Remote user voltage quality monitoring system based on Internet of Things

Abstract

The invention relates to the technical field of user quality monitoring, particularly discloses a remote user voltage quality monitoring system based on the Internet of Things, and solves the problem that an original identification processing mode can only identify the condition of corresponding voltage quality abnormity and cannot identify and confirm the reason of the corresponding voltage quality abnormity. Aiming at the condition that the voltage waveform does not have the coincidence section, the corresponding distortion section is determined from the corresponding waveform sections, the distortion time period is locked from the distortion section, and the current harmonic quality analysis is carried out based on the corresponding distortion time period, so that the specific image condition of the harmonic is confirmed in the specific harmonic quality analysis result, and the current harmonic quality analysis accuracy is improved. By means of the step-by-step analysis mode, the corresponding voltage quality condition can be effectively confirmed, the corresponding harmonic influence condition can also be effectively confirmed, and the overall quality monitoring effect can be effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of user quality monitoring, and in particular to a remote user voltage quality monitoring system based on the Internet of Things. Background Art

[0002] The voltage quality of remote users directly affects the service life and performance of their electrical equipment. Many electrical equipment, such as precision instruments, electronic equipment and motors, have strict voltage requirements. For example, computer servers require a stable voltage supply. Excessive or low voltage may cause serious consequences such as server hardware damage and data loss. By monitoring the voltage quality of remote users, voltage anomalies can be discovered in time and measures can be taken to avoid equipment damage.

[0003] The application with publication number CN114629237A discloses a distribution network equipment operation status monitoring system, including: a remote control terminal for automatic measurement of data and remote control; an intelligent switch for intelligent current signal sampling; a fault analysis auxiliary device for assisting in determining the type of fault; a physical data module for multi-dimensional perception of the equipment operation status; improving the quality of electric energy, monitoring and improving the transient and steady-state voltage quality, providing users with high-quality electric energy, improving the operating economy of the distribution network system, improving the utilization rate of equipment, reducing operating and maintenance costs, reducing line losses, maximizing the economic benefits of the enterprise, reducing and shortening the time and scope of power outages for equipment maintenance, optimizing the network structure and reactive power distribution, and reducing power loss; achieving the ability to control the operation of the distribution network in real time and quickly handle faults, improving the reliability of power distribution and voltage qualification rate in the region, and improving the power supply service capabilities and the lean management level of the distribution network.

[0004] During the status monitoring process of the voltage of the corresponding user, it is generally identified whether the voltage of the corresponding user has quality abnormalities based on the voltage fluctuation of the corresponding user. The original identification and processing method can only identify the abnormal quality of the corresponding voltage, and cannot identify and confirm the cause of the abnormal quality of the corresponding voltage. As a result, when the relevant maintenance personnel maintain the voltage quality in the later stage, there are many maintenance items and the maintenance time is too long, which will affect the electricity experience of the corresponding user and cannot achieve a better user electricity experience. Summary of the invention

[0005] Purpose of the invention: In view of the shortcomings of the prior art, the present invention provides a remote user voltage quality monitoring system based on the Internet of Things, which solves the problem that the original identification and processing method can only identify the corresponding voltage quality abnormality but cannot identify and confirm the cause of the corresponding voltage quality abnormality.

[0006] Technical solution: To achieve the above purpose, the present invention is implemented through the following technical solution: A remote user voltage quality monitoring system based on the Internet of Things, comprising:

[0007] The voltage monitoring terminal monitors the user voltage of the remote user in real time and transmits the real-time monitored user voltage to the fluctuation abnormality determination terminal;

[0008] The abnormal fluctuation determination end confirms the user voltage of different remote users in real time, confirms the floating range of the user voltage based on the line operating voltage of the corresponding remote user, and then evaluates whether the user voltage is abnormal based on the confirmed floating area, and makes a specific determination of the abnormal user based on the duration of the abnormal situation. The specific method is as follows:

[0009] The user voltage of different remote users is calibrated as DY i , where i represents different remote users and is based on the line operating voltage V corresponding to the remote user i , confirm the floating interval [V i -5%V i , V i +5%V i ];

[0010] like A quality failure signal is generated and the duration of the quality failure signal is recorded. If the duration is ≥ 10s, the current remote user is marked as an abnormal user, and the duration of the quality failure signal is marked as an abnormal period; if the duration is < 10s, monitoring continues; if DY i ∈[V i -5%V i , V i +5%V i ], then continue monitoring without any processing;

[0011] The periodic waveform analysis end performs waveform analysis on the voltage waveform segment associated with the abnormal period based on the calibrated abnormal user and the abnormal period associated with the abnormal user, identifies whether there is a coincidence band in the past period, and based on the identification result, determines whether harmonic analysis is required. The specific method is as follows:

[0012] Based on the abnormal time period associated with the corresponding abnormal user, the voltage waveform segment associated with the abnormal time period is locked, the voltage waveform segment is marked as a characteristic band, and the initial point of the characteristic band is marked as a characteristic point;

[0013] Based on the characteristic point of the characteristic band, the past waveform segment of the characteristic band is confirmed in the voltage waveform, and the related point with the same amplitude strength as the characteristic point is confirmed from the past waveform segment, and the associated time length of the past waveform segment is N times the abnormal period, where N is a preset value;

[0014] The past waveform segment is translated to make the characteristic points of the characteristic band overlap with the relevant points. After the overlap is completed, it is identified whether this characteristic band completely overlaps with the past waveform segment. If so, it means that this characteristic band has an overlapping band in the past time period, and an external impact signal display is generated. If not, the corresponding translation process is executed in sequence, and it is confirmed in real time whether there is a complete overlap between the characteristic band and the past waveform segment in the corresponding translation process. If so, an external impact signal display is generated through the signal end. If not, the current harmonic analysis end is executed;

[0015] The current harmonic analysis end determines the distortion band from the voltage waveform segment based on the abnormal time period confirmed by the corresponding abnormal user and the associated voltage waveform segment, and determines the associated time period based on the distortion band, and then locks the current harmonics associated with the corresponding time period, identifies and determines the distortion rate generated by the corresponding current harmonics, and determines whether the abnormal user is interfered by harmonics based on the specific value of the distortion rate. The specific method is as follows:

[0016] Based on the confirmed voltage waveform segment, the voltage waveform segment is marked as a characteristic band;

[0017] Based on the translation verification process of the periodic waveform analysis end, the partial bands in the characteristic bands without overlapping bands are marked as distortion bands, the time period associated with the corresponding distortion band in the characteristic band is identified, and the associated time period is marked as the distortion time period;

[0018] Based on the determined distortion period, the current harmonics associated with the distortion period are identified, and the total number of current harmonics G is determined. k , where k represents different distortion periods, and then the voltage mean corresponding to the current harmonic is determined, and the confirmed voltage mean is calibrated as J k , and the voltage mean associated with this characteristic band is calibrated as Jz;

[0019] use Lock the distortion rate Jb associated with this distortion period, then confirm several distortion periods confirmed in the characteristic band in turn, and simultaneously confirm the distortion rate associated with each different distortion period, average the confirmed several groups of distortion rates, and confirm the evaluation value PD;

[0020] Identify whether the evaluation value PD satisfies: PD≥Y1, where Y1 is a preset value. If it does, it means that the harmonic impact is large, and a harmonic impact signal is generated through the signal terminal for display. If the evaluation value PD does not satisfy PD≥Y1, it means that the harmonic impact is small, and a voltage fault signal is generated through the signal terminal for display.

[0021] Preferably, the external influence signal is directly displayed in an external display terminal.

[0022] Beneficial effects: The present invention provides a remote user voltage quality monitoring system based on the Internet of Things. Compared with the prior art, it has the following beneficial effects:

[0023] The present invention monitors the voltage of the remote users of the Internet of Things, confirms the abnormal users and the associated abnormal time periods based on the monitoring results, and preferentially analyzes the voltage fluctuations. By confirming the abnormal waveforms associated with the corresponding abnormal time periods and performing coincidence verification analysis on the abnormal waveforms, it is identified whether there are coincident waveform segments in the past waveform segments. Based on the identification results, it is confirmed whether such poor voltage quality is caused by external influences or its own harmonic currents.

[0024] In the case where there is no overlapping segment in the voltage waveform, the corresponding distortion segment is determined from the corresponding waveform segment, and the distortion time period is locked from the distortion segment. The current harmonic quality analysis is performed based on the corresponding distortion time period, so that the specific image of the harmonics can be confirmed from the specific harmonic quality analysis results, thereby confirming whether such poor voltage quality is affected by harmonics. This step-by-step analysis method can not only effectively confirm the corresponding voltage quality situation, but also effectively confirm the corresponding harmonic impact situation, which can effectively ensure the overall quality monitoring effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0026] Figure 2 It is a schematic diagram of harmonic image determination of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Example 1

[0029] See also Figure 1 , the present application provides a remote user voltage quality monitoring system based on the Internet of Things, including a voltage monitoring terminal, a fluctuation abnormality determination terminal, a periodic waveform analysis terminal, a current harmonic analysis terminal and a signal terminal, wherein the voltage monitoring terminal, the fluctuation abnormality determination terminal and the periodic waveform analysis terminal are electrically connected from the output node to the input node in sequence, and the periodic waveform analysis terminal is electrically connected to the current harmonic analysis terminal or the signal terminal input node respectively, and the current harmonic analysis terminal is electrically connected to the signal terminal input node;

[0030] The voltage monitoring end monitors the user voltage of the remote user in real time, and transmits the real-time monitored user voltage to the fluctuation abnormality determination end, wherein the real-time monitored user voltage is numerically monitored by a designated voltage sensor, and the real-time voltage value monitored by the sensor is directly transmitted to the fluctuation abnormality determination end for specific determination of the fluctuation abnormality;

[0031] The abnormal fluctuation determination end confirms the user voltage of different remote users in real time, confirms the floating range of the user voltage based on the line operating voltage of the corresponding remote user, and then evaluates whether the user voltage is abnormal based on the confirmed floating area, and makes a specific determination of the abnormal user based on the duration of the abnormal situation. The specific method of determining the abnormal user is as follows:

[0032] The user voltage of different remote users is calibrated as DY i , where i represents different remote users and is based on the line operating voltage V corresponding to the remote user i , confirm the floating interval [V i -5%V i , V i +5%V i ], and its floating range is ±5% of the original operating voltage;

[0033] If DY i ∈[V i -5%V i , V i +5%V i ], then continue monitoring without any processing;

[0034] like A quality failure signal is generated (indicating an abnormal situation), and the duration of the quality failure signal is recorded. If the duration is ≥10s, the current remote user is marked as an abnormal user, and the duration of the quality failure signal is marked as an abnormal period. If the duration is <10s, monitoring continues (it may be due to the corresponding voltage fluctuation causing the voltage abnormality. Under normal circumstances, such voltage abnormality will not occur). Specifically, the normal line voltage is generally 35Kv or 10Kv. When the line voltage is 35Kv, the set floating range is 5%. When the line voltage is 10Kv, the set floating range is 7%. In order to make the determined floating range value more accurate, 5% is selected as the floating range here to ensure the accuracy of the quality failure signal determination.

[0035] Among them, the periodic waveform analysis end performs waveform analysis on the voltage waveform segment associated with the abnormal period based on the calibrated abnormal user and the abnormal period associated with the abnormal user, identifies whether there is an overlapping band in the past period, and confirms whether harmonic analysis is needed based on the identification result. Specifically, when the corresponding user is abnormal, the corresponding total period of time during which the abnormality lasts is the associated abnormal period. Under normal circumstances, if the corresponding voltage has relevant fluctuations, resulting in fluctuations in voltage data, but the associated voltage waveform is still in the state of a sine wave, it means that the currently monitored voltage fluctuation does not belong to the voltage fluctuation of the normal operation of this line, but is an interference fluctuation caused by an external line or node. If the corresponding sine wave changes accordingly, it means that the corresponding voltage fluctuation exists in this line, and harmonic analysis confirmation is required to identify its specific quality reasons.

[0036] Among them, the specific method of identifying whether this waveform segment has an overlapping band in the past period is:

[0037] Based on the abnormal time period associated with the corresponding abnormal user, the voltage waveform segment associated with the abnormal time period is locked (through the initial moment and the end moment of the abnormal time period, in the corresponding original voltage waveform, the waveform segment associated with the corresponding moment is locked), the voltage waveform segment is marked as a characteristic band, and the initial point of the characteristic band is marked as a characteristic point;

[0038] Based on the characteristic point of the characteristic band, the past waveform segment of the characteristic band is confirmed in the voltage waveform (that is, the relevant voltage waveform segment generated in the time period before the characteristic band), and the relevant points with the same amplitude strength as this characteristic point are confirmed from the past waveform segments (that is, several relevant points and this characteristic point are all on the same horizontal line), and the correlation time of the past waveform segment is N times the abnormal period, where N is a preset value, generally 10, which is prepared in advance by relevant operators based on experience;

[0039] The past waveform segment is translated to make the characteristic points of the characteristic band overlap with the relevant points. After the overlap is completed, it is identified whether this characteristic band completely overlaps with the past waveform segment. If so, it means that this characteristic band has an overlapping band in the past time period, and an external impact signal display is generated (indicating that the current voltage quality reduction is caused by other external lines or other situations). If not, the corresponding translation process is executed in sequence, and it is confirmed in real time whether there is a complete overlap between the characteristic band and the past waveform segment in the corresponding translation process. If so, an external impact signal display is generated through the signal end. If not, it means that the waveform associated with the current abnormal period did not appear in the past period, that is, the voltage of this line fluctuates, and harmonic analysis is required, so the current harmonic analysis end is executed;

[0040] Among them, the external impact signal is directly displayed in the external display terminal.

[0041] Specifically, the voltage waveform is continuously generated in the state of a sine wave during the generation process. When the corresponding abnormal period exists, if the power of the user fluctuates, resulting in power quality problems, then the corresponding voltage waveform does not exist in the past period, so the current harmonics can be directly re-analyzed;

[0042] If the corresponding waveform overlaps with the past waveform, it means that the waveform generated during this abnormal period is generated according to the original regularity. In this case, there is no problem with the power quality of this user. However, the voltage value is still abnormal, which is caused by external factors. In this case, a corresponding external influence signal is generated for display for the corresponding operators to view.

[0043] Example 2

[0044] Compared with the above-mentioned embodiments, this embodiment is mainly aimed at a specific harmonic analysis process during the specific implementation process. The corresponding harmonic analysis process is performed by the corresponding current harmonic analysis terminal to assess whether such voltage fluctuation is caused by harmonic interference resulting in poor quality or because of the existence of a specific fault, so harmonic analysis assessment is required;

[0045] Among them, combined Figure 2 The current harmonic analysis end determines the distortion band from the voltage waveform segment based on the abnormal time period confirmed by the corresponding abnormal user and the associated voltage waveform segment, and determines the associated time period based on the distortion band, and then locks the current harmonic associated with the corresponding time period, identifies and determines the distortion rate generated by the corresponding current harmonic, and determines whether the abnormal user is interfered by harmonics based on the specific value of the distortion rate, wherein the specific method of determining is:

[0046] Based on the confirmed voltage waveform segment, the voltage waveform segment is marked as a characteristic band;

[0047] Based on the translation verification process of the periodic waveform analysis end, the part of the characteristic band that does not have the overlapping band is marked as the distortion band (in the gradual translation process, the characteristic band has the situation that some bands overlap, and some bands have the situation that the overlapping band is not found, and the corresponding waveform segment of the overlapping band is the distortion band), the time period associated with the corresponding distortion band in the characteristic band is identified, and the associated time period is marked as the distortion time period;

[0048] Based on the determined distortion period, the current harmonics associated with the distortion period are identified, and the total number of current harmonics G is determined. k, where k represents different distortion periods, and then the voltage mean corresponding to the current harmonic is determined, and the confirmed voltage mean is calibrated as J k , and the voltage mean associated with this characteristic band is calibrated as Jz;

[0049] use Lock the distortion rate Jb associated with this distortion period, then confirm several distortion periods confirmed in the characteristic band in turn, and simultaneously confirm the distortion rate associated with each different distortion period, average the confirmed several groups of distortion rates, and confirm the evaluation value PD;

[0050] Identify whether the assessment value PD satisfies: PD≥Y1, where Y1 is a preset value, and its specific value is formulated by the operator based on experience. If it satisfies, it means that the harmonic impact is large, and a harmonic impact signal is generated through the signal end for display. Based on this harmonic impact signal, external related operators manage the harmonic conditions existing in the user's voltage to reduce the relevant impact caused by the corresponding harmonics. If it is not satisfied, it means that the harmonic impact is small, and a voltage fault signal is generated through the signal end for display. For the case where the harmonic impact is small, it is generally the corresponding user in the actual processing process, due to the corresponding equipment failure or other fault conditions, resulting in a large abnormality in the corresponding voltage value, thereby causing the voltage value to fluctuate. Therefore, for such abnormal conditions, the corresponding voltage fault signal can be directly generated for display.

[0051] Specifically, when the corresponding voltage fluctuates, it is generally due to a corresponding fault or its own influence. When the voltage fluctuates, but its voltage waveform does not change, it means that there is no problem with the voltage quality of the user itself. The reason for such fluctuations is the voltage fluctuation caused by the voltage difference of the external line.

[0052] When the corresponding voltage waveform is distorted, either there is a fault in the voltage itself, resulting in distortion of the voltage waveform, or the degree of harmonic influence in the corresponding user is large, resulting in specific distortion. By analyzing the distortion rate of the corresponding harmonic influence, the specific degree of the corresponding harmonic influence is locked. When the harmonic influence is small, it means that the corresponding voltage fluctuation is caused by the related voltage fault. When the harmonic influence is large, it means that the corresponding voltage fluctuation is caused by the corresponding harmonic, resulting in a large degree of influence.

[0053] Example 3

[0054] The specific implementation process of this embodiment includes all the implementation processes of the above two groups of embodiments.

[0055] Some of the data in the above formulas are numerically calculated by removing their dimensions. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0056] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The remote user voltage quality monitoring system based on the Internet of Things is characterized by: include: The voltage monitoring terminal monitors the user voltage of the remote user in real time and transmits the real-time monitored user voltage to the fluctuation abnormality determination terminal; The abnormal fluctuation determination terminal confirms the user voltage of different remote users in real time, confirms the floating range of the user voltage based on the line operating voltage of the corresponding remote user, and then evaluates whether the user voltage is abnormal based on the confirmed floating area, and makes a specific determination of the abnormal user based on the duration of the abnormal situation; The periodic waveform analysis end performs waveform analysis on the voltage waveform segment associated with the abnormal period based on the calibrated abnormal user and the abnormal period associated with the abnormal user, identifies whether there is a coincidence band in the past period, and confirms whether harmonic analysis is needed based on the identification result; The current harmonic analysis end determines the distortion band from the voltage waveform segment based on the abnormal time period confirmed by the corresponding abnormal user and the associated voltage waveform segment, and determines the associated time period based on the distortion band, and then locks the current harmonics associated with the corresponding time period, identifies and determines the distortion rate generated by the corresponding current harmonics, and determines whether the abnormal user is interfered by harmonics based on the specific size of the distortion rate value.

2. The remote user voltage quality monitoring system based on the Internet of Things according to claim 1 is characterized in that: The specific method of determining abnormal fluctuations at the abnormal user end is as follows: The user voltage of different remote users is calibrated as DY i , where i represents different remote users and is based on the line operating voltage V corresponding to the remote user i , confirm the floating interval [V i -5%V i , V i +5%V i ]; like A quality failure signal is generated and the duration of the quality failure signal is recorded. If the duration is ≥ 10s, the current remote user is marked as an abnormal user, and the duration of the quality failure signal is marked as an abnormal period.

3. The remote user voltage quality monitoring system based on the Internet of Things according to claim 2 is characterized in that: If the duration is less than 10s, continue monitoring.

4. The remote user voltage quality monitoring system based on the Internet of Things according to claim 2 is characterized in that: If DY i ∈[V i -5%V i , V i +5%V i ], monitoring continues without any processing.

5. The remote user voltage quality monitoring system based on the Internet of Things according to claim 1 is characterized in that: The specific method of the periodic waveform analysis end to confirm whether harmonic analysis is required is: Based on the abnormal time period associated with the corresponding abnormal user, the voltage waveform segment associated with the abnormal time period is locked, the voltage waveform segment is marked as a characteristic band, and the initial point of the characteristic band is marked as a characteristic point; Based on the characteristic point of the characteristic band, a past waveform segment of the characteristic band is confirmed in the voltage waveform, and a related point with the same amplitude strength as the characteristic point is confirmed from the past waveform segment; the past waveform segment is a related voltage waveform segment generated in the time period before the characteristic band; The past waveform segment is translated to make the characteristic points of the characteristic band overlap with the relevant points. After the overlap is completed, it is identified whether this characteristic band completely overlaps with the past waveform segment. If so, it means that this characteristic band has an overlapping band in the past time period, and an external impact signal display is generated. If not, the corresponding translation process is executed in sequence, and it is confirmed in real time whether there is a complete overlap between the characteristic band and the past waveform segment in the corresponding translation process. If so, an external impact signal display is generated through the signal end. If not, the current harmonic analysis end is executed.

6. The remote user voltage quality monitoring system based on the Internet of Things according to claim 5 is characterized in that: The associated duration of the past waveform segment is N times the abnormal period, where N is a preset value.

7. The remote user voltage quality monitoring system based on the Internet of Things according to claim 5 is characterized in that: The external influence signal is directly displayed in the external display terminal.

8. The remote user voltage quality monitoring system based on the Internet of Things according to claim 5 is characterized in that: The current harmonic analysis terminal determines whether the abnormal user is interfered by harmonics in the following specific manner: Based on the confirmed voltage waveform segment, the voltage waveform segment is marked as a characteristic band; Based on the translation verification process of the periodic waveform analysis end, the partial bands in the characteristic bands without overlapping bands are marked as distortion bands, the time period associated with the corresponding distortion band in the characteristic band is identified, and the associated time period is marked as the distortion time period; Based on the determined distortion period, the current harmonics associated with the distortion period are identified, and the total number of current harmonics G is determined. k , where k represents different distortion periods, and then the voltage mean corresponding to the current harmonic is determined, and the confirmed voltage mean is calibrated as J k , and the voltage mean associated with this characteristic band is calibrated as Jz; use Lock the distortion rate Jb associated with this distortion period, then confirm several distortion periods confirmed in the characteristic band in turn, and simultaneously confirm the distortion rate associated with each different distortion period, average the confirmed several groups of distortion rates, and confirm the evaluation value PD; Identify whether the evaluation value PD satisfies: PD ≥ Y1, where Y1 is a preset value. If it satisfies, it means that the harmonic impact is large, and a harmonic impact signal is generated through the signal end for display.

9. The remote user voltage quality monitoring system based on the Internet of Things according to claim 8 is characterized in that: If the evaluation value PD does not satisfy PD≥Y1, it means that the harmonic influence is small, and a voltage fault signal is generated through the signal terminal for display.

10. The remote user voltage quality monitoring system based on Internet of Things according to claim 8, characterized in that: During the gradual translation of characteristic bands, some of the characteristic bands overlap, and some of the characteristic bands fail to overlap. The corresponding waveform segments of the bands that fail to overlap are distorted bands.

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