Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction
Chu, JG; Zhang, C; Fu, GT; et al.Li, Y; Zhou, HC
Date: 12 August 2015
Article
Journal
Hydrology and Earth System Sciences
Publisher
European Geosciences Union (EGU) / Copernicus Publications
Publisher DOI
Related links
Abstract
This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol’s method is used to screen insensitive decision variables and guide the formulation of the optimization problems ...
This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol’s method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational
demands required for attaining high-quality approximations of optimal trade-off relationships between con-
flicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation
problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results
show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed
dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of
multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when
solving complex multi-objective reservoir operation problems.
Engineering
Faculty of Environment, Science and Economy
Item views 0
Full item downloads 0