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Combined evaluation of hydropower viability and cost-efficacy in the context of climatic stressors with the utilization of Inception-V4 network on the basis of the Flexible Geyser-Inspired Algorithm

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  • Lei Zhang
  • Shanghong Sun
  • Mohammadreza Fathi

Abstract

This study highlights the interdependence among dwindling water resources, their restrictions on hydropower generation, and consequently the impacts on their dynamics within electricity markets due to climate change. River streamflow patterns assessment for the viability of water-dependent energy systems to be analyzed using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS). Accurate short-term electric price forecasts are made using the Inception-V4 deep learning network. The Flexible Geyser-Inspired Algorithm (FGIA) presents a new method in metaheuristic optimization, enhanced with chaos and Lévy flight theory to avert premature convergence. This research will be the first to integrate HEC-HMS, Inception-4, and FGIA for the complete analysis of climate-induced hydropower stress. It has been found that across many climate scenarios, hydropower production potential is significantly reduced. It is expected that there will be a gradual increase in electricity prices from about 0.5 CNY (2023) to 0.95 CNY (2050). A 10% reduction in hydropower potential increases the electricity cost by 13.07%, indicating that the energy market is sensitive to the availability of water. The prospective decrease in energy generation from hydropower facilities will continue till 2050 with a concomitant increase in the regional price of electricity.

Suggested Citation

  • Lei Zhang & Shanghong Sun & Mohammadreza Fathi, 2025. "Combined evaluation of hydropower viability and cost-efficacy in the context of climatic stressors with the utilization of Inception-V4 network on the basis of the Flexible Geyser-Inspired Algorithm," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 2062-2075.
  • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:2062-2075.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf137
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