Planning & Management

Oral

394393 - A two stage method using scenario-based forecasts for reservoir operation

Wednesday, June 6
2:00 PM - 3:30 PM
Location: Northstar B

Reservoir operation is very critical to the realization of comprehensive utilization benefits. This study is aimed at developing a real-time operation model with scenario-based forecasts to obtain more utilization benefits. Two stage sampling stochastic dynamic programming (TS-SSDP), an improved sampling stochastic dynamic programming (SSDP), is proposed to derive the on-line operation policies by using the forecast horizon point to divide the future operation horizon into two stages, while the first stage is the forecast horizon which is provided with scenario-based forecasts and the second stage is the remaining horizon which is described by using historical scenarios. To describe the transition probabilities from scenario-based forecasts to historical scenarios, two TS-SSDP schemes are then developed. One has the equal transition probabilities (TS-SSDP1), and the other considers the empirical transition probabilities (TS-SSDP2). The proposed method is applied to the Three Gorges Reservoir in China. Finally, six schemes, including the conventional operation, deterministic dynamic programming, stochastic dynamic programming, SSDP, TS-SSDP1 and TS-SSDP2, are implemented for comparative purposes. Results indicate that the proposed TS-SSDP2 method is useful for reservoir operation.

Pan Liu

Wuhan University

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He Li

Wuhan University

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Maoyuan Feng, PhD candidate

PhD candidate
Wuhan University

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