Water Resources Management and Planning under Uncertainty: an Inexact Multistage Joint-Probabilistic Programming Method |
| |
Authors: | Y. P. Li G. H. Huang S. L. Nie |
| |
Affiliation: | (1) College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China;(2) Environmental Systems Engineering Program, University of Regina, Regina, SK S4S 0A2, Canada;(3) Chinese Research Academy of Environmental Science, Beijing Normal University, Beijing, 100012-100875, China;(4) College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100022, China |
| |
Abstract: | In this study, an inexact multistage joint-probabilistic programming (IMJP) method is developed for tackling uncertainties presented as interval values and joint probabilities. IMJP improves upon the existing multistage programming and inexact optimization approaches, which can help examine the risk of violating joint-probabilistic constraints. Moreover, it can facilitate analyses of policy scenarios that are associated with economic penalties when the promised targets are violated within a multistage context. The developed method is applied to a case study of water-resources management within a multi-stream, multi-reservoir and multi-period context, where mixed integer linear programming (MILP) technique is introduced into the IMJP framework to facilitate dynamic analysis for decisions of surplus-flow diversion. The results indicate that reasonable solutions for continuous and binary variables have been generated. They can be used to help water resources managers to identify desired system designs against water shortage and for flood control, and to determine which of these designs can most efficiently accomplish optimizing the system objective under uncertainty. |
| |
Keywords: | Dynamics Inexact optimization Multistage Joint probability Planning Scenario analysis Uncertainty Water resources |
本文献已被 SpringerLink 等数据库收录! |
|