was that they entered the buildings had a tendency to be very large. To begin with, was elected buildings larger than 30,000 m2 removed immediately. At a later stage of the project we had to look even smaller buildings. The selection criteria used in the telephone conversation with the property owners are:

The total area should be between 200 m2 and 5,000 m2 (previously 30,000 m2). Larger buildings can be discussed.

At least 80% of the building should be leased office space. Buildings with further supply of heat or electricity to other buildings should be avoided. A full year's media statistics with existing installations and tenants should be. Buildings with too many tenants who have their own reading of electricity (limit 12-15 pcs) should be avoided. A prerequisite for participation in the project is that property owners, property managers and caretakers are

interested in helping with viewing and production of statistics. We offered assistance in obtaining media statistics if we had power of attorney (s).

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With this thinning needed sample supplemented to the number of buildings would be big enough. The new buildings were chosen so that the geographical spread was better (see Table 2), except that they also fulfill the above criteria.

Inventories

When inventory is a walking tour of the current building with floor plans and notepad - most entries are made directly on the drawing.

Together with the contact person for the building frequented boiler room and ventilation room, and statistics of operation are checked. Clarification of the building parts heating 41 system, electricity, or installations with adjacent building (s) are made. Electricity consumption for operation of fans and pumps can be measured by current sensor.

Other public areas exhibited by the building facilitator, energy consumption is estimated for business electricity for lighting, lifts, etc. in these areas.

Tenants are visited, and surveyor calculates and evaluates equipment in offices and common areas. With the help of the model proposed metrics and talks with a representative of the tenant then estimated the annual energy use for business electricity of the tenants in the building.

Protocol

Quality Assurance

The model is structured so that the measured and estimated data should correspond to actual operating data, and each inspection official to be correct so that no large "residual" of unidentified energy remains.

Main inspectors then makes a quality control, where the plausibility of certain key indicators are examined. Main inspectors will determine whether the assumptions seem reasonable or not, and for a dialogue with the surveyor if necessary.

Main inspectors are the ones who determine whether re-survey of a building to take place. Project budget contains only a limited entry for surveys, and selecting possible surveys made final until all items are inventoried and proper prioritization can be done.

Possible Re-survey

On behalf of the principal inspectors, some buildings have to re-survey. The division of responsibilities at follow up surveys decided on by the inspectors.

Summary

In the model, there are various spreadsheet for input. There are also two worksheets compilations, one for quality and one that is used to deliver results to the Swedish Energy Agency and Statistics Sweden.

Results for the property owner

Based on the results summaries of the model can be a result file provided to the property owner who experience feedback. This reversal can serve two purposes:

1. To encourage actions (by, for example, enter averages for different ratios, those who have high relative energy use in one or more areas get knowledge about this).

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2. To create the opportunity to ask about follow-up measurements that can be made later.

Analysis

Calculations of specific values, kWh / m2 per year, has been made for each building separately. Subsequently, an average calculated for all buildings specific electricity consumption per application. For all parameters have differences regarding ownership category examined, but only in a few cases reported differences. In general they are very small.

The material obtained through this project is very extensive and detailed. The material can be the basis for a large number of further studies. A first presented in Appendix 5, where the material used to create a picture of energy use for various purposes in office buildings on a national level, and to compare the obtained results with the results of STYLE study from 1990. This gives a picture of how electricity use in facilities developed over the past 15 years.

The material can also be used for further analyzes are required to facilitate the implementation of the EU Directive on buildings' energy labeling and to allow the identification of efficiency measures. With the help of this resulting statistics, it is possible to analyze the characteristics of an office building with low energy consumption. This can be done by categorizing the material to a number of office building types with respect to age, size, etc. then made for each category, the average energy consumption and the upper and lower classes. Using this classification, identification may be made to what the installation in terms of the characteristics of a good and efficient building, known as a "best practice building". A "best practice building" will serve as a model for comparison for property owners in various electricity usage areas such as lighting, ventilation and cooling installations.

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