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论文类型：期刊论文

发表时间：2013-10-01

发表刊物：SCIENCE CHINA-TECHNOLOGICAL SCIENCES

收录刊物：SCIE、EI、Scopus

卷号：56

期号：10

页面范围：2540-2552

ISSN号：1674-7321

关键字：cascaded hydropower reservoirs; forecasting inflow; stochastic dynamic programming; decision tree; hedging rule

摘要：This paper evaluates the performances of the models that incorporate forecasting inflow for cascaded hydropower reservoirs operation. These models are constructed separately on the concepts of explicit stochastic optimization (ESO) and implicit stochastic optimization (ISO) as well as parameterization-simulation-optimization (PSO). Firstly, the aggregation-disaggregation method is implemented in ESO models to reduce the complexity of stochastic dynamic programming (SDP). And the aggregate flow SDP (AF-SDP) and aggregation-disaggregation SDP (AD-SDP) are constructed respectively. Secondly, in ISO model, decision tree is the well-known and widespread algorithm. The algorithm C 5.0 is selected to extract the if-then-else rules for reservoir operation. Thirdly, based on the PSO model, the hedging rule curves (HRCs) are pre-defined by fusing the storage and inflow as state variable. The parameters of the HRCs are determined by using the simulation-optimization model. Finally, China's Hun River cascade hydropower reservoirs system is taken as an example to illustrate the efficiency and reliability of the models. In addition, the values of quantitative precipitation forecasts of the global forecast system (10 days lead-time) are implemented to forecast the 10 days inflow.