the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A novel framework of deriving joint impoundment rules for large-scale reservoir system based on a classification-aggregation-decomposition approach
Abstract. Joint and optimal impoundment operation of the large-scale reservoir system has become more crucial for modern water management. Since the existing techniques fail to optimize the large-scale multi-objective impoundment operation due to the complex inflow stochasticity and high dimensionality, we develop a novel combination of parameter simulation optimization and classification-aggregation-decomposition approach here to overcome these obstacles. There are four main steps involved in our proposed framework: (1) reservoirs classification based on geographical location and flood prevention targets; (2) assumption of a hypothetical single reservoir in the same pool; (3) the derivation of the initial impoundment policies by the non-dominated sorting genetic algorithm-II (NSGA-II); (4) further improvement of the impoundment policies via Parallel Progressive Optimization Algorithm (PPOA). The framework potential is performed on China's mixed 30-reservoir system in the upper Yangtze River. Results indicate that our method can provide a series of schemes to refer to different flood event scenarios. The best scheme outperforms the conventional operating rule, as it increases impoundment efficiency from 89.50 % to 94.16 % and hydropower generation by 7.70 billion kWh (or increase 3.79 %) while flood control risk is less than 0.06.
- Preprint
(1993 KB) - Metadata XML
- BibTeX
- EndNote
-
RC1: 'hess-2019-586 -- Review', Anonymous Referee #1, 14 Apr 2020
- AC1: 'Reply to reviewer 1', Shenglian Guo, 28 Apr 2020
-
RC2: 'hess-2019-586-r1', Anonymous Referee #2, 30 Apr 2020
- AC2: 'Reply to reviewer 2', Shenglian Guo, 05 Jun 2020
-
RC1: 'hess-2019-586 -- Review', Anonymous Referee #1, 14 Apr 2020
- AC1: 'Reply to reviewer 1', Shenglian Guo, 28 Apr 2020
-
RC2: 'hess-2019-586-r1', Anonymous Referee #2, 30 Apr 2020
- AC2: 'Reply to reviewer 2', Shenglian Guo, 05 Jun 2020
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
723 | 248 | 54 | 1,025 | 52 | 47 |
- HTML: 723
- PDF: 248
- XML: 54
- Total: 1,025
- BibTeX: 52
- EndNote: 47
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
Shaokun He
Shenglian Guo
Chong-Yu Xu
Kebing Chen
Zhen Liao
Lele Deng
Huanhuan Ba
Dimitri Solomatine
curse of dimensionalityand inflow stochasticity problem. It is tested with a mixed 30-reservoir system in China. The results show that our method can provide lots of schemes to refer to different flood event scenarios. The best scheme outperforms the conventional operating rule, as it increases impoundment efficiency and hydropower generation while flood control risk is less.