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6.2.12. Monitoring Data (only EINSTEIN plus)

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6.3. Consistency Check Module

List of EINSTEIN Parameters

A systematic analysis of the so called “status-quo” (present state (original)) is the starting point for the further identification of energy saving opportunities for a company. However, in most of the cases, this requires the acquisition of a rather large number of data. Besides the quantity, also the accuracy and the consistency of the available data affect significantly the reliability of the alternative solutions envisaged.

In filling in the questionnaire for data acquisition You may face one or both of the following problems:

· Redundancy of information and possible conflicts among figures. Redundancy may exist when two or more different ways to calculate the same parameter are possible. If the different ways lead to the same result, no problem arises. On the other hand, if results differs then You must choose the most reliable (which is the right one, which the wrong one ?) and – whatever You decide - as a consequence of the uncertainty You may still have doubts.

· Lack of information. You may not have all the information required for a detailed calculation. E.g. Both, the total and the most consuming process heat demand can be calculated (from the fuel consumption), but there may be no information on how the residual heat demand is spread between two other small processes.

An EINSTEIN basic consistency check allows to create a consistent data set with respect to mathematical and physical relationships and with respect to practical limit values given by engineering knowledge. In the case of redundancy, conflicts are automatically detected and a list of error messages is produced. In case of lack of information (and no conflict) the EINSTEIN software tool is able to calculate and to complete automatically the questionnaire with the missing data.

Therefore, You can use the “consistency check module” in order to check: a) whether the data gathered are consistent, or whether there are contradictions in the information You got (e.g. incorrect units of measurements) b) whether relevant data are missing (and which data), so that You can ask explicitly for or estimate those figures.

For more information, see also paragraph 3.6.1 of the EINSTEIN Audit Guide ”Consistency and completeness checking of data” and paragraph 3.6.2 “Acquisition of missing information”.

And now, let’s start.

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Figure 5.1 Scheme of the basic consistency check procedure in the EINSTEIN software tool. “Nones” stands for unknown data (blank cells).

6.3.1. 5.1 How to get familiar with the consistency check ?

In order to get familiar with the data input and the consistency-check concept, if You are a first-time user, it is recommended to perform first the example 4.2 (Go to the menu “Edit industry data”-> Projects in the database and open the project “Einstein Guide 4.2 Basecase” and followings) according the description given into the Audit Guide, chapter 4.2.

Following a simple procedure for data entering may help to pass the consistency check in a shorter time. In general, when entering data, it is recommended to enter the process’ data first - and to check the consistency-, then the equipments’ (but without any constraint such as e.g. the load factor) - and to check the consistency-, then the pipes’ - and to check the consistency- and last, the overall energy consumption and to check the consistency of the complete data set. Anyhow, take in mind that in order to perform the consistency check, equipments and pipes have to be previously created and linked each other and to the processes – but it can be done in the intermediates steps without adding any specific parameter such as the power etc.

It is also recommended to analyse (i.e. to enter and check) sub-system by sub-system (e.g. enter FIRST data of equipment 1 and the related pipes and related processes THEN check the consistency and enter the second set of data: equipment 2 -> related pipes -> related processes…).

6.3.2. 5.2 Lay-out of the consistency check module

In the first quadrant (top) “Cross checking of data”:

  1. The list of data calculated with insufficient accuracy (max error > ±50%) is shown. To any parameter 5 attributes are associated :
  • Code Name of the parameter.

    Any parameter (such as FET, USH,UPH etc..) appear with a number into brackets. E.g. USH[1] etc. In fact, to any “class of objects” used in EINSTEIN for modelling an energy system it is associated an index identifying a specific object within a class: * i to fuels * j to equipments * m to pipes * k to processes.

    Moreover [0] stays for the total. E.g USH[0] is equal to the sum of the USH of any equipment “i” listed into the project equipment list: USH[0] = Σ USH (i) E.g. if the number of equipments is 3 then: USH[0] = USH[1] + USH[2] + USH[3] It is clear now that any index different from 0 refers to equipment, fuel, process etc. number 1,2,3. E.g. UPH[1] represents the useful process heat of process 1 (as shown into the process list entered by the user) while e.g. FEC [2] is the final energy consumption of the fuel number 2, and so on.

  • Description of the parameter as reported into the related field of the questionnaire

  • (Numeric) Value of the parameter as calculated by the internal consistency check algorithm

  • Max (relative) error associated to the numeric value expressing the figure accuracy. E.g if the parameter Value = 100 and Max error = ±70% this means that, under the given assumptions and known data, acceptable values for the parameter range between 30 and 170

  • Action to be taken according the degree of analysis’ accuracy chosen.

  1. The required accuracy pop-up list (top-left) give to the user the possibility to chose the level of detail and accuracy of the analysis among Quick & dirty, Standard, Detailed.

Below the first quadrant there are 3 buttons allowing the following functions:

  • The basic check (right-hand side). Clicking on this button the user runs the consistency check of the data previously entered into the electronic questionnaire
  • The data estimate (in the middle). Clicking on this button the tool estimates the new value of some of the parameters automatically calculated by the system with a low accuracy. The algorithm attributes to those parameters some “default” values based mainly on the engineering knowledge (e.g. an estimated value for the conversion efficiency of a standard gas fired boiler is 85%)
  • A check list (left-hand side) creation (not currently in operation).

In the second quadrant (bottom) “ Cross check statistics” 3 statistics are shown as soon as the consistency check have been run:

  • The number of data checked by the system
  • The number of input data fixed after estimation (not currently in operation)
  • The number of missing data estimated automatically by the algorithm.

Clicking on the OK button (bottom-left) user confirms and accepts the consistency check results, and accedes directly to the energy statistics modules.

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Figure 5.2 Screen shot of the consistency check module rinnunig in a standard mode.

Moreover, a windows named “Conflicts in parameter specifications” pops up anytime that there is a conflict among different values associated to one parameter. In this case the name and the values of the parameter are shown on the left-hand side, the level of accuracy in the central column while the background parameters into the right-hand side. The “background parameters” are those parameters that have been internally taken into consideration by the algorithm for the calculation. Based on energy balances, it is known that a variable can be calculated according different mathematical paths: if executing these different calculation paths the algorithm detects a conflict (i.e. two different results are obtained for the same parameter, e.g. for the final energy consumption of an equipment) then both figures will be shown into the conflicts list under the same parameter name together with the background parameters used for the calculations (e.g. in one case the power and the number of operating hours, and in the other, the fuel consumption and the conversion efficiency).

The list of the parameters affected by a conflict are reported together with the following attributes:

  • Parameters (values in conflict). Within this column, for each parameter the user can find 2 types of information (and 3 data). On one hand, in the orange row it is reported the code name of the parameter affected by the conflict. In picture 5.3, the first row shows the following text (top-right): USHBoiler1[<>USHBoiler2]. It means that the parameter USHBoiler calculated according the equation 1 differs from the USHBoiler calculated according the equation 2. The index 1 and 2 refer to two different calculating ways (energy balances) run in the background by the consistency check module. For which boiler the conflict arises it is shown in the column data group (accuracy) where in the first orange row it is reported the type (Equipment) and the number of the unit ([2]). On the hand, the 2 rows under the orange one show two figures: they are the values of the parameter calculated respectively according the procedure 1 and 2.
  • Data group (accuracy). As already explained above, for each conflict this column gives 2 types of information (and 3 data): the reference unit (e.g. Equipment [2]) and the accuracies of the 2 values calculated respectively according the procedure 1 and 2.
  • Description (calculated from). This column shows the background parameters used to calculate the values in conflicts (e.g. USHBoiler1 and USHBoiler2). Two list of parameters are given here e.g.:
    1. HCGPnom, HPerDayEq…They mean that USHBoiler1 = HCGPnom x HPerDayEq x ….
    2. …, HCGTEfficiency, FETFuel [4] [1], … They mean that USHBoiler2 = … HCGTEfficiency x FETFuel [4] [1]… The 2 indexes refer respectively to equipment number ([4]) and to fuel number ([1] e.g. natural gas).

Concerning the “conflict messages”, besides the most important quantities such as FET/UPH/USH/QHX/QWH, described into the AUDIT GUIDE in chapter 2 and in the glossary, the following abbreviations/indexes/acronyms are used to compose the code name of a parameter:

  • Proc for process related items
  • Eq for equipment related items
  • Pipe for pipe and duct related items
  • Temp for temperature related items
  • PT for process temperature
  • M for mass related items
  • Vol or V for volume related items
  • H for hours
  • Env for environment
  • Flow for (e.g.mass, medium..) flow related items
  • In/out for in/out (e.g. flows)
  • N for number (e.g. NDaysEq=Number of operating Days of an Equipment)
  • Nom for nominal (e.g power)
  • HCG for heat and cold generation related items (e.g. HCGPnom=heat or cold generation Nominal Power; HCGTEfficiency= Thermal Efficiency for Heat or Cold Generation)
  • Consum for consumption
  • Electr for electricity related items
  • Fact for factor
  • Loss for losses related items.

The overall set of code names with the description and the translation into the project languages is also available as MS excel file.

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Figure 5.3 Screen shot of the “conflict” window inthe consistency check module

6.3.3. Levels of analysis in the consistency check module

The EINSTEIN methodology distinguishes between three levels of analysis with increasing level of detail and accuracy that are also taken into consideration for the consistency check (required accuracy option as previously described):

  • Level 1: Quick&Dirty analysis. For quick&dirty analysis it is enough to know with a certain minimum accuracy (as minimum accuracy EINSTEIN considers an error margin of less than +/- 50 %) the energy consumption and the main temperature levels (process temperature) of the most energy consuming processes in the company (and also FEC/FET(0), USH(0) and (UPH (0) i.e. the totals)
  • Level 2: Standard analysis. For the EINSTEIN standard level of analysis at least the following parameters should be known with the minimum level of accuracy: * energy consumption of the main energy consuming processes and it’s decomposition in heat&cold demand for circulation, maintenance and start-up * all temperature levels (inlet, process, outlet) and hours of operation of those processes and the corresponding heat & cold supply equipment * waste heat streams from the main energy consuming processes
  • Level 3: Detailed analysis. For a detailed level of analysis at least the full set of information as given by the EINSTEIN basic questionnaire should be available with the required accuracy.

6.3.4. How to run the consistency check module ?

First, fill in data into the electronic questionnaire then select the consistency check option from the main function tree (right-hand side). Chose the level of required accuracy and click on the basic check button.

If the conflict window pops up click on the OK button (bottom – left) and go back to the questionnaire to modify or enter new data according the conflict messages. Until when the conflict is not solved it is not possible to go further and to accede to the energy statistic module and to configure alternatives.

If no conflict is detected, or after it is solved, user can either accept the results of the consistency check by clicking on the Ok button and go ahead, or he/she can go back to the questionnaire, enter manually the missing data and/or ask to EINSTEIN to estimate some parameters. In this case, before clicking on the button “estimate data”, it is necessary to pass again the consistency check.

In order to change the data entered into the questionnaire, it is necessary first to go to the main menu bar: click on the command “view” and select “present state (original)”. Any time this operation is done the consistency check has to be passed again.

If the “present state (checked)” is selected after the consistency check, the user can accede the questionnaire to check the figures automatically calculated by the algorithm instead of “Nones” or blank fields.