Basin future hydroelectric power generation capacity prediction method and system considering climate change

Abstract

The invention discloses a basin future hydroelectric power generation capacity prediction method and system considering climate change, and belongs to the field of hydrological forecasting and power generation scheduling crossover, and the method comprises the steps: predicting basin future rainfall and air temperature scenes through the combination of GCMs forecasting factors and a statistical downscaling model; collecting historical runoff data, inputting basin historical meteorological data and the historical runoff data into the VIC hydrological model, calibrating and checking model parameters of the VIC hydrological model to obtain a basin rainfall runoff model, and inputting predicted basin future rainfall and temperature scenes into the rainfall runoff model to obtain a basin section future runoff scene; and establishing a basin reservoir group combined power generation optimization scheduling model, inputting the basin section future runoff situation into the basin reservoir group combined power generation optimization scheduling model, and predicting the basin future hydropower generation capacity. Basin climate changes are considered, uneven basin underlying surface distribution is considered, and the problem of dimensionality disasters of large-scale reservoir group scheduling is relieved.

Description

technical field [0001] The invention belongs to the cross fields of hydrological forecasting and power generation dispatching, and more specifically relates to a method and system for predicting the future hydropower generation capacity of a watershed considering climate change. Background technique [0002] The watershed reservoir group is a complex and huge system. The prediction of its power generation capacity involves the fields of hydrological forecasting and reservoir dispatching. There are many influencing factors and the prediction is difficult. Breakthroughs and innovations are needed in methods and ideas. For the prediction of future runoff in watersheds, the existing methods can be divided into data statistics methods and genetic analysis methods. The former mainly includes classical regression analysis methods, neural network methods, nonlinear time series analysis methods and fuzzy mathematics methods. Statistical relationships are mainly established through dat...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above deficiencies or improvement needs of the prior art, the present invention provides a method and system for predicting the future hydropower generation capacity of a watershed considering climate change, thus solving the existing problems in the prior art that do not consider the climate change of the watershed and the underlying surface of the watershed Technical Problems of Uneven Distribution and Curse of Dimensionality

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