CN108089095B - Power grid low-frequency oscillation parameter prediction method and device - Google Patents
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Abstract
The invention discloses a method and a device for predicting low-frequency oscillation parameters of a power grid, and solves the technical problems that in the prior art, based on the fact that analysis and identification application of a scheduling master station to low-frequency oscillation of the power grid is not mature, a detection method and a detection means which are effective and reliable for the analysis function of the low-frequency oscillation of the power grid of the scheduling master station are lacked, a case base for analyzing and comparing low-frequency oscillation characteristic parameters is an effective and reliable detection means for the analysis function of the low-frequency oscillation, and the construction of a typical case base for the low-frequency oscillation of the power grid depends on the analysis and prediction of typical oscillation parameters, so that a method for predicting the low-frequency oscillation parameters of.
Description
Technical Field
The invention relates to the technical field of power grid analysis and test, in particular to a method and a device for predicting low-frequency oscillation parameters of a power grid.
Background
Low frequency oscillations are power swings on the tie-line after the power system suffers disturbances, and system dynamic instability is caused by divergent oscillations after disturbances due to insufficient damping or even negative damping. At present, based on the fact that analysis and identification application of a scheduling master station to power grid low-frequency oscillation is not mature, an effective and reliable detection method and means for a power grid low-frequency oscillation analysis function of the scheduling master station are lacked, a case base for analyzing and comparing low-frequency oscillation characteristic parameters is an effective and reliable detection means for the low-frequency oscillation analysis function, and construction of a typical case base for the power grid low-frequency oscillation depends on analysis and prediction of typical oscillation parameters, so that the establishment of a prediction method for the power grid low-frequency oscillation parameters is a technical problem to be solved by technical personnel in the field.
Disclosure of Invention
The invention provides a power grid low-frequency oscillation parameter prediction method and a power grid low-frequency oscillation parameter prediction device, which are used for solving the technical problems that in the prior art, based on the fact that analysis and identification application of a scheduling master station to power grid low-frequency oscillation is not mature, a detection method and a detection means which are effective and reliable to a power grid low-frequency oscillation analysis function of the scheduling master station are lacked, a case base for analyzing and comparing low-frequency oscillation characteristic parameters is an effective and reliable detection means for the low-frequency oscillation analysis function, and the construction of a typical case base for power grid low-frequency oscillation depends on analysis and prediction of typical oscillation parameters, so that a prediction method for the power grid low-frequency oscillation parameters needs to be.
The invention provides a power grid low-frequency oscillation parameter prediction method, which comprises the following steps:
constructing a power grid model according to preset topological structure information, network parameter information, element information and measurement configuration information, wherein the power grid model specifically comprises the following steps: a 2-region 4-machine system model and a 10-machine 39-node system model;
adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode;
acquiring power grid low-frequency oscillation mode data in the power grid model;
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation mode data, wherein the prediction parameter expression is in a form of sum of a real part and an imaginary part;
sampling the power grid low-frequency oscillation mode data at equal intervals to obtain sampling results, obtaining a corresponding linear matrix equation according to the sampling results, and solving a characteristic root of the linear matrix equation;
and calculating an estimated value of the low-frequency oscillation mode parameters according to the characteristic root, wherein the estimated value of the low-frequency oscillation mode parameters comprises an amplitude estimated value, an initial phase estimated value, a damping coefficient estimated value and a frequency estimated value.
Preferably, a suitable prediction parameter expression is determined by a Prony algorithm according to the power grid low-frequency oscillation mode data, and the prediction parameter expression is in a form of the sum of a real part and an imaginary part and specifically comprises the following steps:
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation modal data, wherein the power grid low-frequency oscillation modal data are as follows:
wherein m is the number of low-frequency oscillation modes of the power grid, AiTo amplitude of oscillation, σiTo the oscillation phase, fiIn order to be able to oscillate the frequency,
is a damping coefficient;
the prediction parameter expression is as follows:
wherein,
wherein denotes a complex conjugate.
Preferably, the low-frequency oscillation mode is specifically: local oscillation mode, interval oscillation mode and undamped constant amplitude oscillation mode.
Preferably, the power grid low-frequency oscillation mode data includes: the generator rotor position angle, the generator active power, the generator positive sequence voltage, the line active power, the load active power, the node voltage amplitude and the node voltage phase angle respectively correspond to the local oscillation mode, the interval oscillation mode and the non-attenuation constant amplitude oscillation mode.
The invention provides a device for predicting low-frequency oscillation parameters of a power grid, which comprises:
the first building module is used for building a power grid model according to preset topological structure information, network parameter information, element information and measurement configuration information, wherein the power grid model specifically comprises the following components: a 2-region 4-machine system model and a 10-machine 39-node system model;
the first adding module is used for adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode;
the first acquisition module is used for acquiring the low-frequency oscillation modal data of the power grid in the power grid model;
the first determination module is used for determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation mode data, wherein the prediction parameter expression is in a form of the sum of a real part and an imaginary part;
the first calculation module is used for sampling the power grid low-frequency oscillation modal data at equal intervals to obtain a sampling result, obtaining a corresponding linear matrix equation according to the sampling result and solving a characteristic root of the linear matrix equation;
and the second calculation module is used for solving the estimation value of the low-frequency oscillation modal parameter according to the characteristic root, wherein the estimation value of the low-frequency oscillation modal parameter comprises an amplitude estimation value, an initial phase estimation value, a damping coefficient estimation value and a frequency estimation value.
Preferably, the first determining module is specifically configured to:
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation modal data, wherein the power grid low-frequency oscillation modal data are as follows:
wherein m is the number of low-frequency oscillation modes of the power grid, AiTo amplitude of oscillation, σiTo the oscillation phase, fiIn order to be able to oscillate the frequency,
is a damping coefficient;
the prediction parameter expression is as follows:
wherein,
wherein denotes a complex conjugate.
Preferably, the first adding module is specifically configured to:
adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode, wherein the low-frequency oscillation mode specifically comprises the following steps: local oscillation mode, interval oscillation mode and undamped constant amplitude oscillation mode.
Preferably, the first obtaining module is specifically configured to:
acquiring power grid low-frequency oscillation mode data in the power grid model, wherein the power grid low-frequency oscillation mode data comprises: the generator rotor position angle, the generator active power, the generator positive sequence voltage, the line active power, the load active power, the node voltage amplitude and the node voltage phase angle respectively correspond to the local oscillation mode, the interval oscillation mode and the non-attenuation constant amplitude oscillation mode.
According to the technical scheme, the invention has the following advantages:
the invention provides a method for setting operation constraint of a power distribution network containing a distributed power supply, which comprises the following steps: constructing a power grid model according to preset topological structure information, network parameter information, element information and measurement configuration information, wherein the power grid model specifically comprises the following steps: a 2-region 4-machine system model and a 10-machine 39-node system model; adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode; acquiring power grid low-frequency oscillation mode data in the power grid model; determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation mode data, wherein the prediction parameter expression is in a form of sum of a real part and an imaginary part; sampling the power grid low-frequency oscillation mode data at equal intervals to obtain sampling results, obtaining a corresponding linear matrix equation according to the sampling results, and solving a characteristic root of the linear matrix equation; and calculating an estimated value of the low-frequency oscillation mode parameters according to the characteristic root, wherein the estimated value of the low-frequency oscillation mode parameters comprises an amplitude estimated value, an initial phase estimated value, a damping coefficient estimated value and a frequency estimated value.
In the invention, disturbance is added to a power grid model to generate a low-frequency oscillation mode, a proper prediction parameter expression is determined by adopting a Prony algorithm for power grid low-frequency oscillation mode data, and a corresponding linear matrix equation is solved to obtain an estimated value, so that the technical problems that in the prior art, analysis and identification application of power grid low-frequency oscillation based on a scheduling master station is not mature, an effective and reliable detection method and means for a power grid low-frequency oscillation analysis function of the scheduling master station are lacked, a case library for analyzing and comparing low-frequency oscillation characteristic parameters is an effective and reliable detection means for the low-frequency oscillation analysis function, and the construction of the typical case library for the power grid low-frequency oscillation depends on analysis and prediction of typical oscillation parameters, so that a prediction method for the power grid low-frequency oscillation parameters needs to be established are solved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of an embodiment of a method for predicting a low-frequency oscillation parameter of a power grid according to the present invention;
fig. 2 is a schematic structural diagram of an embodiment of a power grid low-frequency oscillation parameter prediction apparatus provided by the present invention.
Detailed Description
The embodiment of the invention provides a power grid low-frequency oscillation parameter prediction method and a power grid low-frequency oscillation parameter prediction device, and solves the technical problems that in the prior art, based on the fact that analysis and identification application of a scheduling master station to power grid low-frequency oscillation is not mature, a detection method and a detection means which are effective and reliable to a power grid low-frequency oscillation analysis function of the scheduling master station are lacked, a case base for analyzing and comparing low-frequency oscillation characteristic parameters is an effective and reliable detection means for the low-frequency oscillation analysis function, and construction of a typical case base for power grid low-frequency oscillation depends on analysis and prediction of typical oscillation parameters, so that a power grid low-frequency oscillation parameter prediction method needs to be established.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides an embodiment of a method for predicting a low-frequency oscillation parameter of a power grid, including:
101: constructing a power grid model according to preset topological structure information, network parameter information, element information and measurement configuration information, wherein the power grid model specifically comprises the following steps: a 2-region 4-machine system model and a 10-machine 39-node system model;
102: adding disturbance to a generator, a line and a load in a power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode;
103: acquiring power grid low-frequency oscillation mode data in a power grid model;
it should be noted that, based on the selected power grid model, adding disturbance to the source end (generator), line, and load, respectively, exciting a low-frequency oscillation mode, and collecting corresponding operation data according to a simulation time sequence, includes:
1) corresponding parameter data of the generator: rotor position angle, active power, positive sequence voltage relative to a reference motor angle;
2) corresponding parameter data of the line: active power;
3) corresponding parameter data of the load: active power;
4) respective parameter data of the node: voltage amplitude, voltage phase angle;
104: determining a proper prediction parameter expression by adopting a Prony algorithm according to the low-frequency oscillation mode data of the power grid, wherein the prediction parameter expression is in the form of the sum of a real part and an imaginary part;
105: sampling the low-frequency oscillation mode data of the power grid at equal intervals to obtain a sampling result, obtaining a corresponding linear matrix equation according to the sampling result and solving a characteristic root of the linear matrix equation;
it should be noted that the characteristic root of the linear matrix equation can be obtained as follows:
and (3) performing N times of equal interval sampling on the output y (t), wherein the sampling interval is delta t, and at the time t being k, the Prony estimated value of the output signal is as follows:
definition of zi＝exp(λiΔ t), has
Written in matrix form, as shown in the following formula:
the first equation of the matrix equation may be multiplied on both sides by- αpThe second equation is multiplied by- αp-1By analogy, the p-th equation is multiplied by- α1The (p + 1) th equation is multiplied by 1, and these equations are added to obtain the formula (1):
let zi(i ═ 1,2, …, p) is the root of a polynomial of order p, which is shown in formula (2):
π(z)＝(z-z1)(z-z2)…(z-zp)＝zp-α1zp-1-…-αp-1z-αp＝0；(2)
formula (2) may be simplified to y (p) α1y(p-1)+α2y(p-2)+…+αpy (0), repeating the above process to obtain a p-order linear equation system, and writing the p-order linear equation system into a matrix form as shown in formula (3):
if N is 2p +1, the matrix equation can be directly solved, and if N is greater than 2p +1, the matrix equation can be solved through a least square method to obtain a characteristic root of pi (z);
106: according to the characteristic root, calculating an estimated value of the low-frequency oscillation mode parameter, wherein the estimated value of the low-frequency oscillation mode parameter comprises an amplitude estimated value, an initial phase estimated value, a damping coefficient estimated value and a frequency estimated value;
z is obtained by pi (z)iThen b can be obtainediThe value of (c).
On the basis of the above, the amplitude A is calculated respectivelyiPhase of
Damping coefficient sigmaiAnd frequency fiEstimated value of (a):
Ai＝|bi|
σi＝ln|zi|/Δt
fi＝arctan(Im(zi)/Re(zi))/2πΔt。
in the embodiment of the invention, disturbance is added to a power grid model to generate a low-frequency oscillation mode, a proper prediction parameter expression is determined for power grid low-frequency oscillation mode data by adopting a Prony algorithm, and a corresponding linear matrix equation is solved to obtain an estimated value, so that the technical problems that in the prior art, the analysis and identification application of a scheduling master station to power grid low-frequency oscillation is not mature, an effective and reliable detection method and means for a power grid low-frequency oscillation analysis function of the scheduling master station are lacked, the construction of a case base for analyzing and comparing low-frequency oscillation characteristic parameters is an effective and reliable detection means for the low-frequency oscillation analysis function, and the construction of a typical case base for power grid low-frequency oscillation depends on the analysis and prediction of typical oscillation parameters, so that a prediction method for power grid low-frequency oscillation parameters needs to be established are.
The above is a description of an embodiment of a power grid low-frequency oscillation parameter prediction method, and an embodiment of a power grid low-frequency oscillation parameter prediction device will be described below.
Referring to fig. 2, an embodiment of a device for predicting low-frequency oscillation parameters of a power grid according to the present invention includes:
the first building module 201 is configured to build a power grid model according to preset topology structure information, network parameter information, element information, and measurement configuration information, where the power grid model specifically includes: a 2-region 4-machine system model and a 10-machine 39-node system model;
the first adding module 202 is configured to add disturbance to a generator, a line, and a load in the power grid model, respectively, so that the power grid model generates a low-frequency oscillation mode, where the low-frequency oscillation mode specifically is: a local oscillation mode, an interval oscillation mode and a non-attenuation constant amplitude oscillation mode;
the first obtaining module 203 is configured to obtain power grid low-frequency oscillation mode data in a power grid model, where the power grid low-frequency oscillation mode data includes: the generator rotor position angle, the generator active power, the generator positive sequence voltage, the line active power, the load active power, the node voltage amplitude and the node voltage phase angle respectively correspond to a local oscillation mode, an interval oscillation mode and a non-attenuation constant amplitude oscillation mode;
the first determining module 204 is configured to determine a suitable prediction parameter expression by using a Prony algorithm according to the power grid low-frequency oscillation modal data, where the power grid low-frequency oscillation modal data is:
wherein m is the number of low-frequency oscillation modes of the power grid, AiTo amplitude of oscillation, σiTo the oscillation phase, fiIn order to be able to oscillate the frequency,
is a damping coefficient;
the prediction parameter expression is:
wherein,
wherein denotes a complex conjugate;
the first calculation module 205 is configured to sample the power grid low-frequency oscillation modal data at equal intervals to obtain a sampling result, obtain a corresponding linear matrix equation according to the sampling result, and solve a characteristic root of the linear matrix equation;
and a second calculating module 206, configured to calculate an estimated value of the low-frequency oscillation mode parameter according to the feature root, where the estimated value of the low-frequency oscillation mode parameter includes an amplitude estimated value, an initial phase estimated value, a damping coefficient estimated value, and a frequency estimated value.
The specific implementation in this embodiment has been described in the above embodiments, and is not described here again.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the system and the module described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed modules and methods may be implemented in other ways. For example, the above-described module embodiments are merely illustrative, and for example, the division of the module is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (2)
1. A power grid low-frequency oscillation parameter prediction method is characterized by comprising the following steps:
constructing a power grid model according to preset topological structure information, network parameter information, element information and measurement configuration information, wherein the power grid model specifically comprises the following steps: a 2-region 4-machine system model and a 10-machine 39-node system model;
adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode;
acquiring power grid low-frequency oscillation mode data in the power grid model;
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation mode data, wherein the prediction parameter expression is in a form of sum of a real part and an imaginary part;
sampling the power grid low-frequency oscillation mode data at equal intervals to obtain sampling results, obtaining a corresponding linear matrix equation according to the sampling results, and solving a characteristic root of the linear matrix equation;
according to the characteristic root, calculating an estimated value of the low-frequency oscillation mode parameter, wherein the estimated value of the low-frequency oscillation mode parameter comprises an amplitude estimated value, an initial phase estimated value, a damping coefficient estimated value and a frequency estimated value;
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation mode data, wherein the prediction parameter expression is in a form of the sum of a real part and an imaginary part and specifically comprises the following steps:
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation modal data, wherein the power grid low-frequency oscillation modal data are as follows:
wherein m is the number of low-frequency oscillation modes of the power grid, AiTo amplitude of oscillation, σiTo the oscillation phase, fiIn order to be able to oscillate the frequency,
is a damping coefficient;
the prediction parameter expression is as follows:
wherein,
wherein denotes a complex conjugate;
the low-frequency oscillation mode specifically comprises the following steps: a local oscillation mode, an interval oscillation mode and a non-attenuation constant amplitude oscillation mode;
wherein the power grid low-frequency oscillation mode data comprises: the generator rotor position angle, the generator active power, the generator positive sequence voltage, the line active power, the load active power, the node voltage amplitude and the node voltage phase angle respectively correspond to the local oscillation mode, the interval oscillation mode and the non-attenuation constant amplitude oscillation mode.
2. A power grid low-frequency oscillation parameter prediction device is characterized by comprising:
the first building module is used for building a power grid model according to preset topological structure information, network parameter information, element information and measurement configuration information, wherein the power grid model specifically comprises the following components: a 2-region 4-machine system model and a 10-machine 39-node system model;
the first adding module is used for adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode;
the first acquisition module is used for acquiring the low-frequency oscillation modal data of the power grid in the power grid model;
the first determination module is used for determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation mode data, wherein the prediction parameter expression is in a form of the sum of a real part and an imaginary part;
the first calculation module is used for sampling the power grid low-frequency oscillation modal data at equal intervals to obtain a sampling result, obtaining a corresponding linear matrix equation according to the sampling result and solving a characteristic root of the linear matrix equation;
the second calculation module is used for solving the estimation value of the low-frequency oscillation modal parameter according to the characteristic root, wherein the estimation value of the low-frequency oscillation modal parameter comprises an amplitude estimation value, an initial phase estimation value, a damping coefficient estimation value and a frequency estimation value;
wherein the first determining module is specifically configured to:
determining a proper prediction parameter expression by adopting a Prony algorithm according to the power grid low-frequency oscillation modal data, wherein the power grid low-frequency oscillation modal data are as follows:
wherein m is the number of low-frequency oscillation modes of the power grid, AiTo amplitude of oscillation, σiTo the oscillation phase, fiIn order to be able to oscillate the frequency,
is a damping coefficient;
the prediction parameter expression is as follows:
wherein,
wherein denotes a complex conjugate;
wherein the first adding module is specifically configured to:
adding disturbance to a generator, a line and a load in the power grid model respectively to enable the power grid model to generate a low-frequency oscillation mode, wherein the low-frequency oscillation mode specifically comprises the following steps: a local oscillation mode, an interval oscillation mode and a non-attenuation constant amplitude oscillation mode;
the first obtaining module is specifically configured to:
acquiring power grid low-frequency oscillation mode data in the power grid model, wherein the power grid low-frequency oscillation mode data comprises: the generator rotor position angle, the generator active power, the generator positive sequence voltage, the line active power, the load active power, the node voltage amplitude and the node voltage phase angle respectively correspond to the local oscillation mode, the interval oscillation mode and the non-attenuation constant amplitude oscillation mode.
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| CN106571638A (en) * | 2016-11-10 | 2017-04-19 | 南京南瑞集团公司 | Method for judging type of low-frequency oscillation |
| CN106849131A (en) * | 2017-04-01 | 2017-06-13 | 福州大学 | A kind of low-frequency oscillation modal identification method based on quadravalence mixing average accumulated amount with improvement TLS ESPRIT algorithms |
| CN107681658A (en) * | 2017-09-30 | 2018-02-09 | 广东电网有限责任公司电力科学研究院 | A kind of electricity grid oscillating analysis test method and system towards scheduling station |
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