Method for comprehensively predicting generation capacity of multi-radial flow type small hydropower station group area
A small hydropower group and power generation technology, applied in the field of electric power, can solve problems such as the difficulty of accurately describing multicollinearity of factors, the difficulty of finding statistical laws of things, and the low prediction accuracy of power generation in areas with many small hydropower plants.
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Embodiment 1
[0073] Embodiment 1: as Figure 1-2 As shown in the figure, a comprehensive forecasting method for power generation in multi-runoff small hydropower cluster areas, first adopts the partial least squares model to obtain the linear multiple regression equation between the power generation in multi-runoff small hydropower cluster areas and the relevant factors affecting power generation ; At the same time, the improved gray forecasting model is used to model the series of related factors to obtain the predicted value of related factors; then, the predicted value of related factors is substituted into the linear multiple regression equation obtained by the partial least squares model, and the multi-runoff small hydropower station is obtained The predicted value of power generation in the group area; finally, the relative error is obtained according to the predicted value of power generation.
[0074] The concrete steps of described method are as follows:
[0075] A. According to ...
Embodiment 2
[0088] Embodiment 2: as Figure 1-2 As shown, a method for comprehensive forecasting of power generation in a multi-runoff small hydropower group area, the specific implementation steps of the method are as follows:
[0089] The monthly power generation data of runoff small hydropower groups in a certain area from 2009 to 2011 were selected as historical data, and the monthly power generation in 2012 was predicted. Hydrological water flow, hydrological precipitation, and meteorological precipitation, which are closely related to power generation, are selected as independent variable factors for prediction and analysis. It can be seen that the number of sample observation points is 3 and the number of related factors is 3. Using Matlab7.0 simulation software, the prediction of the small hydropower group in March 2012 is taken as an example to illustrate. The original data are shown in Table 1.
[0090]
[0091] First, the above three sets of data are selected for PLS (Parti...
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