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Method for predicting power supply reliability of power grid based on BP neural network

A BP neural network, grid power supply technology, applied in the field of power system, can solve the problems of inability to determine the target year network structure, complex grid structure, large amount of data, etc., to improve the accuracy and generalization ability, improve the prediction efficiency, reduce the algorithm The effect of complexity

Inactive Publication Date: 2012-10-10
HOHAI UNIV +1
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Problems solved by technology

[0004] Traditional reliability prediction methods require accurate power grid structure and historical data of component reliability indicators for many years. However, the power grid structure is complex, the amount of data is large, and the specific network structure of the target year cannot be determined at present, so traditional methods cannot be used to predict Prediction of power supply reliability of the entire grid

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  • Method for predicting power supply reliability of power grid based on BP neural network
  • Method for predicting power supply reliability of power grid based on BP neural network
  • Method for predicting power supply reliability of power grid based on BP neural network

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Embodiment Construction

[0018] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0019] The idea of ​​the present invention is to use artificial intelligence neural network to build a power grid reliability prediction model, and use the prediction model to predict the power grid reliability at the time to be predicted. The process of establishing the prediction model will be described in detail below.

[0020] Selection of input variables:

[0021] Since the power supply reliability of the power grid is mainly inseparable from the power supply capacity of the power grid itself and the natural environment in which the power grid is located, the present invention selects the availability coefficient of power grid equipment, power supply reliability rate, power supply radius, and capacity-load ratio that reflect the power grid's own supply capacity. , power loss due to power rationing, new capacity for transformation per unit of addit...

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Abstract

The invention discloses a method for predicting power supply reliability of a power grid based on a BP neural network. According to the method in the invention, the BP neural network is adopted to perform modeling prediction, and then, the BP neural network is trained and a prediction model of the power grid reliability is established with power supply capacity of the power grid as well as natural disasters faced by the power grid and other factors acting as input variables of the model, and power grid fault outage time which affects the power supply reliability acting as output variables of the model; based on the previous steps, principal component analysis is adopted to perform reducing-dimension processing on inputted samples, and therefore, input structure of the artificial neural network is simplified, thereby improving learning speed and accuracy of the network.

Description

technical field [0001] The invention relates to a power grid power supply reliability prediction method, which belongs to the technical field of power systems. Background technique [0002] Power supply reliability refers to the ability of the power supply system to continuously supply power to users. With the development of society and the improvement of people's living standards, the society has higher and higher requirements for the reliability of power supply. Improving the reliability of power supply is not only the need of users, but also the goal pursued by power supply enterprises. In recent years, large-scale and long-term power outages in large power grids at home and abroad have not only caused huge economic losses, but also endangered social order. Therefore, it is more necessary and urgent to quantitatively evaluate and improve the power supply reliability of the power system. It can be said that the formation and development of the reliability of the power sys...

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Application Information

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IPC IPC(8): G06Q10/02G06Q50/06
Inventor 卫志农刘亚南孙国强孙永辉韦延方杨雄袁阳陆子刚王越陈婷杨友情江龙才吴常胜钱瑛周军李进
Owner HOHAI UNIV
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