Interharmonic measurement method, apparatus and device based on power system

Abstract

The application relates to a power system-based inter-harmonic measurement method, device and equipment. The method comprises the following steps: collecting parameter information of a power system by using a wavelet transform algorithm; sequentially performing fitting processing and extraction processing on the parameter information based on a pre-constructed inter-harmonic measurement model to obtain an inter-harmonic frequency; and determining an inter-harmonic of the power system based on the inter-harmonic frequency. The method can reduce the hardware cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, in particular to a method, device and equipment for measuring inter-harmonics based on a power system. BACKGROUND

[0002] With the wide access of distributed energy to power systems, and the increasing popularity of nonlinear loads and power electronic devices in power systems, non-sinusoidal current and voltage are easily generated during the operation of power systems, thereby causing inter-harmonics. Inter-harmonics refer to the phenomenon that the periodic alternating current contains non-integer multiple frequency components of the fundamental frequency. Inter-harmonics not only affect the normal operation of devices in the power system, but also seriously endanger the overall stability of the power system.

[0003] Traditional technologies usually use optimal control methods to quickly identify and measure harmonics and inter-harmonics. The optimal control method requires high-performance compensation devices such as active power filters and static var compensators. These devices rely on high-performance power electronic components and complex control systems, especially in large-scale applications, the hardware cost is particularly prominent. SUMMARY

[0004] Therefore, it is necessary to provide a method, device and equipment for measuring inter-harmonics based on a power system, which can reduce the hardware cost.

[0005] In a first aspect, the present application provides a method for measuring inter-harmonics based on a power system, comprising:

[0006] Collecting parameter information of the power system by using a wavelet transform algorithm;

[0007] Based on a pre-constructed inter-harmonic measurement model, the parameter information is sequentially fitted and extracted to obtain an inter-harmonic frequency.

[0008] Based on the inter-harmonic frequency, the inter-harmonic of the power system is determined.

[0009] In one embodiment, the inter-harmonic measurement model includes a target function and an extraction model. The target function is a function with the goal of minimizing risk. Based on the pre-constructed inter-harmonic measurement model, the parameter information is sequentially fitted and extracted to obtain the inter-harmonic frequency, comprising:

[0010] The parameter information is fitted based on the target function, and the frequency characteristics of the parameter information are determined according to the fitting result;

[0011] The frequency characteristics are input into the extraction model to obtain the inter-harmonic frequency.

[0012] In one of the embodiments, the fitting processing is performed on the parameter information based on the target function, and the frequency characteristic of the parameter information is determined according to the fitting result, including:

[0013] The regression function is constructed based on the parameter information, and the regression function includes the corresponding relationship between the parameter information and the parameter information mapped in the high-dimensional feature space function, the bias term and the weight vector;

[0014] The fitting processing is performed on the regression function and the target function constructed in advance, and the bias term and the weight vector in the regression function are adjusted according to the fitting result;

[0015] In the case where the fitting degree between the regression function and the target function meets the convergence condition, the frequency characteristic of the parameter information is determined from the regression function.

[0016] In one of the embodiments, the frequency characteristic is input into the extraction model to obtain the inter-harmonic frequency, including:

[0017] The frequency characteristic is decomposed to obtain a plurality of harmonic frequencies;

[0018] The inter-harmonic frequency is determined from the plurality of harmonic frequencies.

[0019] In one of the embodiments, the inter-harmonic frequency is determined from the plurality of harmonic frequencies, including:

[0020] The fundamental frequency of the power system is obtained, and the non-integer multiple frequency of the fundamental frequency is determined;

[0021] The non-integer multiple frequency of the plurality of harmonic frequencies is determined as the inter-harmonic frequency.

[0022] In one of the embodiments, the method further includes:

[0023] The inter-harmonic frequency is optimized to obtain an optimized inter-harmonic frequency;

[0024] Correspondingly, the inter-harmonic of the power system is determined based on the inter-harmonic frequency, including:

[0025] The inter-harmonic of the power system is determined based on the optimized inter-harmonic frequency.

[0026] In a second aspect, the present application also provides an inter-harmonic measurement device based on a power system, including:

[0027] The acquisition module is configured to acquire parameter information of the power system by using a wavelet transform algorithm;

[0028] The processing module is configured to sequentially perform fitting processing and extraction processing on the parameter information based on a pre-constructed inter-harmonic measurement model to obtain an inter-harmonic frequency;

[0029] The determining module is configured to determine the inter-harmonic of the power system based on the inter-harmonic frequency.

[0030] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0031] The parameter information of the power system is collected by using a wavelet transform algorithm;

[0032] The parameter information is sequentially subjected to fitting processing and extraction processing based on a pre-constructed inter-harmonic measurement model, so as to obtain the inter-harmonic frequency;

[0033] The inter-harmonic of the power system is determined based on the inter-harmonic frequency.

[0034] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the following steps when executed by a processor:

[0035] The parameter information of the power system is collected by using a wavelet transform algorithm;

[0036] The parameter information is sequentially subjected to fitting processing and extraction processing based on a pre-constructed inter-harmonic measurement model, so as to obtain the inter-harmonic frequency;

[0037] The inter-harmonic of the power system is determined based on the inter-harmonic frequency.

[0038] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, and the computer program implements the following steps when executed by a processor:

[0039] The parameter information of the power system is collected by using a wavelet transform algorithm;

[0040] The parameter information is sequentially subjected to fitting processing and extraction processing based on a pre-constructed inter-harmonic measurement model, so as to obtain the inter-harmonic frequency;

[0041] The inter-harmonic of the power system is determined based on the inter-harmonic frequency.

[0042] The above inter-harmonic measurement method, device and equipment based on the power system first collect the parameter information of the power system by using a wavelet transform algorithm; then sequentially subject the parameter information to fitting processing and extraction processing based on a pre-constructed inter-harmonic measurement model, so as to obtain the inter-harmonic frequency; finally determine the inter-harmonic of the power system based on the inter-harmonic frequency. Traditional technologies usually use optimal control methods to quickly identify and measure harmonics and inter-harmonics, but this requires high-performance compensation devices, which rely on expensive power electronic components and complex control systems, especially in large-scale applications, the hardware cost is very high. However, the method of the present application does not require these compensation devices, thereby effectively reducing the hardware cost. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is an internal structural diagram of a computer device in one embodiment;

[0045] Figure 2 This is a flowchart illustrating an interharmonic measurement method based on a power system in one embodiment;

[0046] Figure 3 This is a flowchart illustrating an interharmonic measurement method based on a power system in another embodiment;

[0047] Figure 4 This is a flowchart illustrating an interharmonic measurement method based on a power system in another embodiment;

[0048] Figure 5 This is a flowchart illustrating an interharmonic measurement method based on a power system in another embodiment;

[0049] Figure 6 This is a flowchart illustrating an interharmonic measurement method based on a power system in another embodiment;

[0050] Figure 7 This is a structural block diagram of an interharmonic measurement device based on a power system in one embodiment. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0052] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 1As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capability. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data in the process of measuring interharmonic based on the power system. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with the terminal outside through network connection. The computer program is executed by the processor to realize a method for measuring interharmonic based on the power system.

[0053] Those skilled in the art can understand that, Figure 1 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or less components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0054] In an exemplary embodiment, as Figure 2 shown, a method for measuring interharmonic based on the power system is provided. The method is applied to the computer device in Figure 1 as an example, including the following steps 201 to 203. Among them:

[0055] Step 201, using wavelet transform algorithm to collect parameter information of power system.

[0056] Among them, the wavelet function corresponding to the wavelet transform algorithm can use Morlet complex wavelet, which has good time-frequency localization characteristics, can effectively capture the change of different frequency components in power system signal with time, and is helpful to accurately extract related parameter information subsequently.

[0057] In the embodiments of the present application, first, a wavelet function suitable for analyzing the characteristics of power system signals needs to be selected. For the selected wavelet function, the range and step of its related parameters are reasonably determined. For example, for the scale parameter and the translation parameter in the wavelet transform process, they need to be set in combination with the actual situation of the power system signals. The scale parameter will affect the analysis accuracy of different frequency components. A smaller scale is used for focusing on the analysis of high frequency components, and a larger scale is beneficial for the analysis of low frequency components. The translation parameter is related to the coverage and analysis accuracy of the relevant signals in the power system in the time dimension. The appropriate value range and step size are determined according to the signal length and the desired time resolution.

[0058] Then, the voltage or current signals in the power system can be obtained by using a data acquisition device. These signals carry rich frequency-related information under the operating state of the power system. The selected and configured wavelet transform algorithm is used to process the collected signals as raw data. Through the wavelet transform algorithm, the original power system signals are decomposed and converted, and parameter information reflecting the characteristic intensity of the signals at different frequencies and time positions is extracted, providing basic data support for the application of the subsequent inter-harmonic measurement model.

[0059] In some embodiments, the wavelet transform method is used to collect the operating frequency signals of the distributed energy access power system. The continuous wavelet transform of the power system frequency signal is represented as:

[0060] (1)

[0061] wherein, is the scaling and translation of the Morlet complex wavelet, is the scale parameter, is the displacement parameter, and t is the time.

[0062] The Morlet complex wavelet is selected as the mother wavelet of the adjustable window continuous wavelet transform of the power system operating frequency signal. The frequency domain expression of the Morlet complex wavelet function is:

[0063] (2)

[0064] wherein, represents the center frequency of the frequency band of the mother wavelet; represents the bandwidth of the mother wavelet function. The larger the bandwidth, the narrower the frequency passband of the bandpass filter, and the smaller the influence of the band aliasing, is the frequency.

[0065] In step 202, the parameter information is sequentially fitted and extracted based on the pre-constructed inter-harmonic measurement model, and the inter-harmonic frequency is obtained.

[0066] In the embodiments of the present application, the parameter information is input into the pre-constructed inter-harmonic measurement model, and the inter-harmonic measurement model starts to perform matching analysis on the input parameter information according to its built-in algorithms and rules. In this process, the inter-harmonic measurement model will try to find the correlation and matching degree between the input parameter information and different inter-harmonic conditions according to the existing knowledge and experience mode of the power system inter-harmonic. For example, the inter-harmonic measurement model will determine which inter-harmonic characteristic mode the frequency variation characteristics and signal intensity distribution in the parameter information conform to, so as to gradually determine the potential relationship between the data and the inter-harmonic.

[0067] In order to make the processing result of the inter-harmonic measurement model on the input parameter information more consistent with the actual inter-harmonic condition, iteration optimization is needed. In each iteration process, the inter-harmonic measurement model adjusts some adjustable parameters (which may involve weight allocation of different frequency characteristics, threshold setting of signal characteristic judgment, etc.) in itself according to the current matching analysis situation, so as to optimize the processing effect of the inter-harmonic measurement model on the data. This iteration process is repeated constantly until the processing of the inter-harmonic measurement model on the input parameter information reaches a relatively stable and expected state, that is, the model can reflect the inter-harmonic related characteristic information as accurately as possible according to the input data, and complete the fitting processing stage.

[0068] After completing the fitting processing, the potential inter-harmonic characteristics in the output result of the inter-harmonic measurement model are identified. Since the inter-harmonic has characteristics different from the conventional harmonic (such as integer multiple frequency components of the fundamental frequency), for example, its frequency is a non-integer multiple of the fundamental frequency, by carefully combing and analyzing the frequency-related characteristics in the model output result, those parts conforming to the inter-harmonic frequency characteristics are marked. For example, if the power system fundamental frequency is 50Hz, the frequency components of 75Hz, 125Hz and other non-integer multiples of 50Hz will be focused on and preliminarily screened out.

[0069] In some embodiments, the preliminarily marked potential inter-harmonic characteristic information can also be further screened and verified. This can involve comparing data collected at different time points, referring to the current running state of the power system and other factors, excluding some misjudgment caused by interference or error, determining the frequency components that really belong to the inter-harmonic, and finally obtaining the accurate inter-harmonic frequency.

[0070] Step 203, determining the inter-harmonic of the power system based on the inter-harmonic frequency.

[0071] In the embodiments of the present application, a reasonable inter-harmonic frequency screening range is set according to the fundamental frequency of the power system. For example, for a common power system with a given fundamental frequency, it is specified that the inter-harmonic frequency is usually in a certain frequency interval corresponding to a non-integer multiple of the fundamental frequency, which is used as a preliminary judgment basis to distinguish the possible inter-harmonic frequency from the conventional harmonic frequency.

[0072] For the identified inter-harmonic frequency, further search for other key parameters corresponding thereto, such as amplitude, phase, etc. By combining these related parameters with the inter-harmonic frequency, the specific state of the inter-harmonic in the power system is determined, thereby determining the existence of the inter-harmonic in the power system.

[0073] In the above inter-harmonic measurement method based on the power system, the parameter information of the power system is first collected by using the wavelet transform algorithm; then the parameter information is sequentially fitted and extracted based on the pre-constructed inter-harmonic measurement model to obtain the inter-harmonic frequency; finally, the inter-harmonic of the power system is determined based on the inter-harmonic frequency. Traditional technology usually uses an optimal control method to quickly identify and measure harmonics and inter-harmonics, but this requires high-performance compensation devices, which rely on expensive power electronic components and complex control systems, especially in large-scale applications, the hardware cost is very high. The method of the present application does not require these compensation devices, thereby effectively reducing the hardware cost.

[0074] In an exemplary embodiment, the inter-harmonic measurement model includes a target function and an extraction model, and on this basis, the target function is a function with the goal of minimizing risk, as shown in Figure 3 The above "fitting and extraction processing of the parameter information based on the pre-constructed inter-harmonic measurement model" includes steps 301 to 302. Wherein:

[0075] Step 301, fitting the parameter information based on the target function, and determining the frequency characteristics of the parameter information according to the fitting result.

[0076] In the embodiments of the present application, first, the target function in the inter-harmonic measurement model is determined, which aims to minimize the risk, so as to make the target function achieve the best matching effect on the input parameter information. The power system parameter information obtained by wavelet transform is introduced into the action range of the target function, so that it becomes the object of analysis and optimization of the target function, and establishes data association for the subsequent processing process.

[0077] The objective function starts to perform feature matching operation on the input parameter information according to its preset optimization direction and rules. It analyzes various features contained in the parameter information, such as the frequency variation trend of the parameter information in different time intervals, the intensity distribution characteristics of different frequency components, and then determines the matching point between these features and the ideal inter-harmonic related features expected by the objective function according to the requirement of minimizing the risk. In this process, the objective function measures the closeness of the parameter information to the preset inter-harmonic mode from multiple dimensions, and continuously adjusts the analysis angle to find the feature correlation mode that best reflects the fitting effect.

[0078] Through continuous feature matching and adjustment, the objective function gradually tends to reach the state of minimizing the risk. In the optimal fitting state, the frequency characteristics of the parameter information are determined. These frequency characteristics are the key performances closely related to the inter-harmonic and best reflecting the existence and characteristics of the inter-harmonic after being screened and optimized by the objective function, such as the concentrated reflection of signal characteristics in certain specific frequency intervals, the relatively stable correlation mode between different frequency components, etc.

[0079] In step 302, the frequency characteristics are input into the extraction model to obtain the inter-harmonic frequency.

[0080] In the embodiments of the present application, the frequency characteristics of the parameter information determined in the fitting processing stage are input into the pre-constructed extraction model.

[0081] After receiving the frequency characteristic data, the extraction model analyzes the input frequency characteristics according to the inter-harmonic frequency judgment rules and algorithm logic set in it, so as to obtain the inter-harmonic frequency. For example, according to the characteristic that the inter-harmonic frequency is usually a non-integer multiple of the fundamental frequency, the frequency components that meet this condition are accurately located and screened out from the input frequency characteristics, while the regular harmonic frequency components that are integer multiples of the fundamental frequency and the abnormal frequency information that may be generated due to interference and other factors are excluded, so as to ensure that the screened frequency information accurately points to the inter-harmonic.

[0082] After the rigorous analysis and screening process of the extraction model, the frequency information that meets the characteristics of the inter-harmonic is finally determined and output, that is, the inter-harmonic frequency is obtained. These inter-harmonic frequencies can reflect the existence of the inter-harmonic in the power system and its specific performance in the frequency dimension, and provide key basic data support for subsequent further analysis of power quality, harmonic influence and other aspects of the power system.

[0083] In the above embodiments, based on the inter-harmonic measurement model with the objective function and the extraction model, the fitting processing and extraction processing can be effectively completed from the parameter information of the power system, and the inter-harmonic frequency can be accurately obtained.

[0084] In one exemplary embodiment, as Figure 4As shown, the above "fitting processing of the parameter information based on the target function, and determining the frequency characteristics of the parameter information according to the fitting result" includes steps 401 to 403. Among them:

[0085] Step 401, constructing a regression function based on the parameter information; the regression function includes the corresponding relationship between the parameter information and the parameter information mapping in the high-dimensional feature space function, the bias term and the weight vector.

[0086] Among them, the regression function aims to establish the corresponding relationship between the parameter information and the parameter information mapping in the high-dimensional feature space function, the bias term and the weight vector, and the purpose is to mine the characteristics related to the interharmonic hidden behind the parameter information through this corresponding relationship, and to prepare for subsequent analysis and determination of the interharmonic frequency.

[0087] In the embodiments of the present application, the specific structure of the regression function is established according to the demand of power system interharmonic analysis. This structure should reflect how to reasonably associate the parameter information with the high-dimensional feature space function, and determine the conversion and mapping path from the input parameter information to the corresponding representation in the high-dimensional feature space. For example, it is necessary to clearly stipulate how different components in the parameter information (such as frequency values at different time points, signal intensity, etc.) affect the value of the corresponding function in the high-dimensional feature space, so as to build a clear corresponding relationship architecture between the two.

[0088] After determining the basic structure and mapping logic, further improve the settings of the regression function to make it complete for practical application. This can include clearly defining various elements involved in the function, such as determining some intermediate variables that may be needed in the mapping process, initial settings of parameters, etc., so that the regression function can perform effective operation and analysis according to the given parameter information, and provide a standard and reasonable function framework for subsequent fitting processing with the target function.

[0089] Step 402, fitting the regression function and the pre-constructed target function, and adjusting the bias term and the weight vector in the regression function according to the fitting result.

[0090] Among them, the bias term is a fixed offset in the overall function mapping relationship, and the weight vector determines the relative importance of each component of the parameter information in constructing the corresponding relationship.

[0091] In the embodiments of the present application, the constructed regression function is connected with the pre-constructed target function, and the target function is a function with the goal of minimizing risk, which represents the optimal state that the regression function is expected to reach. By establishing this association, the fitting process is ready to start, and the regression function is adjusted and optimized towards the optimal fitting direction set by the target function.

[0092] According to the evaluation criteria and rules set by the objective function, the performance of the regression function in processing parameter information is analyzed and compared. The objective function examines the differences between the regression function output and the ideal state from multiple angles, such as determining whether the frequency characteristic trend reflected by the regression function is consistent with the expectations of the objective function, whether the response under different parameter information inputs meets expectations, etc. Through these detailed evaluations, the fitting degree between the current regression function and the objective function is determined, and the direction for adjustment and optimization is found.

[0093] According to the results of the fitting analysis, the bias term and weight vector in the regression function are adjusted to change the output characteristics of the regression function, so that it can better fit the expected fitting effect of the objective function. For example, if it is found that the output of the regression function in some frequency interval deviates greatly from the requirements of the objective function, the weight of the corresponding weight vector related to the frequency interval can be appropriately adjusted, and the value of the bias term can be appropriately changed to gradually reduce the deviation and improve the fitting degree.

[0094] Step 403, in the case where the fitting degree between the regression function and the objective function meets the convergence condition, the frequency characteristics of the parameter information are determined from the regression function.

[0095] The convergence condition is a pre-set standard for measuring whether the fitting process has reached an ideal stable state, such as setting the change amplitude of the fitting degree to be very small for several consecutive times, or the fitting degree reaching a certain specific threshold close to the optimal value, etc. By continuously comparing the current fitting degree with the convergence condition, it is determined whether the convergence requirement is met.

[0096] In the embodiments of the present application, during the process of continuously adjusting the regression function and fitting with the objective function, the fitting degree between the two is closely monitored.

[0097] When it is determined that the fitting degree between the regression function and the objective function meets the convergence condition, it means that the regression function has been optimized to a relatively stable and expected state. At this time, based on this optimized regression function, the frequency characteristics of the parameter information are extracted. These frequency characteristics are the key frequency characteristics that best reflect the relevant conditions of the power system harmonics after the regression function is optimized according to the fitting with the objective function, such as the frequency components with significant characteristics in a specific frequency interval, the stable correlation pattern between different frequencies, etc.

[0098] The above embodiments can complete the construction of the regression function based on the parameter information, the fitting process with the objective function, and the final determination of the frequency characteristics of the parameter information, laying a foundation for the smooth progress of the entire harmonics measurement process.

[0099] In an exemplary embodiment, as shown inFigure 5 As shown in the above, the "inputting the frequency feature into the extraction model to obtain the inter-harmonic frequency" includes steps 501 to 502. Among them:

[0100] Step 501, the frequency feature is decomposed to obtain a plurality of harmonic frequencies.

[0101] In the embodiment of the present application, the computer device decomposes the frequency feature, marks out the frequencies meeting the harmonic definition one by one from the complex frequency feature, separates out a plurality of harmonic frequencies step by step, and completes the preliminary decomposition work.

[0102] Then, the identified harmonic frequencies are sorted out, and the specific values of each harmonic frequency and some corresponding related features (such as the performance in different time intervals, if there are relevant data) are recorded. These harmonic frequencies are summarized to form a relatively complete harmonic frequency set, which clearly presents all the harmonic frequency conditions decomposed from the original frequency feature, facilitating further screening of the inter-harmonic frequency.

[0103] Step 502, the inter-harmonic frequency is determined from the plurality of harmonic frequencies.

[0104] In the embodiment of the present application, based on the inter-harmonic frequency determination standard, each frequency in the summarized harmonic frequency set is checked one by one. The conventional harmonic frequencies belonging to the integer multiples of the fundamental frequency are excluded from the set, and only the frequency components not meeting the condition of the integer multiples of the fundamental frequency are left, which are the potential inter-harmonic frequencies.

[0105] The potential inter-harmonic frequencies screened out are verified, considering the possible interference factors, data errors and other conditions, combining the current actual operation state of the power system and the relevant experience in the past and other factors, and confirming again that these frequencies indeed meet the characteristics of inter-harmonic, rather than misjudgment caused by abnormal conditions. After the verification process, the inter-harmonic frequency is finally determined.

[0106] Through the above embodiment, the frequency feature can be decomposed and processed in an orderly manner, and the inter-harmonic frequency can be accurately determined from a plurality of harmonic frequencies, providing strong support for the related analysis and research of the power system.

[0107] In an exemplary embodiment, as shown in the above, Figure 6 As shown in the above, the "determining the inter-harmonic frequency from the plurality of harmonic frequencies" includes steps 601 to 602. Among them:

[0108] Step 601, the fundamental frequency of the power system is obtained, and the non-integer multiple frequency of the fundamental frequency is determined.

[0109] Step 602, determine non-integer multiple frequencies in the plurality of harmonic frequencies as inter-harmonic frequencies.

[0110] In the embodiments of the present application, the voltage or current signals in the power system are collected by using the power signal collection device. The collected signals are processed by using the selected spectrum analysis method to obtain the corresponding spectrum information. In the spectrum information, there are usually multiple frequency peaks, and the frequency component with the lowest frequency and relatively large amplitude and obvious periodic characteristics is the fundamental frequency.

[0111] After obtaining the fundamental frequency, all frequency components obtained by the previous spectrum analysis are sorted. These frequency components are classified and sorted according to the multiple relationship with the fundamental frequency, and it is clear which frequency is an integer multiple of the fundamental frequency (belongs to the conventional harmonic frequency) and which frequency is not an integer multiple of the fundamental frequency, which prepares for the subsequent accurate screening of inter-harmonic frequencies.

[0112] According to the definition of inter-harmonic, that is, it is a non-integer multiple of the fundamental frequency, all frequency components after sorting are screened. The frequency components that do not meet the integer multiple relationship of the fundamental frequency are extracted separately. These extracted frequencies are potential inter-harmonic frequencies, and the screening work based on the multiple relationship is preliminarily completed.

[0113] Finally, the potential inter-harmonic frequencies screened out are further verified, considering various factors that may exist in the actual operation environment of the power system, such as signal interference, device characteristics and the influence of frequency measurement, to avoid misjudgment caused by these factors. By combining the current actual operation state of the power system, referring to the experience data of similar situations in the past, and other comprehensive judgments, it is confirmed that these screened frequencies are indeed frequencies that meet the real characteristics of inter-harmonic, and finally they are determined as inter-harmonic frequencies.

[0114] Through the above embodiments, the fundamental frequency of the power system can be obtained in order and accurately, and the non-integer multiple frequencies of the fundamental frequency are determined, and the non-integer multiple frequencies in the plurality of harmonic frequencies are determined as inter-harmonic frequencies, thereby laying a foundation for comprehensively mastering the harmonic condition of the power system.

[0115] In an exemplary embodiment, the above method further comprises:

[0116] Optimizing the inter-harmonic frequency to obtain an optimized inter-harmonic frequency.

[0117] Correspondingly, based on the inter-harmonic frequency, the inter-harmonic of the power system is determined, including:

[0118] Based on the optimized inter-harmonic frequency, the inter-harmonic of the power system is determined.

[0119] In the embodiments of the present application, first, the acquired inter-harmonic frequencies are comprehensively evaluated for data quality. It is checked whether there are obvious outliers in the inter-harmonic frequencies, for example, some frequency values are too different from the overall data distribution, or the frequency range does not conform to the logic of normal operation of the power system, etc.

[0120] Then, according to the results of the data quality evaluation, the obviously abnormal inter-harmonic frequency data is identified and removed. The abnormal data may be caused by interference in the signal acquisition process, temporary failure of the measurement equipment, etc. If these abnormal values are retained, it will affect the subsequent accurate analysis of the inter-harmonic situation. By setting reasonable abnormality judgment criteria, for example, based on historical normal frequency range, common inter-harmonic frequency interval of the same type of power system, etc., the frequency values beyond the reasonable range are removed from the data set.

[0121] Through the above embodiments, the inter-harmonic frequencies can be effectively optimized, and the inter-harmonic situation in the power system can be accurately determined based on the optimized inter-harmonic frequencies, which provides strong support for subsequent work such as operation analysis and power quality evaluation of the power system.

[0122] According to some embodiments of the present application, a method for measuring inter-harmonic based on a power system is provided. Taking the method applied to a computer device as an example, it can include the following steps:

[0123] Step 1, using a wavelet transform algorithm to collect parameter information of the power system.

[0124] Step 2, constructing a regression function based on the parameter information. The regression function includes the corresponding relationship between the parameter information, the parameter information mapped in the high-dimensional feature space function, the bias term and the weight vector.

[0125] Step 3, fitting the regression function and the pre-constructed target function, and adjusting the bias term and the weight vector in the regression function according to the fitting result.

[0126] Step 4, in the case that the fitting degree between the regression function and the target function meets the convergence condition, determining the frequency characteristics of the parameter information from the regression function.

[0127] Step 5, decomposing the frequency characteristics to obtain a plurality of harmonic frequencies.

[0128] Step 6, acquiring the fundamental frequency of the power system and determining the non-integer multiple frequency of the fundamental frequency.

[0129] Step 7, determining the non-integer multiple frequency in the plurality of harmonic frequencies as the inter-harmonic frequency.

[0130] Step 8, optimizing the inter-harmonic frequency to obtain the optimized inter-harmonic frequency.

[0131] Step 9, determining the inter-harmonic of the power system based on the optimized inter-harmonic frequency.

[0132] It should be understood that, although each step in the flowchart involved in each of the above embodiments is shown in sequence according to the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each of the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be alternately or alternately executed with at least part of other steps or steps or stages in other steps.

[0133] Based on the same inventive concept, the embodiments of the present application also provide a power system-based inter-harmonic measurement device for implementing the above-mentioned power system-based inter-harmonic measurement method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more power system-based inter-harmonic measurement device embodiments provided below can refer to the limitations of the power system-based inter-harmonic measurement method described above, which will not be repeated here.

[0134] In one exemplary embodiment, as shown in Figure 7 a power system-based inter-harmonic measurement device is provided, comprising: an acquisition module 701, a processing module 702 and a determination module 703, wherein:

[0135] The acquisition module 701 is configured to acquire parameter information of the power system using a wavelet transform algorithm.

[0136] The processing module 702 is configured to sequentially perform fitting processing and extraction processing on the parameter information based on a pre-constructed inter-harmonic measurement model, to obtain an inter-harmonic frequency.

[0137] The determination module 703 is configured to determine the inter-harmonic of the power system based on the inter-harmonic frequency.

[0138] In one embodiment, the inter-harmonic measurement model includes a target function and an extraction model, the target function is a function with the goal of minimizing risk, and the above processing module 702 is specifically configured to perform fitting processing on the parameter information based on the target function, and determine the frequency characteristics of the parameter information according to the fitting result; input the frequency characteristics into the extraction model to obtain the inter-harmonic frequency.

[0139] In an embodiment, the processing module 702 described above is specifically configured to construct a regression function based on the parameter information; the regression function includes a corresponding relationship between the parameter information and a mapping of the parameter information in a high-dimensional feature space function, a bias term, and a weight vector; the regression function and a pre-constructed target function are subjected to fitting processing, and the bias term and the weight vector in the regression function are adjusted according to a fitting result; in a case where a fitting degree between the regression function and the target function meets a convergence condition, the frequency feature of the parameter information is determined from the regression function.

[0140] In an embodiment, the processing module 702 described above is specifically configured to input the frequency feature into an extraction model to obtain an inter-harmonic frequency, including: performing decomposition processing on the frequency feature to obtain a plurality of harmonic frequencies; and determining the inter-harmonic frequency from the plurality of harmonic frequencies.

[0141] In an embodiment, the processing module 702 described above is specifically configured to obtain a fundamental frequency of the power system and determine a non-integer multiple frequency of the fundamental frequency; and determine the non-integer multiple frequency in the plurality of harmonic frequencies as the inter-harmonic frequency.

[0142] In an embodiment, the device described above further includes:

[0143] The optimization module 704 is configured to perform optimization processing on the inter-harmonic frequency to obtain an optimized inter-harmonic frequency; and correspondingly, determine the inter-harmonic of the power system based on the inter-harmonic frequency, including: determining the inter-harmonic of the power system based on the optimized inter-harmonic frequency.

[0144] The various modules in the inter-harmonic measurement device for the power system described above can be realized by software, hardware, and combinations thereof, in whole or in part. The various modules described above can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so as to be called and executed by a processor to perform the operations corresponding to the various modules.

[0145] In an exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0146] Parameter information of the power system is collected by using a wavelet transform algorithm;

[0147] The parameter information is subjected to fitting processing and extraction processing in sequence based on a pre-constructed inter-harmonic measurement model to obtain an inter-harmonic frequency;

[0148] The inter-harmonic of the power system is determined based on the inter-harmonic frequency.

[0149] In one embodiment, the inter-harmonic measurement model comprises a target function and an extraction model, the target function is a function aiming at minimizing a risk, and the processor, when executing the computer program, further implements the following steps:

[0150] fitting processing is performed on the parameter information based on the target function, and a frequency characteristic of the parameter information is determined according to a fitting result;

[0151] The frequency characteristic is input into the extraction model, and an inter-harmonic frequency is obtained.

[0152] In one embodiment, the processor, when executing the computer program, further implements the following steps:

[0153] A regression function is constructed based on the parameter information; the regression function comprises a corresponding relationship between the parameter information and a high-dimensional feature space function to which the parameter information is mapped, a bias term and a weight vector;

[0154] The regression function and the pre-constructed target function are fitted, and the bias term and the weight vector in the regression function are adjusted according to a fitting result;

[0155] In a case where a fitting degree between the regression function and the target function meets a convergence condition, a frequency characteristic of the parameter information is determined from the regression function.

[0156] In one embodiment, the processor, when executing the computer program, further implements the following steps:

[0157] The frequency characteristic is decomposed to obtain a plurality of harmonic frequencies;

[0158] An inter-harmonic frequency is determined from the plurality of harmonic frequencies.

[0159] In one embodiment, the processor, when executing the computer program, further implements the following steps:

[0160] A fundamental frequency of the power system is obtained, and a non-integer multiple frequency of the fundamental frequency is determined;

[0161] The non-integer multiple frequency of the plurality of harmonic frequencies is determined as the inter-harmonic frequency.

[0162] In one embodiment, the processor, when executing the computer program, further implements the following steps:

[0163] The inter-harmonic frequency is optimized to obtain an optimized inter-harmonic frequency;

[0164] Correspondingly, based on the inter-harmonic frequency, the inter-harmonic of the power system is determined to comprise:

[0165] Based on the optimized inter-harmonic frequency, the inter-harmonic of the power system is determined.

[0166] In one embodiment, a computer readable storage medium is provided, having stored thereon a computer program, the computer program being executed by a processor to implement the following steps:

[0167] Parameter information of the power system is collected by using a wavelet transform algorithm;

[0168] The parameter information is sequentially fitted and extracted based on a pre-constructed inter-harmonic measurement model to obtain an inter-harmonic frequency;

[0169] Based on the inter-harmonic frequency, an inter-harmonic of the power system is determined.

[0170] In one embodiment, the inter-harmonic measurement model includes a target function and an extraction model, the target function is a function aiming to minimize risk, and the computer program is executed by the processor to further implement the following steps:

[0171] The parameter information is fitted based on the target function, and a frequency feature of the parameter information is determined according to a fitting result;

[0172] The frequency feature is input into the extraction model to obtain the inter-harmonic frequency.

[0173] In one embodiment, the computer program is executed by the processor to further implement the following steps:

[0174] A regression function is constructed based on the parameter information; the regression function includes a corresponding relationship between the parameter information and the parameter information mapped in a high-dimensional feature space function, a bias term and a weight vector;

[0175] The regression function and the pre-constructed target function are fitted, and the bias term and the weight vector in the regression function are adjusted according to a fitting result;

[0176] In a case where a fitting degree between the regression function and the target function meets a convergence condition, the frequency feature of the parameter information is determined from the regression function.

[0177] In one embodiment, the computer program is executed by the processor to further implement the following steps:

[0178] The frequency feature is decomposed to obtain a plurality of harmonic frequencies;

[0179] The inter-harmonic frequency is determined from the plurality of harmonic frequencies.

[0180] In one embodiment, the computer program is executed by the processor to further implement the following steps:

[0181] A fundamental frequency of the power system is obtained, and a non-integer multiple frequency of the fundamental frequency is determined;

[0182] The non-integer multiple frequency of the plurality of harmonic frequencies is determined as the inter-harmonic frequency.

[0183] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0184] optimizing the inter-harmonic frequency to obtain an optimized inter-harmonic frequency;

[0185] Correspondingly, the inter-harmonic of the power system is determined based on the inter-harmonic frequency, including:

[0186] The inter-harmonic of the power system is determined based on the optimized inter-harmonic frequency.

[0187] In one embodiment, a computer program product is provided, including a computer program which, when executed by the processor, implements the following steps:

[0188] The parameter information of the power system is collected by using a wavelet transform algorithm;

[0189] The parameter information is sequentially fitted and extracted based on a pre-constructed inter-harmonic measurement model to obtain the inter-harmonic frequency;

[0190] The inter-harmonic of the power system is determined based on the inter-harmonic frequency.

[0191] In one embodiment, the inter-harmonic measurement model includes a target function and an extraction model, the target function is a function with the goal of minimizing risk, and the computer program, when executed by the processor, further implements the following steps:

[0192] The parameter information is fitted based on the target function, and the frequency characteristics of the parameter information are determined according to the fitting result;

[0193] The frequency characteristics are input into the extraction model to obtain the inter-harmonic frequency.

[0194] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0195] A regression function is constructed based on the parameter information; the regression function includes the corresponding relationship between the parameter information and the parameter information mapped in a high-dimensional feature space function, a bias term and a weight vector;

[0196] The regression function and the pre-constructed target function are fitted, and the bias term and the weight vector in the regression function are adjusted according to the fitting result;

[0197] In the case that the fitting degree between the regression function and the target function meets the convergence condition, the frequency characteristics of the parameter information are determined from the regression function.

[0198] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0199] The frequency characteristics are decomposed to obtain a plurality of harmonic frequencies;

[0200] The inter-harmonic frequency is determined from the plurality of harmonic frequencies.

[0201] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0202] The fundamental frequency of the power system is obtained, and a non-integer multiple frequency of the fundamental frequency is determined;

[0203] The non-integer multiple frequency of the plurality of harmonic frequencies is determined as the inter-harmonic frequency.

[0204] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0205] The inter-harmonic frequency is optimized to obtain an optimized inter-harmonic frequency;

[0206] Correspondingly, based on the inter-harmonic frequency, the inter-harmonic of the power system is determined, including:

[0207] Based on the optimized inter-harmonic frequency, the inter-harmonic of the power system is determined.

[0208] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. The non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. The volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0209] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the present application.

[0210] The above-described embodiments are merely illustrative of several embodiments of the present application, and the description is relatively specific and detailed, but should not be understood as a limitation on the scope of the patent. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of protection of the present application should be subject to the appended claims.

Claims

1. A method for measuring interharmonics based on a power system, characterized by, The method comprises: collecting parameter information of a power system by using a wavelet transform algorithm; performing fitting processing and extraction processing on the parameter information in sequence based on a pre-constructed interharmonic measurement model to obtain an interharmonic frequency; determining an interharmonic of the power system based on the interharmonic frequency; the interharmonic measurement model comprises a target function and an extraction model, the target function is a function with the goal of minimizing risk, and the performing of the fitting processing and the extraction processing on the parameter information in sequence based on the pre-constructed interharmonic measurement model to obtain an interharmonic frequency comprises: constructing a regression function based on the parameter information; the regression function comprises a corresponding relationship between the parameter information and a high-dimensional feature space function, a bias term and a weight vector to which the parameter information is mapped; performing fitting processing on the regression function and the pre-constructed target function, and adjusting the bias term and the weight vector in the regression function according to the fitting result; in a case where a fitting degree between the regression function and the target function meets a convergence condition, determining a frequency feature of the parameter information from the regression function; performing decomposition processing on the frequency feature to obtain a plurality of harmonic frequencies; obtaining a fundamental frequency of the power system and determining a non-integer multiple frequency of the fundamental frequency; determining the non-integer multiple frequency in the plurality of harmonic frequencies as the interharmonic frequency.

2. The method of claim 1, wherein, The method further comprises: performing optimization processing on the interharmonic frequency to obtain an optimized interharmonic frequency; correspondingly, the determining of the interharmonic of the power system based on the interharmonic frequency comprises: determining the interharmonic of the power system based on the optimized interharmonic frequency.

3. An interharmonic measurement device based on a power system, characterized by, The device comprises: a collection module configured to collect parameter information of a power system by using a wavelet transform algorithm; a processing module configured to perform fitting processing and extraction processing on the parameter information in sequence based on a pre-constructed interharmonic measurement model to obtain an interharmonic frequency; a determination module configured to determine an interharmonic of the power system based on the interharmonic frequency; the interharmonic measurement model comprises a target function and an extraction model, the target function is a function with the goal of minimizing risk, and the processing module is specifically configured to construct a regression function based on the parameter information; the regression function comprises a corresponding relationship between the parameter information and a high-dimensional feature space function, a bias term and a weight vector to which the parameter information is mapped; perform fitting processing on the regression function and the pre-constructed target function, and adjust the bias term and the weight vector in the regression function according to the fitting result; in a case where a fitting degree between the regression function and the target function meets a convergence condition, determine a frequency feature of the parameter information from the regression function; perform decomposition processing on the frequency feature to obtain a plurality of harmonic frequencies; obtain a fundamental frequency of the power system and determine a non-integer multiple frequency of the fundamental frequency; determine the non-integer multiple frequency in the plurality of harmonic frequencies as the interharmonic frequency.

4. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor implements the steps of the method of any one of claims 1 to 2 when executing the computer program.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, which when executed by a processor, implements the steps of the method of any one of claims 1 to 2.

6. A computer program product comprising a computer program, characterized in that, The computer program, which when executed by a processor, implements the steps of the method of any one of claims 1 to 2.

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