An interpretable physics-informed artificial intelligence model for daily hydropower generation prediction in cascaded reservoirs incorporating spatiotemporal correlations

Renewable Energy 2026

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Authors: Jing-shuai Zhang, Zhong-kai Feng, Wen-jing Niu, Bo Zhou, Bin Luo, Shumin Miao

DOI: 10.1016/j.renene.2026.125952

Cited by: 1

References: 40

Fields of Study & Subjects

Water resources management and optimization Hydrological Forecasting Using AI Energy Load and Power Forecasting

References 40