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On-line Calculation Method of Probabilistic Power Flow Based on bp Neural Network

A BP neural network and probabilistic power flow technology, applied in the field of power system and its automation, can solve problems such as speeding up the power flow solution speed, difficult online analysis, etc. Effect

Active Publication Date: 2021-11-16
CHONGQING UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

Most of the improved iterative algorithms are based on Newton's method, such as fast decoupling method, quasi-Newton method, etc., which speed up the power flow solution to a certain extent, but iterative calculation is still required, so it is difficult to be used for online analysis

Method used

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  • On-line Calculation Method of Probabilistic Power Flow Based on bp Neural Network
  • On-line Calculation Method of Probabilistic Power Flow Based on bp Neural Network
  • On-line Calculation Method of Probabilistic Power Flow Based on bp Neural Network

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Experimental program
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Effect test

Embodiment 1

[0069] see figure 1 , a probabilistic power flow online calculation method based on BP neural network, which mainly includes the following steps:

[0070] 1) Establish a BP neural network power flow model.

[0071] Further, the BP neural network is a multilayer feed-forward network trained by the error backpropagation algorithm. The BP neural network power flow model includes an input layer, a hidden layer and an output layer.

[0072] The number of neurons in the input layer is set to n. Any neuron in the input layer is denoted as x i , i=1, 2...n.

[0073] The number of neurons in the hidden layer is 1.

[0074] The number of neurons in the output layer is set to m. Any neuron in the output layer is denoted as d e , e=1, 2...m.

[0075] The values ​​of n and m are determined by the scale and complexity of the power system.

[0076] 2) Initialize the basic parameters of the BP neural network power flow model, mainly including: the weight W from the input layer to the...

Embodiment 2

[0127] An experiment of applying the probabilistic power flow online calculation method based on BP neural network to the power system mainly includes the following steps:

[0128] 1) Establish a BP neural network power flow model.

[0129] 2) Initialize the basic parameters of the BP neural network power flow model, mainly including: the weight W from the input layer to the hidden layer ij and the weight W from the hidden layer to the output layer je and learning rate η.

[0130] In this embodiment, the training sample input and the training sample input are divided into 1000 small batches. After removing the elements with the same input data, the remaining 189 elements, the number of neurons in the hidden layer can be 200, the learning rate is initially 0.8, after 500 iterations, the learning rate decays to 0.1, and the momentum factor is 0.5.

[0131] 3) Obtain training sample data. The training sample data mainly includes wind speed, irradiance and load of the power sy...

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Abstract

The invention discloses an online calculation method of probability power flow based on BP neural network, which mainly includes the following steps: 1) establishing a BP neural network power flow model. 2) Initialize the basic parameters of the BP neural network power flow model. 3) Obtain training sample data. 4) Determine the training target. The training sample data is used to train the BP neural network power flow model, so as to obtain the trained BP neural network power flow model. 5) Obtain calculation samples. 6) Input the training sample data obtained in step 3 into the BP neural network power flow model trained in step 4 at one time to obtain the training target, thereby judging the solvability of the power flow of all training samples; calculating the power flow value of the solvable sample . 7) Statistical probability power flow index. The invention can be widely applied to the online calculation of the probability flow of the electric power system, and is especially suitable for the situation that the high proportion of new energy access causes the uncertainty of the electric power system to increase.

Description

technical field [0001] The invention relates to the field of electric power system and automation thereof, in particular to an online calculation method of probability power flow based on BP neural network. Background technique [0002] Power systems essentially operate in uncertain environments. Probabilistic power flow can take into account the influence of uncertain factors, obtain the probability characteristics of system state variables, and use it in power system planning and operation. In recent years, due to the increasing penetration of renewable energy such as photovoltaics and wind power, the uncertainty of the power system has surged. In order to meet the requirements of power system operation and scheduling, the demand for online probabilistic power flow calculation is becoming more and more urgent. [0003] At present, the probabilistic power flow solution methods mainly include analytical method and simulation method. Analytical methods (convolution method,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/08
CPCG06N3/084
Inventor 余娟任鹏凌郭林严梓铭杨燕向明旭
Owner CHONGQING UNIV
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