Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation

Shaokun He; Shenglian Guo; Kebing Chen; Lele Deng; Zhen Liao; Feng Xiong; Jiabo Yin

doi:10.1016/j.dib.2019.104440

Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation

Data Brief. 2019 Aug 28:26:104440. doi: 10.1016/j.dib.2019.104440. eCollection 2019 Oct.

Authors

Shaokun He¹, Shenglian Guo¹, Kebing Chen¹, Lele Deng¹, Zhen Liao¹, Feng Xiong¹, Jiabo Yin¹

Affiliation

¹ State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 430072, China.

Abstract

The dataset contains reservoir characteristic parameters, streamflow series of reservoirs in the upper Yangtze River, the standard operating rules (SORs) and the seasonal top of buffer pools (seasonal TBPs) for these reservoirs, which were provided by the Yangtze River Commission. Moreover, annual hydropower of these reservoirs is tested to evaluate operation performance. These research materials are related to the research article in Advances in Water Resources, entitled 'Optimal impoundment operation for cascade reservoirs coupling parallel dynamic programming with importance sampling and successive approximation' (He et al., 2019). The dataset could be used to derive optimal operating rules to explore the potential benefits of water resources via our proposed algorithm (importance sampling - parallel dynamic programming, IS-PDP) in different runoff scenarios. It can also be further applied for water resources management and other potential users.

Keywords: Cascade reservoirs; Importance sampling; Impoundment operation; Parallel dynamic programming; Seasonal top of buffer pools; Streamflow observation; Yangtze river basin.