CN108089095A - A kind of electricity grid oscillating parameter prediction method and device - Google Patents
A kind of electricity grid oscillating parameter prediction method and device Download PDFInfo
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Abstract
The invention discloses a kind of electricity grid oscillating parameter prediction method and devices, it solves in the prior art, it is still immature to the analysis and identification application of electricity grid oscillating based on scheduling station, lack to the effectively reliable detection method of the electricity grid oscillating analytic function of scheduling station and means, the case library for building to analyze and compare the Characteristics of Low Frequency Oscillations parameter is to the effectively reliable detection means of Low Frequency Oscillation Analysis function, the analysis and prediction of typical oscillatory parameter are depended on for the structure in electricity grid oscillating typical case storehouse, therefore, the technical issues of needing to establish a kind of Forecasting Methodology of electricity grid oscillating parameter.
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 established.
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, A i To amplitude of oscillation, σ i To the oscillation phase, f i In order to be able to oscillate the frequency,is a damping coefficient;
the prediction parameter expression is as follows:
wherein the content of the first and second substances,
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-zone 4-machine system model and a 10-machine 39-node system model;
the first adding module is used for respectively adding disturbance to a generator, a line and a load in the power grid model so as to enable the power grid model to generate a low-frequency oscillation mode;
the first acquisition module acquires power grid low-frequency oscillation modal data 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, A i To amplitude of oscillation, σ i To the oscillation phase, f i In order to be able to oscillate the frequency,is a damping coefficient;
the prediction parameter expression is as follows:
wherein the content of the first and second substances,
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.
Drawings
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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to 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: disturbance is added 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;
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 relative to a reference motor angle, active power, positive sequence voltage;
2) Respective 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 a form of the sum of a real part and an imaginary part;
105: 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;
it should be noted that the characteristic root of the linear matrix equation can be obtained as follows:
and N times of equal interval sampling are carried out on the output y (t), the sampling interval is delta t, and at the time t = k, the Prony estimated value of the output signal is as follows:
definition of z i ＝exp(λ i Δ t), has
Written in matrix form, as shown in the following formula:
the first equation of the matrix equation can be multiplied by-alpha on both sides p The second equation is multiplied by- α p-1 By analogy, the p-th equation is multiplied by- α 1 The (p + 1) th equation is multiplied by 1, and these equations are added to obtain the formula (1):
let z i (i =1,2, \8230;, p) is the root of a polynomial of order p, which is shown in particular in formula (2):
π(z)＝(z-z 1 )(z-z 2 )…(z-z p )＝z p -α 1 z p-1 -…-α p-1 z-α p ＝0；(2)
the formula (2) can be simplified to y (p) = α 1 y(p-1)+α 2 y(p-2)+…+α p y (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 =2p +1, the matrix equation can be directly solved, and if N >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) i Then b can be obtained i The value of (c).
On the basis of the above, the amplitude A is calculated respectively i Phase of the magnetic fluxDamping coefficient sigma i And frequency f i The estimated value of (c):
A i ＝|b i |
σ i ＝ln|z i |/Δt
f i ＝arctan(Im(z i )/Re(z i ))/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 solved.
The above is a description of an embodiment of a method for predicting low-frequency oscillation parameters of a power grid, and an embodiment of a device for predicting low-frequency oscillation parameters of a power grid 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 the local oscillation mode, the interval oscillation mode and the undamped 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 are:
wherein m is the number of low-frequency oscillation modes of the power grid, A i To amplitude of oscillation, σ i To oscillate phase, f i In order to be able to oscillate the frequency,is a damping coefficient;
the prediction parameter expression is:
wherein, the first and the second end of the pipe are connected with each other,
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 embodiment, and is not described herein 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 module 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 (8)
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;
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.
2. The power grid low-frequency oscillation parameter prediction method according to claim 1, wherein a suitable prediction parameter expression is determined by a Prony algorithm according to the power grid low-frequency oscillation modal data, and the prediction parameter expression is in a form of a sum of a real part and an imaginary part and specifically comprises:
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, A i To amplitude of oscillation, σ i To oscillate phase, f i In order to be able to oscillate the frequency,is a damping coefficient;
the prediction parameter expression is as follows:
wherein, the first and the second end of the pipe are connected with each other,λ i ＝σ i +jω i ,ω i ＝2πf i ；
wherein denotes a complex conjugate.
3. The power grid low-frequency oscillation parameter prediction method according to claim 2, wherein the low-frequency oscillation mode is specifically: local oscillation mode, interval oscillation mode and undamped constant amplitude oscillation mode.
4. The power grid low-frequency oscillation parameter prediction method of claim 3, 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.
5. 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 respectively adding disturbance to a generator, a line and a load in the power grid model so as to enable the power grid model to generate a low-frequency oscillation mode;
the first acquisition module acquires power grid low-frequency oscillation modal data 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.
6. The grid low-frequency oscillation parameter prediction device according to claim 5, wherein the first determination 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, A i To amplitude of oscillation, σ i To oscillate phase, f i In order to be able to oscillate the frequency,is a damping coefficient;
the prediction parameter expression is as follows:
wherein the content of the first and second substances,λ i ＝σ i +jω i ,ω i ＝2πf i ；
where denotes a complex conjugate.
7. The grid low-frequency oscillation parameter prediction device according to claim 6, 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: local oscillation mode, interval oscillation mode and undamped constant amplitude oscillation mode.
8. The grid low-frequency oscillation parameter prediction device according to claim 7, wherein 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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| CN109524972B (en) * | 2018-10-10 | 2022-03-29 | 华南理工大学 | Low-frequency oscillation parameter estimation method based on GSO and SVM algorithms |
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| CN110927442B (en) * | 2019-12-06 | 2021-11-02 | 云南电网有限责任公司 | Multimode oscillation on-line monitoring and early warning system based on edge calculation |
| CN113569464A (en) * | 2021-06-21 | 2021-10-29 | 国网山东省电力公司电力科学研究院 | Wind turbine generator oscillation mode prediction method and device based on deep learning network and multi-task learning strategy |
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