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method for detecting bad data in state estimation based on improve BP neural network

A BP neural network and state estimation technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of bad data detection, low accuracy, long training time of BP neural network, etc. The effect of good detection and identification, shortening training time

Inactive Publication Date: 2019-02-22
FUSHUN POWER SUPPLY COMPANY OF STATE GRID LIAONING ELECTRIC POWER SUPPLY +3
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Problems solved by technology

[0010] The technical problem to be solved by the present invention is to provide a detection method based on the bad data in the state estimation of the improved BP neural network for the above-mentioned deficiencies in the prior art, so as to overcome the problems of the BP neural network when detecting and identifying bad data in the state estimation of the power system. The training time is too long and the accuracy is low, so as to realize the detection of bad data in the power system state estimation

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  • method for detecting bad data in state estimation based on improve BP neural network
  • method for detecting bad data in state estimation based on improve BP neural network
  • method for detecting bad data in state estimation based on improve BP neural network

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[0048] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0049] In this embodiment, the state estimation data of a power system is taken as an example, and the bad data in these data are detected by using the detection method for bad data in the state estimation based on the improved BP neural network of the present invention.

[0050] A detection method based on bad data in improved BP neural network state estimation, such as figure 1 shown, including the following steps:

[0051] Step 1, for example figure 2 The traditional BP neural network shown is improved by selecting a new activation function and increasing the adjustment factor, increasing the momentum item and bias adjustment, and dynamically adjusting the iterative ...

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Abstract

A method for detecting bad data in state estimation based on improve BP neural network relates to that technical field of power system state estimation. This method firstly improves the traditional BPneural network, then inputs the good data of power system state estimation into the improved BP neural network, and trains the improved BP neural network. Then, through the trained improved BP neuralnetwork model, the doubtful data sets in the power system are screened out. Finally, the traditional quartile method is used to detect and identify the bad data in power system. The invention provides a method for detecting bad data in state estimation based on improved BP neural network, The improved BP neural network can better detect and identify the data in power system state estimation, at the same time, it can shorten the time of detecting data, effectively eliminate bad data, and improve the accuracy of data in state estimation.

Description

technical field [0001] The invention relates to the technical field of power system state estimation, in particular to a detection method based on bad data in the state estimation of the improved BP neural network. Background technique [0002] The detection and identification of data in power system state estimation is the most basic part of data processing in state estimation. How to detect and identify data accurately and in real time is the key to power system state estimation. At present, BP neural network has been widely used in the field of data processing and has become the basic platform for intelligent data processing. BP neural network is a kind of feed-forward neural network according to error backpropagation. A neural network consists of an input layer, a hidden layer, and an output layer. Each layer of the neural network is composed of neuron nodes in each layer, and each neuron node is connected to all nodes in the previous layer. The output data of the pre...

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06Q50/06
CPCG06N3/084G06Q50/06G06N3/048
Inventor 张海黄博南张辉高凯汪广明刘鑫蕊孙秋野张瑶瑶任冬霞
Owner FUSHUN POWER SUPPLY COMPANY OF STATE GRID LIAONING ELECTRIC POWER SUPPLY
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