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Geospatial simulation and decision optimization towards identifying the layout suitability and priority for wind-photovoltaic-hydrogen-ammonia project: An empirical study in China

Author

Listed:
  • Zhou, Jianli
  • Liu, Dandan
  • Sha, Ru
  • Sun, Jingbing
  • Wang, Yubao
  • Wu, Yunna

Abstract

China is vigorously developing clean energy to achieve the low-carbon strategy. Fully utilizing renewable energy to build a clean production and consumption system has become the core path. The wind-photovoltaic-hydrogen-ammonia project could fully absorb green electricity and have significant environmental benefits. However, the prerequisite for developing this project is to solve the layout problem. Firstly, a three-step method for identifying the project's critical factors to determine the analysis input is proposed for the first time. Secondly, the suitability and priority of the layout are measured by constructing the geospatial simulation and decision optimization model. Then, the three northern regions of China are selected for empirical study. Geospatial simulation provides the suitability of the overall layout of the region and identifies seven possibilities. The decision technique that considers multiple factors provides priority among possibilities. Finally, the deep analysis demonstrated the reliability and progressiveness of the model. The scenario analysis provides the sensitivity of this project to wind and solar power and discusses the impact of decision preferences on outcomes. This study presents a theoretical model and analytical framework that decision-makers can use to plan clean energy projects strategically. Furthermore, the empirical findings from this study can serve as valuable guidance for practical implementation.

Suggested Citation

  • Zhou, Jianli & Liu, Dandan & Sha, Ru & Sun, Jingbing & Wang, Yubao & Wu, Yunna, 2024. "Geospatial simulation and decision optimization towards identifying the layout suitability and priority for wind-photovoltaic-hydrogen-ammonia project: An empirical study in China," Energy, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:energy:v:286:y:2024:i:c:s0360544223028839
    DOI: 10.1016/j.energy.2023.129489
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