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A multidimensional factorial enviro-economic model: Approaches of retrospective decomposition and prospective projection for energy systems

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  • Zhai, Mengyu
  • Wu, Yufeng
  • Gu, Yifan
  • Liu, Lirong
  • Su, Shuai
  • Zang, Hongkuan

Abstract

Understanding the patterns of energy usage through simulation and prediction from multiple perspectives is crucial for alleviating energy-environmental conflicts and achieving sustainable energy system development. Despite their importance, multidimensional interactions among the production, demand, and supply sides have not been systematically characterized, thus representing a significant research gap. This paper aims to address this gap by developing a a multidimensional factorial enviro-economic (MFEE) model, which offers an in-depth investigation of Guangdong's energy system. This model, designed for retrospective decomposition (1997–2017) and prospective projections (2035), uniquely links historical and future analysis from systematic and sectoral perspectives through structural decomposition analysis, sectoral evolution analysis, and the Biproportional Scaling RAS method. Our findings reveal that the final demand level and Research & development (R & D) are the principal drivers of increased energy usage. We also found that the wholesale and retail sector have the most significant impact on demand and input sides, accounting for over 70 %. Furthermore, the interaction of key sectors from the production-based perspective notably influences system symbiosis. To effectively manage these dynamics, our study recommends regulating and controlling measures for the circulation sector that consider the benefits of both the energy sector and the accommodation and catering sector. This comprehensive analysis, therefore, offers scientifically-supported guidance for sustainable energy system development.

Suggested Citation

  • Zhai, Mengyu & Wu, Yufeng & Gu, Yifan & Liu, Lirong & Su, Shuai & Zang, Hongkuan, 2024. "A multidimensional factorial enviro-economic model: Approaches of retrospective decomposition and prospective projection for energy systems," Energy, Elsevier, vol. 287(C).
    • Handle: RePEc:eee:energy:v:287:y:2024:i:c:s0360544223025872
    DOI: 10.1016/j.energy.2023.129193
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