A short-term photovoltaic power generation power prediction method and system based on multi-source heterogeneous data

Abstract

The present invention relates to a short-term photovoltaic power prediction method and system for multi-source heterogeneous data. The method includes: receiving the input of unstructured data, and obtaining the future unstructured data feature map through the Res-Unet model, wherein the feature map is used as The input of the attention mechanism and the long-term short-term memory network module in the decoder; the encoder module receives the input of structured data at the same time, and after the long-term short-term memory network and the attention mechanism module of the encoder module, the structured data feature map is obtained , and then fused with the unstructured data feature map, input to the decoder module; receive the feature after the fusion of the structured data feature map and the unstructured data feature map, and decode it through the attention mechanism and the long-term short-term memory network module, Get the photovoltaic output at the future moment.

Description

technical field [0001] The invention relates to a short-term photovoltaic power generation power prediction technology, in particular to a short-term photovoltaic power generation power prediction method and system of multi-source heterogeneous data. Background technique [0002] In the past two decades, global warming has been intensifying and extreme disasters have occurred frequently. In the face of the imminent climate crisis, it is an inevitable reform direction to build a sustainable energy system with new energy and renewable energy as the mainstay. The development and utilization of solar energy has become an important field of global energy transformation, and photovoltaic power generation has entered the stage of large-scale development, showing a good development prospect. Photovoltaic power generation has the advantages of cleanness and environmental protection, low investment cost, etc. Accurate prediction of photovoltaic power generation can improve the operati...

AI Technical Summary

Problems solved by technology

[0003] However, since the output of photovoltaic power generation is greatly affected by weather and other factors, its strong intermittency and volatility make the power system a huge impact and challenge after a high proportion of photovoltaics are connected.

The indirect prediction method uses meteorological data as input to construct a radiation prediction model and a photoelectric conversion model to predict photovoltaic output power. This method is difficult to obtain the characteristics of structured data and unstructured data at the same time, and the prediction accuracy is low.

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