CN108256465A - Electrical energy power quality disturbance event recognition method and device - Google Patents

Electrical energy power quality disturbance event recognition method and device Download PDF

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Publication number
CN108256465A
CN108256465A CN201810029546.8A CN201810029546A CN108256465A CN 108256465 A CN108256465 A CN 108256465A CN 201810029546 A CN201810029546 A CN 201810029546A CN 108256465 A CN108256465 A CN 108256465A
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disturbance
waveform section
phase
parameter
residual
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牛益国
李岩峰
崔志强
董紫辉
于惠慧
秦励寒
项秉元
何淼
张海霞
黄立昕
李晓松
宣文华
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State Grid Corp of China SGCC
Qinhuangdao Power Supply Co of State Grid Jibei Electric Power Co Ltd
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State Grid Corp of China SGCC
Qinhuangdao Power Supply Co of State Grid Jibei Electric Power Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08Feature extraction
    • G06F2218/10Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12Classification; Matching
    • G06F2218/16Classification; Matching by matching signal segments

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  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Artificial Intelligence (AREA)
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  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
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Abstract

The present invention provides a kind of electrical energy power quality disturbance event recognition method and devices, are related to electric energy detection technical field.The electrical energy power quality disturbance event recognition method includes:To the electrical energy power quality disturbance time series phase space reconstruction of the sampled signal of power quality, so as to obtain phase space reconfiguration as a result, phase space reconfiguration result includes phase path and phase point;The normal waveform section and disturbance waveform section in the waveform of sampled signal are obtained based on phase path and phase point;Based on normal waveform section and disturbance waveform section, the 1st grade of residual component of the disturbance waveform section after disturbance waveform section removal fundametal compoment is obtained;To the perturbation features parameter to be identified of the 1st grade of residual component extraction disturbance component of disturbance waveform section;Relationship based on pre-stored perturbation features parameter Yu disturbance event type obtains the corresponding disturbance event type of perturbation features parameter to be identified.The electrical energy power quality disturbance event recognition method can realize the acquisition for disturbing type in electric power signal.

Description

Electrical energy power quality disturbance event recognition method and device
Technical field
The present invention relates to electric energy detection technical field, in particular to a kind of electrical energy power quality disturbance event recognition method And device.
Background technology
With the large-scale use of various non-linear power electronic equipments and sensitive load in modern industry and micro- electricity The generation of the various electric power access ways such as net, distributed generation resource so that power quality problem becomes increasingly conspicuous in modern power systems. It is the key that improve power grid power quality that a large amount of power quality disturbance datas of power network monitoring, which effectively analyze and handle,. Appropriate the decompositing of complicated disturbing signal ingredient that these are only represented to different event process comes, could be to included in it Elementary event is preferably analyzed.
Invention content
In view of this, an embodiment of the present invention provides a kind of electrical energy power quality disturbance event recognition method and devices.
To achieve these goals, technical solution used in the embodiment of the present invention is as follows:
In a first aspect, an embodiment of the present invention provides a kind of electrical energy power quality disturbance event recognition method, the method includes: To the electrical energy power quality disturbance time series phase space reconstruction of the sampled signal of power quality, so as to obtaining phase space reconfiguration as a result, The phase space reconfiguration result includes phase path and phase point;The sampling letter is obtained based on the phase path and the phase point Number waveform in normal waveform section and disturbance waveform section;Based on the normal waveform section and the disturbance waveform Section obtains the 1st grade of residual component of the disturbance waveform section after the disturbance waveform section removal fundametal compoment;To institute State the perturbation features parameter to be identified of the 1st grade of residual component extraction disturbance component of disturbance waveform section;Based on pre-stored The relationship of perturbation features parameter and disturbance event type obtains the corresponding disturbance event class of the perturbation features parameter to be identified Type.
Second aspect, an embodiment of the present invention provides a kind of electrical energy power quality disturbance event recognition device, described device includes: Phase space reconfiguration module, waveform segments module, residual error acquisition module, parameter extraction module and disturbed depth module, wherein, institute Electrical energy power quality disturbance time series phase space reconstruction of the phase space reconfiguration module for the sampled signal to power quality is stated, so as to Phase space reconfiguration is obtained as a result, the phase space reconfiguration result includes phase path and phase point;The waveform segments module is used for The normal waveform section and disturbance waveform in the waveform of the sampled signal are obtained based on the phase path and the phase point Section;The residual error acquisition module is used to be based on the normal waveform section and the disturbance waveform section, is disturbed described in acquisition 1st grade of residual component of the disturbance waveform section after dynamic undulating segment removal fundametal compoment;The parameter extraction module is used In the perturbation features parameter to be identified of the 1st grade of residual component extraction disturbance component to the disturbance waveform section;The disturbance Identification module is used for the relationship based on pre-stored perturbation features parameter Yu disturbance event type, obtains the disturbance to be identified The corresponding disturbance event type of characteristic parameter.
Electrical energy power quality disturbance event recognition method and device provided in an embodiment of the present invention, pass through the sampling to power quality The electrical energy power quality disturbance time series phase space reconstruction of signal, so as to obtain phase space reconfiguration as a result, phase space reconfiguration result packet Phase path and phase point are included, then the normal waveform section in the waveform of sampled signal is obtained based on phase path and phase point and is disturbed Dynamic undulating segment then based on normal waveform section and disturbance waveform section, obtains disturbance waveform section removal fundametal compoment Then 1st grade of residual component of disturbance waveform section afterwards extracts disturbance component to the 1st grade of residual component of disturbance waveform section Perturbation features parameter to be identified, be finally based on the relationship of pre-stored perturbation features parameter and disturbance event type, obtain The corresponding disturbance event type of perturbation features parameter to be identified.The electrical energy power quality disturbance event recognition method and device are disturbed in acquisition Phase space reconstruction technique is utilized during dynamic event type, so as to excavate the potential characteristic information of signal, makes to obtain The perturbation features parameter taken is more abundant, and according to perturbation features gain of parameter disturbance event type, for administer disturbance provide according to According to.
For the above objects, features and advantages of the present invention is enable to be clearer and more comprehensible, preferred embodiment cited below particularly, and coordinate Appended attached drawing, is described in detail below.
Description of the drawings
Purpose, technical scheme and advantage to make the embodiment of the present invention are clearer, below in conjunction with the embodiment of the present invention In attached drawing, the technical solution in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is Part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art All other embodiments obtained without making creative work shall fall within the protection scope of the present invention.
Fig. 1 shows the block diagram of electronic equipment provided in an embodiment of the present invention;
Fig. 2 shows the flow charts of electrical energy power quality disturbance event recognition method provided in an embodiment of the present invention;
Fig. 3 shows the flow of step S110 in electrical energy power quality disturbance event recognition method provided in an embodiment of the present invention Figure;
Fig. 4 shows the module map of electrical energy power quality disturbance event recognition device provided in an embodiment of the present invention.
Specific embodiment
Below in conjunction with attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete Ground describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.Usually exist The component of the embodiment of the present invention described and illustrated in attached drawing can be configured to arrange and design with a variety of different herein.Cause This, the detailed description of the embodiment of the present invention to providing in the accompanying drawings is not intended to limit claimed invention below Range, but it is merely representative of the selected embodiment of the present invention.Based on the embodiment of the present invention, those skilled in the art are not doing Go out all other embodiments obtained under the premise of creative work, shall fall within the protection scope of the present invention.
It should be noted that:Similar label and letter represents similar terms in following attached drawing, therefore, once a certain Xiang Yi It is defined in a attached drawing, does not then need to that it is further defined and explained in subsequent attached drawing.Meanwhile the present invention's In description, term " first ", " second " etc. are only used for distinguishing description, and it is not intended that instruction or hint relative importance.
Fig. 1 shows a kind of structure diagram that can be applied to the electronic equipment in the embodiment of the present invention.It is as shown in Figure 1, electric Sub- equipment 100 includes memory 102, storage control 104, one or more (one is only shown in figure) processors 106, peripheral hardware Interface 108, radio-frequency module 110, audio-frequency module 112, display unit 114 etc..These components by one or more communication bus/ Signal wire 116 mutually communicates.
Memory 102 can be used for storage software program and module, such as the electrical energy power quality disturbance thing in the embodiment of the present invention Part recognition methods and the corresponding program instruction/module of device, processor 106 are stored in the software in memory 102 by operation Program and module, so as to perform various functions application and data processing, such as power quality provided in an embodiment of the present invention is disturbed Dynamic event recognition method.
Memory 102 may include high speed random access memory, may also include nonvolatile memory, such as one or more magnetic Property storage device, flash memory or other non-volatile solid state memories.Processor 106 and other possible components are to storage The access of device 102 can carry out under the control of storage control 104.
Various input/output devices are coupled to processor 106 and memory 102 by Peripheral Interface 108.In some implementations In example, Peripheral Interface 108, processor 106 and storage control 104 can be realized in one single chip.In some other reality In example, they can be realized by independent chip respectively.
Radio-frequency module 110 is used to receive and transmit electromagnetic wave, realizes the mutual conversion of electromagnetic wave and electric signal, thus with Communication network or other equipment are communicated.
Audio-frequency module 112 provides a user audio interface, may include that one or more microphones, one or more raises Sound device and voicefrequency circuit.
Display unit 114 provides a display interface between electronic equipment 100 and user.Specifically, display unit 114 Video output is shown to user, and the content of these videos output may include word, figure, video and its arbitrary combination.
It is appreciated that structure shown in FIG. 1 is only to illustrate, electronic equipment 100 may also include it is more than shown in Fig. 1 or Less component or with the configuration different from shown in Fig. 1.Each component shown in Fig. 1 may be used hardware, software or its Combination is realized.
First embodiment
The flow chart of electrical energy power quality disturbance event recognition method provided in an embodiment of the present invention as shown in Figure 2.It refers to Fig. 2, this method include:
Step S110:To the electrical energy power quality disturbance time series phase space reconstruction of the sampled signal of power quality, so as to obtain Phase space reconfiguration is obtained as a result, the phase space reconfiguration result includes phase path and phase point.
When electrical energy power quality disturbance event is identified, the sampled signal of power quality, electric energy matter can be obtained first The sampled signal of amount can be monitored by monitoring device and be obtained.Wherein, the sampled signal of power quality is standard sine signal.
After the sampled signal for obtaining power quality, the electrical energy power quality disturbance sample sequence of sampled signal can be extracted, so Phase space is constructed using State Space Reconstruction afterwards, so that during subsequent extracted perturbation features parameter, abundant disturbance can be obtained Characteristic parameter.
In embodiments of the present invention, Fig. 3 is referred to, step S110 can include:
Step S111:Best Times delay parameter is determined based on mutual information function method.
In embodiments of the present invention, mutual information function can be utilized to send the optimal delay in determining phase space reconfiguration to join Number.Specifically, determining Best Times delay parameter τ based on mutual information function method, can include:
X is enabled to represent that original power quality sampling time sequence x (t), Y represent the time delay sequence x (t+ τ) of x (t), [even X, Y]=[x (t), x (t+ τ)], then mutual information function I (X, Y) is related with the value of time delay τ.The value of I (τ) is big It is small to reflect under conditions of known original time series x (t), the deterministic size of time delayed sequence x (t+ τ).Choosing The delay time corresponding to first minimum point of I (τ) is taken to postpone for Best Times.
Step S112:Smallest embedding dimension number is determined based on correlation dimension method.
In embodiments of the present invention, correlation dimension method can be utilized to determine the smallest embedding dimension number in phase space reconfiguration.Tool Body, determine that smallest embedding dimension number can be based on correlation dimension method:
Smallest embedding dimension number m meets:M >=2d+1, wherein, d is the correlation dimension of system.
Correlation dimension m takes the minimum value for meeting m >=2d+1.Phase is reconstructed to obtained power quality sampling time sequence first Space calculates the correlation integral of phase space
Wherein, N is sampling number, and r is radius, xiAnd xjIt is any two points in phase space, u (t) is unit-step function, that is, is worked as T >=0, u (t)=1;Work as t<0, u (t)=0.
By carrying out scale to C (r) and r, the double-log relation curve of lnC (r)~lnr of standard sine signal is obtained, LnC (r)~lnr relation curves are fitted, obtain its best-fitting straight line, then this straight slope is correlation dimension d, M is determined with this.
Step S113:Based on the Best Times delay parameter and the smallest embedding dimension number, coordinate delay method is utilized To the electrical energy power quality disturbance time series phase space reconstruction, so as to obtain phase space reconfiguration as a result, the phase space reconfiguration knot Fruit includes phase path and phase point.
In the Best Times delay parameter τ needed for acquisition phase space reconfiguration and smallest embedding dimension number m and then utilize seat It marks delay method and phase space reconfiguration is carried out to above-mentioned electrical energy power quality disturbance time series, obtain phase space reconfiguration as a result, and mutually empty Between be included in the phase path and phase point of Different Plane in reconstruction result.Certainly, phase can also be included in phase space reconfiguration result The quantity of point.Phase space reconstruction technique can excavate the potential characteristic information in the sampled signal of power quality, after can improving The fundamental wave of continuous Atomic Decomposition process and the specific aim and accuracy of disturbance parameter extraction.
Step S120:The normal waveform in the waveform of the sampled signal is obtained based on the phase path and the phase point Section and disturbance waveform section.
Phase space is reconstructed in the electrical energy power quality disturbance time series of the sampled signal to power quality, obtains phase space After reconstruction result, waveform segments are being carried out to phase path, to obtain normal waveform section and disturbance waveform section.
In embodiments of the present invention, step S120 can include:
Based on the phase path, the first phase point being not belonging in the phase point in fundamental wave phase path threshold range is obtained;Point The isolated phase point in first phase point is not removed in the phase path and belongs to the phase point of transition portion, so as to obtain respectively Obtain the normal waveform section and disturbance waveform section in the waveform of the sampled signal.
Specifically, all phase points in above-mentioned phase path can be marked, such as will be in fundamental wave phase path threshold value model Phase point in enclosing is labeled as 1, and or not the phase point in fundamental wave phase path threshold range labeled as 0, then removal is not labeled as 0 part Isolated phase point in phase point set, obtains the normal waveform section in the waveform of sampled signal, and removal is labeled as 0 part phase point The phase point of transition portion in set obtains the disturbance waveform section in the waveform of sampled signal.
It is understood that the normal waveform section and disturbance waveform section that obtain can be multiple.
Step S130:Based on the normal waveform section and the disturbance waveform section, the disturbance waveform area is obtained 1st grade of residual component of the disturbance waveform section after section removal fundametal compoment.
It, can be according to normal after normal waveform section and disturbance waveform section in the waveform for obtaining sampled signal Undulating segment obtain fundametal compoment after, remove the fundametal compoment then at disturbance waveform section to obtain initial residual component, i.e., on State the 1st grade of residual component.
Specifically, step S130 can include:
Based on first normal waveform section in the normal waveform section, once changed using matching pursuit algorithm Generation extraction fundametal compoment;The fundametal compoment is removed in the disturbance waveform section, obtains the 1st of the disturbance waveform section Grade residual component.
It is understood that above-mentioned normal waveform section first normal waveform section directly using MP algorithms i.e. An iteration extraction fundametal compoment and parameter are carried out with tracing algorithm, in each disturbance waveform section of above-mentioned disturbance waveform section The fundametal compoment that removal said extracted arrives, obtains the initial residual component of each disturbance waveform section, i.e., above-mentioned 1st grade of residual error point Amount.
Step S140:It is special to the disturbance to be identified of the 1st grade of residual component extraction disturbance component of the disturbance waveform section Levy parameter.
In embodiments of the present invention, after the 1st grade of residual component is obtained, to the 1st grade of residual error point of each disturbance section Amount extracts disturbance component and parameter one by one.
In embodiments of the present invention, step S140 can include:
The forcing frequency search range of energy maximum in the disturbance waveform section is obtained based on fast fourier algorithm;Base In the forcing frequency search range, the 1st grade of residual component and default atom are obtained using particle swarm optimization algorithm Maximum inner product in atom is worth corresponding particle, so as to obtain the best match particle of one group of disturbance;Based on the best match The small-scale atom of particle, each parameter preset discretization range and the generation of discretization rule, is obtained using matching pursuit algorithm Take the best match atom in the small-scale atom;The parameter of the best match atom is obtained, so as to obtain described disturb The perturbation features parameter to be identified of dynamic component.
In embodiments of the present invention, can damped sinusoidal quantity original be established according to the analytical form of Power Quality Disturbance Word bank model is as above-mentioned default atom.
Wherein, the analytical form of Power Quality Disturbance is:
In formula,For parameter group, f is frequency parameter,It is phase parameter, ρ is attenuation coefficient, tsAnd te It is damped sinusoidal quantity starting and end time parameter, K respectivelyγTo make | | g (t) | |=1 coefficient, u (t) they are unit step letters Number.
Following discretization is carried out to parameter group again, obtained complete above-mentioned damped sinusoidal quantity atom model.Discretization For:
In formula, length of the N for sampled signal, fsFor sample frequency.Each discretization parameter value ranging from w ∈ [0, N-1], p ∈ [0, N-1], r ∈ [- N, N], 0≤ns<ne≤N-1。
Specifically, the forcing frequency search of energy maximum in the disturbance waveform section is obtained based on fast fourier algorithm Range can include:
The frequency spectrum of the disturbance waveform section is obtained based on fast fourier algorithm;Obtain maximum extreme point in the frequency spectrum Corresponding frequency;Disturbance frequency based on energy maximum in the maximum extreme point corresponding frequency acquisition disturbance waveform section Rate search range.
It is understood that for processed disturbance waveform section, calculated using FFT, that is, fast fourier algorithm current The frequency spectrum of the signal component of disturbance waveform section to be decomposed obtains the frequency corresponding to the extreme point of amplitude maximum on spectrogram, Determine the forcing frequency search range of energy maximum in current disturbing signal.Wherein, forcing frequency search range can be amplitude The frequency range near frequency corresponding to maximum extreme point.
After forcing frequency search range is obtained, the parameter of the PSO optimization algorithms of input, i.e. particle swarm optimization algorithm are obtained Parameter:Inertial factor ω and Studying factors C is set1、C2Value, and set population scale NmWith evolution number M.With atom IndexTo treat optimizing particle, wherein the search range of the first dimension particle f is searched for for above-mentioned forcing frequency Range, the value range of other dimension particles are consistent with damped sinusoidal quantity atom parameter group value range.Utilize PSO optimization algorithms During the best match particle for obtaining disturbance, evaluated using the 1st grade of residual signals and atom inner product value as fitness function Particle, finds the particle with current signal inner product value maximum to be decomposed, and optimizing searches for obtain the best match particle of one group of disturbance.
It is hereby achieved that the best match particle of one group of disturbance, can improve the i.e. matching pursuit algorithm of follow-up MP algorithms The specific aim of search improves the whole efficiency of Atomic Decomposition process.
After the best match particle for obtaining one group of above-mentioned disturbance, each parameter discretization in default atom Range and discretization criterion generate small-scale atom, and fine searching is targetedly carried out to parameters using MP algorithms, It extracts this time to the best match atom during disturbance waveform segment signals processing, obtains the disturbance waveform section The corresponding best match atom of 1st grade of residual component.
Then, the corresponding parameter of best match atom in above-mentioned small-scale atom is obtained, so as to obtain one group of disturbance Optimum matching parameter, i.e. the 1st of the disturbance waveform section grade residual component disturbance parameter to be identified.
It is understood that the 1st grade of residual component for each disturbance waveform section carries out above-mentioned processing, can be disturbed The perturbation features parameter to be identified of the 1st grade of corresponding disturbance component of component of each disturbance waveform section in dynamic undulating segment.
Step S150:Relationship based on pre-stored perturbation features parameter Yu disturbance event type is waited to know described in acquisition The corresponding disturbance event type of other perturbation features parameter.
In embodiments of the present invention, pre-stored perturbation features parameter can be according to electricity with the relationship of disturbance event type The associated description of energy quality disturbance is established with defining.According to the 1st of each disturbance waveform section of the above-mentioned acquisition of the relation pair the The perturbation features parameter to be identified of the corresponding disturbance component of grade component is identified, so as to obtain institute in all disturbance waveform sections Type containing disturbance event obtains all perturbation features parameters in the disturbing signal of power quality and power quality The type of contained all disturbance events in disturbing signal.
In embodiments of the present invention, for improve obtain the corresponding perturbation features parameter to be identified of disturbance waveform section and its The accuracy of corresponding disturbance event can also carry out successive ignition, obtain best perturbation features parameter to be identified, and based on upper The relationship of perturbation features parameter and disturbance event type is stated, so as to obtain best disturbance event type.
Therefore, which can also include:
It will be to the perturbation features parameter to be identified of the 1st of the disturbance waveform section the grade of residual component extraction disturbance component Step carries out iterative process described in n times as the 1st iterative process, so as in the sampled signal disturbance component it is best Perturbation features parameter to be identified;Relationship based on the pre-stored perturbation features parameter Yu disturbance event type obtains institute State the corresponding disturbance event type of best perturbation features parameter to be identified.
It is understood that the 1st grade of residual component to disturbance waveform section extracts the spy to be identified of disturbance component The process for levying parameter is the 1st iterative process, then carry out multiple iteration, makes residual signals minimum, most preferably waits to know so as to obtain Other perturbation features parameter.
For example, carrying out the m times above-mentioned iterative process, can include:
M-1 grades of residual components are subtracted to the best match atom obtained in iterative process described in m-1, obtain m grades Residual component;Judge whether the residual energy of the m grades of residual components is greater than or equal to preset energy and judges iteration time Whether number m is less than default iterations;It is greater than or equal to the preset energy in the residual energy of the m grades of residual components, And the iterations m obtains the m times iteration corresponding perturbation features to be identified when being less than the default iterations Parameter.
It is understood that after the m-1 times above-mentioned iterative process is carried out, by m-1 grades in m-1 iterative process Residual signals subtract the best match atom obtained in m-1 grades of iterative process, so as to obtain m grades of residual components.Judge again Whether stopping criterion for iteration is met, it is residual when not meeting stopping criterion for iteration, then based on above-mentioned the 1st grade to disturbance waveform section The method of the perturbation features parameter to be identified of difference component extraction disturbance component, obtains the corresponding disturbance component of m grades of residual components Perturbation features parameter to be identified, that is, obtain the corresponding perturbation features parameter to be identified of the m times iteration.
Wherein, judge whether that meeting stopping criterion for iteration can be:Judge whether the residual energy of m grades of residual components is big In or equal to preset energy and judge whether iterations m is less than default iterations, be judged as m grades of residual components Residual energy when being greater than or equal to preset energy and iterations m and being less than default iterations, then be judged to not meeting repeatedly For end condition.
Meeting stopping criterion for iteration, i.e., the residual energy of m grades of residual components not greater than or equal to preset energy or When iterations m is not less than default iterations, iteration is terminated, at this point, the disturbance to be identified that the m-1 times iterative process obtains is special Sign parameter is above-mentioned best perturbation features parameter to be identified.
Then, further according to above-mentioned pre-stored perturbation features parameter and the relationship of disturbance event type, acquisition is most preferably treated Identify the corresponding disturbance event type of perturbation features parameter, the type as contained disturbance event in disturbance waveform section.
Above-mentioned processing is carried out to each disturbance waveform section, you can obtain the disturbance component in each disturbance waveform section The type of contained disturbance event in best perturbation features parameter and each disturbance waveform section, so as to obtain power quality All best perturbation features parameters in sampled signal and all disturbance events contained in the disturbing signal of power quality Type.
The electrical energy power quality disturbance event recognition method that first embodiment of the invention provides provides a kind of based on phase space weight The analysis method that structure is combined with Atomic Decomposition is reducing algorithm calculation amount and is ensureing the situation of disturbance parameter extraction accuracy Under, give disturbance waveform segmentation, perturbation features parameter extraction and the recognition methods for disturbing type.By introducing phase space reconfiguration Technology carries out segment processing to sample waveform data, obtains normal and disturbance portion waveshape section, improves follow-up Atomic Decomposition The specific aim and accuracy of fundamental wave and the disturbance parameter extraction of process.The search being combined using FFT and PSO algorithms with MP algorithms Algorithm reduces the calculation amount of parameter matching process.The fundamental wave and disturbance component characteristic parameter energy of Atomic Decomposition process segment extraction The constituent of enough parametrization analytic representation disturbing signals.By the logic identification of disturbance, it is possible to obtain disturbing whole spies While levying parameter, the type that is disturbed provides better foundation further to administer to disturb.
Second embodiment
Second embodiment of the invention provides a kind of electrical energy power quality disturbance event recognition device 200, refers to Fig. 4, described Electrical energy power quality disturbance event recognition device 200 includes:Phase space reconfiguration module 210, waveform segments module 220, residual error obtain mould Block 230, parameter extraction module 240 and disturbed depth module 250.Wherein, the phase space reconfiguration module 210 is used for electric energy The electrical energy power quality disturbance time series phase space reconstruction of the sampled signal of quality, so as to obtain phase space reconfiguration as a result, the phase Space Reconstruction result includes phase path and phase point;The waveform segments module 220 is used for based on the phase path and described Phase point obtains normal waveform section and disturbance waveform section in the waveform of the sampled signal;The residual error acquisition module 230 are used for based on the normal waveform section and the disturbance waveform section, obtain the disturbance waveform section removal fundamental wave 1st grade of residual component of the disturbance waveform section after component;The parameter extraction module 240 is used for the disturbance waveform The perturbation features parameter to be identified of the 1st grade of residual component extraction disturbance component of section;The disturbed depth module 250 is used for base In pre-stored perturbation features parameter and the relationship of disturbance event type, it is corresponding to obtain the perturbation features parameter to be identified Disturbance event type.
It is to be understood that the electrical energy power quality disturbance event recognition device 200 that second embodiment of the invention provides is this hair The corresponding device of electrical energy power quality disturbance event recognition method that bright first embodiment provides, other detailed contents may refer to above-mentioned The content for the electrical energy power quality disturbance event recognition method that first embodiment of the invention provides, this is no longer going to repeat them.
In conclusion electrical energy power quality disturbance event recognition method provided in an embodiment of the present invention and device, by electric energy The electrical energy power quality disturbance time series phase space reconstruction of the sampled signal of quality, so as to obtain phase space reconfiguration as a result, phase space Reconstruction result includes phase path and phase point, then the normal waveform in the waveform of sampled signal is obtained based on phase path and phase point Section and disturbance waveform section then based on normal waveform section and disturbance waveform section, obtain disturbance waveform section and go Except the 1st grade of residual component of the disturbance waveform section after fundametal compoment, then the 1st grade of residual component of disturbance waveform section is carried The perturbation features parameter to be identified of disturbance component is taken, is finally based on pre-stored perturbation features parameter and disturbance event type Relationship obtains the corresponding disturbance event type of perturbation features parameter to be identified.The electrical energy power quality disturbance event recognition method and dress It puts and phase space reconstruction technique is utilized during disturbance event type is obtained, so as to excavate the potential feature of signal Information, the perturbation features parameter for making acquisition is more abundant, and according to perturbation features gain of parameter disturbance event type, is disturbed to administer It is dynamic that foundation is provided.
It should be noted that each embodiment in this specification is described by the way of progressive, each embodiment weight Point explanation is all difference from other examples, and just to refer each other for identical similar part between each embodiment. For device class embodiment, since it is basicly similar to embodiment of the method, so description is fairly simple, related part is joined See the part explanation of embodiment of the method.
In several embodiments provided herein, it should be understood that disclosed device and method can also pass through it Its mode is realized.The apparatus embodiments described above are merely exemplary, for example, the flow chart and block diagram in attached drawing are shown The device of multiple embodiments according to the present invention, architectural framework in the cards, the work(of method and computer program product are shown It can and operate.In this regard, each box in flow chart or block diagram can represent one of a module, program segment or code Point, a part for the module, program segment or code includes one or more and is used to implement the executable of defined logic function Instruction.It should also be noted that at some as in the realization method replaced, the function of being marked in box can also be attached to be different from The sequence marked in figure occurs.For example, two continuous boxes can essentially perform substantially in parallel, they also may be used sometimes To perform in the opposite order, this is depended on the functions involved.It is it is also noted that each in block diagram and/or flow chart The combination of box and the box in block diagram and/or flow chart function or the dedicated of action can be based on as defined in execution The system of hardware is realized or can be realized with the combination of specialized hardware and computer instruction.
In addition, each function module in each embodiment of the present invention can integrate to form an independent portion Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized in the form of software function module and is independent product sale or in use, can be with It is stored in a computer read/write memory medium.Based on such understanding, technical scheme of the present invention is substantially in other words The part contribute to the prior art or the part of the technical solution can be embodied in the form of software product, the meter Calculation machine software product is stored in a storage medium, is used including some instructions so that a computer equipment (can be People's computer, server or network equipment etc.) perform all or part of the steps of the method according to each embodiment of the present invention. And aforementioned storage medium includes:USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic disc or CD.It needs Illustrate, herein, relational terms such as first and second and the like be used merely to by an entity or operation with Another entity or operation distinguish, and without necessarily requiring or implying between these entities or operation, there are any this realities The relationship or sequence on border.Moreover, term " comprising ", "comprising" or its any other variant are intended to the packet of nonexcludability Contain so that process, method, article or equipment including a series of elements not only include those elements, but also including It other elements that are not explicitly listed or further includes as elements inherent to such a process, method, article, or device. In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including the element Process, method, also there are other identical elements in article or equipment.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, that is made any repaiies Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.It should be noted that:Similar label and letter exists Similar terms are represented in following attached drawing, therefore, once being defined in a certain Xiang Yi attached drawing, are then not required in subsequent attached drawing It is further defined and is explained.
The above description is merely a specific embodiment, but protection scope of the present invention is not limited thereto, any Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in change or replacement, should all contain Lid is within protection scope of the present invention.Therefore, protection scope of the present invention described should be subject to the protection scope in claims.

Claims (10)

1. a kind of electrical energy power quality disturbance event recognition method, which is characterized in that the method includes:
To the electrical energy power quality disturbance time series phase space reconstruction of the sampled signal of power quality, so as to obtain phase space reconfiguration knot Fruit, the phase space reconfiguration result include phase path and phase point;
Normal waveform section and the disturbance in the waveform of the sampled signal are obtained based on the phase path and the phase point Undulating segment;
Based on the normal waveform section and the disturbance waveform section, the disturbance waveform section removal fundametal compoment is obtained 1st grade of residual component of the disturbance waveform section afterwards;
To the perturbation features parameter to be identified of the 1st grade of residual component extraction disturbance component of the disturbance waveform section;
Relationship based on pre-stored perturbation features parameter Yu disturbance event type obtains the perturbation features parameter to be identified Corresponding disturbance event type.
2. the according to the method described in claim 1, it is characterized in that, electrical energy power quality disturbance time series to sampled signal Phase space reconstruction, so as to obtain phase space reconfiguration as a result, including:
Best Times delay parameter is determined based on mutual information function method;
Smallest embedding dimension number is determined based on correlation dimension method;
Based on the Best Times delay parameter and the smallest embedding dimension number, using coordinate delay method to the power quality Disturb time series phase space reconstruction, so as to obtain phase space reconfiguration as a result, the phase space reconfiguration result include phase path with And phase point.
3. according to the method described in claim 1, it is characterized in that, based on being adopted described in the phase path and phase point acquisition Normal waveform section and disturbance waveform section in the waveform of sample signal, including:
Based on the phase path, the first phase point being not belonging in the phase point in fundamental wave phase path threshold range is obtained;
Respectively at the isolated phase point removed in the phase path in first phase point and the phase point for belonging to transition portion, thus The normal waveform section and disturbance waveform section in the waveform of the sampled signal are obtained respectively.
4. according to the method described in claim 1, it is characterized in that, based on the normal waveform section and the disturbance waveform Section obtains the 1st grade of residual component of the disturbance waveform section after the disturbance waveform section removal fundametal compoment, packet It includes:
Based on first normal waveform section in the normal waveform section, carry out an iteration using matching pursuit algorithm and carry Take fundametal compoment;
The fundametal compoment is removed in the disturbance waveform section, obtains the 1st grade of residual component of the disturbance waveform section.
5. according to the method described in claim 1, it is characterized in that, the 1st grade of residual component to the disturbance waveform section carries The perturbation features parameter to be identified of disturbance component is taken, including:
The forcing frequency search range of energy maximum in the disturbance waveform section is obtained based on fast fourier algorithm;
Based on the forcing frequency search range, the 1st grade of residual component and default original are obtained using particle swarm optimization algorithm Maximum inner product in the atom of word bank is worth corresponding particle, so as to obtain the best match particle of one group of disturbance;
Small-scale atom based on the generation of the best match particle, each parameter preset discretization range and discretization rule Library obtains the best match atom in the small-scale atom using matching pursuit algorithm;
The parameter of the best match atom is obtained, so as to obtain the perturbation features parameter to be identified of the disturbance component.
6. according to the method described in claim 5, it is characterized in that, described obtain the perturbation wave based on fast fourier algorithm The forcing frequency search range of energy maximum in shape section, including:
The frequency spectrum of the disturbance waveform section is obtained based on fast fourier algorithm;
Obtain the corresponding frequency of maximum extreme point in the frequency spectrum;
Forcing frequency search based on energy maximum in the maximum extreme point corresponding frequency acquisition disturbance waveform section Range.
It is 7. according to the method described in claim 1, it is characterized in that, described based on pre-stored perturbation features parameter and disturbance The relationship of event type, after obtaining the corresponding disturbance event type of the perturbation features parameter to be identified, the method is also wrapped It includes:
The step of perturbation features parameter to be identified for disturbance component being extracted to the 1st of the disturbance waveform section the grade of residual component As the 1st iterative process, and iterative process described in n times is carried out, so as to which the best of disturbance component is waited to know in the sampled signal Other perturbation features parameter;
Relationship based on the pre-stored perturbation features parameter Yu disturbance event type obtains the best disturbance to be identified The corresponding disturbance event type of characteristic parameter.
8. the method according to the description of claim 7 is characterized in that carry out the m times iterative process, including:
M-1 grades of residual components are subtracted to the best match atom obtained in iterative process described in m-1, obtain m grades of residual errors Component;
Judge whether the residual energy of the m grades of residual components is greater than or equal to preset energy and judges that iterations m is It is no to be less than default iterations;
It is greater than or equal to the preset energy in the residual energy of the m grades of residual components and the iterations m is less than During the default iterations, the corresponding perturbation features parameter to be identified of the m times iteration is obtained.
9. according to the method described in claim 8, it is characterized in that, judge the m grades of residual components residual energy whether More than or equal to preset energy and after judging whether iterations m is less than default iterations, the method further includes:
It is not less than institute not greater than or equal to preset energy or the iterations m in the residual energy of the m grades of residual components When stating default iterations, iteration is terminated, the perturbation features parameter to be identified that the m-1 times iterative process is obtained is as institute State best perturbation features parameter to be identified.
10. a kind of electrical energy power quality disturbance event recognition device, which is characterized in that described device includes:Phase space reconfiguration module, wave Shape segmentation module, residual error acquisition module, parameter extraction module and disturbed depth module, wherein,
The electrical energy power quality disturbance time series reconstruct that the phase space reconfiguration module is used for the sampled signal of power quality is mutually empty Between, so as to obtain phase space reconfiguration as a result, the phase space reconfiguration result includes phase path and phase point;
The waveform segments module is used to obtain in the waveform of the sampled signal based on the phase path and the phase point Normal waveform section and disturbance waveform section;
The residual error acquisition module is used to, based on the normal waveform section and the disturbance waveform section, obtain the disturbance 1st grade of residual component of the disturbance waveform section after undulating segment removal fundametal compoment;
The parameter extraction module is used for the to be identified of the 1st grade of residual component extraction disturbance component of the disturbance waveform section Perturbation features parameter;
The disturbed depth module is used for the relationship based on pre-stored perturbation features parameter Yu disturbance event type, obtains institute State the corresponding disturbance event type of perturbation features parameter to be identified.
CN201810029546.8A 2018-01-12 2018-01-12 Electrical energy power quality disturbance event recognition method and device Pending CN108256465A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113780364A (en) * 2021-08-18 2021-12-10 西安电子科技大学 Model and data combined driving SAR image target identification method

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6360178B1 (en) * 1997-12-09 2002-03-19 Antony Cozart Parsons System and method for locating a disturbance in a power system based upon disturbance power and energy
CN102230951A (en) * 2011-03-28 2011-11-02 武汉大学 Method for monitoring and identifying single or multiple electric energy disturbance events of electric power system on line
CN204945269U (en) * 2015-08-21 2016-01-06 常州埃依琦科技有限公司 Power quality supervisory information system
CN107315111A (en) * 2017-07-17 2017-11-03 浙江群力电气有限公司 A kind of Power Quality Disturbance Classification Method and system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6360178B1 (en) * 1997-12-09 2002-03-19 Antony Cozart Parsons System and method for locating a disturbance in a power system based upon disturbance power and energy
CN102230951A (en) * 2011-03-28 2011-11-02 武汉大学 Method for monitoring and identifying single or multiple electric energy disturbance events of electric power system on line
CN204945269U (en) * 2015-08-21 2016-01-06 常州埃依琦科技有限公司 Power quality supervisory information system
CN107315111A (en) * 2017-07-17 2017-11-03 浙江群力电气有限公司 A kind of Power Quality Disturbance Classification Method and system

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
MURAT UYAR 等: "An effective wavelet-based feature extraction method for classificationof power quality disturbance signals", 《ELECTRIC POWER SYSTEMS RESEARCH》 *
崔志强 等: "基于分层匹配追踪算法的电能质量复合扰动参数辨识方法", 《电力自动化设备》 *
王宁 等: "基于相空间重构的电压缺口检测及特征参数辨识", 《中国电机工程学报》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113780364A (en) * 2021-08-18 2021-12-10 西安电子科技大学 Model and data combined driving SAR image target identification method

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Application publication date: 20180706