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Optimal Scheme of Early Refill Operation for the Three Gorges Reservoir

Yu Li, Shenglian Guo, Tianyuan Li, Yanlai Zhou

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Abstract

A joint distribution function and conditional probability distribution of this samples using copula was built and inflow series in September were obtained by stochastic simulation method. Furthermore, a refill operation optimization model of the Three Gorges Reservoir was established in this paper to derive the opti- mal refill scheme. The results show that the optimal refill scheme depends on the reservoir inflow in late Au- gust. In the wet year, refill begins in late September with storage level reaching 166 m on September 30 line- arly. Comparing with designed scheme, the scheme can generate extra about 1.57 × 10 8 kW·h electrical en- ergy (by 1.46%) and save 10.72 × 10 8 m 3 water resources (by 12.89%) annually without increasing the flood control risk; In the normal year, refill begins in middle September with storage level reaching 166 m on Sep- tember 30 linearly. Comparing with designed scheme, the scheme can generate extra about 3.45 × 10 8 kW·h electrical energy (by 3.40%) and save 22.59 × 10 8 m 3 water resources (by 34.19%) annually without increas- ing the flood control risk; In the dry year, refill begins in early September with storage level reaching 166 m on September 30 linearly by strengthening real-time monitoring. Comparing with designed scheme, the scheme can generate extra about 5.50 × 10 8 kW·h electrical energy (by 6.12%) and save 19.18 × 10 8 m 3 water resources (by 51.89%) annually without increasing the flood control risk.

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What this paper is about

A joint distribution function and conditional probability distribution of this samples using copula was built and inflow series in September were obtained by stochastic simulation method. Furthermore, a refill operation optimization model of the Three Gorges Reservoir was established in this paper to derive the opti- mal refill scheme. The results show that the optimal refill scheme depends on the reservoir inflow in late Au- gust. In the wet year, refill begins in late September with storage level reaching 166 m on September 30 line- arly. Comparing with designed scheme, the scheme can generate extra about 1.57 × 10 8 kW·h electrical en- ergy (by 1.46%) and save 10.72 × 10 8 m 3 water resources (by 12.89%) annually without increasing the flood control risk; In the normal year, refill begins in middle September with storage level reaching 166 m on Sep- tember 30 linearly. Comparing with designed scheme, the scheme can generate extra about 3.45 × 10 8 kW·h electrical energy (by 3.40%) and save 22.59 × 10 8 m 3 water resources (by 34.19%) annually without increas- ing the flood control risk; In the dry year, refill begins in early September with storage level reaching 166 m on September 30 linearly by strengthening real-time monitoring. Comparing with designed scheme, the scheme can generate extra about 5.50 × 10 8 kW·h electrical energy (by 6.12%) and save 19.18 × 10 8 m 3 water resources (by 51.89%) annually without increasing the flood control risk.

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Available abstract

A joint distribution function and conditional probability distribution of this samples using copula was built and inflow series in September were obtained by stochastic simulation method. Furthermore, a refill operation optimization model of the Three Gorges Reservoir was established in this paper to derive the opti- mal refill scheme. The results show that the optimal refill scheme depends on the reservoir inflow in late Au- gust. In the wet year, refill begins in late September with storage level reaching 166 m on September 30 line- arly. Comparing with designed scheme, the scheme can generate extra about 1.57 × 10 8 kW·h electrical en- ergy (by 1.46%) and save 10.72 × 10 8 m 3 water resources (by 12.89%) annually without increasing the flood control risk; In the normal year, refill begins in middle September with storage level reaching 166 m on Sep- tember 30 linearly. Comparing with designed scheme, the scheme can generate extra about 3.45 × 10 8 kW·h electrical energy (by 3.40%) and save 22.59 × 10 8 m 3 water resources (by 34.19%) annually without increas- ing the flood control risk; In the dry year, refill begins in early September with storage level reaching 166 m on September 30 linearly by strengthening real-time monitoring. Comparing with designed scheme, the scheme can generate extra about 5.50 × 10 8 kW·h electrical energy (by 6.12%) and save 19.18 × 10 8 m 3 water resources (by 51.89%) annually without increasing the flood control risk.

Key concepts: Inflow, Environmental science, Flood control, Flood myth, Hydrology (agriculture), Mathematics, Engineering, Meteorology

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