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A Comprehensive Classification Method of Load Characteristics Based on Markov Monte Carlo

A classification method, a technology of load characteristics, applied in the fields of instrument, calculation, character and pattern recognition, etc., can solve the problem that the randomness and time-varying of the load cannot be considered.

Active Publication Date: 2019-01-01
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the deficiencies in the prior art, the present invention discloses a classification feature aimed at the randomness and time-varying nature of electric load, and provides a high-accuracy classification and synthesis method aimed at the randomness and time-varying nature of electric load, which overcomes the Existing load modeling methods cannot consider the randomness and time-varying nature of load

Method used

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  • A Comprehensive Classification Method of Load Characteristics Based on Markov Monte Carlo
  • A Comprehensive Classification Method of Load Characteristics Based on Markov Monte Carlo
  • A Comprehensive Classification Method of Load Characteristics Based on Markov Monte Carlo

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Experimental program
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Embodiment Construction

[0088] The present invention will be described in detail below in conjunction with the drawings:

[0089] Such as figure 2 As shown, perform step 01 to start;

[0090] Next, perform step 02 to calculate statistics This statistic obeys the degree of freedom (n-1) 2 Χ 2 distributed.

[0091] Let m ij Means X (0) (t) The frequency of transition from state i to state j in one step, and the sum of each column of the transition frequency matrix is ​​divided by the sum of each row and column, and the value obtained is denoted as P' j :

[0092]

[0093] Remember

[0094]

[0095] Statistics

[0096]

[0097] Given the confidence level α, look up the table to get Value if The sequence is considered to be Markovian, otherwise it is not a Markov chain.

[0098] Once again, step 03 is executed to obtain the probability transition matrix based on non-linear programming based on PSO.

[0099] In this paper, a non-linear programming based on particle swarm optimization simulated annealing algorithm ...

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Abstract

The invention discloses a comprehensive classification method of load characteristics based on Markov Monte Carlo. Whether the change between the load categories is Markovian, divide all the data into time-average segments, and establish a Markovian chain probability transition matrix for each segment of data based on the idea of ​​maximum likelihood; judge whether the digital characteristics have changed, if not, then Go to step 5, otherwise, cluster the load data of the time period according to the corresponding digital characteristics of the matrix, and obtain the probability transition matrix for the load data of each time period with changed data characteristics; use Markov Monte Carlo simulation to describe the load Variations; Hidden Markov Models are used to process sequences reflecting load category transformations. This method improves the Markov chain Monte Carlo simulation, which effectively reduces the possibility of the matrix falling into a steady state after iteration.

Description

Technical field [0001] The invention relates to a load characteristic classification and synthesis method based on Markov Monte Carlo. Background technique [0002] Load modeling is a basic and key issue in power system modeling. Establishing a load model that can accurately reflect load characteristics has always been a challenging and difficult problem. The biggest difficulty in load modeling lies in the randomness and time-varying nature of the load, which includes changes in the size of the load and changes in the composition of the load. Even so, there are certain regularities in the load characteristics. [0003] In order to solve the problem of randomness and time-varying of load composition on the basis of grasping the law, classify and synthesize the dynamic characteristics of load. The classification and synthesis of load dynamic characteristics is to classify similar load components in the dynamic load characteristic data of the same substation collected at different t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/241G06F18/295
Inventor 王振树周光耀
Owner SHANDONG UNIV