4 Scenario modeling

This section explains how to modify each one of the sheets inside B1_Scenario_Config.xlsx (see Figure 1). The scenario description used for the analysis is inside this repository’s paper: “Prioritizing policy options to transform energy systems: aligning decarbonization and production sophistication in Costa Rica.” The file consists of nine sheets:

  • Scenarios: it defines the scenarios to model in the simulation. Generally, there are two main scenarios. One of them is the business-as-usual (BAU) scenario where fossil fuels prevail. The other is a decarbonization scenario. It has electrification and other measures that make the energy system more efficient. Other scenarios derive from the other two.

  • Overall_Parameters: it defines the Initial_Year_of_Uncertainty. It is a parameter that B1_Base_Scenarios.py uses to start separating demand and restriction projections between scenarios.

  • Distance_Levers: it changes the distance traveled by every vehicle group. By default, this value is 1. The entered value multiplies the 2050 value from the parameterization phase. The table in the sheet must specify the scenario and the transport group technology.

  • Mode_Shift: it is another scenario-specific and technology-specific table. Under the “Conext” column, modelers can specify “Demand” or “Technology”, depending on the set under “Tech_Set”. “Demand” sets are used to parameterize the mode shift equations presented in the article. The technology sets activate or deactivate the entrance of rail transport options.

  • Occupancy_Rate: it changes the occupancy rate of a transport group set and works like the Distance_Levers sheet.

  • TElasticity: changes the SpecifiedAnnualDemand parameter of passenger and freight demand commodity sets. Hence, any change to demand in a scenario because of changes in elasticity of demand must be done exogenously.

  • Tech_Adoption: has the same logic as the Mode_Shift but specifies technological penetration. Another difference is the “Restriction_Type” column: “Max” fixes the TotalAnnualMaxCapacity restriction, “Min” the TotalAnnualTechnologyActivityLowerLimit, and “Min/Max” both.

  • Electrical: has a table per scenario and technology. This sheet is reserved for technologies in Table 2, which represent power generation technologies. Modelers must enter the parameter they want to change: often TotalAnnualMaxCapacity and TotalAnnualMinCapacity to enter a fixed amount of new installed capacity or place a cap. Other parameters are TotalAnnualTechnologyActivityLowerLimit and TotalAnnualTechnologyActivityUpperLimit to determine the electricity generation per power plant in Petajoules. These two, combined with CapacityFactor, can reflect a determined operational result. The ResidualCapacity parameter can be changed to phase-out plants existing in the base year.

  • Efficiency: is similar to TElasticity for demand sectors in Petajoule units, i.e., the sets with a simple approach demand.

In the following subsections, we elaborate on implementation details not covered in the previous list.

4.1 Defining scenarios

The Scenarios sheet has columns “Name” and “Description” to define the scenario. The scenario can be activated by entering “YES” under the “Activated” column or a “NO” for an opposite condition.

Only the BAU scenario should have a “YES” under the “Base” column because the parameterization phase is for the BAU; the rest should have a “NO”. If a scenario is a copy of another, modelers should type “based” under “Reference” and the reference scenario under the “Based_On” column.

Conversely, if the scenario needs to be specified across all sheets, the “Reference” scenario must have the name of the scenario itself and the “Based_On” column must have the string “ref”.

4.2 Modeling mode shift and technology adoption

Here we explain how to populate the common columns in the Mode_Shift and Tech_Adoption. First, the “Logistic” and “Linear” columns indicate the shape of the time series. If one of the two columns has a “YES” for a given row, the other column must have a “NO”.

Notably, the values of both sheets are ratios normalized to 1 as 100%.

For a logistic curve, users must specify the “L”, “C”, and “M”: the last value, the value in the inflection year, and the infection year, respectively. Other columns are “R2021” and “R2050” which make the curve fit the customary 2021-2050 planning horizon. Edits to the code must be made if the planning horizon is to change as well.

The linear curves have the option of decadal interpolation. Columns” v_2030”, “v_2040”, and “v_2050” are for placing the desired values on each year. If the modeler only needs an interpolation to 2050, they must type “interp” on the other columns. The “y_ini” column indicates the year in which the interpolation starts; values before this year will be the existing under the initial parameterization (see section 3) or zero.

4.3 Modeling the electrical sector

The Electrical sheet has a “Built-in Parameter Set” column: modelers must enter “NO” if they had not defined the parameter in the parameterization phase (primary technologies section). If they wish to overwrite the previous value, they must indicate “YES” under the column. In this sheet, all the values must be “YES” under the “Linear” column.

The” Exact_Years” and “Exact_Values” columns have values separated with semicolons “;”. The string entered must have the same number of years and values. If the parameter is built-in, the modelers can enter “intact” to leave the parameter unchanged for the corresponding scenario and technology combination.

The “y_ini” column indicates the start of an interpolation, most useful for the “intact” option. If it is empty, the last year in the” Exact_Years” string is the initial year of the interpolation.

The “Milestone_Year” and “Milestone_Value” columns work in tandem: they are the final value for the parameter (specific to the scenario – technology combination). These values are multiplied by the “Security_Multiplier” column, which helps modelers avoid incoherent restriction definitions. The “Unit” column is informative only.

The “Method” column specifies instructions about the manipulation of the time series, separated by semicolons. The options are described below:

  • The “Write” and “Overwrite” substrings relate to whether the parameter is built-in or not.

  • The “Interpolate” option makes a linear interpolation between the last known value and the desired value. On the other hand, the “Interpolate_Escalate” value fixes the last known value until the year before the target year.

  • The “Fix_Last” option fixes the target value for all years after the target year. In contrast, the “Fix_Indicated” option leaves a single value under the “Exact_Values” column as constant throughout the period.