Method and system for establishing neural network model for determining power grid line loss

A neural network model and power grid line technology, which is applied in the field of power grid line loss modeling, can solve problems such as prolonging the learning and training time of neural network, affecting the accuracy of the model, and unfavorable model establishment.

Active Publication Date: 2019-04-16
CHINA ELECTRIC POWER RES INST +4
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Problems solved by technology

In fact, among so many influencing factors, some factors will have little influence on the line loss. Such factors will not be conducive to the

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  • Method and system for establishing neural network model for determining power grid line loss
  • Method and system for establishing neural network model for determining power grid line loss
  • Method and system for establishing neural network model for determining power grid line loss

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[0078] Exemplary embodiments of the present invention will now be described with reference to the drawings; however, the present invention may be embodied in many different forms and are not limited to the embodiments described herein, which are provided for the purpose of exhaustively and completely disclosing the present invention. invention and fully convey the scope of the invention to those skilled in the art. The terms used in the exemplary embodiments shown in the drawings do not limit the present invention. In the figures, the same units / elements are given the same reference numerals.

[0079] Unless otherwise specified, the terms (including scientific and technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it can be understood that the terms defined by commonly used dictionaries should be understood to have consistent meanings in the context of their related fields, and should not be understood as idealized or ...

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Abstract

The invention provides a method and a system for establishing a neural network model for determining power grid line loss. The method and the system aim at an optimization problem of line loss modeling input. a mutual information principle method is adopted to identify the intensity degree of main factors influencing line loss; then, based on a training set in a sample set of the collected line loss and influence factors, the influence factors are grouped and sequentially substituted into a training neural network model. The method comprises the steps of determining a plurality of neural network models, determining an evaluation index of each neural network model by utilizing a test set in a sample set, and grouping the evaluation indexes to calculate an evaluation index average value so as to determine an influence factor serving as input of an optimal neural network model, thereby improving the line loss prediction accuracy of the established neural network model.

Description

technical field [0001] The invention relates to the field of power grid line loss modeling, and more specifically, relates to a method and system for establishing a neural network model for determining power grid line loss. Background technique [0002] With the rapid development of social economy, the demand for energy is increasing day by day, and the realization of energy-saving and low-carbon development has far-reaching significance for the green and sustainable development of the national economy. As an important secondary energy source, electric energy will generate a certain loss during line transmission. Due to the increasingly complex grid structure and huge scale of the power grid, the power loss in the line is also increasing. Therefore, how to establish a line loss model with high prediction accuracy has become a hot spot in power system research in recent years. [0003] Due to the development and wide application of artificial neural network in recent years, ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06N3/04
CPCG06Q10/04G06Q10/06393G06Q50/06G06N3/045
Inventor 刘丽平白江红江木张家安王宇星孙云超周前周琪岑炳成
Owner CHINA ELECTRIC POWER RES INST
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