Hydropower station rolling medium-term rolling scheduling method with CFS ensemble forecasting product used

Abstract

The invention relates to the field of hydropower station forecasting and scheduling, and discloses a hydropower station rolling medium-term rolling scheduling method with a CFS ensemble forecasting product used. According to the technical scheme, a multi-core parallel downloading technology based on a Fork/Join framework is used for downloading and analyzing CFS ensemble forecasting files with longer forecasting periods from an American CFS ensemble forecasting server everyday at fixed time, up-to-date rainfall forecasts of a hydropower station are obtained, a BP neural network model which is already completed through effective historical data in a calibrating mode is input so as to carry out runoff forecasting, and rolling calculation is conducted according to up-to-date forecasting information, the actual working state and the selected optimization model of the hydropower station and by the utilization of optimization methods such as POA and DDDP to obtain an optimal scheduling strategy of the hydropower station. The hydropower station rolling medium-term rolling scheduling method with the CFS ensemble forecasting product used has the advantages that the actual scheduling requirements of the hydropower station are foreseen, practical applications of the CFS ensemble forecasting product are developed, medium-term scheduling of the hydropower station is guided and the method has important significance in optimization scheduling operation management of hydropower stations (groups) in China.

Description

Technical field [0001] The invention relates to a scheduling strategy and method using ensemble forecast products, in particular to the mid-term optimal scheduling operation of hydropower stations (groups) based on CFS ensemble forecasting, and belongs to the field of forecasting and scheduling operation. technical background [0002] Runoff is the most important input for the optimal operation model of hydropower stations (groups). Whether the uncertainty description conforms to the actual situation is related to the optimization operation model and whether the solution results can be directly applied to the actual production. Precipitation is a key factor affecting runoff, and a single rainfall forecast has limited information, which may lead to large deviations in hydrological forecasts for certain events, which in turn affects the optimal operation of hydropower stations (groups). [0003] In recent years, the development of ensemble numerical weather prediction technology has...

AI Technical Summary

Problems solved by technology

[0005] At present, the relevant research results and literature reports at home and abroad are m...

Images