The key energy demand variable in IFs, ENDEM, tracks total primary energy demand. For the most part, IFs does not represent the transformation of this primary energy into final energy forms, or end-user energy demand. The one exception relates to electricity use, which is described in the documentation of the Infrastructure model.
In the first year, total primary energy demand is calculated as an apparent demand, with attention paid to stocks and expected growth in production.
- ENP, ENM, ENX, ENST, and AVEPR are energy production, energy imports, energy exports, energy stocks, and an average of the expected growth in production across all energy types. The calculations of the initial values of these variables are described later in the Equations section under the appropriate headings.
Note that this calculation does not directly use the historical data on total primary energy demand and there can be a significant difference between the initialized value of ENDEM and the actual historical data for the base year. This information is used by the variable ENDEMSH, which is described in the Infrastructure documentation.
In future years, the calculation of total primary energy demand begins with an estimate of the predicted amount of energy demand per unit of GDP (in PPP terms), compendemperunit, as a function of GDP per capita (in PPP terms). This function is show in the figure below:
A small amount, 0.0005, is added to this computed value to account for the fact that the demand data used to estimate the function above is less than apparent demand globally.
The initial data for countries is unlikely to fall exactly on this function. To reconcile this fact, IFs calculates values for both predicted energy demand per unit GDP in the first year, compendemperuniti, and empirical demand per unit GDP (in PPP terms) in the first year, actendemperuniti. Over a time period controlled by the parameter enconv , IFs gradually adjusts the difference between these two values so that the estimate of energy demand per unit GDP (in PPP terms) eventually does fall on the function.
IFs then calculates an initial estimate of total energy demand, endemba, by multiplying this adjusted value of energy demand per unit GDP (in PPP terms), endemperunit, by GDP (in PPP terms).
IFs then considers the effect of price on total primary energy demand. IFs keeps track of the global energy price as both an index (WEP, base year = 100) and as an actual dollar value (WEPBYEAR, $ per BBOE). It also tracks a country level energy price index (ENPRI, base year =100). Finally, it can also consider a tax on carbon, expressed by the variable CarTaxEnPriAdd, which has the units $ per BBOE.
The calculation of the effect of prices on total energy begins with the calculation of a variable called renpri. renpri is a moving average country-level price index that starts at the level of the country level price index in the base year, ENPRII, and then tracks changes in world energy prices and country-level carbon taxes. The historical weight is controlled by the parameter ehw , so that:
- renpri is the moving average country level price index
- ehw is the weight given to the historical value of renpri
- WEP is the global energy price index
- WEPBYEAR is the global energy price in $ per BBOE
- CarTaxEnPriAdd is the country level carbon tax in $ per BBOE of total energy and is calculated as the exogenous value of the carbon tax in $ per ton of carbon, carbtax , times a production weighted average of the carbon contents of oil, gas, and coal, carfuel1-3 :
The parameter specifying the price elasticity of energy demand, elasde , is adjusted based on the relationship between renpri and and ENPRII to yield a new parameter, elasadjusted.
This, in effect, decreases the price elasticity of energy demand as prices increase.
This adjusted elasticity is then used to calculate the impact on energy demand, elasterm, as
The user can also introduce a further adjustment to total primary energy demand with a multiplier, endemm , yielding:
IFs makes a final adjustment to total primary energy demand related to changes in energy efficiency of the economy unrelated to prices. All countries receive an annual boost in energy efficiency related to technology given by the parameter enrgdpr . In addition, if a country is not a major energy exporter and its economy is less energy efficient than the global average, measured as ENDEM divided by GDP (in PPP terms), it gets an additional boost to its energy efficiency. This effect is cumulative, so ENDEM is adjusted as follows:
- EnRGDPGRCalc is the annual average boost in energy efficiency
- iy is the number of years since the base year plus 1
Finally, IFs makes an initial estimate of energy use per unit GDP in MER terms, ENRGDP. An estimate of GDP based on the previous year’s GDP in MER terms and a growth rate is used due to the order of calculations, but this is corrected later in the model sequence.
 Here, IFs uses GDP from the previous time cycle, with an estimate of growth, to calculate GDPPCP, because the recursive structure of IFs computes current GDP later. The current value of population, POP, has already been computed at this stage.
 The exact equation is compendemperunit = 0.0023428 -0.0003878*ln(GDPPCP).
 Again, IFs uses GDP from the previous time cycle here, because the recursive structure of IFs computes current GDP later.
 The model also has a variable representing the price index in each economic sector, one of which is energy. This value is stored in the variable PRI, which uses an index value of 1 in the base year. ENPRI and PRI (energy) track each other, with former having a value 100 times that of the latter due to the different initial index values.
 Because energy prices and carbon taxes are computed later in the model sequence, the previous year’s values are used here.
 This is generally referred to as autonomous energy efficiency improvement, or aeei.
 An estimate of this year’s GDPP based on the previous year’s GDPP and a growth rate is used here due to the order of calculations.