Power quality disturbance time period determination method and device and electronic equipment

Abstract

The invention discloses a power quality disturbance time period determination method and device and electronic equipment. The method comprises the following steps: acquiring an electric energy quality signal of a target electric power system in a current time period; based on the peak difference value of the power quality signal, determining a power quality detection result of the target power system in the current time period; under the condition that the electric energy quality detection result indicates that electric energy quality disturbance exists in the target electric power system in the current time period, a difference sequence is determined based on the electric energy quality signal, and multiple elements included in the difference sequence correspond to multiple sampling moments in the current time period in a one-to-one mode; and obtaining the power quality disturbance time period of the target power system based on the difference sequence. According to the invention, the technical problem of insufficient positioning accuracy of the power quality disturbance of the power system in a complex scene in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of power quality monitoring technology, and more specifically, to a method, apparatus, and electronic device for determining the period of power quality disturbance. Background Technology

[0002] With the transformation of the global energy structure, the proportion of renewable energy sources such as wind and solar power is continuously increasing, especially in megacities where the grid connection scale of fluctuating energy sources such as wind and solar power is expanding. Simultaneously, the trend of transportation electrification is evident, with the rapid development of electric vehicles and their supporting large-scale charging and discharging facilities, posing unprecedented challenges to the power system. On the one hand, the uncertainty of renewable energy increases the difficulty of grid management, especially during periods of fluctuating wind and solar resources, significantly increasing the requirements for grid frequency and voltage regulation capabilities. On the other hand, the nonlinear and random characteristics of electric vehicle charging and discharging behavior, as well as the high-power operation of charging and discharging stations, have triggered a series of power quality problems, mainly including voltage fluctuations and flicker, and increased harmonic pollution. In particular, the superposition of higher-order harmonics poses a potential threat to grid stability and the safety of electrical equipment. Faced with these challenges, the relevant technologies have significant shortcomings in power quality disturbance detection, mainly in the following aspects:

[0003] While Fourier transform-based disturbance detection methods can effectively analyze the frequency components of stationary signals, they are limited in analyzing non-stationary signals, particularly in accurately capturing the time-varying characteristics of signals. They are susceptible to spectral leakage and the picket-fence effect, and their detection performance for non-stationary disturbances such as voltage sags and transient pulses is poor. Wavelet transform, while able to compensate for the shortcomings of Fourier transform to some extent by providing time-frequency information, suffers from limitations in complex disturbance detection due to its dependence on basis function selection and potential mode aliasing during signal decomposition. Furthermore, advanced signal processing methods such as Stockwell transform and Hilbert-Huang transform, while better suited for non-stationary signals, have high computational complexity, posing a challenge for real-time monitoring, and are highly sensitive to parameters, making precise control difficult. Although power quality disturbance detection methods in related technologies can achieve a certain degree of disturbance identification within a limited scope, their inability to effectively capture transient signal changes and identify complex disturbances leads to insufficient accuracy in locating power quality disturbances in power systems when facing complex scenarios.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method, apparatus, and electronic device for determining power quality disturbance periods, in order to at least solve the technical problem of insufficient accuracy in locating power quality disturbances in power systems when facing complex scenarios in related technologies.

[0006] According to one aspect of the present invention, a method for determining the power quality disturbance period is provided, comprising: acquiring a power quality signal of a target power system in the current period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; determining a power quality detection result of the target power system in the current period based on the peak difference value of the power quality signal, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; when the power quality detection result indicates that there is a power quality disturbance in the target power system in the current period, determining a differential sequence based on the power quality signal, wherein multiple elements included in the differential sequence correspond one-to-one with multiple sampling times in the current period, and any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time; and obtaining the power quality disturbance period of the target power system based on the differential sequence.

[0007] According to another aspect of the present invention, a power quality disturbance period determination device is also provided, comprising: a power quality signal acquisition module, configured to acquire a power quality signal of a target power system in the current period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; a power quality detection result determination module, configured to determine the power quality detection result of the target power system in the current period based on the peak difference value of the power quality signal, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; a differential sequence determination module, configured to determine a differential sequence based on the power quality signal when the power quality detection result indicates that there is a power quality disturbance in the target power system in the current period, wherein multiple elements included in the differential sequence correspond one-to-one with multiple sampling times in the current period, and any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time; and a power quality disturbance period determination module, configured to obtain the power quality disturbance period of the target power system based on the differential sequence.

[0008] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium storing a plurality of instructions adapted for loading by a processor and executing any one of the power quality disturbance period determination methods described herein.

[0009] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the power quality disturbance period determination method described in any one of the present invention.

[0010] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the power quality disturbance period determination method described in any one of the present invention.

[0011] In this embodiment of the invention, the power quality signal of the target power system in the current time period is acquired, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; based on the peak difference value of the power quality signal, the power quality detection result of the target power system in the current time period is determined, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; when the power quality detection result indicates that there is a power quality disturbance in the target power system in the current time period, a differential sequence is determined based on the power quality signal, wherein multiple elements included in the differential sequence correspond one-to-one with multiple sampling times in the current time period, and any element in the differential sequence represents the power quality signal at the corresponding sampling time and the difference between the peak and trough of the power quality signal. The difference between the power quality signal at the previous sampling time and the sampling time should be used; based on the differential sequence, the power quality disturbance period of the target power system is obtained. This achieves the goal of accurately determining the power quality disturbance period of the target power system by acquiring the power quality signal of the target power system in the current period, determining the power quality detection result based on the peak difference of the power quality signal, and determining the differential sequence when the power quality detection result indicates that there is a power quality disturbance in the target power system. This improves the technical effect of locating power quality disturbances in the power system and solves the technical problem of insufficient accuracy in locating power quality disturbances in the power system when facing complex scenarios. Attached Figure Description

[0012] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0013] Figure 1 This is a flowchart of a method for determining the power quality disturbance period according to an embodiment of the present invention;

[0014] Figure 2 This is a flowchart of an optional method for determining the power quality disturbance period according to an embodiment of the present invention;

[0015] Figure 3 This is a schematic diagram of a power quality disturbance period determination device according to an embodiment of the present invention. Detailed Implementation

[0016] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0017] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0018] According to an embodiment of the present invention, a method for determining the power quality disturbance period is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0019] Figure 1 This is a flowchart of a method for determining the power quality disturbance period according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0020] Step S102: Obtain the power quality signal of the target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system.

[0021] Optionally, power quality signals refer to electrical signals that reflect the power quality status of the target power system, collected by monitoring devices (including but not limited to power quality monitors, current transformers, and voltage transformers) within the target power system. Power quality signals may include, but are not limited to, voltage signals, current signals, frequency, and power. Monitoring devices are installed at specific locations within the target power system (including but not limited to substations, transmission lines, and user terminals). These devices are capable of acquiring power quality signals in real time. The acquired power quality signals undergo preprocessing, including but not limited to filtering, noise reduction, and digital signal conversion, to eliminate interference and ensure the accuracy of subsequent analysis. The preprocessed power quality signals can be stored in a data analysis system, providing a high-quality data foundation for subsequent disturbance detection and location.

[0022] Step S104: Based on the peak difference value of the power quality signal, determine the power quality detection result of the target power system in the current time period, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal.

[0023] Optionally, after acquiring the power quality signal, the spectrum of the larger amplitude high-frequency dominant frequency points can be obtained by calculating the normalized spectrum of the power quality signal, and it can be determined whether the number of larger amplitude dominant frequency points is greater than or equal to 1. The larger amplitude high-frequency dominant frequency points refer to the frequency points in the spectrum whose amplitude is greater than a preset first amplitude. When the number of detected larger amplitude dominant frequency points is greater than 1, it indicates that there is a significant high-frequency disturbance component in the power quality signal, caused by power quality disturbance. When the number of detected larger amplitude dominant frequency points is less than or equal to 1, i.e., no larger amplitude dominant frequency points are detected, it indicates that the high-frequency disturbance component in the power quality signal is not significant, or the disturbance event may manifest as transient characteristic changes in the time domain. In this case, a time-domain detection method based on peak difference will be used to locate and identify the disturbance event. The peak difference value, i.e., the amplitude difference between the peaks and troughs of the power quality signal, is searched in real time during the current time period. The peak difference value is a sensitive indicator of transient disturbances in the power quality signal. For example, under normal operating conditions, the power quality signal in a target power system exhibits a stable sinusoidal waveform with a predictable and relatively constant peak-to-trough difference. However, when the target power system experiences disturbances, including but not limited to voltage sags, swells, harmonic injection, and flicker, the waveform of the power quality signal deviates from its normal sinusoidal characteristics, and the peak-to-trough difference changes significantly. Specifically, when the voltage decreases, the peak-to-trough difference of the power quality signal decreases because the overall voltage level drops, reducing the signal's fluctuation range. When the voltage increases, the peak-to-trough difference of the power quality signal increases because the sudden increase in voltage level expands the signal's fluctuation range. Harmonic injection also increases the peak-to-trough difference because the superposition of harmonic components increases the signal's complexity and irregularity, leading to an increase in the difference between peaks and troughs. Power quality disturbance detection methods based on peak-to-trough differences can achieve rapid identification of disturbance events in the target power system while maintaining computational efficiency.

[0024] In one optional embodiment, the power quality detection result of the target power system in the current time period is determined based on the peak difference value of the power quality signal, including: if the peak difference value is greater than a preset peak difference threshold, the power quality detection result is determined to be that there is a power quality disturbance in the target power system in the current time period; or if the peak difference value is less than or equal to the preset peak difference threshold, the power quality detection result is determined to be that there is no power quality disturbance in the target power system in the current time period.

[0025] Optionally, the presence of power quality disturbances in the target power system can be determined by real-time monitoring of the peak-to-peak difference value of the power quality signal and comparing it with a preset peak-to-peak difference threshold. This involves two conditions: when the peak-to-peak difference value exceeds the preset threshold, it indicates significant fluctuations or distortions in the power quality signal, a direct manifestation of power quality disturbances (such as voltage flicker, swells, and dips). In this case, it is determined that the target power system has a power quality disturbance in the current time period, necessitating subsequent precise location processing for timely control measures. Conversely, if the peak-to-peak difference value remains below the preset threshold, it indicates that the fluctuations in the power quality signal are within the normal range, and no abnormal disturbance events have been detected. In this case, it is determined that the target power system does not have a power quality disturbance in the current time period, maintaining normal system monitoring and avoiding unnecessary resource consumption.

[0026] Step S106: When the power quality detection result indicates that there is a power quality disturbance in the target power system during the current period, a differential sequence is determined based on the power quality signal. The differential sequence includes multiple elements that correspond one-to-one with multiple sampling times during the current period. Any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time.

[0027] Optionally, if the power quality detection results indicate that the target power system experiences a power quality disturbance during the current time period, a differential sequence is obtained by calculating the difference between the power quality signal at each sampling point within the current time period and the power quality signal at the previous sampling point, in order to more accurately pinpoint the start and end times of the disturbance. Each element in the differential sequence can intuitively reflect the rate of change of the power quality signal between adjacent sampling times. Under normal operating conditions, the rate of change of the power quality signal is relatively stable, and the value of the differential sequence will also be relatively flat. However, at the instant that a power quality disturbance occurs, the power quality signal will exhibit a significant jump or inflection point, causing the corresponding element value in the differential sequence to increase sharply.

[0028] Step S108: Based on the differential sequence, the power quality disturbance period of the target power system is obtained.

[0029] Optionally, focus on elements with large difference values ​​in the difference sequence, which typically appear at the start or end of power quality disturbances. This method of locating power quality disturbances based on difference sequence analysis is a time-domain operation, offering advantages such as computational simplicity and fast response, making it suitable for power system environments requiring real-time monitoring and response.

[0030] In one optional embodiment, the power quality disturbance period of the target power system is obtained based on the differential sequence, including: determining the sampling time corresponding to the first element in the differential sequence that exceeds a preset difference threshold as the reference power quality disturbance start time; determining the sampling time corresponding to the last element in the differential sequence that exceeds the preset difference threshold as the reference power quality disturbance end time; and obtaining the power quality disturbance period based on the reference power quality disturbance start time and the reference power quality disturbance end time.

[0031] Optionally, by finding the first element in the differential sequence that exceeds a preset difference threshold, the sampling time corresponding to this element is taken as the reference power quality disturbance start time, i.e., element position a. The preset difference threshold needs to be set considering the signal variation range during normal operation of the target power system to ensure accurate capture of abnormal changes. The differential sequence is continued to be scanned until the last element exceeding the preset difference threshold is found. The sampling time corresponding to this element is taken as the reference power quality disturbance end time, i.e., element position b, marking the termination of the disturbance's impact. The preset difference threshold can effectively filter out slight fluctuations and noise in the power quality signal, ensuring that only signal changes that significantly deviate from normal operating conditions are identified as disturbances, thereby improving the accuracy of disturbance detection.

[0032] In one optional embodiment, the power quality disturbance period is obtained based on a reference power quality disturbance start time and a reference power quality disturbance end time, including: determining a first disturbance interval based on the reference power quality disturbance start time, wherein the first disturbance interval is a predetermined time interval before and / or after the reference power quality disturbance start time; determining a second disturbance interval based on the reference power quality disturbance end time, wherein the second disturbance interval is a predetermined time interval before and / or after the reference power quality disturbance end time; detecting whether the first disturbance interval and the second disturbance interval overlap, and obtaining an overlap detection result; and processing the differential sequence based on the overlap detection result to obtain the power quality disturbance period.

[0033] Optionally, if element position a equals 0 or element position b equals 0, it indicates that there are no difference elements exceeding the preset difference threshold, i.e., there is no significant disturbance. In this case, the power quality signal is transformed in the frequency domain again to obtain its amplitude spectrum. The amplitude spectrum is then normalized, and each point in the normalized spectrum is sorted according to its amplitude. Frequency points with amplitudes less than the preset second amplitude are selected as the main frequencies with smaller amplitudes. If the number of main frequencies with smaller amplitudes is greater than 1, the sampling time corresponding to each main frequency point is used to analyze the time period with the most drastic frequency component changes, find the sampling points where the disturbance begins and ends, and finally output the detection result of the specific power quality disturbance. If the number of main frequencies with smaller amplitudes is less than or equal to 1, it indicates that there may be no significant power quality disturbance in the power quality signal, or the disturbance characteristics are so weak that they are difficult to identify in the frequency domain. In this case, the detection process will re-detect the input power quality signal. If element position a equals 0 or element position b equals 0 (not true), the interval [t1, t2] where the disturbance begins is determined based on a, and the interval [t3, t4] where the disturbance ends is determined based on b. It is then determined whether [t1, t2] and [t3, t4] overlap. Based on the determined reference power quality disturbance start time, a predetermined time interval is extended forward and / or backward, defined as the first disturbance interval [t1, t2]. The first disturbance interval covers the initial response of the power quality signal change at the start of the disturbance, helping to capture the precursors and initial effects of the disturbance. Similarly, based on the determined reference power quality disturbance end time, a predetermined time interval is also extended forward and / or backward, defined as the second disturbance interval [t3, t4]. The second disturbance interval covers any potential short-term effects of the disturbance. The true boundary of the disturbance is determined by detecting whether the first and second disturbance intervals overlap. This disturbance interval, determined based on reference start and end times, combined with differential sequence processing and overlap detection, can achieve high-precision definition of power quality disturbance periods, reducing false alarms and missed alarms.

[0034] In an optional embodiment, based on the overlap detection result, the differential sequence is processed to obtain the power quality disturbance period, including: when the overlap detection result indicates that the first disturbance interval and the second disturbance interval overlap, merging the overlapping part between the first disturbance interval and the second disturbance interval to obtain the target disturbance interval; determining the local accumulation sequence corresponding to the target disturbance interval, wherein multiple elements included in the local accumulation sequence correspond one-to-one with multiple sampling times in the target disturbance interval, and any element in the local accumulation sequence is obtained by summing the corresponding element in the differential sequence with a predetermined number of elements preceding the corresponding element; determining the extreme value sequence corresponding to the target disturbance interval, wherein the extreme value sequence represents the set of elements in the local accumulation sequence that exceed a preset extreme value threshold, and multiple elements included in the extreme value sequence are arranged sequentially according to multiple sampling times in the local accumulation sequence; determining the sampling time corresponding to the first element in the extreme value sequence as the target power quality disturbance start time; determining the sampling time corresponding to the last element in the extreme value sequence as the target power quality disturbance end time; and obtaining the power quality disturbance period based on the target power quality disturbance start time and the target power quality disturbance end time.

[0035] Optionally, when the first and second disturbance intervals overlap, these overlapping portions are merged to form a continuous target disturbance interval. This ensures that the complete cycle of the disturbance is captured, avoiding the erroneous exclusion of the initial or final stages of the disturbance. For the signal within the target disturbance interval, the local cumulative value of the difference sequence is calculated to form a local cumulative sequence. Each element is the absolute or squared value of the sum of its corresponding element in the difference sequence and a predetermined number of elements (such as the number of sampling points within half or one power frequency cycle). The local cumulative sequence can intuitively reflect the rate of change of the power quality signal and amplify the characteristics of the power quality signal through accumulation and summation. From the local cumulative sequence, all elements exceeding a preset extreme value threshold are selected to form an extreme value sequence. The preset extreme value threshold needs to be set according to the characteristics of the power quality signal during normal operation of the target power system to ensure that only true disturbance events are marked. The preset extreme value threshold can be obtained by extracting disturbance-related features from historical power quality signals, including but not limited to amplitude changes, frequency fluctuations, and the statistical characteristics of the local cumulative sequence. Using these features, machine learning models, such as support vector machines, are trained to learn the boundary features that distinguish normal signals from disturbance signals. Next, an adaptive threshold mechanism is introduced to dynamically adjust the extreme value threshold based on the statistical characteristics of the real-time signal, improving the detection capability for signal disturbances under different operating conditions. The sampling time corresponding to the first element of the extreme value sequence is defined as the start time of the target power quality disturbance, and the sampling time corresponding to the last element is considered the end time of the target power quality disturbance. This definition is based on the fact that the disturbance event exhibits a significant peak in the local cumulative sequence. Finally, based on the start and end times of the target disturbance, the actual period of impact of the disturbance, i.e., the power quality disturbance period, is determined. Furthermore, to further improve the accuracy of disturbance detection, a lightweight intelligent confirmation model, such as a binary classification machine learning model, can be designed to perform secondary detection to filter out false positives caused by noise, further improving the localization accuracy. This can be achieved by extracting data segments near the start and end times of the located target power quality disturbance and inputting them into the pre-trained binary classification machine learning model. This model can quickly determine whether a data segment represents a real disturbance edge, thereby significantly improving positioning accuracy while ensuring response speed.

[0036] In one optional embodiment, based on the overlap detection result, the difference sequence is processed to obtain the power quality disturbance period, including: when the overlap detection result indicates that the first disturbance interval and the second disturbance interval do not overlap, determining the local accumulation sequence corresponding to the first disturbance interval and the second disturbance interval respectively, wherein any element in the local accumulation sequence is obtained by summing the corresponding element in the difference sequence with a predetermined number of elements preceding the corresponding element; determining the extreme value sequence corresponding to the first disturbance interval and the second disturbance interval, wherein the extreme value sequence represents the set of elements in the corresponding local accumulation sequence that exceed a preset extreme value threshold, and the multiple elements included in the extreme value sequence are arranged sequentially according to multiple sampling times in the corresponding local accumulation sequence; determining the sampling time corresponding to the first element in the extreme value sequence as the target power quality disturbance start time; determining the sampling time corresponding to the last element in the extreme value sequence as the target power quality disturbance end time; and obtaining the power quality disturbance period based on the target power quality disturbance start time and the target power quality disturbance end time.

[0037] Optionally, when the first and second disturbance intervals do not overlap, indicating that the disturbance events are clearly separated in time, a method of independent analysis for each disturbance interval is used to accurately locate the disturbance period. For the first and second disturbance intervals, local accumulation sequences are generated respectively. Within each local accumulation sequence, all elements exceeding a preset extreme value threshold are extracted, forming an extreme value sequence. The preset extreme value threshold can be dynamically adjusted using machine learning techniques to enhance the flexibility and accuracy of disturbance detection. For example, based on historical labeled data of historical power quality signals, the discrimination rules between disturbance edges and noise background are learned. Features (such as mean, variance, quantiles, signal-to-noise ratio, load state, and peak difference) are input into a preset model, and the probability that each sampling point is a disturbance edge is output. A dynamic threshold is calculated accordingly, such as dynamic threshold = mean + preset weight × standard deviation × compensation coefficient, to achieve noise adaptive and operating condition adaptive control. Finally, only extreme points exceeding the dynamic threshold are retained, and their start and end points are used to accurately pinpoint the start and end times of each independent disturbance, enabling efficient detection in the time domain. Ultimately, the sampling times corresponding to the first and last elements of the extreme value sequence are determined as the start and end times of the target disturbance, respectively. The method for determining the preset threshold when the first and second disturbance intervals do not overlap can also be adaptively adjusted using machine learning. This method, performed in the time domain through local accumulation, avoids complex frequency domain transformations, thereby achieving high-precision, real-time detection of power quality disturbance events.

[0038] Through the above steps S102 to S108, the goal is to obtain the power quality signal of the target power system in the current time period, determine the power quality detection result based on the peak difference value of the power quality signal, and determine the differential sequence when the power quality detection result indicates that there is a power quality disturbance in the target power system, thereby accurately determining the time period of the power quality disturbance in the target power system. This achieves the technical effect of improving the accuracy of power quality disturbance location in the power system, and solves the technical problem of insufficient accuracy in power quality disturbance location in the face of complex scenarios in related technologies.

[0039] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation method. Figure 2 This is a flowchart of an optional method for determining the power quality disturbance period according to an embodiment of the present invention, such as... Figure 2 As shown, the method includes:

[0040] S1: Input power quality signal x(n): Obtain the power quality signal of the target power system in the current time period. The specific implementation process is the same as the previous embodiment, and will not be repeated here.

[0041] S2: Calculate the normalized spectrum of x(n), obtain the spectrum of the major frequency points with larger amplitude, and determine whether the number of major frequency points with larger amplitude is greater than or equal to 1. Specifically:

[0042] S21: Perform frequency domain transformation on the power quality signal x(n) to obtain the amplitude spectrum of the power quality signal;

[0043] S22: Normalize the amplitude spectrum so that the values ​​of all spectrum points are between 0 and 1;

[0044] S23: Sort each point in the normalized spectrum according to its amplitude. Select the frequency points whose amplitude is greater than the preset first amplitude after sorting as the main frequency points with larger amplitude.

[0045] S24: Determine whether the number of major frequency points with larger amplitude values ​​is greater than or equal to 1.

[0046] S3: If the number of major frequency points with larger amplitude values ​​is greater than or equal to 1, capture power quality disturbance data and output the detection result: When the number of major frequency points with larger amplitude values ​​detected is greater than or equal to 1, this indicates that there are significant high-frequency disturbance components in the power quality signal, caused by power quality disturbances. At this time, based on the sampling time corresponding to the major frequency points with larger amplitude values, analyze the time period of most drastic frequency component changes, find the sampling points where the disturbance begins and ends, and finally output the specific power quality disturbance detection result.

[0047] S4: If the number of major frequency points with a large amplitude is less than 1, calculate x1 according to the peak difference detection and positioning principle, calculate the difference sequence x2, find the positions a and b of the first and last elements in x2 whose absolute values ​​are greater than the threshold, and determine whether a equals 0 or b equals 0. Specifically:

[0048] S41: When the number of major frequency points with relatively large amplitude detected is less than 1, that is, no major frequency points with relatively large amplitude detected, it indicates that the high-frequency disturbance component in the power quality signal is not significant, or the disturbance event may manifest as transient characteristic changes in the time domain. In this case, a time-domain detection method based on peak difference will be used to locate and identify the disturbance event;

[0049] S42: Perform peak difference detection, locate the peaks and troughs of the power quality signal in step S1, and then calculate the peak difference value x1 between the peaks and troughs. If the peak difference value is greater than the preset peak difference threshold, determine that the power quality detection result indicates that there is a power quality disturbance in the target power system during the current time period. The specific implementation process is the same as in the aforementioned embodiment, and will not be repeated here.

[0050] S43: Based on the power quality signal, determine the differential sequence x2. Further, determine the sampling time corresponding to the first element in the differential sequence that exceeds the preset difference threshold as the reference power quality disturbance start time, i.e., element position a; determine the sampling time corresponding to the last element in the differential sequence that exceeds the preset difference threshold as the reference power quality disturbance end time, i.e., element position b. The specific implementation process is the same as in the aforementioned embodiment, and will not be repeated here.

[0051] S44: Detect whether there are elements in the difference sequence that exceed the preset difference threshold.

[0052] S5: If a equals 0 or b equals 0, calculate the smaller amplitude dominant frequency point and determine if the smaller amplitude dominant frequency point is greater than 1. If the number of smaller amplitude dominant frequency points is greater than 1, capture the power quality disturbance data and output the detection result. If the number of smaller amplitude dominant frequency points is less than or equal to 1, return to step S2. Specifically:

[0053] S51: If a equals 0 or b equals 0, it indicates that there are no difference elements exceeding the preset difference threshold, i.e., there is no obvious disturbance. At this time, the power quality signal is transformed in the frequency domain again to obtain the amplitude spectrum of the power quality signal, and the amplitude spectrum is normalized.

[0054] S52: Sort each point in the normalized spectrum according to its amplitude. Select the frequency points whose amplitude is less than the preset second amplitude after sorting as the main frequency points with smaller amplitudes;

[0055] S53: If the number of smaller amplitude main frequency points is greater than 1, then based on the sampling time corresponding to the smaller amplitude main frequency points, analyze the time period when the frequency component changes most drastically, find the sampling points where the disturbance begins and ends, and finally output the detection results of the specific power quality disturbance.

[0056] S54: If the number of smaller amplitude main frequency points is less than or equal to 1, it indicates that there may be no significant power quality disturbance in the power quality signal, or the disturbance characteristics are so weak that they are difficult to identify in the frequency domain. The detection process will return to step S2 to recalculate and analyze the normalized spectrum.

[0057] S6: If a equals 0 or b equals 0 is not true, determine the interval [t1, t2] where the disturbance begins based on a, and the interval [t3, t4] where the disturbance ends based on b. Determine whether [t1, t2] and [t3, t4] overlap. Specifically:

[0058] S61: If both a and b are not equal to 0, it indicates that there are difference elements exceeding the preset difference threshold. In this case, a is determined as the start time of the reference power quality disturbance, and b is determined as the end time of the reference power quality disturbance. The specific implementation process is the same as in the previous embodiment, and will not be repeated here.

[0059] S62: Determine the interval [t1, t2] corresponding to the start time of the reference power quality disturbance as the first disturbance interval, and determine the interval [t3, t4] corresponding to the end time of the reference power quality disturbance as the second disturbance interval. The specific implementation process is the same as the previous embodiment, and will not be repeated here.

[0060] S63: Detect whether the first disturbance interval [t1,t2] and the second disturbance interval [t3,t4] overlap.

[0061] S7: If the first disturbance interval [t1,t2] and the second disturbance interval [t3,t4] overlap, they are merged to obtain the target disturbance interval [t1,t4]. Local difference and accumulation calculations are performed in the target disturbance interval [t1,t4] to obtain the difference and accumulation sequence value (local accumulation sequence). Threshold quantization is performed to obtain the extreme value sequence. The start time and end time of the disturbance (the start time and end time of the target power quality disturbance) are determined according to the extreme value sequence. Finally, the power quality disturbance data is captured and the detection result is output. The specific implementation process is the same as the previous embodiment, and will not be repeated here.

[0062] S8: If the first disturbance interval [t1,t2] and the second disturbance interval [t3,t4] do not overlap, perform local difference and accumulation calculations in the intervals to obtain the difference and accumulation sequence values ​​(local accumulation sequence), perform threshold quantization to obtain the extreme value sequence, determine the start time and end time of the disturbance (the start time and end time of the target power quality disturbance) based on the extreme value sequence, finally capture the power quality disturbance data, and output the detection results. The specific implementation process is the same as the aforementioned embodiment, and will not be repeated here.

[0063] This embodiment can achieve at least one of the following effects: (1) High real-time performance and low computational cost. The method completes signal processing in the time domain throughout the process, avoiding complex calculations caused by frequency domain or time-frequency domain transformations such as Fourier transform and wavelet transform. The first stage peak difference warning only involves extreme value search and subtraction operation, and the second stage local difference accumulation mainly involves difference and summation operations. The calculation is simple and highly efficient, meeting the urgent need of large power stations for real-time online monitoring of power quality disturbances. (2) Strong anti-interference and high robustness. A lightweight intelligent confirmation model is introduced to perform intelligent secondary discrimination on suspected disturbance edges, effectively filtering out false triggers caused by noise or slight fluctuations, significantly improving the reliability of detection results, and adapting to the complex operating environment of the actual power grid. (3) Scalability and comprehensive performance advantages. The method in this embodiment is a pure time domain detection scheme, which is easy to combine with other frequency domain analysis methods to form a more comprehensive power quality analysis system. It performs well in handling single disturbances and compound disturbances, providing an efficient and reliable detection basis for power quality management of large charging and discharging stations.

[0064] This embodiment also provides a device for determining the power quality disturbance period. This device is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the terms "module" and "device" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0065] According to an embodiment of the present invention, an apparatus embodiment for implementing the above-described method for determining the power quality disturbance period is also provided. Figure 3 This is a schematic diagram of a power quality disturbance period determination device according to an embodiment of the present invention, as shown below. Figure 3 As shown, the aforementioned power quality disturbance period determination device includes: a power quality signal acquisition module 300, a power quality detection result determination module 302, a differential sequence determination module 304, and a power quality disturbance period determination module 306, wherein:

[0066] The power quality signal acquisition module 300 is used to acquire the power quality signal of the target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system;

[0067] The power quality detection result determination module 302 is connected to the power quality signal acquisition module 300. It is used to determine the power quality detection result of the target power system in the current period based on the peak difference value of the power quality signal. The peak difference value is used to quantify the difference between the peak and trough of the power quality signal.

[0068] The differential sequence determination module 304 is connected to the power quality detection result determination module 302. It is used to determine a differential sequence based on the power quality signal when the power quality detection result indicates that there is a power quality disturbance in the target power system during the current period. The differential sequence includes multiple elements that correspond one-to-one with multiple sampling times during the current period. Any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time.

[0069] The power quality disturbance period determination module 306 is connected to the differential sequence determination module 304 and is used to obtain the power quality disturbance period of the target power system based on the differential sequence.

[0070] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0071] It should be noted that the power quality signal acquisition module 300, power quality detection result determination module 302, differential sequence determination module 304, and power quality disturbance period determination module 306 mentioned above correspond to steps S102 to S108 in the embodiments. The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run in a computer terminal.

[0072] It should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant descriptions in the embodiments, and will not be repeated here.

[0073] The aforementioned power quality disturbance period determination device may further include a processor and a memory. The aforementioned power quality signal acquisition module 300, power quality detection result determination module 302, differential sequence determination module 304, and power quality disturbance period determination module 306 are all stored in the memory as program modules, and the processor executes the aforementioned program modules stored in the memory to realize the corresponding functions.

[0074] The processor contains a core that retrieves the corresponding program modules from memory. One or more cores may be configured. 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 includes at least one memory chip.

[0075] According to an embodiment of this application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein, when the program runs, it controls the device containing the non-volatile storage medium to execute any of the power quality disturbance period determination methods.

[0076] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals, and the non-volatile storage medium includes stored programs.

[0077] Optionally, during program execution, the device containing the non-volatile storage medium is controlled to perform the following functions: acquire the power quality signal of the target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; determine the power quality detection result of the target power system in the current time period based on the peak difference value of the power quality signal, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; if the power quality detection result indicates that there is a power quality disturbance in the target power system in the current time period, determine a differential sequence based on the power quality signal, wherein multiple elements included in the differential sequence correspond one-to-one with multiple sampling times in the current time period, and any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time; and obtain the power quality disturbance period of the target power system based on the differential sequence.

[0078] According to an embodiment of this application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any of the above-described methods for determining power quality disturbance periods.

[0079] According to an embodiment of this application, an embodiment of a computer program product is also provided. Optionally, in this embodiment, the computer program product includes a computer program that, when executed by a processor, implements the steps of the power quality disturbance period determination method described above.

[0080] Optionally, when the aforementioned computer program product is executed on a data processing device, it is suitable to execute an initialization program having the following method steps: acquiring the power quality signal of the target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; determining the power quality detection result of the target power system in the current time period based on the peak difference value of the power quality signal, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; when the power quality detection result indicates that there is a power quality disturbance in the target power system in the current time period, determining a differential sequence based on the power quality signal, wherein multiple elements included in the differential sequence correspond one-to-one with multiple sampling times in the current time period, and any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time; and obtaining the power quality disturbance period of the target power system based on the differential sequence.

[0081] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: acquiring the power quality signal of a target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; determining the power quality detection result of the target power system in the current time period based on the peak difference value of the power quality signal, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; when the power quality detection result indicates that there is a power quality disturbance in the target power system in the current time period, determining a differential sequence based on the power quality signal, wherein multiple elements included in the differential sequence correspond one-to-one with multiple sampling times within the current time period, and any element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time; and obtaining the power quality disturbance period of the target power system based on the differential sequence.

[0082] The order of the above embodiments of the present invention is merely for description and does not represent the superiority or inferiority of the embodiments.

[0083] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of modules described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between modules, and may be electrical or other forms.

[0085] The modules described above as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0086] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0087] If the aforementioned integrated modules are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a non-volatile storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned non-volatile storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0088] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the power quality disturbance period, characterized in that, include: Acquire the power quality signal of the target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; Based on the peak difference value of the power quality signal, the power quality detection result of the target power system in the current time period is determined, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; When the power quality detection result indicates that the target power system has a power quality disturbance in the current time period, a differential sequence is determined based on the power quality signal. The differential sequence includes multiple elements that correspond one-to-one with multiple sampling times in the current time period. Each element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time. Based on the differential sequence, the power quality disturbance period of the target power system is obtained.

2. The method according to claim 1, characterized in that, Determining the power quality detection result of the target power system in the current time period based on the peak difference value of the power quality signal includes: If the peak difference value is greater than a preset peak difference threshold, the power quality detection result is determined to indicate that the target power system has a power quality disturbance in the current time period; or If the peak difference value is less than or equal to the preset peak difference threshold, the power quality detection result is determined to be that the target power system does not have power quality disturbances in the current time period.

3. The method according to claim 1, characterized in that, The process of obtaining the power quality disturbance period of the target power system based on the differential sequence includes: The sampling time corresponding to the first element in the difference sequence that exceeds a preset difference threshold is determined as the reference power quality disturbance start time; The sampling time corresponding to the last element in the difference sequence that exceeds the preset difference threshold is determined as the reference power quality disturbance end time; The power quality disturbance period is obtained based on the start time and end time of the reference power quality disturbance.

4. The method according to claim 3, characterized in that, The process of obtaining the power quality disturbance period based on the reference power quality disturbance start time and the reference power quality disturbance end time includes: Based on the reference power quality disturbance start time, a first disturbance interval is determined, wherein the first disturbance interval is a predetermined time interval before and / or after the reference power quality disturbance start time; Based on the end time of the reference power quality disturbance, a second disturbance interval is determined, wherein the second disturbance interval is a predetermined time interval before and / or after the end time of the reference power quality disturbance. Detect whether the first disturbance interval and the second disturbance interval overlap, and obtain the overlap detection result; Based on the overlap detection results, the differential sequence is processed to obtain the power quality disturbance period.

5. The method according to claim 4, characterized in that, The step of processing the differential sequence based on the overlap detection results to obtain the power quality disturbance period includes: If the overlap detection result indicates that the first disturbance interval and the second disturbance interval overlap, the overlapping portion between the first disturbance interval and the second disturbance interval is merged to obtain the target disturbance interval; Determine the local accumulation sequence corresponding to the target perturbation interval, wherein multiple elements included in the local accumulation sequence correspond one-to-one with multiple sampling times within the target perturbation interval, and any element in the local accumulation sequence is obtained by summing the corresponding element in the difference sequence with a predetermined number of elements preceding the corresponding element; Determine the extreme value sequence corresponding to the target perturbation interval, wherein the extreme value sequence represents the set of elements in the local accumulation sequence that exceed a preset extreme value threshold, and the multiple elements included in the extreme value sequence are arranged sequentially according to multiple sampling times in the local accumulation sequence; The sampling time corresponding to the first element in the extreme value sequence is determined as the start time of the target power quality disturbance; The sampling time corresponding to the last element in the extreme value sequence is determined as the end time of the target power quality disturbance; The power quality disturbance period is obtained based on the start time and end time of the target power quality disturbance.

6. The method according to claim 4, characterized in that, The step of processing the differential sequence based on the overlap detection results to obtain the power quality disturbance period includes: If the overlap detection result indicates that the first perturbation interval and the second perturbation interval do not overlap, a local accumulation sequence corresponding to each of the first perturbation interval and the second perturbation interval is determined, wherein any element in the local accumulation sequence is obtained by summing the corresponding element in the difference sequence with a predetermined number of elements preceding the corresponding element; Determine the extreme value sequences corresponding to the first perturbation interval and the second perturbation interval, wherein the extreme value sequence represents the set of elements in the respective corresponding local accumulation sequence that exceed a preset extreme value threshold, and the multiple elements included in the extreme value sequence are arranged sequentially according to multiple sampling times in the respective corresponding local accumulation sequence; The sampling time corresponding to the first element in the extreme value sequence is determined as the start time of the target power quality disturbance; The sampling time corresponding to the last element in the extreme value sequence is determined as the end time of the target power quality disturbance; The power quality disturbance period is obtained based on the start time and end time of the target power quality disturbance.

7. A device for determining the duration of power quality disturbance, characterized in that, include: A power quality signal acquisition module is used to acquire the power quality signal of the target power system in the current time period, wherein the power quality signal is an electrical signal used to describe the power quality of the target power system; A power quality detection result determination module is used to determine the power quality detection result of the target power system in the current time period based on the peak difference value of the power quality signal, wherein the peak difference value is used to quantify the difference between the peaks and troughs of the power quality signal; A differential sequence determination module is used to determine a differential sequence based on the power quality signal when the power quality detection result indicates that there is a power quality disturbance in the target power system during the current time period. The differential sequence includes multiple elements that correspond one-to-one with multiple sampling times during the current time period. Each element in the differential sequence represents the difference between the power quality signal at the corresponding sampling time and the power quality signal at the previous sampling time. The power quality disturbance period determination module is used to obtain the power quality disturbance period of the target power system based on the differential sequence.

8. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the power quality disturbance period determination method according to any one of claims 1 to 6.

9. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the power quality disturbance period determination method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for determining the power quality disturbance period as described in any one of claims 1 to 6.

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