Microgrid load prediction method based on long and short term neural network model

Abstract

The invention discloses a microgrid load prediction method based on a long and short term neural network model, and relates to the technical field of microgrid load prediction, and the method comprises the steps: obtaining the weight of each influence factor when the clustering interval is maximum, and extracting the feature vector of each influence factor in a current group through a double-layer convolutional neural network; optimizing the long-short-term neural network through an optimizer, and carrying out feature vector screening through the optimized long-short-term neural network; weighting processing is carried out on the screened feature vectors through attention optimization, and optimized feature vectors are obtained; and connecting the optimized feature vectors through a full connection layer and obtaining the predicted load of the current group. According to the invention, the optimized feature vectors are connected through the full connection layer, the predicted load of the current group is obtained, and the long-term and short-term neural network is adopted to solve the problem of long-term dependence in the training process.

Description

technical field [0001] The invention relates to the technical field of microgrid load prediction, in particular to a microgrid load prediction method based on a long-term and short-term neural network model. Background technique [0002] With the rapid development of science and technology and economy in the world, the problem of environmental pollution caused by traditional power generation methods is becoming more and more serious. New energy technologies centered on wind power and photovoltaic power generation have become the focus of research at home and abroad. However, renewable energy itself has considerable randomness and volatility. When large-scale access to the power system, it will adversely affect the stability and reliability of the power grid. As a small-scale, decentralized independent system, microgrid has the advantages of self-control, protection and management. The rapid development of its related technologies makes it possible to promote the large-scal...

AI Technical Summary

Problems solved by technology

[0004] However, although the existing load forecasting methods have their own advantages, the research objects are all traditional power systems, and there is a lack of targeted research on new micro-grids with a large number of new energy sources.

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