CN112990059B - IV curve diagnosis method and device based on curve shape description - Google Patents
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Abstract
The invention provides a method and a device for IV curve diagnosis based on curve shape description, wherein the method comprises the following steps: acquiring an IV curve and key characteristics, dividing the IV curve into a plurality of sections, and giving out curve morphemes in each section; obtaining a morpheme vector from the curved morpheme; obtaining a morpheme wildcard according to the curve morpheme and the morpheme vector, and obtaining a wildcard vector from the morpheme wildcard; and carrying out identification diagnosis on the IV curve according to the morpheme vector and the wild card vector. The method has the advantages that the method has no problem of information loss in the traditional mode feature extraction process, has no absolute requirement on data volume, and can obtain quite accurate IV diagnosis results.
Description
Technical Field
The invention belongs to the field of photovoltaic power generation, and particularly relates to an IV curve diagnosis method and device based on curve shape description.
Background
The existing IV curve description method usually describes signals as vectors, extracts characteristics of signal sequences such as peak values, average values, widths and the like through a statistical method, and carries out pattern recognition through an AI intelligent algorithm such as a neural network, a Bayesian classifier and the like. The objective of such methods for feature extraction is to reduce the dimension, which often comes at the cost of loss of information. In addition, the large data mining mode needs to be based on a large amount of data, and the modeling process is complex.
Disclosure of Invention
The embodiment of the application provides a method and a device for IV curve diagnosis based on curve shape description, which have no problem of information loss, have no absolute requirement on data volume, and can obtain quite accurate IV diagnosis results.
In a first aspect, embodiments of the present application provide a method for IV curve diagnosis based on curve shape description, including:
acquiring an IV curve and key characteristics, dividing the IV curve into a plurality of sections, and giving out curve morphemes in each section;
obtaining a morpheme vector from the curved morpheme;
obtaining a morpheme wildcard according to the curve morpheme and the morpheme vector, and obtaining a wildcard vector from the morpheme wildcard;
and carrying out identification diagnosis on the IV curve according to the morpheme vector and the wild card vector.
The method for obtaining the IV curve and the key features divides the IV curve into a plurality of sections, each section gives out curve morphemes, and the method comprises the following steps:
the interval is divided into:
interval one: 0,0.8 x V mpp ，
Interval two: 0.9 x V mpp ,1.1*V mpp ，
Interval three: 1.2 x V mpp ,V oc ，
Wherein V is mpp Is the maximum power point voltage value, V oc Is an open circuit voltage;
the 3 basic morphemes describing the IV curve change are a ladder section, a descent section and a smooth section, which are respectively numbered as 0, 1 and 2, and the ladder section meets the maximum value D of the second derivative max At [ - ≡18 ] x ]Or [ D ] x ,+∞]The falling segment satisfies the slope G avg At [ - ≡G min ]The smooth segment satisfies the slope G avg In [ G ] min ,G max ]。
The method comprises the steps of acquiring an IV curve and key features, dividing the IV curve into a plurality of intervals, giving out curve morphemes in each interval, and further comprising:
the solving method of each expansion morpheme comprises the following steps:
V x ＝V c /(1-β(25-Tc)) (1)
I x ＝I c (1000/Qc)/(1-α(25-Tc)) (2)
wherein Vx is corrected voltage data, vc is voltage data in IV curve scan data, ix is corrected current data, ic is current data in IV curve scan data, α is a short-circuit current temperature coefficient of the photovoltaic power station string, β is an open-circuit voltage temperature coefficient of the photovoltaic power station string, qc is irradiance during IV curve scan, tc is a back plate temperature of the photovoltaic power station photovoltaic module during IV curve scan;
correcting standard test conditions by using voltage data in IV curve scanning data through a formula (1), correcting standard test conditions by using current data in the IV curve scanning data through a formula (2), taking converted voltage and current data as input, fitting by polynomial regression to obtain model parameters of the IV curve, and respectively solving required characteristic values by using the existing model parameters:
short circuit current: let Vs=0, solve for the value of Is, i.e. I sc ；
Open circuit voltage: let the function is=0, solve for the value of Us, i.e. V oc ；
Maximum power: constructing a power function ps=f (Vs) ×vs, and solving a maximum P of Ps max ；
At the same time, P can be solved max Corresponding maximum power voltage V mpp Further, the FF value is obtained;
constructing a first derivative function Gs of F (Vs):
calculate (0, 0.8 v) mpp ) Average value G of intra-interval function Gs avg_1 ；
Calculate (0.9 v mpp ，1.1*V mpp ) Average value G of slope function Gs in interval avg_2 ；
Calculate (1.2 v mpp ，V oc ) Within the interval, the average value G of the function Gs avg_3 ；
Constructing a second derivative function Ds of F (Vs):
calculate (0, 0.8 v) mpp ) Maximum value D of intra-interval function Ds max_1 ；
Calculate (0.9 v mpp ，1.1*V mpp ) Maximum value D of slope function Ds in interval max_2 。
Wherein the obtaining a morpheme vector from the cursive morpheme comprises:
the morpheme vector is b= (r, C1, C2, C3,..cn), where r is the morpheme number and C1, C2...cn is the n-dimensional attribute of the morpheme.
The method for obtaining the morpheme wild card according to the curve morpheme and the morpheme vector comprises the steps of:
the expression sentence composed of a plurality of continuous morphemes meeting the curve morphemes and morpheme vectors is a morpheme wild card; the wild card vector is w= (r, C1, C2, C3,..cm), where r is the wild card symbol, C1, C2,..cm is the m-dimensional attribute of the wild card.
In a second aspect, the present application provides an apparatus for IV curve diagnosis based on curve shape description, comprising:
the acquisition unit is used for acquiring an IV curve and key characteristics, dividing the IV curve into a plurality of sections, and giving out curve morphemes in each section;
a first vector unit for obtaining a morpheme vector from the curved morpheme;
a second vector unit, configured to obtain a morpheme wildcard according to the curved morpheme and the morpheme vector, and obtain a wildcard vector from the morpheme wildcard;
and the diagnosis unit is used for carrying out identification diagnosis on the IV curve according to the morpheme vector and the wild card vector.
In a third aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods described above.
In a fourth aspect, embodiments of the present application provide a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the methods described above when the program is executed.
The method and the device for IV curve diagnosis based on curve shape description have the following beneficial effects:
the method has no problem of information loss in the traditional mode feature extraction process, and has no absolute requirement on data size. And can obtain quite accurate IV diagnosis results. Is an innovative solution ≡! Morphological characteristics of curves can be described from different scales by adopting morphemes and morpheme vectors on the basis of strict mathematical definition; secondly, the use of wild cards and vectors thereof expands the expression capability of the factory curve expression sentence, so that the description has abstraction, and the attribute vectors of the morphemes and the wild cards are defined, so that the description capability of the curve expression sentence is improved.
Drawings
FIG. 1 is a flow chart of a method for IV curve diagnosis based on curve shape description according to an embodiment of the present application;
FIG. 2 is a flow chart of diagnosing IV curve faults in an embodiment of the present application;
FIG. 3 is a basic morpheme diagram according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a sample and template matching result in an embodiment of the present application;
FIG. 5 is a schematic diagram of a device for IV curve diagnosis based on curve shape description according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The present application is further described below with reference to the drawings and examples.
In the following description, the terms "first," "second," and "first," are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The following description provides various embodiments of the invention that may be substituted or combined between different embodiments, and thus this application is also intended to encompass all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then the present application should also be considered to include embodiments that include one or more of all other possible combinations including A, B, C, D, although such an embodiment may not be explicitly recited in the following.
The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the application. Various examples may omit, replace, or add various procedures or components as appropriate. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
The invention provides an IV curve description method, which is widely applied to the description problem of graphic boundaries by carrying out symbolization coding on a curve to form a chain code. And can obtain quite accurate IV diagnosis results.
As shown in fig. 1-4, the method for IV curve diagnosis described based on curve shape of the present application comprises: s101, acquiring an IV curve and key features, dividing the IV curve into a plurality of sections, and giving out curve morphemes in each section; s103, obtaining a morpheme vector from the curve morpheme; s105, obtaining a morpheme wildcard according to the curve morpheme and the morpheme vector, and obtaining a wildcard vector from the morpheme wildcard; and S107, performing identification diagnosis on the IV curve according to the morpheme vector and the wild card vector. The following is a detailed description.
The terms used below will be explained first:
short-circuit current I sc ；
Open circuit voltage V oc ；
Maximum value D of second derivative max ；
Ping Junxie value G avg (G avg_1 、G avg_2 、G avg_3 Average slope values representing three intervals, respectively);
end-of-interval current value I end (first interval);
maximum power point power value P max ；
Fill factor ff=p max /I sc *V oc ；
Maximum power point voltage value V mpp ；
G max 、G min Respectively represent inclinedA threshold value of the rate;
D x represents D max A threshold value;
(the above threshold may be set based on experimental and practical experience.)
1. IV curve morphology description and matching method
And 1.1, converting the curve into a two-dimensional data table, and finally realizing the numerical description of the morphological characteristics of the curve.
1.1.1 morphemes and morpheme vectors
Just as human language requires a basic vocabulary, the expression of information requires a basic symbol, where the mathematical definition of cursive morphemes is given.
Firstly, acquiring an IV curve and key characteristics in an STC state, and dividing the IV curve into a plurality of sections according to voltage as an abscissa;
first, the interval is divided into:
interval one (S1 for short): (0, 0.8 x V) mpp )
Interval two (S2 for short): (0.9 x V) mpp ,1.1*V mpp )
Interval three (S3): (1.2 x V) mpp ,V oc )
1.1.1.2 Curve morphemes are given per interval
Definition 1: as shown in FIG. 3, the 3 basic morphemes first describing the IV curve change are a step, a down-step and a smooth, numbered "0", "1", "2", respectively, the step meeting the second derivative maximum D max At [ - ≡18 ] x ]Or [ D ] x ,+∞]The falling segment satisfies the slope G avg At [ - ≡G min ]The smooth segment satisfies the slope G avg In [ G ] min ,G max ]The method comprises the steps of carrying out a first treatment on the surface of the A typical IV curve can be fully represented using only the above 3 morphemes and thus can be encoded as a 0-1-2 string. The basic morphemes are consistent, and the characteristics such as short-circuit current, open-circuit voltage, average slope, filling factor and the like are defined as expansion morphemes for the effect of the characteristics in a curve.
S1: basic morpheme + extended morpheme (I) sc ，G avg_1 )
S2: basic morpheme + extended morpheme (G) avg_2 ,FF)
S3: basic morpheme + extended morpheme (G) avg_3 ，V oc )
The following is a solution method for each expansion morpheme:
V x ＝V c /(1-β(25-Tc)) (1)
I x ＝I c (1000/Qc)/(1-α(25-Tc)) (2)
wherein Vx is corrected voltage data, vc is voltage data in IV curve scan data, ix is corrected current data, ic is current data in IV curve scan data, α is a short-circuit current temperature coefficient of the photovoltaic power station string, β is an open-circuit voltage temperature coefficient of the photovoltaic power station string, qc is irradiance during IV curve scan, and Tc is a back plate temperature of the photovoltaic power station photovoltaic module during IV curve scan.
Correcting standard test conditions by using voltage data in IV curve scanning data through a formula (1), correcting standard test conditions by using current data in the IV curve scanning data through a formula (2), taking converted voltage and current data as input, fitting by polynomial regression to obtain model parameters of the IV curve, and respectively solving required important characteristic values by using the existing model parameters:
(1) short circuit current: let Vs=0, solve for the value of Is, i.e. I sc
(2) Open circuit voltage: let the function is=0, solve for the value of Us, i.e. V oc
(3) Maximum power: constructing a power function ps=f (Vs) ×vs, and solving a maximum P of Ps max
(4) At the same time, P can be solved max Corresponding maximum power voltage V mpp Further, the FF value is obtained
(5) Constructing a first derivative function Gs of F (Vs):
calculate (0, 0.8 v) mpp ) Average value G of intra-interval function Gs avg_1
Calculate (0.9 v mpp ，1.1*V mpp ) Average value G of slope function Gs in interval avg_2
Calculate (1.2 v mpp ，V oc ) Within the interval, the average value G of the function Gs avg_3
(6) Constructing a second derivative function Ds of F (Vs):
calculate (0, 0.8 v) mpp ) Maximum value D of intra-interval function Ds max_1
Calculate (0.9 v mpp ，1.1*V mpp ) Maximum value D of slope function Ds in interval max_2
Wherein the basic morpheme: the voltage granularity can be set to 1 volt-ampere (set according to the actual situation).
The cursive morphemes are used as the base symbols of the curve, and the information that can be expressed is limited, thus further defining morpheme vectors.
Definition 2: for a morpheme satisfying definition one, a morpheme vector is defined as a morpheme satisfying definition l, and a morpheme vector is defined as b= (r, C1, C2, C3,..cn), where r is a morpheme number, and C1, C2...cn is an n-dimensional attribute of the morpheme.
The 3 interval expansion morpheme vectors are in turn:
s1: (r, primitive, I) sc ，G avg_1 )
S2: (r, primitive, G) avg_2 ，FF)
S3: (r, primitive, G) avg_3 ，V oc )
Then, for any IV curve, it can be extracted as a vector sequence (the elements in each vector are scalar quantities), and these vector sequences are combined to form a two-dimensional data table, in which the second row represents the category of each vector, and can be used for matching character strings, and the table columns of the two-dimensional table represent the characteristics of the category, so that it is convenient to implement attribute operation.
1.1.2 plain wild card and wild card vector
Since each morpheme is a character of unit length, the expression of a curve can be considered to be a character string consisting of a plurality of characters.
Definition 3 an expression consisting of several consecutive morphemes satisfying definitions l, 2 is called morpheme wildcard, the morpheme wildcard vector is defined as w= (r, C1, C2, C3,..cm), where r is the wildcard symbol, C1, C2,..cm is the m-dimensional attribute of the wildcard, morpheme wildcard is also a morpheme, allowed to be empty, in IV curve diagnostics, the morpheme wildcard vector w= (wildcard number, basic morpheme, I) is defined sc ，G avg_1 ，G avg_2 ，FF，G avg_3 ，V oc ) Wherein the basic morpheme determination rule in the wild card vector: the three interval morphemes S1/S2/S3 should be represented by a concatenation. The description of any IV curve can be realized by identifying and diagnosing the IV curve through the morpheme vector and the wild card vector defined above.
Application of curve morphology description method in intelligent IV diagnosis and experimental analysis:
2.1 Fault diagnosis principle based on IV Curve scanning
The deformation of the IV curve can be caused no matter the environment factors or the failure problem of the component, various abnormal operation conditions and the system abnormality and the deformation of the IV curve have a strong association relation, that is, the system operation problem can be analyzed and judged theoretically through the detection result of the IV curve. Fig. 2 is a specific diagnostic flow.
If the curve shape description method is adopted to describe and identify the induction curve, a plurality of templates are designed first, then the newly collected curve is matched with the templates, and further whether the curve has the shape characteristics of a certain template or not is identified.
The classification ability of how to quantitatively analyze the curve morphology is performed by using the information gain in the information theory.
2.2 examples and results analysis
A template was designed according to the curve morphology description method described above, as shown in table one below. Since there are too many types of templates in the template two-dimensional table, only one example will now be given.
Two-dimensional table of table one and template
And determining a characteristic value limit value according to the characteristic of the characteristic value by utilizing a Laida criterion, wherein the short circuit current limit value is as follows: lower limit = mean-n standard deviation, open circuit voltage limit is: lower limit = mean-n standard deviation, maximum power limit is: lower limit = mean-n standard deviation, transverse strut slope (G avg_1 ) The limit value is: lower limit = mean-n standard deviation, longitudinal slope (G avg_3 ) The limit value is: upper limit=average+n standard deviation, curve slope (G avg_2 ) The limit value is: lower limit = mean-n standard deviation; wherein n is a preset constant, and can be adjusted according to the actual situation of the station and the required detection proportion, the smaller the n value is, the higher the detection sensitivity of the critical value to the abnormal characteristic value is, the n is generally taken as 2, and the detection level of the fault component is about 95%.
As shown in fig. 4, the curves in fig. 4 are the curves of the normal state, the current mismatch, the knee or the abnormal curvature (component aging), the step shape is a typical characteristic of the current mismatch of the IV curve, and the template can be matched with only the third one, so that in practical application, the discovery of the template can be performed by a sample statistics and observation method.
The method has no problem of information loss in the traditional mode feature extraction process, and has no absolute requirement on data size. And can obtain quite accurate IV diagnosis results. Is an innovative solution ≡! Morphological characteristics of curves can be described from different scales by adopting morphemes and morpheme vectors on the basis of strict mathematical definition; secondly, the use of wild cards and vectors thereof expands the expression capability of the factory curve expression sentence, so that the description has abstraction, and the attribute vectors of the morphemes and the wild cards are defined, so that the description capability of the curve expression sentence is improved.
As shown in fig. 5, the present application provides an apparatus for IV curve diagnosis based on curve shape description, comprising: an obtaining unit 201, configured to obtain an IV curve and key features, divide the IV curve into a plurality of sections, and each section gives a curve morpheme; a first vector unit 202 for obtaining a morpheme vector from the curved morpheme; a second vector unit 203, configured to obtain a morpheme wildcard according to the curved morpheme and the morpheme vector, and obtain a wildcard vector from the morpheme wildcard; and the diagnosis unit 204 is used for performing identification diagnosis on the IV curve according to the morpheme vector and the wild card vector.
In this application, an embodiment of the apparatus for IV curve diagnosis based on a curve shape description is substantially similar to an embodiment of the method for IV curve diagnosis based on a curve shape description, and reference is made to the description of the embodiment of the method for IV curve diagnosis based on a curve shape description for the relevant points.
It will be clear to those skilled in the art that the technical solutions of the embodiments of the present invention may be implemented by means of software and/or hardware. "Unit" and "module" in this specification refer to software and/or hardware capable of performing a specific function, either alone or in combination with other components, such as an FPGA (Field-Programmable Gate Array, field programmable gate array), an IC (Integrated Circuit ), etc.
The processing units and/or modules of the embodiments of the present invention may be implemented by an analog circuit that implements the functions described in the embodiments of the present invention, or may be implemented by software that executes the functions described in the embodiments of the present invention.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the above-mentioned method steps of IV curve diagnosis based on curve shape description. The computer readable storage medium may include, among other things, any type of disk including floppy disks, optical disks, DVDs, CD-ROMs, micro-drives, and magneto-optical disks, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
Fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application, such as a laptop computer, a desktop computer, a workstation, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers, as shown in fig. 6. The computer device may also represent various forms of mobile apparatuses, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing apparatuses. The computer device of the present application comprises a processor 401, a memory 402, input means 403 and output means 404. The processor 401, memory 402, input device 403, and output device 404 may be connected by a bus 405 or otherwise. The memory 402 has stored thereon a computer program which is executable on the processor 401 and which when executed by the processor 401 implements the method steps of IV curve diagnosis described above based on curve shape description.
The input device 403 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the data processing computer device, such as a touch screen, keypad, mouse, trackpad, touchpad, pointer stick, one or more mouse buttons, trackball, joystick, and like input devices. The output device 404 may include a display apparatus, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors), among others. Display devices may include, but are not limited to, liquid Crystal Displays (LCDs), light Emitting Diode (LED) displays, plasma displays, and touch screens.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiment of the apparatus is merely illustrative, and for example, the division of the units is merely a logic function division, and there may be other division manners in actual implementation, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The functional units in the embodiments of the present invention may be all integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A method of IV curve diagnosis based on curve shape description, comprising:
acquiring an IV curve and key characteristics, dividing the IV curve into a plurality of sections, and giving out curve morphemes in each section;
obtaining a morpheme vector from the curved morpheme;
obtaining a morpheme wildcard according to the curve morpheme and the morpheme vector, and obtaining a wildcard vector from the morpheme wildcard;
performing identification diagnosis on the IV curve according to the morpheme vector and the wild card vector;
the method for obtaining the IV curve and the key features divides the IV curve into a plurality of intervals, each interval gives out curve morphemes, and the method comprises the following steps:
the interval is divided into:
interval one: 0,0.8 x V mpp ，
Interval two: 0.9 x V mpp ,1.1*V mpp ，
Interval three: 1.2 x V mpp ,V oc ，
Wherein V is mpp Is the maximum power point voltage value, V oc Is an open circuit voltage;
the 3 basic morphemes describing the IV curve change are a ladder section, a descent section and a smooth section, which are respectively numbered as 0, 1 and 2, and the ladder section meets the maximum value D of the second derivative max At [ - ≡18 ] x ]Or [ D ] x ,+∞]The falling segment satisfies the slope G avg At [ - ≡G min ]The smooth segment satisfies the slope G avg In [ G ] min ,G max ]；G max 、G min Thresholds respectively representing slopes; d (D) x Represents D max A threshold value; d (D) max Is the maximum value of the second derivative;
the obtaining a morpheme vector from the curved morpheme includes:
the morpheme vector is b= (r, C1, C2, C3,..cn), where r is the morpheme number, C1, C2...cn is the n-dimensional attribute of the morpheme; the 3 interval expansion morpheme vectors are in turn:
s1: (r, primitive, I) sc ，G avg_1 )
S2: (r, primitive, G) avg_2 ，FF)
S3: (r, primitive, G) avg_3 ，V oc )
I sc Is short-circuit current; v (V) oc Is an open circuit voltage; g avg_1 、G avg_2 、G avg_3 Average slope values representing three intervals, respectively; fill factor ff=p max /I sc *V oc ，P max Is the maximum power point power value;
for any IV curve, the vector sequences can be extracted, the elements in each vector are scalar, and the vector sequences are combined to form a two-dimensional data table.
2. The method of curve diagnosis based on the curve shape description according to claim 1, wherein the obtaining a morpheme wildcard from the curve morpheme, morpheme vector, obtaining a wildcard vector from the morpheme wildcard, comprises:
the expression sentence composed of a plurality of continuous morphemes meeting the curve morphemes and morpheme vectors is a morpheme wild card; the wild card vector is w= (R, E1, E2, E3,..em), where R is the wild card symbol, E1, E2,..em is the m-dimensional attribute of the wild card.
3. An apparatus for IV curve diagnosis based on curve shape description, comprising:
the acquisition unit is used for acquiring an IV curve and key characteristics, dividing the IV curve into a plurality of sections, and giving out curve morphemes in each section;
a first vector unit for obtaining a morpheme vector from the curved morpheme;
a second vector unit, configured to obtain a morpheme wildcard according to the curved morpheme and the morpheme vector, and obtain a wildcard vector from the morpheme wildcard;
the diagnosis unit is used for carrying out identification diagnosis on the IV curve according to the morpheme vector and the wild card vector;
the method for obtaining the IV curve and the key features divides the IV curve into a plurality of intervals, each interval gives out curve morphemes, and the method comprises the following steps:
the interval is divided into:
interval one: 0,0.8 x V mpp ，
Interval two: 0.9 x V mpp ,1.1*V mpp ，
Interval three: 1.2 x V mpp ,V oc ，
Wherein V is mpp Is the maximum power point voltage value, V oc Is an open circuit voltage;
the 3 basic morphemes describing the IV curve change are a ladder section, a descent section and a smooth section, which are respectively numbered as 0, 1 and 2, and the ladder section meets the maximum value D of the second derivative max At [ - ≡18 ] x ]Or [ D ] x ,+∞]The falling segment satisfies the slope G avg At [ - ≡G min ]The smooth segment satisfies the slope G avg In [ G ] min ,G max ]；
The obtaining a morpheme vector from the curved morpheme includes:
the morpheme vector is b= (r, C1, C2, C3,..cn), where r is the morpheme number, C1, C2...cn is the n-dimensional attribute of the morpheme; the 3 interval expansion morpheme vectors are in turn:
s1: (r, primitive, I) sc ，G avg_1 )
S2: (r, primitive, G) avg_2 ，FF)
S3: (r, primitive, G) avg_3 ，V oc )
I sc Is short-circuit current; v (V) oc Is an open circuit voltage; g avg_1 、G avg_2 、G avg_3 Average slope values representing three intervals, respectively; fill factor ff=p max /I sc *V oc ，P max Is the maximum power point power value;
for any IV curve, the vector sequences can be extracted, the elements in each vector are scalar, and the vector sequences are combined to form a two-dimensional data table.
4. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any of the claims 1-2.
5. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of claims 1-2 when the program is executed.
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