Photovoltaic power generation prediction method based on improved generalized weather based on k-means clustering
A technology of photovoltaic power generation and forecasting method, which is applied in forecasting, data processing applications, instruments, etc., and can solve problems such as large difference in power generation curves, increased forecasting error, and low forecasting accuracy of photovoltaic power generation, achieving good forecasting accuracy, The effect of improving prediction accuracy
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[0033] The present invention will be further described below in conjunction with accompanying drawing.
[0034] In view of the shortcomings of the existing generalized weather being too absolute in the process of use, this method clusters the daily historical output data into four clusters through the K-means clustering algorithm in the construction of the generalized weather map, and each cluster corresponds to a cluster center . First make each cluster with a digital label, and then the historical output data in the cluster also carry a digital label. The meteorological professional weather corresponding to the historical output data in the statistical cluster is calculated, and the improved generalized weather map is obtained according to the corresponding relationship. In the improved generalized weather mapping, the same meteorological professional weather corresponds to one or more generalized weather labels, so as to adapt to the possible variability characteristics of...
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