Research on influence factors analysis and countermeasures of improving prediction accuracy of run-of-river small hydropower

2017 
Guizhou Province is rich in water resources, in addition to large and medium-sized hydropower stations, but also has more than 3,600 MW of small hydropower, which accounted for 74.65% of small hydropower. In this paper, the existing small hydropower power forecasting method is analyzed. It is found that the existing forecasting methods have poor adaptability to the power prediction of the small hydropower station, and the precision is difficult to meet the dispatching operation requirement. The main reason for the above problems is that run-of-river small hydropower is mostly in remote mountainous areas. Power generation capacity is affected by climate and geographical environment seriously, which results in strong randomicity of power generation output. Finally, through the comparison and analysis of the actual data and the forecast data of the small hydropower station, it is found that the prediction accuracy of the small hydropower has a great relationship with the historical power data and the quality of the weather forecast. It is suggested that in the future research and engineering practice, forecasting the quality of the historical data and the weather forecast data should be fully considered to improve the forecast accuracy of the run-of-river small hydropower, so as to provide the basis for adjusting the operation plan of the grid dispatching and ensure the safe operation of the grid.
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