DB Engineering

 

Two-variable  MT&F Tool Description

Main Features

- Excel-based, easy-to-use
- Up to 2000 sets of data points
- Multiple regression types for defining the best fit of baseline consumption vs.
  one or two influential factors
- Energy consumption profiling, control band, targeting and  forecasting
- Automatic calculation of degree-days when input mean daily temperatures
- 3D illustrative scatter plot with rotating facility for the 3-variables plot
Description

The MT&F tool is used pimarily in the energy management field. It can also be used in any area where there is a need for identifying changes of the dependency pattern between the analysed variable and its influential factors relative to a baseline or target, to set targets or control bands, to forecast the impact of future values of influential factors on the variable being investigated.

Published infromation indicates that the use of the tool can lead to 5% - 20% energy cost savings in industrial plants and in institutional/comercial buildings by allowing the energy manager to take adequate and timely decisions related to implemetation of energy efficiency measures, energy-related optimization of operation and maintenace, energy consumption control, targeting and monitoring. 
The tool is Excel-based and contains "sheets" that perform automatically various tasks.

The "Historical Data" sheet allows the input of historical data for the investigated variable (e.g.: fuel, electricity or water consumption, etc.) and for one or two influential factors. It also plots the time-dependent profile of the variables for a selected period of time. Data points can be excluded from the analysis if necessary.

The "Regression" sheets perform various types of regressions (e.g.: linear, exponential, logarithmic, power, 2nd or 3rd order polynomial) for the data points selected as representative for the baseline (usually, a period at the begining of the historical data under analysis). The respective X-Y graphs and trend lines are also ploted. The calculated coefficients of the regression equations and the "goodness of fit" coefficient are displayed for each type of regression tried. The 2-variables regression sheet performs the regression analysis of the investigated parameter as a function of two influential factors simultaneously (e.g.: plant fuel consumption vs. production AND weather, building electricity consumption vs. weather AND occupancy, etc.). A 3D illustrative scattered plot with rotating capability is also included.

The single-variable and two-variables "CUSUM" sheets calculate and plot automatically the Cumulative Sum of the differences between the values of the variable being analysed (e.g.: fuel consumption, or electricity consumption, etc.)  predicted by the baseline and the actual values, over the period of time under investigation. Changes in the slope of the respective curve indicate changes in the dependency pattern worth it of investigation. Their identification is one of the goals for using the tool, as subsequent measures can be taken to reduce utility costs.

The "Control" sheet allows the definition of a desirable control "band" of operation and it plots the line graph of the investigated variable and the respective control band. The user can define the width of the "band" according to his own criteria and use it to alert deviations of the variable from facility/equipment/plant operation within the "band".

The "Targets" sheet allows the user to set targets for the investigated parameter based on various criteria and it plots automatically the respective line graphs of target for a linear dependency between the parameter being analyzed and the influential factor under investigation. This represents an useful tool, for example, in supporting energy management projects, outlining potential energy savings, program motivation, etc. 

The "Forecasting" sheet provides a facility to predict values of the parameter being investigated (e.g.: electricity, or fuel, or water consumption, etc.) for given future values of influential factors using the baseline established previously. The forecasting can be done both for single- and two-variable dependency. The forecasting sheet can also be used for quick check of accuracy.

The "Weather Data" sheet allows the input of the mean temperatures at the location where the operation is being analysed and it calculates automatically the heating and cooling degree-days relative to a base temperature selected by the user (typically, 22C for heating and 18C for cooling). The degree-days can then be used as one of the influential factors in the analysis.

A 3-day functional free evaluation file is available from Download page.    


 

                         DB Engineering * 3315 Chokecherry Cres. * Mississauga * ON * Canada * L5L 1B1
              Phone / Fax: (905) 607-2402