Capturing natural resource heterogeneity in top-down energy-economic equilibrium models
Top-down energy-economic modeling approaches often use simplified techniques to represent heterogeneous resource inputs to production. We show that for some policies, such as feed-in tariffs for renewable electricity, detailed representation of renewable resource grades is required to describe the t...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
26 July 2018
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| In: |
Energy economics
Year: 2018, Jahrgang: 74, Pages: 917-926 |
| ISSN: | 1873-6181 |
| DOI: | 10.1016/j.eneco.2018.07.019 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.eneco.2018.07.019 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0140988318302688 
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| Verfasserangaben: | Sebastian Rausch, Da Zhang |
| Zusammenfassung: | Top-down energy-economic modeling approaches often use simplified techniques to represent heterogeneous resource inputs to production. We show that for some policies, such as feed-in tariffs for renewable electricity, detailed representation of renewable resource grades is required to describe the technology more precisely and identify cost-effective policy designs. We demonstrate the hybrid approach for modeling heterogeneity in the quality of natural resource inputs required for renewable energy production in a stylized computable general equilibrium framework. Importantly, compared to the traditional approach, the hybrid approach resolves near-flat or near-vertical sections of the supply curve and improves the precision of policy simulation. We then represent the shape of a resource supply curve based on more detailed data. We show that for the case of onshore wind development in China, a differentiated feed-in tariff design that can only be modeled with the hybrid approach requires less than half of the subsidy budget needed for a uniform feed-in tariff design to achieve the same installation targets. |
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| Beschreibung: | Gesehen am 24.04.2023 |
| Beschreibung: | Online Resource |
| ISSN: | 1873-6181 |
| DOI: | 10.1016/j.eneco.2018.07.019 |