A real-time operation of the Three Gorges Reservoir with flood risk analysis

被引：7

作者：

Sun, Yixiang ^{[1
]}

Tang, Deshan ^{[1
]}

Dai, Huichao ^{[2
]}

Liu, Pan ^{[3
]}

Sun, Yifei ^{[4
]}

Cui, Qingfeng ^{[5
]}

Zhang, Fanping ^{[6
]}

Ding, Yifan ^{[1
]}

Wei, Yuhang ^{[1
]}

Zhang, Jinxin ^{[1
]}

Wang, Mei ^{[1
]}

Li, Aodian ^{[1
]}

Meng, Zhenzhu ^{[1
]}

机构：

[1] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Nanning 210098, Peoples R China

[2] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Minist Educ, Innovat Res Team, Nanning 210098, Peoples R China

[3] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China

[4] Heilongjiang Prov Qing Water Conservancy & Hydrop, Harbin 150000, Peoples R China

[5] Heilongjiang Prov San Jiang Engn Construct Adm Bu, Harbin 150000, Peoples R China

[6] Jiangxi Prov Inst Water Sci, Nanchang 330000, Peoples R China

来源：

WATER SCIENCE AND TECHNOLOGY-WATER SUPPLY | 2016年 / 16卷 / 02期

关键词：

ANFIS; flood risk; GA; multi-objective; reservoir optimal operation; SYSTEM; MODEL; RULE;

D O I：

10.2166/ws.2015.172

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Risk analysis is essential to reservoir operation. In this study, a new analysis for reservoir operation is proposed to enhance the utilization rate of the flood water from the Three Gorges Reservoir (TGR) during the flood season. Based on five scenarios of hydrology forecasting with the adaptive neuro-fuzzy inference system (ANFIS), a multi-objective optimum operation was implemented employing the risk control constraints of the genetic algorithm (GA) for the TGR. The results of this analysis indicated that the optimum hydropower generation was 5.7% higher than the usual operating hydropower generation, which suggested that, during flood season, it would be beneficial to increase hydropower generation from reservoirs, while maintaining a safe degree of flood risk.

引用

页码：551 / 562

页数：12