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A long-term capacity investment and operational energy planning model with power-to-X and flexibility technologies

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  • F, Feijoo
  • A, Pfeifer
  • L, Herc
  • D, Groppi
  • N, Duić

Abstract

In this research, we present a new long-term energy planning model that considers endogenous capacity investment, energy dispatch, Power-to-X, and demand response technologies. A thorough literature review of existing energy planning models is also presented, allowing to present the distinctive characteristics of the proposed model. The proposed model considers an energy system with the objective of minimizing the total capacity investment cost, throughout all technologies, and the operational cost faced by the system in satisfying energy demand. The model also considers the links among different demand sectors, including the links between the electricity, industry, heat, transport, and electro-fuels (e.g., Hydrogen) sectors. The proposed model is used to study the decarbonization of the Croatian energy system under distinct policies associated to RES levels and CO2 emissions goals. We demonstrate that Power-to-X technologies can certainly provide the flexibility that is required by new capacity investments in variable renewable energy sources, obtaining systems with lesser levels of critical excess of energy production. Higher usage of battery storage and Power-to-heat technologies are adopted primarily for variable renewable shares and CO2 reductions of close to 80%, while below such levels, the adoption of such technologies is limited. Additionally, Power-to-heat flexibility options become the major technologies when limits on CO2 emissions from the heating sector are imposed and, particularly, when the variable renewable energy shares in the electricity sector gets close to levels of 60%.

Suggested Citation

  • F, Feijoo & A, Pfeifer & L, Herc & D, Groppi & N, Duić, 2022. "A long-term capacity investment and operational energy planning model with power-to-X and flexibility technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  • Handle: RePEc:eee:rensus:v:167:y:2022:i:c:s1364032122006657
    DOI: 10.1016/j.rser.2022.112781
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