Author(s): Vishesh Kumar Sharma

Abstract: Hydropower stands as the most widely utilized renewable energy source globally, accounting for over 16% of total electricity production and over 60% of renewable energy generation. The design of dams significantly influences the efficiency, safety, and long-term sustainability of hydropower generation. This paper critically examines the optimization of dam design parameters—such as dam height, reservoir capacity, spillway design, and turbine selection-to enhance hydropower output. Drawing upon empirical studies, computational modeling, and field data from large-scale hydropower projects, this study explores the relationships between design variables and power output efficiency. It emphasizes the integration of hydrological, geological, structural, and socio-environmental factors into the optimization process. The paper also investigates how modern techniques such as artificial intelligence (AI), machine learning (ML), and genetic algorithms are revolutionizing dam design for maximizing energy yield with minimal ecological impact.

DOI: 10.22271/27078302.2025.v6.i1a.57

Pages: 05-09 | Views: 47 | Downloads: 20

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