CN112464437B - Parameter identification method of electric power simulation model - Google Patents

Parameter identification method of electric power simulation model Download PDF

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CN112464437B
CN112464437B CN202011190386.9A CN202011190386A CN112464437B CN 112464437 B CN112464437 B CN 112464437B CN 202011190386 A CN202011190386 A CN 202011190386A CN 112464437 B CN112464437 B CN 112464437B
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梁钰
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Electric Power Research Institute of Hainan Power Grid Co Ltd
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Abstract

The invention provides a parameter identification method of an electric power simulation model, which comprises the following steps: s1, establishing a power system simulation model, and setting an initial parameter value of a certain circuit index of the simulation model
Figure DDA0002752594290000019
Setting a simulation threshold delta; s2, generating a parameter disturbance value delta C (j) And calculating the parameter value after disturbance
Figure DDA0002752594290000011
And
Figure DDA0002752594290000012
s3, the parameter values are used
Figure DDA0002752594290000013
And
Figure DDA0002752594290000014
putting the simulation model into the power system for calculation to obtain a first simulation value of the line index
Figure DDA0002752594290000015
And a second simulation value
Figure DDA0002752594290000016
S4, based on a first simulation value
Figure DDA0002752594290000017
And a second simulation value
Figure DDA0002752594290000018
Calculating iterative parameter value C (j+1) The iteration parameter value C (j+1) Putting the power system into the power system simulation model for calculation to obtain a third simulation value delta (j+1) (ii) a S5, if the third simulation value delta (j+1) If the iteration parameter value C meets the requirement (j+1) Is the final parameter value of the line index.

Description

Parameter identification method of electric power simulation model
Technical Field
The invention relates to the technical field of power simulation, in particular to a parameter identification method of a power simulation model.
Background
With the increasing development of power systems, the types of equipment parameters and operation data used for calculation and analysis of the power systems are more and more, the data volume is also increased continuously, accurate equipment parameters are the basis for protection setting, fault analysis, load flow calculation and loss analysis of the power systems, and the method has very important significance for safe and stable operation of the power systems. Because the required parameters are too large to be combed, all the parameters do not have actual measurement data, and the actual measurement results of the parameters have deviation from the actual measurement results under the influence of factors such as a test method, environmental conditions, operation conditions and the like. Therefore, the method for researching the simulation parameter identification of the power system is used for identifying and checking parameters required by simulation, provides simulation accuracy and plays an important role in improving the safety and stability of the power grid.
Because the simulation calculation process of the power system is the solving process of the nonlinear equation, the related parameter quantity is huge, the parameters have mutual coupling relation, and the parameters are difficult to be identified independently, and a model-free identification method is needed to identify the parameters of the power system.
Disclosure of Invention
The present invention is directed to a method for identifying parameters of an electrical simulation model to solve the problems set forth in the background art.
The invention is realized by the following technical scheme: a parameter identification method of a power simulation model comprises the following steps:
s1, establishing a power system simulation model, and setting an initial parameter value of a certain circuit index of the simulation model
Figure BDA0002752594270000011
Setting a simulation threshold delta;
s2, generating a parameter disturbance value delta C (j) And is combined withCalculating the perturbed parameter value
Figure BDA0002752594270000021
And
Figure BDA0002752594270000022
s3, the parameter values are compared
Figure BDA0002752594270000023
And
Figure BDA0002752594270000024
putting the power system into the power system simulation model for calculation to obtain a first simulation value of the line index
Figure BDA0002752594270000025
And a second simulation value
Figure BDA0002752594270000026
S4, based on first simulation value
Figure BDA0002752594270000027
And a second simulation value
Figure BDA0002752594270000028
Calculating an iterative parameter value C (j+1) The iteration parameter value C (j+1) Putting the simulation model into the power system for calculation to obtain a third simulation value delta (j+1) ；
S5, if the third simulation value delta (j+1) If the iteration parameter value C meets the requirement (j+1) Is the final parameter value of the line index.
Preferably, the line indicators include resistance, reactance, and admittance of the line.
Preferably, the theoretical value or the first measured value of the line index is set as an initial parameter value
Figure BDA0002752594270000029
Preferably, any normal number is set as the parameter disturbance value Δ C (j) And a plurality of parameter disturbance values Δ C (j) Independent of each other and in bernoulli distribution.
Preferably, the parameter value
Figure BDA00027525942700000210
The value of the parameter
Figure BDA00027525942700000211
Based on a first simulation value
Figure BDA00027525942700000212
And a second simulation value
Figure BDA00027525942700000213
Calculating iterative parameter value C (j+1) The method comprises the following steps:
calculating a first simulation value
Figure BDA00027525942700000214
And a second simulation value
Figure BDA00027525942700000215
Difference Δ δ therebetween i ；
Calculating an iterative parameter value C by (j+1) ：
Figure BDA00027525942700000216
。
In the formula, mu is a step length coefficient and takes the value of (0, 1).
Preferably, said step S5 includes, if δ (j+1) < delta, the third simulation value delta (j+1) Meets the requirements.
Preferably, the step S5 further comprises, if δ (j+1) When the value is more than or equal to delta, the third simulation value delta (j+1) If the parameter is not qualified, the parameter disturbance value Delta C is regenerated (j) 。
Compared with the prior art, the invention has the following beneficial effects: the parameter identification method of the power simulation model provided by the invention solves the problem that the conventional power system is difficult to independently identify each parameter, and improves the practicability of wide-area power system model parameter identification, thereby having positive effects on improving the simulation analysis precision of the power system and correctly making a power grid construction plan and an operation mode. In addition, the invention can be suitable for various power system simulation software used in the power industry of China at present, thereby having good popularization and application prospects.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only preferred embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a flowchart of a parameter identification method of an electrical simulation model according to the present invention.
Detailed Description
In order to better understand the technical content of the invention, specific embodiments are provided below, and the invention is further described with reference to the accompanying drawings.
Referring to fig. 1, a method for identifying parameters of an electric power simulation model includes the following steps:
s1, establishing a power system simulation model, and setting an initial parameter value of a certain circuit index of the simulation model
Figure BDA0002752594270000031
Setting a simulation threshold delta;
wherein the line index includes resistance, reactance and admittance of the line, and the initial parameter value
Figure BDA0002752594270000032
It may be selected by setting a theoretical or first measured value of the line indicator.
S2, generating a parameter disturbance value delta C (j) And calculating the disturbed parameter value
Figure BDA0002752594270000033
And
Figure BDA0002752594270000034
in the present embodiment, any normal number is set as the parameter disturbance value Δ C (j) The specific setting value can be set according to engineering experience, and the parameter disturbance value delta C (j) The larger the size, the longer the recognition time.
Wherein the parameter value
Figure BDA0002752594270000035
The value of the parameter
Figure BDA0002752594270000036
S3, the parameter values are compared
Figure BDA0002752594270000037
And
Figure BDA0002752594270000038
putting the simulation model into the power system for calculation to obtain a first simulation value of the line index
Figure BDA0002752594270000039
And a second simulation value
Figure BDA00027525942700000310
S4, based on first simulation value
Figure BDA0002752594270000041
And a second simulation value
Figure BDA0002752594270000042
Calculating iterative parameter value C (j+1) The iteration parameter value C (j+1) Putting the simulation model into the power system for calculation to obtain a third simulation value delta (j+1) ；
The specific calculation method is as follows: calculating a first simulation value
Figure BDA0002752594270000043
And a second simulation value
Figure BDA0002752594270000044
Difference Δ δ therebetween i ；
Calculating an iterative parameter value C by (j+1) ：
Figure BDA0002752594270000045
In the formula, mu is a step length coefficient and takes the value of (0, 1).
S5, if δ (j+1) When < delta, the third simulation value delta (j+1) Satisfied, the iteration parameter value C (j+1) Is the final parameter value of the line index.
If delta (j+1) When the value is larger than or equal to delta, the third simulation value delta (j+1) If the parameter is not qualified, the parameter disturbance value Delta C is regenerated (j) 。
It should be noted that the plurality of generated parameter disturbance values Δ C (j) Independent of each other and in bernoulli distribution.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (7)

1. A parameter identification method of a power simulation model is characterized by comprising the following steps:
s1, establishing a power system simulation model, and setting an initial parameter value of a certain circuit index of the simulation model
Figure FDA0003724616240000011
Setting a simulation threshold delta;
s2, generating a parameter disturbance value delta C (j) And calculating the parameter value after disturbance
Figure FDA0003724616240000012
And
Figure FDA0003724616240000013
s3, the parameter values are used
Figure FDA0003724616240000014
And
Figure FDA0003724616240000015
putting the power system into the power system simulation model for calculation to obtain a first simulation value of the line index
Figure FDA0003724616240000016
And a second simulation value
Figure FDA0003724616240000017
S4, based on a first simulation value
Figure FDA0003724616240000018
And a second simulation value
Figure FDA0003724616240000019
Calculating an iterative parameter value C (j+1) The specific calculation method is as follows: calculating a first simulation value
Figure FDA00037246162400000110
And a second simulation value
Figure FDA00037246162400000111
Difference Δ δ therebetween i (ii) a Calculating an iterative parameter value C by (j+1) ：
Figure FDA00037246162400000112
In the formula, mu is a step coefficient, the value is (0, 1), and the iteration parameter value C is (j+1) Putting the power system into the power system simulation model for calculation to obtain a third simulation value delta (j+1) ；
S5, if the third simulation value delta (j+1) If the iteration parameter value C meets the requirement (j+1) Is the final parameter value of the line index.
2. The method of claim 1, wherein the line metrics include resistance, reactance, and admittance of the line.
3. The method of claim 2, wherein the theoretical value or the first measured value of the line index is set as an initial parameter value
Figure FDA00037246162400000113
4. The method of claim 2, wherein any normal constant is set as the parameter disturbance value Δ C (j) And a plurality of parameter perturbation values Δ C (j) Independent of each other and in bernoulli distribution.
5. The method of claim 4, wherein the parameter value is the parameter of the power simulation model
Figure FDA00037246162400000114
The value of the parameter
Figure FDA00037246162400000115
6. The method of claim 5, wherein the step S5 includes determining if δ (j+1) When < delta, the third simulation value delta (j+1) Meets the requirements.
7. The method according to claim 6, wherein the step S5 further comprises determining if δ (j+1) When the value is more than or equal to delta, the third simulation value delta (j+1) If the parameter is not qualified, the parameter disturbance value Delta C is regenerated (j) 。
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103529698A (en) * 2013-10-17 2014-01-22 广东电网公司电力科学研究院 Method for distinguishing parameter of power generator speed regulating system
CN103825521A (en) * 2014-02-25 2014-05-28 河海大学 Method for identifying parameters of double-fed wind turbine generator driving system and generator
CN104199302A (en) * 2014-08-29 2014-12-10 国家电网公司 Molding system and method of pump storage group speed regulating system
CN106599337A (en) * 2016-10-12 2017-04-26 国家电网公司 Power grid frequency simulation parameter identification method based on simplex method
CN106786524A (en) * 2016-12-19 2017-05-31 清华大学 Load model parameters discrimination method based on noise-like signal and improved differential evolution
CN109240124A (en) * 2018-10-31 2019-01-18 海南电网有限责任公司电力科学研究院 A kind of electric power stability control strategy analogue system
CN110516275A (en) * 2019-05-31 2019-11-29 国网辽宁省电力有限公司电力科学研究院 Simulation parameters check method based on disturbance information
CN110555262A (en) * 2019-08-29 2019-12-10 国家电网公司华东分部 Synchronous generator parameter identification method

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10809683B2 (en) * 2017-10-26 2020-10-20 General Electric Company Power system model parameter conditioning tool

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103529698A (en) * 2013-10-17 2014-01-22 广东电网公司电力科学研究院 Method for distinguishing parameter of power generator speed regulating system
CN103825521A (en) * 2014-02-25 2014-05-28 河海大学 Method for identifying parameters of double-fed wind turbine generator driving system and generator
CN104199302A (en) * 2014-08-29 2014-12-10 国家电网公司 Molding system and method of pump storage group speed regulating system
WO2016029694A1 (en) * 2014-08-29 2016-03-03 国家电网公司 Modeling system and method for pumped-storage unit speed regulating system
CN106599337A (en) * 2016-10-12 2017-04-26 国家电网公司 Power grid frequency simulation parameter identification method based on simplex method
CN106786524A (en) * 2016-12-19 2017-05-31 清华大学 Load model parameters discrimination method based on noise-like signal and improved differential evolution
CN109240124A (en) * 2018-10-31 2019-01-18 海南电网有限责任公司电力科学研究院 A kind of electric power stability control strategy analogue system
CN110516275A (en) * 2019-05-31 2019-11-29 国网辽宁省电力有限公司电力科学研究院 Simulation parameters check method based on disturbance information
CN110555262A (en) * 2019-08-29 2019-12-10 国家电网公司华东分部 Synchronous generator parameter identification method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
基于似然剖面的元件模型暂态参数可辨识性分析;陈润泽等;《中国电机工程学报》;20150320(第06期);58-66 *
基于故障录波器的机组参数辨识;林济铿等;《电力自动化设备》;20120810(第08期);31-38 *
基于混沌粒子群算法的水轮机调速系统参数辨识及建模试验;冯雁敏等;《长江科学院院报》;20160809(第08期);141-146+153 *

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