A Saturated Power Load Forecasting Method Based on Long Short-term Memory Neural Network

A long-short-term memory and neural network technology, which is applied in the field of saturated power load forecasting based on long-term short-term memory neural network, can solve the problem of not considering the delay characteristics of load timing, and achieve the effect of improving the effectiveness of forecasting and requiring low correlation

Active Publication Date: 2022-05-31
STATE GRID JIANGSU ECONOMIC RES INST +2
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Problems solved by technology

These studies did not take into account the delay characteristics of load timing continuity and the influence of correlation factors

Method used

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  • A Saturated Power Load Forecasting Method Based on Long Short-term Memory Neural Network
  • A Saturated Power Load Forecasting Method Based on Long Short-term Memory Neural Network
  • A Saturated Power Load Forecasting Method Based on Long Short-term Memory Neural Network

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Embodiment Construction

[0035] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment uses the technical solution of the present invention

[0037] Step 1: select the influencing factor and set the prediction scene, and the value of the influencing factor in each scene is different. this step

[0041]

[0050] The low-speed development of the economy and society means that the population is lower than the predicted equilibrium value by 2%, the GDP is lower than the predicted equilibrium value by 4%, and the proportion of the three industries is

[0055]

[0068]

[0071]

[0073] The preferred embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art have no

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Abstract

The present invention relates to a method for forecasting saturated power load based on long-term short-term memory neural network, including: step 1, setting the influencing factors and forecasting scenarios of saturated load; The long-short-term memory neural network prediction model predicts the saturated power load of the area to be predicted, and obtains the power load saturation time and saturation scale of the area to be predicted under different prediction scenarios. Compared with the prior art, the present invention has the advantages of meeting the load time sequence continuity and the time delay requirements of influence factors on the load.

Description

A Saturated Electricity Load Forecasting Method Based on Long Short-Term Memory Neural Network technical field The present invention relates to a kind of power system load forecasting technology, especially relate to a kind of neural network based on long short term memory A method for predicting the saturated power load of the network. Background technique [0002] The saturated power load forecast refers to the prediction of the time when the regional power load enters saturation and the scale of saturated power consumption. The power load saturation scale and saturation time are affected by many factors, including regional population and economic characteristics. Saturation load gauge The mode and saturation time are the basis for the long-term planning goals of the power grid, and are of great significance for coordinating the short-term power grid construction. Traditional saturated power load forecasting method comprises: adopt improved K-means clustering algori...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 黄俊辉谈健史静姚颖蓓张建平马则良李琥刘国静李冰洁
Owner STATE GRID JIANGSU ECONOMIC RES INST
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