Resident load prediction method based on LSTM-SAM model and pooling
A load forecasting and pooling technology, applied in the field of power systems, can solve problems such as low forecasting accuracy and unused useful information, and achieve the effect of improving forecasting accuracy and ensuring safe and stable economic operation
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[0063] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.
[0064] The present invention provides a resident load forecasting method based on LSTM-SAM model and pooling, such as figure 1 As shown, the method includes the following steps:
[0065] (1) Obtain historical load data and numerical weather forecast data of multiple resident users, and randomly select a user as the target user;
[0066] (2) Use two-stage feature engineering to preprocess each user's data;
[0067] (3) Sort non-target users, select different numbers of non-target users as interco...
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