MAgPIE - An Open Source land-use modeling framework

4.3.5

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Bioenergy (60_bioenergy)

Description

The bioenergy module provides a regional and crop-specific bioenergy demand \(vm\_dem\_bioen\) to the model (to the 16_demand module). For this calculation it requires information on gross energy content (provided by 16_demand module).

In addition to calculation of bioenergy quantities, the costs associated with the production are provided to the objective function in the 11_costs module.

Interfaces

Interfaces to other modules

Input

module inputs (A: 1stgen_priced_dec18)
  Description Unit A
fm_attributes
(attributes, kall)
Conversion factors - where X is ton N P K C DM WM or PJ GE \(X/tDM\) x
im_pop_iso
(t_all, iso)
Population \(10^6/yr\) x
sm_fix_SSP2 year until which all parameters are fixed to SSP2 values \(year\) x

Output

module outputs
  Description Unit
vm_bioenergy_utility
(i)
Utility as negative costs for producing bioenergy \(USD_{05MER}/yr\)
vm_dem_bioen
(i, kall)
Regional bioenergy demand \(10^6 tDM/yr\)

Realizations

(A) 1stgen_priced_dec18

Total demand for bioenergy comes from different origins 1st generation bioenergy demand is a fixed trajectory of minimum production requirements. Second generation bioenergy splits into a Demand for dedicated bioenergy crops, which are fully substitutable based on their energy content, and residues which are also fully substitutable based on their energy content.

q60_bioenergy(i2,kall) ..
      vm_dem_bioen(i2,kall) * fm_attributes("ge",kall) =g=
      sum(ct, i60_1stgen_bioenergy_dem(ct,i2,kall)) +
      v60_2ndgen_bioenergy_dem_dedicated(i2,kall) +
      v60_2ndgen_bioenergy_dem_residues(i2,kall)
      ;

The used first generation bioenergy trajectory contains demand until 2050 based on currently established and planned bioenergy policies (Lotze-Campen et al. (2014)). For the time after 2050 it is assumed that bioenergy production will be fully transformed to 2nd generation bioenergy crops and residues because of their higher estimated efficiency respectively their low costs.

For second generation bioenergy from dedicated bioenergy crops (kbe60 = bioenergy grasses and bioenergy trees), input is given either on regional or global level (defined via switch \(c60\_biodem\_level\)). As the bioenergy demand for all crop types was fixed in the first step it now has to be released again for second generation bioenergy crops (kbe60).

The bioenergy demand calculation for second generation bioenergy is based on the following two equations from which always only one is active: If \(c60\_biodem\_level\) is 1 (regional) the right hand side of the first equation is set to 0, if it is 0 (global) the right hand side of the second equation is set to 0.

q60_bioenergy_glo.. sum((kbe60,i2), v60_2ndgen_bioenergy_dem_dedicated(i2,kbe60))
                    =g= sum((ct,i2),i60_bioenergy_dem(ct,i2))*(1-c60_biodem_level);
q60_bioenergy_reg(i2).. sum(kbe60, v60_2ndgen_bioenergy_dem_dedicated(i2,kbe60))
                    =g= sum(ct,i60_bioenergy_dem(ct,i2))*c60_biodem_level;

Except the implementation of the switches and the fact that in the first equation the bioenergy demand is summed up to a global demand both equations act the same way: In both cases the equation just makes sure that the sum over all second generation energy crop of the bioenergy demand is greater or equal to the demand actually given by the input file \(i60\_bioenergy\_dem\). There is additionally some demand of residues for second generation bioenergy \(i60\_res\_2ndgenBE\_dem\), which is exogenously provided by the estimation that roughly 33% of available residues for recycling on cropland can be used for 2nd generation bioenergy depending on the SSP scenario, since residue stock and use is mainly driven by population and GDP.

q60_res_2ndgenBE(i2) ..
  sum(kres, v60_2ndgen_bioenergy_dem_residues(i2,kres))
  =g=
  sum(ct,i60_res_2ndgenBE_dem(ct,i2));

Finally, an incentive is provided for the production of 1st generation bioenergy from oils and ethanol even beyond the exogeneous minimum demand. The incentive is kept low, but should provide a more realistic overproduction from couple products.

q60_bioenergy_incentive(i2).. vm_bioenergy_utility(i2)
          =e= sum(k1st60, vm_dem_bioen(i2,k1st60) * (-c60_bioenergy_subsidy));

Limitations There are no known limitations.

Definitions

Objects

module-internal objects (A: 1stgen_priced_dec18)
  Description Unit A
c60_biodem_level bioenergy demand level indicator 1 for regional and 0 for global demand \(1\) x
c60_bioenergy_subsidy first generation bioenergy subsidy \(USD_{05MER}/ton\) x
f60_1stgen_bioenergy_dem
(t_all, i, scen1st60, kall)
annual 1st generation bioenergy demand \(10^6 GJ/yr\) x
f60_bioenergy_dem
(t_all, i, scen2nd60)
annual bioenergy demand (regional) \(10^6 GJ/yr\) x
f60_res_2ndgenBE_dem
(t_all, i, scen2ndres60)
annual residue demand for 2nd generation bioenergy(regional) \(10^6 GJ/yr\) x
i60_1stgen_bioenergy_dem
(t, i, kall)
Regional 1st generation bioenergy demand \(10^6 GJ/yr\) x
i60_bioenergy_dem
(t, i)
Regional bioenergy demand per year \(10^6 GJ/yr\) x
i60_res_2ndgenBE_dem
(t, i)
Regional residue demand for 2nd generation bioenergy per year \(10^6 GJ/yr\) x
p60_country_dummy
(iso)
Dummy parameter indicating whether country is selected for selected bioenergy demand scenario \(1\) x
p60_region_BE_shr
(t_all, i)
Bioenergy demand share of the region \(1\) x
q60_bioenergy
(i, kall)
Global total bioenergy demand \(10^6 GJ/yr\) x
q60_bioenergy_glo Global 2nd generation dedicated bioenergy demand \(10^6 GJ/yr\) x
q60_bioenergy_incentive
(i)
Incentive to produce bioenergy \(10^6 USD_{05MER}/yr\) x
q60_bioenergy_reg
(i)
Regional 2nd generation dedicated bioenergy demand \(10^6 GJ/yr\) x
q60_res_2ndgenBE
(i)
Regional residue demand for 2nd generation bioenergy \(10^6 GJ/yr\) x
v60_2ndgen_bioenergy_dem_dedicated
(i, kall)
Bioenergy demand which can come from different regions \(10^6 GJ/yr\) x
v60_2ndgen_bioenergy_dem_residues
(i, kall)
Bioenergy demand which can come from different product types \(10^6 GJ/yr\) x

Sets

sets in use
  description
attributes Product attributes characterizing a product (such as weight or energy content)
ct(t) Current time period
i all economic regions
i_to_iso(i, iso) mapping regions to iso countries
i2(i) World regions (dynamic set)
iso list of iso countries
k1st60(kall) 1st generation bioenergy carriers
kall All products in the sectoral version
kap(k) Animal products
kbe60(kall) bio energy activities
kres(kall) Residues
reg regression parameters for dynamic sticky
scen_countries60(iso) countries to be affected by 2nd generation bionergy demand scenario
scen1st60 first generation bioenergy scenarios
scen2nd60 second generation bioenergy scenarios
scen2ndres60 residues for second generation bioenergy scenarios
t_all(t_ext) 5-year time periods
t(t_all) Simulated time periods
type GAMS variable attribute used for the output

Authors

Jan Philipp Dietrich

See Also

09_drivers, 11_costs, 16_demand

References

Lotze-Campen, Hermann, Martin von Lampe, Page Kyle, Shinichiro Fujimori, Petr Havlik, Hans van Meijl, Tomoko Hasegawa, et al. 2014. “Impacts of Increased Bioenergy Demand on Global Food Markets: An AgMIP Economic Model Intercomparison.” Agricultural Economics 45 (1): 103–16. https://doi.org/10.1111/agec.12092.