The impact of socio-economic–climatic indicators on hydropower production and energy demand correlation using echo state network and quantum-based sand cat swarm optimization algorithm

Bahao Li, Zhimin Wu, Ziwen Zhang, Yingmin Li and Fatemeh Gholinia

International Journal of Low-Carbon Technologies, 2025, vol. 20, 1979-1993

Abstract: The correlation between electricity demand and hydropower production regarding global climate change and socio-economic parameters is a complex issue for policymakers. This study suggests an advanced approach to enhance hydropower output within the framework of climate change and socio-economic parameters. It combines the echo state network (ESN) with a quantum-inspired sand cat swarm optimization (SCSO) algorithm, with a focus on climate-resilient electricity demand. The ESN simulates the nonlinear relationship between climate variables, electricity demand, and socio-economic factors. The SCSO algorithm guides the training of ESN, which improves the optimization procedure.

Keywords: electricity demand; hydropower generation; the echo state network; optimization; climate change; socio-economic factors (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1093/ijlct/ctaf134 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:1979-1993.

Access Statistics for this article

International Journal of Low-Carbon Technologies is currently edited by Saffa B. Riffat

More articles in International Journal of Low-Carbon Technologies from Oxford University Press
Bibliographic data for series maintained by Oxford University Press ().