Dynamic load model modeling method adopting support vector machine linear kernel

A technology of support vector machine and model modeling, applied in the field of establishment and identification of system parameters, it can solve the problems of no parameters, no proposed model, quantization, etc., and achieve the effect of avoiding weak generalization ability.

Active Publication Date: 2017-03-08
TIANJIN UNIV
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Problems solved by technology

At present, there are also literatures that try to use the support vector machine of the RBF kernel to establish a load model, but only use th

Method used

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  • Dynamic load model modeling method adopting support vector machine linear kernel
  • Dynamic load model modeling method adopting support vector machine linear kernel
  • Dynamic load model modeling method adopting support vector machine linear kernel

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Embodiment Construction

[0039] The present invention is described below

[0040] 1. Use PMU (synchronous vector measurement device) to collect grid fault data, three-phase voltage amplitude and phase, three-phase current amplitude and phase of a specific power branch of a grid; calculate and record the corresponding positive sequence voltage change Δu, grid frequency change Δf, and the corresponding change of active power ΔP and reactive power ΔQ; 3) Divide the data of the power branch into three categories, single-phase-to-ground fault, phase-to-phase short-circuit fault, and three-phase short-circuit fault; 4) divide the three types of fault occurrence intervals The data of is summarized as data X(l) and data T(l), where l is the number of data.

[0041] 2. And set the structure of the model as the following structure, and set the model order as n order.

[0042] For active power

[0043] ΔP(k)=d 1 ΔP(k-1)+d 2 ΔP(k-2)+d 3 ΔP(k-3)+…+d n ΔP(k-n)

[0044] +e 1 Δu(k)+e 2 Δu(k-1)+e 3 Δu(k-2)+e...

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Abstract

The invention relates to a dynamic load model modeling method adopting a support vector machine. The method comprises the following steps: collecting power grid failure data of a specific power branch of a certain power grid according to power grid data acquired in real time; summarizing data of a single-phase earth failure, an inter-phase short-circuit failure and a three-phase short-circuit failure, training load model data by the support vector machine to obtain a support vector machine model, and setting a structure of the model; acquiring an active power load difference equation model of the power branch according to a model equivalence principle; and acquiring a parameter theta and a parameter theta' of a system to be determined according to a linear kernel model and the structure of a system to be recognized. Through adoption of the dynamic load model modeling method, comprehensive consideration is given to experience risk minimization and structural risk minimization, so that an obtained power load model has higher generalization capability, can reflect the dynamic state of the system better, and is more approximate to a response feature of a real power system.

Description

technical field [0001] The invention relates to the field of power system dynamic load modeling, in particular to the establishment of a power system load model structure and the identification of system parameters. Background technique [0002] In the field of power systems, load models are mainly used for power system analysis and simulation, and play an important role in the analysis of power system security and stability. Currently, load models are mainly divided into three categories: one is the static load model, and its main representative is the ZIP model (Z represents constant impedance, I represents constant current, and P represents constant power); the second type is dynamic load model, which mainly includes 1) input-output transfer function model; 2) composite load model, which combines an induction motor model with a ZIP The models are obtained in parallel. The dynamic load model is the need to study the dynamics of the power system, and the accuracy of the dy...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06Q50/06
CPCG06F30/20G06Q50/06Y02E60/00
Inventor 何熠梁晓东
Owner TIANJIN UNIV
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