Number types used in energy modeling of buildings:

These are the different types of numbers used in energy modeling:

1. "Scalar Evenly Scheduled" -  A number that is applied to a building parameter independent of schedules because among the calculation used to attain this number, there had been predetermined hours per day of use assumed.  An example of this would be estimated domestic refrigerator energy use.   Typical energy use for a refrigerator is 450 kwh/year.    The schedule of this appliance is 100% 24/7, despite the common knowledge that it cycles on and off.     The cycling, food loads, hungry kids, are all factors taken into account by the original number.  SES numbers are highly volatile and subject to error if used without an understanding of their original assumptions.   
2. "Scalar Definitively Scheduled" -A number that is only valid when used in conjunction with a schedule. Every hour of every day must have a value ranging from 0-100% (or fraction from 0.00 to 1.0).    An example of this is a 60 watt light bulb used 2.4 hours a day distributed with a curve over many hours of the day.   
   • At 2.4 hours a day.   The total kWh used that day would be:  (60w/1000)*2.4 =.14 kWh.  
3. "Interactive Dependent Values"  
   • On a building simulation input side, these type of numbers must be accompanied by appropriate pairs or in groups with other numbers in order to run a working simulation.    If a calculation feature of the program requires 5 individual values to perform the calculation to get one answer, any change in any of the 5 values will have an impact on the result.   Often the modeling professional has to choose between letting the modeling software auto-size or auto-calculate a simulation feature, or intercede this activity by directly inputting several values.    If, for example, only 4 out of 5 of these values are correct, but one number is either not known or incorrect, the simulation results may be volatile in accuracy.  Often, when a modeler overrides features of a program intended to be user-friendly (and thereby rigid and inadaptable) a volatility in the results may occur.   Determining the modeling software programmers' intent of certain auto-calculation features can be a challenge.   
   • On a building simulation output side,  there are a limited quantity of energy values yielding whether a building is of high or low energy performance.  Often it is Electric peak kW, kWh/year, and natural Gas mmbtu/year.    Each one of the energy values are either directly affected by one energy measure or joint affected by many energy measures whose compounded effect can be jointly seen in the results.   Errors can occur, but not be seen, if one input mistakenly over estimates energy savings and another input mistakenly under estimates energy savings.  These two numbers are a pair and relate to one another.   All energy modeling requires a fine combing of the output data to check that inputs both agree in approach and work for the particular program.        
4. "Critical Key Values"  Just as there are potentially dozens or hundreds of input numbers, there is a hiarchy of importance of some over others.   From most numbers an error range of 2-4% may be acceptable, but if key values have such wide tolerance, then this may lead to 10 or more percent difference on the result.  Some numbers magnify their loose tolerances while other numbers have a reduced impact on the overall result accuracy.   In modeling, always find the largest contributing factors to the results.  Such critical key values intrinsically have the greatest potential for error.