Robust and computationally efficient design for run-of-river hydropower
Year: 2024
Type: article
Abstract: This paper introduces innovative approaches for robust and computationally efficient optimal design of run-of-river hydropower plants. Compared with existing design software, it (1) integrates optimized turbine operations into design optimization instead of following predefined operational rules, and (2) combines this with a regular sampling of the flow duration curve to significantly reduce data inputs. Our rigorous benchmarking demonstrates that (1) operation optimization improves design performance at low computational cost, whilst (2) data input reduction slashes computational costs by over 92% with minimal impact on design recommendations and key robustness analysis insights. Taken together, these innovations make integrated design and operation optimization, complete with in-depth robustness analysis, laptop-accessible. They also reinforce sustainability efforts by minimizing the need for high-performance computing and large associated embodied greenhouse gas emissions. • This article includes two rigorously benchmarked innovations to RoR hydropower plant design. • The first innovation integrates both design and operational optimization for RoR hydropower plants for the first time. • The second innovation uses flow sampling along the FDC slashes computational costs by over 90%. • These innovations enable optimization and robustness analysis to be performed on a laptop, reducing computational needs and associated emissions.
Authors: Veysel Yildiz, Solomon Brown, Charles Rougé
Institution: University of Sheffield
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,400
OpenAlex ID: W4402629307