Power distribution network digital power quality detection method and system and storage medium

Abstract

The embodiment of the application provides a kind of power distribution network digital power quality detection method, system and storage medium, belong to power quality detection technical field.The detection method includes: obtaining the power quality parameter in current preset time period in power distribution network and power quality standard threshold;The power quality fluctuation characteristics of current power distribution network is obtained by the power quality parameter in current preset time period in power distribution network and power quality standard threshold, and the quality reference value of current power distribution network can be obtained according to the power quality fluctuation characteristics, so as to obtain the quality reference value of the continuous multiple preset time periods of power distribution network, finally, the power quality of power distribution network is evaluated in combination with multiple quality references;The mode of evaluating power quality using the quality reference value of continuous multiple preset time periods can fully consider the time sequence influence before and after power fluctuation, to improve the accuracy and reliability of power quality evaluation.

Description

Technical Field

[0001] This invention relates to the field of power quality detection technology, and more specifically to a method, system, and storage medium for detecting digital power quality in power distribution networks. Background Technology

[0002] The power distribution network is a crucial component of the power system. Its primary task is to transmit high-voltage electrical energy through transformers, distribution lines, and other facilities to every end user, ensuring a reliable power supply. In maintaining the safe and stable operation of the distribution network, power quality is one of its most important performance indicators.

[0003] In existing technologies, power quality metrics typically include voltage deviation, frequency deviation, voltage sag, and harmonics. Given that power quality involves multiple metrics, current evaluation methods generally employ a weighted average of these metrics. However, while this approach provides a relatively balanced consideration of the impact of each metric and is real-time, it fails to account for temporal factors, leading to low accuracy and poor reliability in power quality assessment.

[0004] In the process of realizing this invention, the inventors of this application discovered that the above-mentioned solutions in the prior art have the defects of low accuracy and poor reliability in power quality evaluation. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, and storage medium for detecting digital power quality in a distribution network. This method, system, and storage medium have high evaluation accuracy and high reliability.

[0006] To achieve the above objectives, embodiments of the present invention provide a method for detecting the digital power quality of a distribution network, comprising:

[0007] Obtain the power quality parameters and power quality standard thresholds in the distribution network within the current preset time period;

[0008] The power quality fluctuation characteristics of the current distribution network are obtained based on the power quality parameters and the corresponding power quality standard thresholds.

[0009] The power quality reference value of the current distribution network is obtained based on the power quality fluctuation characteristics of the current distribution network.

[0010] Obtain quality reference values ​​for the power distribution network over multiple consecutive preset time periods;

[0011] The power quality of the current distribution network is evaluated based on multiple quality reference values.

[0012] Optionally, the power quality parameters include: voltage deviation, frequency deviation, harmonics, voltage sag, three-phase imbalance, and voltage flicker.

[0013] Optionally, obtaining the current power quality fluctuation characteristics of the distribution network based on the power quality parameters and the corresponding power quality standard thresholds includes:

[0014] The voltage deviation fluctuation characteristics of the current distribution network are obtained according to formula (1).

[0015]

[0016] Where, ΔU i U represents the voltage deviation fluctuation characteristics of the distribution network during the current preset time period i. i U represents the voltage of the distribution network during the current preset time period i. i0 Let ΔU be the rated voltage of the power distribution network during the current preset time period i. * The standard threshold for voltage deviation in the power distribution network;

[0017] The frequency deviation fluctuation characteristics of the current distribution network are obtained according to formula (2).

[0018]

[0019] Where, Δf i f represents the frequency deviation fluctuation characteristics of the distribution network during the current preset time period i. i f is the frequency of the distribution network in the current preset time period i. i0 Let Δf be the rated frequency of the distribution network during the current preset time period i. * The standard threshold value for frequency deviation of the power distribution network;

[0020] The harmonic fluctuation characteristics of the current distribution network are obtained according to formula (3).

[0021] ΔTHD i =THD i / ΔTHD * (3)

[0022] Among them, ΔTHD i The harmonic fluctuation characteristics of the power distribution network during the current preset time period i, THD i ΔTHD is the total harmonic distortion rate of the power distribution network during the current preset time period i. * The standard threshold for the total harmonic distortion rate of the power distribution network is denoted as .

[0023] Optionally, obtaining the current power quality fluctuation characteristics of the distribution network based on the power quality parameters and the corresponding power quality standard threshold further includes:

[0024] The voltage sag fluctuation characteristics of the current distribution network are obtained according to formula (4).

[0025] ΔT i =(T i·E -T i·S ) / ΔT * (4)

[0026] Where, ΔT i T represents the voltage sag fluctuation characteristics of the distribution network during the current preset time period i. i·E T is the end time when the voltage of the distribution network is less than the rated voltage in the current preset time period i. i·S ΔT is the starting time when the voltage of the distribution network is less than the rated voltage in the current preset time period i. * The standard threshold for voltage sag time in the power distribution network;

[0027] The three-phase voltage fluctuation characteristics of the current distribution network are obtained according to formula (5).

[0028]

[0029] Where, ΔU ub·i U represents the three-phase voltage fluctuation characteristics of the distribution network during the current preset time period i. ub·i The three-phase voltage imbalance rate of the power distribution network during the current preset time period i. The standard threshold for the three-phase voltage imbalance rate of the power distribution network;

[0030] The voltage flicker fluctuation characteristics of the current distribution network are obtained according to formula (6).

[0031] ΔP st·i =P st·i / P st * (6)

[0032] Wherein, ΔP st·i P represents the voltage flicker fluctuation characteristics of the current distribution network during the current preset time period i. st·i P represents the voltage flicker index of the current distribution network during the current preset time period i. st * This is the standard threshold for voltage flicker in the power distribution network.

[0033] Optionally, obtaining the current power quality reference value of the distribution network based on the current power quality fluctuation characteristics of the distribution network includes:

[0034] Each power quality fluctuation feature of the distribution network is arranged in ascending order to form a power quality fluctuation feature matrix Z. 6×1 ;

[0035] The decision weight for each power quality fluctuation characteristic is obtained according to formula (7).

[0036]

[0037] Where, μ j σ is the decision weight for the j-th power quality fluctuation feature, α is the basic decision coefficient of the power quality fluctuation feature, j is the index of the power quality fluctuation feature, and j is an integer number.

[0038] A decision weight matrix R is constructed based on the decision weight of each power quality fluctuation characteristic. 1×6 .

[0039] Optionally, obtaining the power quality reference value of the current distribution network based on the current power quality fluctuation characteristics of the distribution network further includes:

[0040] The quality reference value of the current distribution network is obtained according to formula (8).

[0041] Q i =Z 6×1 ×R 1×6 (8)

[0042] Among them, Q i This is the quality reference value of the power distribution network during the current preset time period i.

[0043] Optionally, obtaining quality reference values ​​for the distribution network over multiple consecutive preset time periods includes:

[0044] Obtain the power quality fluctuation characteristic matrix of the distribution network during the current preset time period i.

[0045] Obtain the decision weight matrix of the power quality of the distribution network in the current preset time period i.

[0046] The power quality decision weight matrix of the distribution network in the current preset time period i is updated according to formula (9).

[0047]

[0048] in, Power quality parameter A y The decision weight of A in the current preset time period i. y·i·j Power quality parameter A y The value of sorting j in the current preset time period i, where τ is the gradient of change and ρ is the base value of change;

[0049] The quality reference value of the power distribution network in the current preset time period i is obtained according to formula (8).

[0050] Optionally, evaluating the current power quality of the distribution network based on multiple quality reference values ​​includes:

[0051] The quality evaluation value of the current distribution network is obtained according to formula (10).

[0052]

[0053] in, Here, i represents the current quality evaluation value of the distribution network, where i is an integer number and I represents the number of consecutive preset time periods.

[0054] Determine whether the current quality evaluation value of the power distribution network is greater than the evaluation threshold;

[0055] If the current power quality evaluation value of the power distribution network is greater than the evaluation threshold, the power quality of the current power distribution network is determined to be poor.

[0056] If the current power quality evaluation value of the distribution network is less than or equal to the evaluation threshold, the power quality of the current distribution network is determined to be excellent.

[0057] On the other hand, the present invention also provides a digital power quality detection system for power distribution networks, comprising:

[0058] The power quality parameter acquisition module is connected to multiple acquisition points in the distribution network to collect multiple power quality parameters in the distribution network.

[0059] The power quality evaluation module is communicatively connected to the power quality parameter acquisition module and is used to execute any of the detection methods described above.

[0060] In another aspect, the present invention also provides a computer-readable storage medium storing instructions for being read by a machine to cause the machine to perform any of the detection methods described above.

[0061] Through the above technical solution, the distribution network digital power quality detection method, system, and storage medium provided by the present invention obtain the power quality fluctuation characteristics of the current distribution network by using the power quality parameters and power quality standard thresholds of the distribution network within the current preset time period. Based on these power quality fluctuation characteristics, the current power quality reference value of the distribution network can be obtained, thereby obtaining the power quality reference values ​​of the distribution network for multiple consecutive preset time periods. Finally, the power quality of the distribution network is evaluated by combining multiple quality references. The method of evaluating power quality by using the quality reference values ​​of multiple consecutive preset time periods can fully consider the temporal effects before and after power fluctuations, thereby improving the accuracy and reliability of power quality evaluation.

[0062] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0063] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0064] Figure 1 This is a flowchart of a method for detecting digital power quality in a distribution network according to an embodiment of the present invention;

[0065] Figure 2 This is a flowchart illustrating the fluctuation characteristics of power quality parameters in a digital power quality detection method for distribution networks according to an embodiment of the present invention.

[0066] Figure 3 This is a flowchart of a method for obtaining quality reference values ​​in a digital power quality detection method for a distribution network according to an embodiment of the present invention;

[0067] Figure 4 This is a flowchart illustrating the acquisition of multiple consecutive quality reference values ​​in a method for detecting the digital power quality of a distribution network according to an embodiment of the present invention.

[0068] Figure 5 This is a flowchart illustrating a method for evaluating the power quality of a distribution network using digital power quality detection according to an embodiment of the present invention. Detailed Implementation

[0069] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0070] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0071] Figure 1 This is a flowchart of a method for detecting digital power quality in a distribution network according to an embodiment of the present invention. Figure 1 In this context, the detection method may include:

[0072] In step S10, the power quality parameters and power quality standard thresholds in the distribution network within the current preset time period are obtained. These power quality parameters may include voltage deviation, frequency deviation, harmonics, voltage sag, three-phase imbalance, and voltage flicker. Specifically, voltage deviation refers to the deviation between the voltage provided by the grid and the rated voltage; frequency deviation refers to the deviation between the grid frequency and the standard frequency; harmonics are higher-order harmonic components in the grid voltage or current waveform; voltage sag refers to the phenomenon where the voltage in the power system drops below the rated value within a certain time period; three-phase imbalance refers to the phenomenon of unbalanced three-phase current or voltage in a three-phase AC system; and voltage flicker refers to the brightness flickering phenomenon caused by voltage fluctuations in the power system, typically manifested as flickering lights or unstable light source brightness. The power quality standard thresholds are the thresholds for each power quality parameter when it is in a normal state.

[0073] In step S11, the power quality fluctuation characteristics of the current distribution network are obtained based on the power quality parameters and the corresponding power quality standard thresholds. Specifically, by combining the power quality parameters with their corresponding standard thresholds, the deviation of the power quality parameters from their rated values ​​can be determined, which represents the power quality fluctuation characteristics of each power quality parameter in the current distribution network.

[0074] In step S12, the power quality reference value of the current distribution network is obtained based on the power quality fluctuation characteristics of the current distribution network. Specifically, after obtaining each power quality fluctuation characteristic, each characteristic can be comprehensively considered to finally obtain the current power quality reference value of the distribution network, which is also the quality reference value for the current preset time period.

[0075] In step S13, quality reference values ​​for multiple consecutive preset time periods of the power distribution network are obtained. The multiple consecutive quality reference values ​​obtained using the above method reflect the fluctuations in power quality caused by time variations.

[0076] In step S14, the power quality of the current distribution network is evaluated based on multiple quality reference values. These multiple continuous quality reference values ​​exhibit continuity due to time variations, allowing the power quality of the distribution network to be evaluated based on these multiple reference values, thus fully considering the impact of time characteristics.

[0077] In steps S10 to S14, the power quality parameters and corresponding standard thresholds for a preset time period of the current distribution network are first obtained. Based on these standard thresholds, the fluctuation characteristics corresponding to each power quality parameter can be obtained. These fluctuation characteristics reflect the real-time state of power quality, and thus, a quality reference value for the preset time period can be obtained based on multiple power quality fluctuation characteristics. Furthermore, multiple consecutive quality reference values ​​in the distribution network are similarly obtained. Finally, the power quality of the distribution network is evaluated by combining these multiple quality reference values.

[0078] Traditional power quality assessment methods typically employ a weighted integration of various indicators. However, this approach provides a relatively balanced consideration of the impact of each indicator and is real-time, neglecting the temporal influence of these indicators. Consequently, the accuracy and reliability of power quality assessments are low. In this embodiment of the invention, a method that evaluates power quality using quality reference values ​​across multiple consecutive preset time periods fully considers the temporal impact of power fluctuations, thereby improving the accuracy and reliability of power quality assessments.

[0079] In this embodiment of the invention, after obtaining the power quality parameters and the corresponding power quality standard thresholds, the power quality fluctuation characteristics of each power quality parameter can be obtained through both. Specifically, the acquisition steps can be as follows: Figure 2 As shown. Specifically, in Figure 2 In addition, the detection method may also include:

[0080] In step S110, the voltage deviation fluctuation characteristics of the current distribution network are obtained according to formula (1).

[0081]

[0082] Where, ΔU i U represents the voltage deviation fluctuation characteristics of the distribution network during the current preset time period i. i U represents the voltage of the distribution network during the current preset time period i. i0 Let ΔU be the rated voltage of the distribution network during the current preset time period i. * This is the standard threshold for voltage deviation in the distribution network. Specifically, the standard threshold for voltage deviation is generally within the range of ±10%. Formula (1) uses an absolute value method, which can limit the voltage deviation to a positive number, that is, the standard threshold for voltage deviation is 0 to 10%. This method can facilitate the improvement of calculation accuracy and precision in the subsequent process of obtaining quality reference values.

[0083] In step S111, the frequency deviation fluctuation characteristics of the current distribution network are obtained according to formula (2).

[0084]

[0085] Where, Δf i f represents the frequency deviation fluctuation characteristics of the distribution network during the current preset time period i. i f is the frequency of the distribution network in the current preset time period i. i0 Let Δf be the rated frequency of the distribution network during the current preset time period i. * This refers to the standard threshold for frequency deviation in the distribution network. Specifically, the standard threshold for frequency deviation is generally within the range of ±0.5Hz.

[0086] In step S112, the harmonic fluctuation characteristics of the current distribution network are obtained according to formula (3).

[0087] ΔTHD i =THD i / ΔTHD * (3)

[0088] Among them, ΔTHD i The harmonic fluctuation characteristics of the distribution network during the current preset time period i, THD i Let ΔTHD be the total harmonic distortion rate of the distribution network during the current preset time period i. * This is the standard threshold for the total harmonic distortion (THD) rate of the distribution network. Specifically, the calculation method for the THD rate over a preset time period may include first acquiring the actual waveform of the current or voltage, converting the time-domain waveform to the frequency domain through Fourier transform, extracting the amplitude of each frequency component, calculating the amplitude of each harmonic frequency, and finally calculating the THD rate according to formula (11).

[0089]

[0090] Where THD is the total harmonic distortion, H1 is the amplitude of the fundamental frequency, and H2, H3, ... are the amplitudes of the various higher harmonic components (2nd, 3rd, ...). Specifically, the standard threshold for total harmonic distortion is generally 5%, meaning that fewer harmonics are better.

[0091] In step S113, the voltage sag fluctuation characteristics of the current distribution network are obtained according to formula (4).

[0092] ΔT i =(T i·E -T u·S ) / ΔT * (4)

[0093] Where, ΔT i T represents the voltage sag fluctuation characteristics of the distribution network during the current preset time period i. i·E T is the end time when the voltage in the distribution network is less than the rated voltage during the current preset time period i. i·S Let ΔT be the starting point when the voltage in the distribution network is lower than the rated voltage within the current preset time period i. * This refers to the standard threshold for voltage sag time in the distribution network. Specifically, a voltage sag is typically defined as a voltage drop exceeding 10%, while the standard threshold for voltage sag time is generally in the hundreds of milliseconds.

[0094] In step S114, the three-phase voltage fluctuation characteristics of the current distribution network are obtained according to formula (5).

[0095]

[0096] Where, ΔU ub·i U represents the three-phase voltage fluctuation characteristics of the distribution network during the current preset time period i. ub·i The three-phase voltage imbalance rate of the distribution network during the current preset time period i. This is the standard threshold for the three-phase voltage imbalance rate of the distribution network. Specifically, the calculation of the three-phase voltage imbalance rate is generally based on the amplitude of the three-phase voltage, which can be obtained according to formula (12).

[0097]

[0098] Among them, U ub U is the three-phase voltage imbalance rate. ub·max U is the maximum amplitude of the three-phase voltage. ub·min U is the minimum amplitude of the three-phase voltage. avg This represents the average amplitude of the three-phase voltage. The standard threshold for the three-phase voltage imbalance rate is typically 2%.

[0099] In step S115, the voltage flicker fluctuation characteristics of the current distribution network are obtained according to formula (6).

[0100] ΔP st·i =P st·i / P st * (6)

[0101] Wherein, ΔP st·i P represents the voltage flicker fluctuation characteristics of the current distribution network during the current preset time period i. st·i P represents the voltage flicker index of the current distribution network during the current preset time period i. st * This is the standard threshold for voltage flicker in the distribution network. Specifically, there are generally two voltage flicker indicators: short-term flicker and long-term flicker. This application focuses on converting short-term flicker, which can be calculated using formula (13).

[0102]

[0103] Among them, P st The voltage short-term flicker index is given by m, where m is the number of sampling points within the preset time period i, and V. q V represents the voltage fluctuation amplitude during time interval q (i.e., multiple smaller time intervals) within a preset time interval i. ref This is a reference voltage value. The standard threshold for voltage flicker is typically 1.0, and the short-term voltage flicker index P... st A value exceeding 1.0 can have a significant impact on the human eye.

[0104] In steps S110 to S115, after obtaining the power quality parameters and corresponding power quality standard thresholds, the fluctuation characteristics of each power quality parameter can be calculated. Specifically, when calculating the fluctuation characteristics of each power quality parameter, it is compared with the corresponding standard threshold to obtain the degree of fluctuation of each power quality parameter. Furthermore, each power quality parameter is normalized so that the value of each fluctuation characteristic is between 0 and 1, which facilitates the subsequent calculation of the quality reference value.

[0105] In this embodiment of the invention, after obtaining multiple power quality fluctuation characteristics, a power quality reference value for the distribution network can be obtained based on these characteristics. Specifically, the acquisition steps can be as follows: Figure 3 As shown. Specifically, in Figure 3 In addition, the detection method may also include:

[0106] In step S120, each power quality fluctuation characteristic of the distribution network is arranged in ascending order to form a power quality fluctuation characteristic matrix Z. 6×1 The power quality fluctuation characteristic matrix can be represented by formula (14).

[0107] Z 6×1 =[A1A2A3A4A5A3],(14)

[0108] Among them, A1, A2, A3, A4, A5, and A6 refer to the power quality fluctuation characteristics corresponding to the six power quality parameters.

[0109] In step S121, the decision weight of each power quality fluctuation characteristic is obtained according to formula (7).

[0110]

[0111] Where, μ j Let α be the decision weight for the j-th power quality fluctuation feature, σ be the basic decision coefficient for the power quality fluctuation feature, α be the weight gradient, and j be the index of the power quality fluctuation feature, where j is an integer. Specifically, based on the weight gradient, the decision weight for each power quality fluctuation feature can be obtained according to an arithmetic progression. This increases the weight of more unstable factors in the distribution network, i.e., those closer to the corresponding standard threshold, thus strengthening the proportion of power quality parameters with obvious fluctuation characteristics and improving the sensitivity of the quality reference value. Furthermore, for the value of j, considering the number of power quality parameters used in this application, j ≤ 6.

[0112] In step S122, a decision weight matrix R is constructed based on the decision weights of each power quality fluctuation characteristic.1×6 The decision weight matrix can be represented as shown in formula (15).

[0113]

[0114] In step S123, the current quality reference value of the distribution network is obtained according to formula (8).

[0115] Q i =Z 6×1 ×R 1×6 (8)

[0116] Among them, Q i This is the quality reference value of the distribution network during the current preset time period i.

[0117] In steps S120 to S123, the power quality fluctuations of the distribution network are first arranged in ascending order to form a power quality fluctuation feature matrix. Then, the decision weight of each power quality fluctuation feature is obtained, forming a decision weight matrix. Finally, the power quality reference value of the distribution network is calculated based on the power quality fluctuation feature matrix and the decision weight matrix. The quality reference value obtained in this way can fully reflect the power quality fluctuation characteristics, and thus accurately represent the power quality within the preset time period.

[0118] In this embodiment of the invention, after obtaining the quality reference value within the current preset time period, the same method is used to obtain quality reference values ​​within multiple consecutive preset time periods, so as to facilitate an effective and sufficient analysis of the power quality of the distribution network. The steps for obtaining the quality reference values ​​within multiple consecutive preset time periods can be as follows: Figure 4 As shown. Specifically, in Figure 4 In addition, the detection method may also include:

[0119] In step S130, the power quality fluctuation characteristic matrix of the distribution network in the current preset time period i is obtained.

[0120] In step S131, the decision weight matrix of power quality of the distribution network in the current preset time period i is obtained. For the preset time period when i=1, the decision weight matrix can be obtained according to formula (7). However, as the power quality parameters change continuously over time, that is, the preset time period when i>1, considering that some power quality parameters have large or small continuous fluctuations, it is necessary to update the decision weights of some power quality parameters so that the decision weight matrix can be more balanced and more accurately reflect the power quality.

[0121] In step S132, the decision weight matrix of power quality of the distribution network in the current preset time period i is updated according to formula (9).

[0122]

[0123] in, Power quality parameter A y The decision weight of A in the current preset time period i. y·i·j Power quality parameter A y In the current preset time period i, the value of sorting j (sorting of the power quality fluctuation feature matrix) is τ, which is the gradient of change and can generally be taken as 0.1-0.2. ρ is the base value of change and the number of power quality parameters, i.e., ρ = 6. Specifically, formula (9) fully considers that the fluctuation amplitude of the last three power quality parameters in the fluctuation feature matrix is ​​large, which can effectively increase the influence ratio of the last three power quality parameters in the fluctuation feature matrix, while reducing the influence ratio of the first three power quality parameters in the fluctuation feature matrix, so as to determine the current power quality more effectively and accurately. For power quality parameters whose decision weights have not been updated, the previous decision weight of the power quality parameter remains unchanged. In addition, formula (9) further increases the influence ratio of power quality parameters that are continuously stable in the last three or increase for multiple preset time periods, that is, it amplifies the proportion of continuous large fluctuation amplitude, thereby improving the evaluation accuracy of power quality.

[0124] In step S133, the quality reference value of the distribution network in the current preset time period i is obtained according to formula (8).

[0125] In steps S130 to S133, the power quality fluctuation characteristic matrix and decision weight matrix of the current distribution network in the preset time period i are obtained. These are then combined with the quality fluctuation characteristic matrix of the previous preset time period to update the current decision weight matrix, thus fully considering the impact of continuous fluctuations. Finally, the quality reference value for the current preset time period is obtained. This method can amplify the influence of power quality parameters with large fluctuations and reduce the influence of power quality parameters with small fluctuations, while fully considering the impact of large continuous fluctuations, to obtain a more accurate quality reference value for the current preset time period.

[0126] In this embodiment of the invention, after obtaining multiple consecutive quality reference values, the power quality of the current distribution network can be calculated by combining the multiple quality reference values. The specific calculation steps can be as follows: Figure 5 As shown. Specifically, in Figure 5 In addition, the detection method may also include:

[0127] In step S140, the current distribution network quality evaluation value is obtained according to formula (10).

[0128]

[0129] in, , where i is the current quality evaluation value of the distribution network, and I is the number of consecutive preset time periods.

[0130] In step S141, it is determined whether the current quality evaluation value of the distribution network is greater than the evaluation threshold.

[0131] In step S142, if the current power quality evaluation value of the distribution network is greater than the evaluation threshold, the power quality of the current distribution network is determined to be poor. Specifically, if the current power quality evaluation value of the distribution network is too high, it indicates that multiple or individual power quality parameters have large fluctuations, that is, the stability is poor, and in this case, the power quality of the current distribution network can be determined to be poor.

[0132] In step S143, if the current power quality evaluation value of the distribution network is less than or equal to the evaluation threshold, the power quality of the current distribution network is determined to be excellent. Specifically, if the current power quality evaluation value is too low, it indicates that the power quality parameters fluctuate less and have better stability; in this case, the power quality of the current distribution network can be determined to be excellent.

[0133] In steps S140 to S143, a quality evaluation value is obtained based on quality reference values ​​for multiple consecutive preset time periods of the current power distribution network, and this quality evaluation value is compared with an evaluation threshold. If the quality evaluation value is greater than the evaluation threshold, it indicates that the power quality parameters of the current power distribution network are unstable and fluctuate greatly, and the current power quality is judged to be poor; conversely, it indicates that the power quality of the current power distribution network is stable and fluctuates less, and the current power quality is judged to be excellent.

[0134] On the other hand, the present invention also provides a digital power quality detection system for power distribution networks. Specifically, the detection system may include a power quality parameter acquisition module and a power quality evaluation module.

[0135] The power quality parameter acquisition module is connected to multiple acquisition points in the distribution network to collect various power quality parameters. The power quality evaluation module is communicatively connected to the power quality parameter acquisition module and is used to execute any of the above detection methods.

[0136] In another aspect, the present invention also provides a computer-readable storage medium storing instructions for being read by a machine to cause the machine to perform any of the detection methods described above.

[0137] Through the above technical solution, the distribution network digital power quality detection method, system, and storage medium provided by the present invention obtain the power quality fluctuation characteristics of the current distribution network by using the power quality parameters and power quality standard thresholds of the distribution network within the current preset time period. Based on these power quality fluctuation characteristics, the current power quality reference value of the distribution network can be obtained, thereby obtaining the power quality reference values ​​of the distribution network for multiple consecutive preset time periods. Finally, the power quality of the distribution network is evaluated by combining multiple quality references. The method of evaluating power quality by using the quality reference values ​​of multiple consecutive preset time periods can fully consider the temporal effects before and after power fluctuations, thereby improving the accuracy and reliability of power quality evaluation.

[0138] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0139] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0140] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0142] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0143] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0144] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0145] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0146] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for detecting the power quality of a digital power distribution network, characterized in that, include: Obtain the power quality parameters and power quality standard thresholds in the distribution network within the current preset time period; The power quality fluctuation characteristics of the current distribution network are obtained based on the power quality parameters and the corresponding power quality standard thresholds. The power quality reference value of the current distribution network is obtained based on the power quality fluctuation characteristics of the current distribution network. The power quality reference value is calculated based on the power quality fluctuation characteristic matrix and the decision weight matrix of the distribution network to express the power quality within the current preset time period. Obtain quality reference values ​​for the power distribution network over multiple consecutive preset time periods; The power quality of the current distribution network is evaluated based on multiple quality reference values. Evaluating the current power quality of the distribution network based on multiple quality reference values ​​includes: The quality evaluation value of the current distribution network is obtained according to formula (10). ，（10） in, This represents the current quality evaluation value of the distribution network. For the distribution network in the current preset time period Quality reference value, Numbered by integer. The number of consecutive preset time periods; Determine whether the current quality evaluation value of the power distribution network is greater than the evaluation threshold; If the current power quality evaluation value of the power distribution network is greater than the evaluation threshold, the power quality of the current power distribution network is determined to be poor. If the current power quality evaluation value of the distribution network is less than or equal to the evaluation threshold, the power quality of the current distribution network is determined to be excellent. The power quality parameters include: voltage deviation, frequency deviation, harmonics, voltage sag, three-phase imbalance, and voltage flicker. The quality reference value of the current distribution network is obtained based on the current power quality fluctuation characteristics of the distribution network, including: Each power quality fluctuation feature of the distribution network is arranged in ascending order to form a power quality fluctuation feature matrix. ; According to formula (7) The decision weight of each power quality fluctuation feature within a preset time period. ，（7） in, For the first The decision weights for the power quality fluctuation characteristics mentioned above. These are the fundamental decision coefficients for the power quality fluctuation characteristics. For the weight gradient, Let be the sequence number of the power quality fluctuation characteristic, and Numbered by integer; Construct a decision weight matrix based on the decision weight of each power quality fluctuation characteristic. ; Obtaining quality reference values ​​for the distribution network over multiple consecutive preset time periods includes: Obtain the distribution network in the current preset time period Power quality fluctuation characteristic matrix ; Obtain the distribution network in the current preset time period Power quality decision weight matrix ; Update the power distribution network according to formula (9) in the current preset time period. The decision weight matrix for power quality at that time. ，（9） in, Power quality parameters During the current preset time period Decision weights, Power quality parameters In the current preset time period sorting The value, For the changing gradient, The base value is the variable. Obtain the distribution network in the current preset time period The quality reference value.

2. The detection method according to claim 1, characterized in that, The power quality fluctuation characteristics of the current distribution network are obtained based on the power quality parameters and the corresponding power quality standard thresholds, including: The voltage deviation fluctuation characteristics of the current distribution network are obtained according to formula (1). ，（1） in, For the distribution network in the current preset time period Voltage deviation fluctuation characteristics, For the distribution network in the current preset time period voltage, For the distribution network in the current preset time period Rated voltage, The standard threshold for voltage deviation in the power distribution network; The frequency deviation fluctuation characteristics of the current distribution network are obtained according to formula (2). ，（2） in, For the distribution network in the current preset time period The frequency deviation fluctuation characteristics, For the distribution network in the current preset time period frequency, For the distribution network in the current preset time period The rated frequency, The standard threshold value for frequency deviation of the power distribution network; The harmonic fluctuation characteristics of the current distribution network are obtained according to formula (3). ，（3） in, For the distribution network in the current preset time period The characteristics of harmonic fluctuations, For the distribution network in the current preset time period Total harmonic distortion, The standard threshold for the total harmonic distortion rate of the power distribution network is denoted as .

3. The detection method according to claim 2, characterized in that, Obtaining the current power quality fluctuation characteristics of the distribution network based on the power quality parameters and the corresponding power quality standard thresholds also includes: The voltage sag fluctuation characteristics of the current distribution network are obtained according to formula (4). ，（4） in, For the distribution network in the current preset time period Voltage sag fluctuation characteristics. For the distribution network in the current preset time period The end time when the voltage is less than the rated voltage. For the distribution network in the current preset time period The initial moment when the voltage is lower than the rated voltage. The standard threshold for voltage sag time in the power distribution network; The three-phase voltage fluctuation characteristics of the current distribution network are obtained according to formula (5). ，（5） in, For the distribution network in the current preset time period The three-phase voltage fluctuation characteristics, For the distribution network in the current preset time period The three-phase voltage imbalance rate, The standard threshold for the three-phase voltage imbalance rate of the power distribution network; The voltage flicker fluctuation characteristics of the current distribution network are obtained according to formula (6). ，（6） in, For the current distribution network in the current preset time period Voltage flicker fluctuation characteristics, For the current distribution network in the current preset time period Voltage flicker index, This is the standard threshold for voltage flicker in the power distribution network.

4. The detection method according to claim 3, characterized in that, Obtaining the power quality reference value of the current distribution network based on the current power quality fluctuation characteristics also includes: The quality reference value of the current distribution network is obtained according to formula (8). ，（8）。 5. A digital power quality detection system for a power distribution network, characterized in that, include: The power quality parameter acquisition module is connected to multiple acquisition points in the distribution network to collect multiple power quality parameters in the distribution network. The power quality evaluation module is communicatively connected to the power quality parameter acquisition module and is used to execute the detection method as described in any one of claims 1-4.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that are read by a machine to cause the machine to perform the detection method as described in any one of claims 1-4.

Images