The utilization pathways of certain energy sources may become unprofitable when production costs surpass remunerations. In fact, some completed studies, which optimize energy systems as a whole from the macroeconomic perspective of a single observer, might have violated the principle of profitability. The solution to avoid this issue is to resort to an exogenous approach to the modelling of remunerations. This methodology is based on the integration of a profitability constraint into every optimization model for any energy utilization pathway. The constraint constitutes a restriction on utilization pathway’s costs from the standpoint of plant operators or investors concerned. The aim of these constraints is to ensure profitable investments at the microeconomic level of each utilization pathway. Besides, integrating profitability constraints is clearly an easy task for energy system models with a single sector (data block). But if there is more than one sector, it is not straightforward to model energy and material flows across such blocks. This objective can be achieved through two sets of specific variables: the energy and material contributions to a facility and the virtual flows.
The exogenous methodology is proved in this work by applying it to the special case of bioenergy generation. A general bioenergy subsystem is modelled as a complement or add-on module of a cost minimization model describing the whole energy system. A mixed integer linear programming (MILP) approach is selected to create such a software extension called BioSPHERE. By using a sensitivity analysis, this add-on allows assessing the impact of the decrease in remunerations on a particular bioenergy subsystem. As a result, an array of macroeconomically cost-efficient bioenergy configurations of microeconomically profitable conversion units with ever lower electricity production costs and different spatial arrangements are generated. The production costs caused by the biomass contributions of each spatial unit to a given facility relate to a number of cost components that finally allow evaluating the respective utilization pathway’s profitability.