Incorporating indirect costs into energy system optimization models

Application to the Dutch national program Regional Energy Strategies

Journal Article (2023)
Authors

Ni Wang (TNO, TU Delft - Energy and Industry)

Remco Verzijlbergh (TU Delft - Energy and Industry)

Petra Heijnen (TU Delft - Energy and Industry)

P. M. Herder (TU Delft - ChemE/Chemical Engineering)

Research Group
Energy and Industry
Copyright
© 2023 N. Wang, R.A. Verzijlbergh, P.W. Heijnen, P.M. Herder
To reference this document use:
https://doi.org/10.1016/j.energy.2023.127558
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 N. Wang, R.A. Verzijlbergh, P.W. Heijnen, P.M. Herder
Research Group
Energy and Industry
Volume number
276
DOI:
https://doi.org/10.1016/j.energy.2023.127558
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Abstract

Energy system optimization models are widely used to aid long-term investment decision-making for energy systems. From a socio-technical system viewpoint, existing models focus on the cost modeling of the technical subsystem, while the indirect costs of the social subsystem are not often modeled. This paper incorporates indirect costs into such a model, including those associated with generation capacity, energy production, and bilateral trades, respectively. As a proof-of-concept, the model has been applied to a case study for the Dutch power system, reflecting the Dutch national program Regional Energy Strategies, where regions collectively plan wind and solar energy capacities. We conclude that incorporating indirect costs significantly changed the optimal investment capacities and the associated costs for the regions compared to benchmark results from the conventional models. Furthermore, in this case study, a potential free-rider problem with regard to the national climate target occurs. Our model is used as a negotiation simulator to inform the regions about the hypothetical free-riding behaviors and thus helps to achieve a socially acceptable investment plan. The proposed energy system optimization model with indirect costs goes beyond the prevalent cost-minimization paradigm, and can be used to study transaction costs, trading barriers, and willingness to pay.