Auditac tg7 benchmarking guide for ac based on elec bills

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Auditac tg7 benchmarking guide for ac based on elec bills

  1. 1. Technical guides for owner/manager of an air conditioning system: volume 7A benchmarking guide adapted to airconditioning based on electricity bills 1
  2. 2. Team France (Project coordinator) Armines - Mines de Paris Austria Slovenia Austrian Energy Agency University of Ljubljana Belgium UK Université de Liège Association of Building Engineers Italy BRE Politecnico di Torino (Building Research Establishment Ltd) Portugal University of Porto Welsh School of Architecture Eurovent-CertificationAuthors of this volumeJérôme ADNOT (Armines, France)Daniela BORY (Armines, France)Maxime DUPONT (Armines, France)Roger HITCHIN (BRE, UK) The sole responsibility for the content of this publication lies with the authors. It does not represent the opinion of the European Communities. The European Commission is not responsible for any use that may be made of the information contained therein. 2
  3. 3. Objectives of the guideThe objective of this guide is mainly to help building owners to detect changes in energyconsumption of their air conditioning plant as a first step in identifying and correcting faults. Evenin the absence of obvious faults , building owners should monitor energy consumption and bealert for early signs of problems. This will enable them to react promptly through behavioralchanges, operational changes (system adjustments), investment in component replacement orin extreme cases with a complete retrofit. When changes have been introduced, monitoringallows the effectiveness and actual payback times to be assessed for future use.In order to help the managers an action plan has been defined: a complete scheme of the plan isreported in the next page and it is detailed all along the document.Moreover, some example of ratios of energy consumption are presented in the annex asindicative values that should be considered for their order of magnitude more than the valueitself. 3
  4. 4. ACTION PLAN PRELIMINARY ACTIONS Determine the electricity uses included in the bill in general Collect electricity bills (prefer monthly to annual basis to get more accuracy) Determine parameters having effect on electricity consumption in general 1st Part: Basic benchmarking of 2nd Part: Benchmark typical energy 3rd Part: climate based energy 4th Part: multi-parameter energy energy consumption ratios signature signature Collect activity indicators that might Choose main activity indicators that Determine the best time period Choose main activity and climate justify variations in electricity justify variations in electricity (monthly/weekly for DD, daily for average indicators that justify variations in consumption consumption temperature) electricity consumption Note any changes other that climate Calculate electricity consumption on the Determine the best temperature reference Determine the best time period (monthly,(process, adjustments) from one time time period (the same as the one used in (usually 18°C in winter, from 14°C to 24°C weekly, daily) period to another statistics) in summer) Measure/get every chosen indicators forCollect electricity bills (prefer monthly For each activity indicator and the same Measure/get average daily temperature or each time periodto annual basis to get more accuracy) time period, divide energy consumption calculate/get degree-days for each time by the indicator period Measure/get from bills the electricityDraw the diagram: time period on the consumption of each time periodX-axis and kWh/time period on the Y- Compare each ratio from one time period Separate cooling degree-days from If enough dots are available, establish axis to another heating degree-days the linear regression (E=Σai.Pi + b) between electricity consumption E and Try to explain variations in Try to explain possible variations Measure /get from the bills electricity every parameters Pi consumption thanks to previous (climate, adjustments etc…) consumption on each time period changes or activity indicators Try to find the reasons why a new dot is Compare each ratio to statistics Draw the diagram for each time period: outside the scatter – If differences areIf variations are unexplainable, call a average temperature or DD on the X-axis too important, too frequent andprofessional (energy supplier, ESCO Try to explain possible differences (size, and kWh on the Y-axis unexplainable, call a professional etc.) for an energy audit climate, adjustments etc…) As soon as a season/year is complete, (energy supplier, ESCO etc.) for an determine the (linear) regression between energy audit Try to continue that follow-up of If variations/differences are consumption and climate parameters energy consumption even if no unexplainable, call a professional Calculate energy ratios by extracting problem is detected (energy supplier, ESCO etc.) for an Try to find the reasons why a new dot is multiplier coefficients ai energy audit outside the scatter – If differences are too important, too frequent and Compare to statistics – Try to explain Try to continue that benchmarking of unexplainable, call a professional (energy possible differences (size, activity, energy ratios even if no problem is supplier, ESCO etc.) for an energy audit adjustments etc…) detected Calculate climate independent energy ratios (slope of the regression curve) in Try to continue the energy signature kWh/m2.DD even if no problem is detected Compare to statistics – Try to explain possible differences (size, activity, adjustments etc…) 4
  5. 5. 1. Pre-requisiteEnergy uses having effect on the electricity bill of a buildingAny building owner must be aware that, for more accuracy, direct measurements on individualitems of equipment (chiller for example) or energy use (lighting for example) - which may need tobe organized by himself – are preferable overall utility energy bills. The latter combine energyconsumption by numerous end-uses and may relate to time periods that are not ideal formonitoring purposes.The total electricity bill mainly includes the consumption of lighting, ventilating and small powerappliances (kitchen or office equipments, HI-FI etc…) and sometimes process loads such as aircompressors, pumps, fans etc…Air conditioning, is included because non-electric cooling is rare.Building heating and domestic water heating can also be provided by the Joule effect (directelectric) or with a heat pump. However these two activities often use fossil fuels and are thenaccounted in a separate bill.Interpretation of electricity bills requires the listing of each type of electrical appliances whoseconsumption is included in the energy bill. When possible, try to evaluate the electrical powerthey absorb in operation by looking at their electrical plate or documentation (see Table 1). Appliances type Number of Electric unit Operation hours Energy (kWh) equipments power Computers 40 300 4380 13140 Printers type A 10 400 500 2000 (20 stand by) 1000 200 Bulbs type X 50 60 5000 3000 Bulbs type Y 10 100 5000 5000 Neon type Z 70 40 1540 616 Electric heaters 10 1200 2500 30000 Etc. …. … … … Total energy (kWh) xxx Table 1 An example of listing the electric appliances and their nominal power.It is important also to estimate the number of hours they operate during the period covered bythe meter readings.. Absorbed power and time of operation can be used to estimate the energyconsumption. The total amount of energy calculated should be compared to the actualmeasured consumption in order to verify the consistency of the list and its exhaustiveness.Keep in mind that the analysis of air conditioning performances using global energy bills will beaccurate only if the share of air conditioning energy consumption in the bill is significant. Ifenergy consumption for cooling is submerged by that from other uses, accurate estimation willbe impossible without sub-metering.Parameters having effects on air conditioning energy consumptionSeveral parameters have effects on air conditioning energy consumption and more generally onall thermal energy consumption. It is possible to distinguish four types: 5
  6. 6. - Building parameters are intrinsic to the construction of the building. The building shell thermal characteristics, the glazing surface, heated/cooled areas and their location are part of them. They were fixed by the first owner of the building and are difficult for following building owners to change because of the costs of retrofits and relatively long payback times. - Policy parameters depend only on the current building owner’s decisions and his will to save energy. Equipment choices and investments, operational parameters such as temperature and humidity set points (if building centralized), the time of operation or maintenance and follow-up policies are among them. The sensitivity of energy consumption to these parameters is really important. - Behavioral parameters depend on the occupants’ choices. Operational parameters such as temperature and humidity set points (if room localized) or the natural uneconomic behavior of occupants are part of them. Their influence on energy consumption can be large although the duration of the “good practice” behavior can be short. - Activity parameters depend mostly on the use of each space . These are largely determined by the business needs of the organization. They have an important influence on energy consumption but a building owner or energy manager cannot usually change them.Interpretation requires the identification of the most important parameters affecting each type ofenergy consumption. Special attention must be paid to causes that might be improved by thebuilding owner.These are then the preliminary actions to develop in order to begin the analysis of the energyconsumption of the building and are necessary to all the processes developed in the followingparagraphs. PRELIMINARY ACTIONS Determine the electricity uses included in the bill in general Collect electricity bills (prefer monthly to annual basis to get more accuracy) Determine parameters having effect on electricity consumption in general Figure 1: Preliminary part of ACTION PLAN 6
  7. 7. 2. Basic benchmarking of energy consumptionWith such numerous parameters, it is clear that the energy consumption of buildings can differstrongly. The first part of this guide is dedicated to the simple follow-up of energy consumption ofone building from one time period to another. Most of owners only focus on energy bills at thebuilding level looking almost only at the amount of money they pay, but several factors should beconsidered when comparing bills such as energy prices (that vary in general form one year toanother), climate effects, activity and changes in the building structure, operation etc. Thinkingabout energy uses can bring however a lot of additional information.After listing energy uses and influent parameters, it is important for a building owner todetermine the optimal measurement frequency (less than an hourly, hourly, daily, weekly,monthly, yearly etc…). The objective is to maximize the information available while minimizingthe quantity of measurements and associated costs. Again, when certain parameters (climate forexample) vary a lot, it is relevant to reduce the time period to get more accuracy. Prefertherefore monthly billing to yearly billing for thermal uses. If it is not possible, try to make yourown measurement using additional metrology (general meter, sub-meter, portable metrology).As soon as consumption of at least two time periods for the same building are available, you canbegin the comparison. The objective of such a follow-up is not only to be aware of variations inenergy consumption but also to look at parameters responsible of such variations. Logically ifthermal uses (pure cooling system, joule effect heating or reversible heat-pump) are notnegligible in the bill in comparison to process uses, electricity consumption must be maximal insummer (July or August) and in winter (December, January or February). Therefore, detectpossible problems on energy consumption magnitudes and variations with time by trying toexplain the bill through the main influent parameters you found previously. Once the responsibleparameters are underlined, think to possible actions that would allow optimizing energyconsumption1 or call a professional to assist you and perform a detailed energy audit.Observe for example the variations of annual electricity consumption in some banking agencies(Figure 2). Electricity uses (office equipments, cash dispensers, lighting, HVAC) are known andunlikely to change unless in terms of quantity especially for cash dispensers. Opening hours areconstant from one year to another in a bank agency so that electrical appliances operate for thesame duration each year. On these examples, the area of the bank agencies and the staff areunchanged from one year to another. The only parameters that can explain such variationscould be: activity variations of the agency (customers?), process changes (quantity, type?),operational changes (temperature set-points, operating hours?) or climate variations (winter,summer or both?). In that case, the agency manager is finally the best person able to determinethe origins of these variations, to know if they are normal or not and to decide to carry outactions.1 You can consult for a full list of Energy conservation opportunities the ECOs list on the AuditAC web siteand the AuditAC technical guide 5 - ECOs for AC auditors. 7
  8. 8. Figure 2: Examples of variations in annual electricity consumption in some banking agencies.Then observe for example the variations of monthly gas and electricity consumption in a servicebuilding in Portugal. Of course the use of gas is related only with the winter season and becausethe building is air conditioned all along the summer season, monthly consumptions are related tothe weather. Figure 3: Examples of variations in annual gas and electricity consumption in a library in Portugal2.2 AuditAC Case studies brochure: Case studies: Portugal, n°3. 8
  9. 9. 1st Part: Basic benchmarking of energy consumption Collect activity indicators that might justify variations in electricity consumption Note any changes other that climate (process, adjustments) from one time period to another Collect electricity bills (prefer monthly to annual basis to get more accuracy) Draw the diagram: time period on the X-axis and kWh/time period on the Y-axis Try to explain variations in consumption thanks to previous changes or activity indicators If variations are unexplainable, call a professional (energy supplier, ESCO etc.) for an energy audit Try to continue that follow-up of energy consumption even if no problem is detected Figure 4: First part of ACTION PLAN3. Benchmark typical energy ratiosThe lack of reference often leads us to think that everything is OK. The objectives of the secondpart of that guide are to allow building owners to compare their energy consumption. Although itis difficult, the idea of benchmarking is then to try to build “universal” indicators that can becompared in the same activity sector whatever the building. To reach that independency fromthe activity level, the best way is to calculate energy ratios (kWh/activity parameter/time period)by dividing energy consumption of a system (building, energy use, equipment) during a certaintime period by one or more activity indicators.The first task is to choose the best time period on which you will calculate energy ratios. Unlessyou want to regularly follow-up your energy consumption because your activity parameters varystrongly and frequently, it is useless to consider short time periods such as a week or a month.Indeed, smaller is the reference more the climate dependence is relevant, so to choose monthlyreference allows to mitigate punctual peak or minimum of temperatures. Prefer typical timeperiods such as a year or a season also in order to distinguish between heating and coolingconsumptions.There exist an obvious relationship between the number of energy uses, their size and powerand the area of the building so that the most common indicator is the cooled area (in square-meters). It can be used in every air-conditioned spaces especially buildings without specificprocesses (office or residential buildings) where no other indicators are present.Another obvious relationship exists between the area of the building and its occupancyespecially for constant occupancy buildings (no or limited numbers of external visitors) so thatthe use of that indicator should then be equivalent to the use of square-meters. In practice, it isnot as clear (Figure 5) and the distinction between the two indicators allows sometimes tomaximize the information. 9
  10. 10. 30 25 Permanent occupancy 20 15 10 5 Permanent occupancy = 0,0211 x Square-meters + 2,1101 2 R = 0,7038 0 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 2 Bank agency area (m ) Figure 5: relationship between area and permanent occupancy in the banking sector.Everybody knows that the more the activity level of a building, the higher its energyconsumption. Thermal uses are not an exception and energy consumption is correlated tooccupancy. For example, heat and humidity productions and inlets due to temporary occupancyhave to be fought against by air conditioning systems. As it is often difficult to count visitors of abuilding during a time period, it is better use other indicators that are necessarily such as:occupied beds in a hospitals, occupied bedrooms in hotels, students in schools, meals inrestaurants, tickets sold in museums or concert-halls etc… In case of variable occupancy, theseindicators should be used in addition to kWh/m2 ratios.Keep in mind that benchmarking only provides valid results (Figure 6) for the same building onseveral time periods or at least for the same category of buildings. Two buildings from the sameactivity sector may have totally different energy ratios because of their different sizes. Indeed,most processes, their intrinsic efficiencies and their control systems are often better in large-scale buildings. Moreover, these ratios do not take into account the climate influence (outdoortemperature, sun, wind etc…) on energy consumption so that comparisons of buildings in toodifferent locations may be analyzed carefully. 600 50000 550 45000 500 2003 2004 2005 2003 2004 2005 Energy ratio (kWh/person.yr) Energy ratio (kWh/m2.year) 40000 450 35000 400 350 30000 300 25000 250 20000 200 15000 150 100 10000 50 5000 0 0 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 0 5 10 15 20 25 30 Bank angency area (m2) Agency staffFigure 6: the kWh/m².year ratio decreases with the surface (left) and the staff (right) in the banking sector. 10
  11. 11. If your ratios (compare several ones) are lower than other building ratios or statistics, yourbuilding seems energy-efficient and you have probably no action to carry out or investment tomake. Continue however to regularly follow-up your indicators to anticipate problems. In theother case, you should probably contact a professional to consider some ways of improvements. 2nd Part: Benchmark typical energy ratios Choose main activity indicators that justify variations in electricity consumption Calculate electricity consumption on the time period (the same as the one used in statistics) For each activity indicator and the same time period, divide energy consumption by the indicator Compare each ratio from one time period to another Try to explain possible variations (climate, adjustments etc…) Compare each ratio to statistics Try to explain possible differences (size, climate, adjustments etc…) If variations/differences are unexplainable, call a professional (energy supplier, ESCO etc.) for an energy audit Try to continue that benchmarking of energy ratios even if no problem is detected Figure 7 Second part of ACTION PLAN for benchmarking of energy ratios.The EPlabel3 project has developed a simple software that records details of a building, its keydescriptors and its energy use and produces a summary of the measured annual energyconsumption and calculates Energy Performance indicators in units of total weighted energy perm² of internal area. The software main idea is to label the building energy performance asdemanded in the European Energy Performance Building Directive, but it can be used to definereference ratios (as built or operational rating) and visually describe the energy content of thebuilding.4. Establish the climate based energy “signature” of the buildingPrevious energy ratios are climate dependent so that only statistical ranges are published.Several climatic parameters (sun, wind, outdoor temperature, outdoor humidity) play animportant role in energy consumption of thermal uses. The objective of that paragraph is then todetermine the sensitivity of energy consumption to climate parameters. It is focused especiallyon the outdoor temperature because that parameter is easier to feel and measure for a buildingowner.3 EPLabel: A programme to deliver energy certificates based on measured energy consumption for display in Publicbuildings across Europe within a harmonizing framework. http://www.eplabel.org/ 11
  12. 12. The particular interest of such a method is to distinguish between climate dependent energyconsumption (variable part) and them that are not (constant part). The building “signature” isthen a curve that describes in a unique way the behavior if the building as a function of a climaticparameter. However, find a correlation between energy consumption and outdoor temperaturenecessarily requires a representative dot scattering, in other words much more dots. Therefore,monthly energy bills or weekly measurements should be preferred to annual energy bills. Thereare three possibilities concerning the temperature: either measure it, or get free daily-averagedmeasurements (can be found on the internet4) or pay for local hourly measurements (to nationalweather institute).Two climate indicators can be used in the energy signature. The first one is directly the averagedoutdoor temperature of the time period. As a consequence, the correlation function is growing forcooling in summer and decreasing for heating in winter. The second indicator is degree-daysthat can be calculated for heating (HDD) in winter and cooling (CDD) in summer. HDD(respectively CDD) is the sum on the chosen time period (higher than a day) of the product of“the number of days during the time period for which the outdoor temperature is lower(respectively higher) than a reference value” by “the difference between the daily averagedoutdoor temperature and that reference value”. HDD (respectively CDD) represent how cold(respectively hot) is a winter (respectively summer) time period.The main difficulty of using degree-days is to choose the good reference temperature. In theory,that value is the averaged temperature ensured only by the building shell without any additionalheating (or cooling) system. Logically, the balance temperature in winter is different from the onein summer. For heating, the reference temperature is usually taken equal to 18°C in Europe. Asheat gains can contribute to about 3°C in buildings and due to the averaged decrease of buildingshell thermal conductivity, the reference temperature for heating tends to rise. For cooling, thesame problem exist so that in large office buildings, air conditioning system may start for anoutdoor temperature of 14°C whereas in residential buildings, accounting less heat gains, thereference temperature may reach 24°C. Observe that not knowing the "proper" basetemperature is, in practice, rarely a problem for detecting changes in consumption: energyconsumption correlates well with "wrong" degree-days - since degree-day values to differentbase temperatures are strongly correlated with each other.Once you got enough dots for your energy signature, you are able to detect rapidly drifts inenergy consumption due to some defaults compared to the past normal operation. It is thusbetter to apply this method as soon as the start-up of a new thermal process in order to havereference (without default) dots. The Figure 8 sums-up some of the typical defaults that can bedetected from an energy signature analysis.4 For example, a French website centralizes several climate data in a lot of locations in the countryahttp://www.meteociel.fr/climatologie/climato.php 12
  13. 13. kWh/time unit kWh/time unit Reference Tightness CDD/time unit CDD/time unit Problems on Default on kWh/time unit kWh/time unit controls or the supply thermal probes reduction system CDD/time unit CDD/time unit Effects of Oversizing or kWh/time unit kWh/time unit Sun other overcooling climate Wind CDD/time unit CDD/time unitFigure 8: Few problems that can be detected by the climate-based energy signature of a building.That method works almost perfectly for heating and is often used in operation and maintenancecontracts with guarantee of results. However, it is not as accurate for cooling because of thehigher number and power of electrical auxiliaries, the stronger influence of humidity and solarradiation on air conditioning and the non-uniformity of temperature and humidity set points inbuildings due to a lack of regulation.Once the correlation between energy consumption and degree-days or average temperature isestablished, climate independent energy ratios are directly available calculating the slope of thecurve. It is then possible to compare your building ratios with those from any other buildingwhatever their locations. Remember that measuring only the power absorbed by the consideredthermal use (an air conditioning system for example) allows to strongly limit the offset magnitudeof the curve and to better underline the effect of climate (slope) on energy consumption. Energybills are a mix of consumption from different uses attenuating the visibility of pure thermal uses.Thus, always take care to the framework to compare ratios with statistics or between buildings. 13
  14. 14. 3rd Part: climate based energy signature Determine the best time period (monthly/weekly for DD, daily for average temperature) Determine the best temperature reference (usually 18°C in winter, from 14°C to 24°C in summer) Measure/get average daily temperature or calculate/get degree-days for each time period Separate cooling degree-days from heating degree-days Measure /get from the bills electricity consumption on each time period Draw the diagram for each time period: average temperature or DD on the X-axis and kWh on the Y-axis As soon as a season/year is complete, determine the (linear) regression between consumption and climate parameters Try to find the reasons why a new dot is outside the scatter – If differences are too important, too frequent and unexplainable, call a professional (energy supplier, ESCO etc.) for an energy audit Calculate climate independent energy ratios (slope of the regression curve) in kWh/m2.DD Compare to statistics – Try to explain possible differences (size, activity, adjustments etc…) Try to continue the energy signature even if no problem is detected Figure 9: Third part of ACTION PLAN for establishment and the use of the climate based energy signature of the building.5. Establish the multi-parameter energy signature of the buildingWe showed that energy consumption were due to a lot of parameters and underlined especiallythe influences of building parameters (area, staff), activity parameters (occupancy, production)and climate. However, it is impossible to analyze one parameter independently of the others.Concerning air conditioning for example, a more temperate climate than forecasts can becompensated by a much higher occupancy than in normal conditions so that the only climate oractivity analysis will provide biased results. As all of these parameters have a common influenceon energy consumption, it is important to analyze their effects simultaneously. The idea of thatparagraph is then to find the energy signature of the building by considering not only the climatebut also main activity parameters (pure occupancy, indirect occupancy, production etc…).Building parameters (surface, staff etc…) can be added in order to determine the energysignature of several similar buildings of the same activity sector (see next example).This method is exactly the same as the previous one but additional parameters are this timeincluded into the linear regression. As for climate parameters, building and activity parametersmust be measured precisely for each time period so that specific metrologies or proceduresshould be set-up. Again, time periods must be short in order to get more dots and then accuracy.Finally, to be able to find a correlation between consumption and all the parameters, you will 14
  15. 15. need at least as many time periods as parameters. For example, if the main parameters havingeffects on your building energy consumption E are the degree-days DD and the occupancy O ina supermarket, the regression method requires at least two time periods on which thecoordinates (E, DD, O) are distinct. However, to reach higher levels of representativeness, it isbetter to scan a large range for every parameter.For example, in the banking sector the information available for each agency is: area S, staffNwkr, the annual electricity consumption for three years and finally the location allowing tocalculate both cooling (CDD) and heating (HDD) annual degree-days. As building parameters(area and staff) are constant for one agency in the time, they only intervene into the magnitudeof consumption but not in their variations with time. On the opposite, variations of cooling andheating degree-days lead to variations in annual electricity consumption for one agency. As onlythree dots were available for each agency, the results of each energy signature were neitheraccurate nor representative. Although the approach is strictly the same, the energy signaturewas applied not to each agency but to the whole banking sector including every agencies inorder to determine a general profile of electricity consumption. Several models were tested:influence of the area (S), of the winter climate (HDD), of the summer climate (CDD), of bothwinter and summer climates (H&CDD) depending on the type of heating system (joule orreversible heat-pump), of the staff (Nwkr). The Table 2 presents both results and accuracy (R2)obtained by such models. Obviously, the more the parameters, the more accurate but forcomparison purposes they cannot be all kept. Model (kWh/year) A B C R² A.HDD.S+B 0.101 11680 0.67 A.HDD.S+B.Nwkr+C 0.047 3822 4652 0.77 A.CDD.S+B 0.411 27170 0.27 A.CDD.S+B.Nwkr+C 0.139 4000 1766 0.64 Heating by Joule effect (COP=1) A.H&CDD.S+B 0.099 11481 0.67 A.H&CDD.S+B.Nwkr+C 0.0461 3813 4700 0.77 Heating by Heat Pump (COP=2.5) A.H&CDD.S+B 0.099 11174 0.68 A.H&CDD.S+B.Nwkr+C 0.0479 3700 4740 0.77 Table 2: modeling of electricity consumption in the banking sector in France using a linear regression methodOnce the multi-parameter energy signature of the building is established, drifts in energyconsumption generated by defaults may be detected as soon as new dots deviate from thescatter. As for the simple climate base energy signature, energy ratios relative to eachparameter may be deduced from the correlation function calculated by extracting multipliercoefficient before each variable.Eventually, the DD regression not being be enough precise or of hard interpretation, it existsother methods such as the CUSUM method5 that allow to reveal trends that are occurring in thebuilding energy performance that are not visible through the only regression method.5 For more detail about the CUSUM method you can look at the: “CTG004- Degree days for energymanagement — a practical introduction”, Carbon trust at http://www.carbontrust.co.uk/publications 15
  16. 16. 4th Part: multi-parameter energy signature Choose main activity and climate indicators that justify variations in electricity consumption Determine the best time period (monthly, weekly, daily) Measure/get every chosen indicators for each time period Measure/get from bills the electricity consumption of each time period If enough dots are available, establish the linear regression (E=Σai.Pi + b) between electricity consumption E and every parameters PiTry to find the reasons why a new dot is outside the scatter – If differences are too important, toofrequent and unexplainable, call a professional (energy supplier, ESCO etc.) for an energy audit Calculate energy ratios by extracting multiplier coefficients ai Compare to statistics – Try to explain possible differences (size, activity, adjustments etc…) Try to continue the energy signature even if no problem is detected Figure 10: fourth part of ACTION PLAN for establishment and the use of the multi-parameter energy signature of the building. 16
  17. 17. Annex1) Some EECCAC (Energy Efficiency and Certification of Central Air Conditioners - FINAL REPORT - APRIL 2003) Ratios of total consumptions for EU 15 countries weighted all sectors and systems (kWh/m².year) Cooling Heating Cooling & Heating Austria 26,1 147,1 173,2 Belgium 19,5 135,6 155,0 Denmark 14,1 170,4 184,5 Finland 15,0 192,1 207,1 France 32,6 114,6 147,3 Germany 22,8 152,6 175,3 Greece 48,3 97,2 145,4 Ireland 19,5 119,4 139,0 Italy 50,1 94,5 144,7 Luxembourg 19,1 135,9 155,1 Netherlands 17,7 136,0 153,7 Portugal 49,7 96,0 145,7 Spain 81,5 28,5 110,0 Sweden 14,9 192,1 207,0 UK 19,7 119,5 139,2Electricity consumption for cooling (system and auxiliaries) in offices buildings for CAV (Constant Air Volume system) and RAC (room air conditioner) AC consumption (kWh/m2.year) Seville-CAV 99,26 London-CAV 32,77 Milan-CAV 70,49 Seville-RAC 58,52 London-RAC 8,39 Milan-RAC 28,53 Some indicative ratios for air conditioning consumptions for UK different sectors (All ratios are based on AC (kWh/m²) AC (kWh/m²) Ventilation based on cooled area) Central systems Packaged systems (kWh/m²) Hospitals (all health 94 170 71 sector) Hotels/restaurant/bar 94 170 71 Offices (commercial only) 49 270 117 Commercial 144 123 52 establishments (retail) Collective housing Schools (all education) 94 170 71 Leisure 94 170 71 Government buildings 94 170 71 Warehouses 94 170 71 17
  18. 18. 2) Some indicative ratios for French offices from an internal study of the Ecole de Mines: Use Additional remarks Ratios All consumptions The ratio take into account the 240 climate correction kWh/m².year Heating and cooling The ratio take into account the 150 - 170 climate correction kWh/m².year Cooling The ratio take into account the 25 -50 climate correction kWh/m².year DHW kWh/m3 70 (electric) 100-150 Lighting kWh/m².year 40 - 65 Lift As % of total energy 2 consumption 18

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