Photovoltaic power prediction method and system based on Elman neural network and satellite cloud picture
A satellite cloud image and power prediction technology, applied in neural learning methods, biological neural network models, predictions, etc., can solve problems such as slow convergence speed, poor global stability, and large errors, and achieve improved accuracy, good global stability, and convergence fast effect
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Embodiment 1
[0043] like Figure 1-8 As shown, this embodiment provides a photovoltaic power prediction method based on the Elman neural network and satellite cloud images. This embodiment uses the method applied to the server as an example. It can be understood that the method can also be applied to the terminal. It can be applied to a terminal, a server and a system, and is realized through the interaction between the terminal and the server. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or it can provide cloud services, cloud database, cloud computing, cloud function, cloud storage, network server, cloud communication, intermediate Cloud servers for basic cloud computing services such as software services, domain name services, security service CDN, and big data and artificial intelligence platforms. The terminal may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart sp...
Embodiment 2
[0089] The present embodiment provides a kind of photovoltaic power prediction system based on Elman neural network and satellite cloud image, comprising:
[0090] The data acquisition module is configured to acquire historical power consumption data and satellite images of the power consumption system to be predicted and perform preprocessing;
[0091] The model building module is configured to build an Elman dynamic recursive neural network model and input preprocessed data for training;
[0092] The photovoltaic power prediction module is configured to input the preprocessed data into the trained Elman model and output the prediction result.
[0093]It should be noted here that the above-mentioned data acquisition module, model building module and photovoltaic power prediction module correspond to steps S100 to S300 in Embodiment 1, and the examples and application scenarios implemented by the above-mentioned modules are the same as those of the corresponding steps, but are...
Embodiment 3
[0095] This embodiment provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the photovoltaic power prediction method based on the Elman neural network and satellite cloud image as described in the first embodiment above. step.
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