Electricity consumption behavior analysis method based on artificial intelligence ammeter

Abstract

The invention relates to the technical field of power system big data, in particular to a power consumption behavior analysis method based on an artificial intelligence ammeter. According to the invention, the electricity consumption of the user is periodically collected to form the electricity consumption data, the electricity consumption data is processed to remove abnormal values and noise, the electricity consumption data is normalized, and the electricity consumption behavior is judged based on the electricity consumption. The judgment comprises the steps of judging whether the power consumption behavior meets the standard or not and judging the reason that the power consumption behavior does not meet the standard, generating a corresponding processing instruction based on a judgment result or completing periodic judgment on the power consumption behavior, and re-determining a preset power consumption difference, or re-determining a noise reduction rate, or re-determining a screening standard based on the received processing instruction. Or a corresponding notice is sent out. According to the invention, accurate analysis of the power consumption behavior of the user based on the artificial intelligence ammeter is effectively realized, and the analysis efficiency of the power consumption behavior of the user is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of power system big data technology, and in particular to a method for analyzing electricity consumption behavior based on an artificial intelligence electric meter. Background Art

[0002] Traditional electricity meters are metering devices used to measure electricity consumption. Artificial intelligence (AI) meters are intelligent metering devices that integrate AI technology with traditional meters. Electricity behavior analysis refers to the process of collecting, organizing, and analyzing user electricity usage data to uncover patterns, characteristics, and patterns in user electricity usage. Electricity behavior analysis based on AI meters is a method that uses AI technology and data collected by meters to conduct in-depth research and understanding of user electricity usage behavior. AI meters have high-precision data acquisition capabilities and can collect electricity usage data such as electricity consumption in real time. They can also perform high-frequency sampling and accurately capture instantaneous changes in electricity usage, providing rich and accurate data support for analysis. Analyzing electricity usage behavior plays a significant role in ensuring electricity safety and providing timely warnings of abnormal electricity usage. Therefore, the research on electricity behavior analysis based on AI meters is of great significance.

[0003] Chinese patent application publication number: CN112396087B, discloses a method and device for analyzing electricity consumption data of elderly people living alone based on smart meters, including: collecting electricity consumption data of all users in a residential community through smart meters; extracting feature data from the electricity consumption data based on preset indicator characteristics; inputting the feature data into a fusion classification model containing several machine learning classifiers, and judging whether the user corresponding to the feature data is an elderly person living alone based on the classification results of the fusion classification model; if it is judged that the elderly person is an elderly person living alone, performing an abnormal electricity consumption analysis on the feature data of the elderly person, and deciding whether to issue an abnormal electricity consumption behavior alarm based on the analysis results.

[0004] As can be seen, the above solution uses smart meters to obtain electricity usage data, performs data mining on users' smart meter data based on feature extraction algorithms, and then combines the classification results of multiple machine learning classifiers to improve the accuracy of identifying elderly people living alone and reduce the cost of manual investigation. However, the above solution cannot accurately analyze users' electricity usage behavior based on artificial intelligence meters, and cannot guarantee the efficiency of analyzing users' electricity usage behavior. Summary of the Invention

[0005] To this end, the present invention provides a method for analyzing electricity usage behavior based on an artificial intelligence electricity meter, so as to overcome the problem in the prior art that it is impossible to accurately analyze the user's electricity usage behavior based on the artificial intelligence electricity meter, resulting in low efficiency in analyzing the user's electricity usage behavior.

[0006] To achieve the above objectives, the present invention provides a method for analyzing electricity usage behavior based on an artificial intelligence electric meter, comprising:

[0007] Periodically collect electricity consumption data of users;

[0008] Processing the power consumption data to remove outliers and noise, and normalizing the power consumption data;

[0009] Determining electricity usage behavior based on the electricity usage;

[0010] Generate corresponding processing instructions based on the judgment results,

[0011] or, completing the periodic determination of the electricity usage behavior and determining the electricity usage behavior in the next period;

[0012] The determination includes determining whether the electricity usage behavior complies with the standards and determining the reasons why the electricity usage behavior does not comply with the standards;

[0013] Based on the received processing instruction, the preset power consumption difference is re-determined, or the noise reduction ratio is re-determined, or the screening standard is re-determined, or a corresponding notification is issued.

[0014] Furthermore, the process of determining whether the electricity usage behavior meets the standard based on the electricity usage includes:

[0015] Obtaining the power consumption of each item and calculating an average value, and recording the obtained average value as the average power consumption;

[0016] Calculating the absolute value of the difference between the average power consumption value and the preset average power consumption value, and recording the obtained absolute value as the power consumption difference;

[0017] determining whether the electricity usage behavior meets the standard based on the electricity usage difference;

[0018] When the power consumption difference is less than or equal to a first preset power consumption difference, determining that the power consumption behavior meets the standard, completing the periodic determination of the power consumption behavior, and determining the power consumption behavior of the next period;

[0019] When the power usage difference is greater than the first preset power usage difference and less than or equal to the second preset power usage difference, determining that the power usage behavior does not meet the standard, and determining whether the power usage behavior meets the standard based on the historical average power usage value;

[0020] When the power usage difference is greater than the second preset power usage difference, it is determined that the power usage behavior does not meet the standard, and the reason why the power usage behavior does not meet the standard is determined based on the power usage difference.

[0021] Furthermore, the process of determining whether the electricity usage behavior meets the standard based on the historical average electricity usage includes:

[0022] Determine the average value of each of the historical electricity consumptions within each historical period;

[0023] Construct a time-power consumption average curve based on the historical power consumption average and the historical power consumption average;

[0024] Obtaining the absolute value of the slope of the time-power consumption average value curve at the current cycle node, and recording the obtained absolute value of the slope as the average value slope;

[0025] determining whether the electricity usage behavior meets the standard based on the average value slope;

[0026] When the average value slope is less than or equal to a preset average value slope, determining that the electricity usage behavior meets the standard, and correcting the preset electricity usage difference based on the average value slope;

[0027] When the average value slope is greater than the preset average value slope, it is determined that the electricity usage behavior does not meet the standard, and the reason why the electricity usage behavior does not meet the standard is determined based on the electricity usage difference.

[0028] Furthermore, the process of correcting the preset power consumption difference based on the average value slope includes:

[0029] Calculating the difference between the preset average slope and the average slope, and recording the obtained difference as the slope change value;

[0030] The preset power consumption difference is increased based on the slope change value, and the increase amplitude of the preset power consumption difference is inversely proportional to the slope change value.

[0031] Furthermore, the process of determining the reason why the electricity usage behavior does not meet the standard based on the electricity usage difference includes:

[0032] Calculating a ratio of the second preset power consumption difference to the power consumption difference, and recording the obtained ratio as the power consumption ratio;

[0033] Determining the reason why the electricity usage behavior does not meet the standard based on the electricity usage ratio;

[0034] When the power consumption ratio is less than or equal to a first preset power consumption ratio, determining whether the processing of the power consumption data meets the standard based on the power consumption;

[0035] When the power consumption ratio is greater than the first preset power consumption ratio and less than or equal to the second preset power consumption ratio, determining whether the collection of the power consumption meets the standard based on the variance of the power consumption;

[0036] When the power consumption ratio is greater than the second preset power consumption ratio, it is determined that the reason why the power consumption behavior does not meet the standard is that the power consumption behavior is abnormal, and a notification of abnormal power consumption is issued.

[0037] Furthermore, the process of determining whether the processing of the power consumption data complies with the standard based on the power consumption includes:

[0038] sequentially drawing a time-power consumption curve for each of the artificial intelligence electric meters;

[0039] determining whether the processing of the power consumption data complies with standards according to the time-power consumption curve;

[0040] For each of the time-power consumption curves, when the frequency ratio of a single type of anomaly is greater than or equal to a preset frequency ratio, determining that a corresponding type of anomaly exists in the processing of the power consumption data, and generating a corresponding processing method based on the determined type of anomaly;

[0041] When the frequency ratio of a single type of abnormality is less than a preset frequency ratio, whether the collection of the power consumption meets the standard is determined based on the variance of the power consumption.

[0042] Furthermore, the process of generating the corresponding processing method based on the determined abnormal type problem includes:

[0043] When the abnormality problem of the time-power consumption curve is the curve jitter, determining that the noise removal of the power consumption data does not meet the standard, and correcting the noise reduction factor based on the frequency ratio;

[0044] When the abnormal type problem of the time-power consumption curve is the power consumption outside the screening standard, it is determined that the power consumption data has an abnormal value, and the screening standard is corrected based on the power consumption ratio.

[0045] Furthermore, the process of correcting the noise reduction ratio based on the frequency ratio includes:

[0046] Calculating a difference between the frequency ratio and the preset frequency ratio, and recording the obtained difference as a frequency ratio difference;

[0047] The noise reduction factor is increased based on the frequency ratio difference, and the increase amplitude of the noise reduction factor is proportional to the frequency ratio difference.

[0048] Furthermore, the process of reducing the screening standard based on the power consumption ratio includes:

[0049] Calculating a difference between the first preset power consumption ratio and the power consumption ratio, and recording the obtained difference as the power consumption ratio difference;

[0050] The screening standard is reduced based on the power consumption ratio difference, and the reduction range of the screening standard is proportional to the power consumption ratio difference.

[0051] Furthermore, the process of determining whether the collection of the power consumption meets the standard based on the variance of the power consumption includes:

[0052] Calculating the variance of each of the power consumptions, and recording the obtained variance as the power consumption variance;

[0053] Determining whether the collection of the power consumption meets the standard based on the power consumption variance;

[0054] When the power consumption variance is less than or equal to a preset power consumption variance, determining that the collection of the power consumption meets the standard, and determining whether the processing of the power consumption data meets the standard based on the power consumption;

[0055] When the power consumption variance is greater than the preset power consumption variance, it is determined that the collection of the power consumption does not meet the standard, and a notification of a problematic electric meter is issued.

[0056] Compared with the prior art, the beneficial effect of the present invention is that the present invention can timely and accurately complete the judgment of electricity usage behavior by judging electricity usage behavior based on the electricity consumption collected within a period, and effectively realizes the precise analysis of the user's electricity usage behavior based on the artificial intelligence meter. The judgment includes determining whether the electricity usage behavior meets the standards and determining the reasons why the electricity usage behavior does not meet the standards. Based on the judgment result, the corresponding processing instructions are generated, and based on the received processing instructions, the preset electricity consumption difference, or noise reduction ratio, or screening standard is re-determined, or corresponding notifications are issued, which effectively improves the efficiency of the analysis of the user's electricity usage behavior.

[0057] Furthermore, the present invention determines whether electricity usage behavior meets the standards based on the difference in electricity consumption, and can accurately determine whether electricity usage behavior meets the standards. While further realizing the precise analysis of users' electricity usage behavior based on artificial intelligence meters, it further improves the efficiency of analyzing users' electricity usage behavior.

[0058] Furthermore, the present invention determines whether the electricity usage behavior meets the standards based on the average value slope, thereby avoiding misjudgment. While further realizing accurate analysis of the user's electricity usage behavior based on the artificial intelligence meter, it further improves the efficiency of analysis of the user's electricity usage behavior.

[0059] Furthermore, when the average value slope is less than or equal to the preset average value slope, the present invention increases the preset power consumption difference based on the slope change value, effectively ensuring the judgment accuracy. While further realizing the accurate analysis of the user's power consumption behavior based on the artificial intelligence meter, it further improves the analysis efficiency of the user's power consumption behavior.

[0060] Furthermore, the present invention determines the reason why electricity usage behavior does not meet the standards based on the electricity usage ratio, and can promptly and accurately determine the reason for non-compliance with the standards. While further realizing the precise analysis of the user's electricity usage behavior based on the artificial intelligence meter, it further improves the efficiency of the analysis of the user's electricity usage behavior.

[0061] Furthermore, when the power consumption ratio is less than or equal to a first preset power consumption ratio, the present invention determines whether the processing of the power consumption data meets the standards based on the time-power consumption curve. According to the curve, problems existing in the processing process can be accurately analyzed, while further realizing the accurate analysis of the user's power consumption behavior based on the artificial intelligence meter, and further improving the analysis efficiency of the user's power consumption behavior.

[0062] Furthermore, the present invention generates corresponding processing methods based on the determined abnormal type problems, effectively solving the abnormal type problems in a targeted manner, and further realizes the accurate analysis of the user's electricity usage behavior based on the artificial intelligence meter, while further improving the analysis efficiency of the user's electricity usage behavior.

[0063] Furthermore, when the abnormal type problem of the time-power consumption curve is curve jitter, the present invention determines that the denoising of the power consumption data does not meet the standards, and increases the noise reduction factor based on the frequency ratio difference, thereby effectively avoiding the occurrence of the situation where the power consumption difference does not meet the standards due to the noise reduction factor not meeting the standards. While further realizing the accurate analysis of the user's power consumption behavior based on the artificial intelligence meter, the efficiency of the analysis of the user's power consumption behavior is further improved.

[0064] Furthermore, when the abnormal type problem of the time-power consumption curve is the power consumption outside the screening standard, the present invention reduces the screening standard based on the power consumption ratio difference, effectively avoiding the occurrence of the situation where the power consumption difference does not meet the standard due to the screening standard not meeting the standard. While further realizing the accurate analysis of the user's power consumption behavior based on the artificial intelligence meter, it further improves the analysis efficiency of the user's power consumption behavior.

[0065] Furthermore, the present invention determines whether the collection of electricity consumption meets the standards based on the electricity consumption variance, and can timely and accurately complete the determination of whether the collection of electricity consumption meets the standards, avoiding the occurrence of misjudgment. When it is determined that the collection of electricity consumption does not meet the standards, a notification of problematic meters is issued, and the problematic meters can be dealt with in a timely manner. While further realizing the accurate analysis of users' electricity consumption behavior based on artificial intelligence meters, the efficiency of analysis of users' electricity consumption behavior is further improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1This is a structural block diagram of an electricity usage behavior analysis system based on an artificial intelligence electricity meter according to an embodiment of the present invention;

[0067] Figure 2 This is a flow chart of a method for analyzing electricity usage behavior based on an artificial intelligence electric meter according to an embodiment of the present invention;

[0068] Figure 3 This is a flow chart of an embodiment of the present invention for determining whether electricity usage behavior meets the standard and determining whether a preset electricity usage difference meets the standard;

[0069] Figure 4 This is a flow chart of an embodiment of the present invention for determining the reason why electricity usage behavior does not meet the standards. DETAILED DESCRIPTION

[0070] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0071] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0072] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0073] See also Figure 1 As shown in FIG, it is a structural block diagram of the power consumption behavior analysis system based on artificial intelligence electric meter according to an embodiment of the present invention. The structure of the embodiment of the present invention includes a collection unit, a processing unit, an analysis unit and a control unit; wherein,

[0074] The collecting unit is used to periodically collect the user's power consumption to form power consumption data;

[0075] The processing unit is connected to the collection unit, and is used to process the power consumption data to remove abnormal values ​​and noise, and to normalize the power consumption data;

[0076] The analysis unit is connected to the processing unit and is used to determine the electricity usage behavior based on the electricity usage;

[0077] The analysis unit is further configured to generate corresponding processing instructions based on the determination result, or to complete the periodic determination of the electricity usage behavior and to determine the electricity usage behavior of the next period; wherein the determination includes determining whether the electricity usage behavior meets the standard and determining the reason why the electricity usage behavior does not meet the standard;

[0078] The control unit is connected to the processing unit and the analysis unit respectively, and is used to redetermine the preset power consumption difference, redetermine the noise reduction ratio, redetermine the screening standard, or issue a corresponding notification based on the received processing instruction;

[0079] Specifically, the cycle for collecting users' electricity consumption is 2.5 hours.

[0080] See also Figure 2 As shown in FIG, it is a flow chart of a method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to an embodiment of the present invention. The method according to the embodiment of the present invention includes:

[0081] Periodically collect electricity consumption data of users;

[0082] Processing the power consumption data to remove outliers and noise, and normalizing the power consumption data;

[0083] Determining electricity usage behavior based on the electricity usage;

[0084] Generate corresponding processing instructions based on the judgment results,

[0085] or, completing the periodic determination of the electricity usage behavior and determining the electricity usage behavior in the next period;

[0086] The determination includes determining whether the electricity usage behavior complies with the standards and determining the reasons why the electricity usage behavior does not comply with the standards;

[0087] The operating parameters of the power usage behavior analysis are re-determined based on the received processing instruction.

[0088] See also Figure 3 As shown, it is a flow chart of determining whether the electricity usage behavior meets the standard and determining whether the preset electricity usage difference meets the standard according to an embodiment of the present invention. The process of determining whether the electricity usage behavior meets the standard based on the electricity usage according to the embodiment of the present invention includes:

[0089] Obtaining the power consumption of each item and calculating an average value, and recording the obtained average value as the average power consumption;

[0090] Calculating the absolute value of the difference between the average power consumption value and the preset average power consumption value, and recording the obtained absolute value as the power consumption difference;

[0091] determining whether the electricity usage behavior meets the standard based on the electricity usage difference;

[0092] When the power consumption difference is less than or equal to a first preset power consumption difference ΔE1, the power consumption behavior is determined to meet the standard, the periodic determination of the power consumption behavior is completed, and the power consumption behavior of the next period is determined. In this embodiment, the first preset power consumption difference ΔE1 = 30 degrees;

[0093] When the power consumption difference is greater than the first preset power consumption difference ΔE1 and less than or equal to the second preset power consumption difference ΔE2, it is determined that the power consumption behavior does not meet the standard, and whether the power consumption behavior meets the standard is determined based on the historical average power consumption. In this embodiment, the second preset power consumption difference ΔE2 = 128 degrees;

[0094] When the power usage difference is greater than the second preset power usage difference ΔE2, it is determined that the power usage behavior does not meet the standard, and the reason why the power usage behavior does not meet the standard is determined based on the power usage difference.

[0095] Please continue reading Figure 3 As shown, the process of determining whether the electricity usage behavior meets the standard based on the historical average electricity usage in this embodiment of the present invention includes:

[0096] Determine the average value of each of the historical electricity consumptions within each historical period;

[0097] Construct a time-power consumption average curve based on the historical power consumption average and the historical power consumption average;

[0098] Obtaining the absolute value of the slope of the time-power consumption average value curve at the current cycle node, and recording the obtained absolute value of the slope as the average value slope;

[0099] determining whether the electricity usage behavior meets the standard based on the average value slope;

[0100] When the average value slope is less than or equal to a preset average value slope L, the electricity usage behavior is determined to meet the standard, and the preset electricity usage difference is corrected based on the average value slope. In this embodiment, the preset average value slope L=1.13;

[0101] When the average value slope is greater than the preset average value slope L, it is determined that the electricity usage behavior does not meet the standard, and the reason why the electricity usage behavior does not meet the standard is determined based on the electricity usage difference.

[0102] Please continue reading Figure 3 As shown, the process of correcting the preset power consumption difference based on the average value slope in the embodiment of the present invention includes:

[0103] Calculating the difference between the preset average slope and the average slope, and recording the obtained difference as the slope change value;

[0104] increasing the preset power consumption difference based on the slope change value;

[0105] When the slope change value is greater than a second preset slope change value B2, the preset power consumption difference is increased to 1.09 times the initial preset power consumption difference, wherein, in the embodiment of the present invention, the second preset slope change value B2=0.098;

[0106] When the slope change value is less than or equal to the second preset slope change value B2 and greater than the first preset slope change value B1, the preset power consumption difference is increased to 1.12 times the initial preset power consumption difference, wherein, in the embodiment of the present invention, the first preset slope change value B1=0.063;

[0107] When the slope change value is less than or equal to the first preset slope change value B1, the preset power consumption difference is increased to 1.16 times the initial preset power consumption difference.

[0108] See also Figure 4 As shown, it is a flow chart of determining the reason why the electricity usage behavior does not meet the standard according to an embodiment of the present invention. The process of determining the reason why the electricity usage behavior does not meet the standard based on the electricity usage difference according to the embodiment of the present invention includes:

[0109] Calculating a ratio of the second preset power consumption difference to the power consumption difference, and recording the obtained ratio as the power consumption ratio;

[0110] Determining the reason why the electricity usage behavior does not meet the standard based on the electricity usage ratio;

[0111] When the power consumption ratio is less than or equal to a first preset power consumption ratio R1, determining whether the processing of the power consumption data meets the standard based on the power consumption, wherein, in this embodiment, the first preset power consumption ratio R1=55.41%;

[0112] When the power consumption ratio is greater than the first preset power consumption ratio R1 and less than or equal to the second preset power consumption ratio R2, determining whether the power consumption collection meets the standard based on the variance of the power consumption, wherein, in this embodiment, the second preset power consumption ratio R2=76.19%;

[0113] When the power consumption ratio is greater than the second preset power consumption ratio R2, it is determined that the reason why the power consumption behavior does not meet the standard is that the power consumption behavior is abnormal, and a power consumption behavior abnormality notification is issued.

[0114] Please continue reading Figure 4As shown, the process of determining whether the processing of the power consumption data meets the standard based on the power consumption in this embodiment of the present invention includes:

[0115] sequentially drawing a time-power consumption curve for each of the artificial intelligence electric meters;

[0116] determining whether the processing of the power consumption data complies with standards according to the time-power consumption curve;

[0117] For each of the time-power consumption curves, when the frequency ratio of a single type of anomaly is greater than or equal to a preset frequency ratio U, it is determined that a corresponding abnormal type problem exists in the processing of the power consumption data, and a corresponding processing method is generated based on the determined abnormal type problem, wherein the abnormal type problem includes curve jitter and power consumption outside the screening standard. The preset frequency ratio U=6;

[0118] When the frequency ratio of a single type of abnormality is less than the preset frequency ratio U, it is determined that the reason why the electricity usage behavior does not meet the standard is that there is an abnormality in the electricity usage behavior, and a notification of abnormality in the electricity usage behavior is issued;

[0119] Specifically, the time-power consumption curve is compared and analyzed with a noise-free fitting curve, and any fluctuations are marked as curve jitter;

[0120] Calculate the average value of each power consumption of each time-power consumption curve, record the obtained average value as the power consumption average value, calculate the standard deviation of each power consumption in the time-power consumption curve, calculate the difference between each power consumption and the power consumption average value in turn, and record the obtained difference as the power consumption difference, calculate the absolute value of the ratio of each power consumption difference to the standard deviation, record the obtained ratio as the standard deviation ratio, record the corresponding power consumption when the standard deviation ratio Z is greater than 3 as an abnormal value, and record 3 as the screening standard, and the screening standard can be drawn in the time-power consumption curve to determine whether there is power consumption outside the screening standard in the time-power consumption curve.

[0121] Please continue reading Figure 4 As shown, the process of generating the corresponding processing method based on the determined abnormal type problem in the embodiment of the present invention includes:

[0122] When the abnormality problem of the time-power consumption curve is the curve jitter, determining that the noise removal of the power consumption data does not meet the standard, and correcting the noise reduction factor based on the frequency ratio;

[0123] When the abnormal type problem of the time-power consumption curve is the existence of power consumption outside the screening standard, it is determined that the power consumption data has an abnormal value, and the screening standard is corrected based on the power consumption ratio.

[0124] Please continue reading Figure 4As shown, the process of correcting the noise reduction ratio based on the frequency ratio in the embodiment of the present invention includes:

[0125] Calculating a difference between the frequency ratio and the preset frequency ratio, and recording the obtained difference as a frequency ratio difference;

[0126] increasing the noise reduction factor based on the frequency ratio difference;

[0127] When the frequency ratio difference is greater than a second preset frequency ratio difference P2, the noise reduction magnification is increased to 1.36 times the initial noise reduction magnification, wherein, in the embodiment of the present invention, the second preset frequency ratio difference P2=12;

[0128] When the frequency ratio difference is less than or equal to the second preset frequency ratio difference P2 and greater than the first preset frequency ratio difference P1, the noise reduction magnification is increased to 1.23 times the initial noise reduction magnification, wherein, in the embodiment of the present invention, the first preset frequency ratio difference P1=5;

[0129] When the frequency ratio difference is less than or equal to the first preset frequency ratio difference P1, the noise reduction magnification is increased to 1.12 times the initial noise reduction magnification.

[0130] Please continue reading Figure 4 As shown, the process of reducing the screening standard based on the power consumption ratio in the embodiment of the present invention includes:

[0131] Calculating a difference between the first preset power consumption ratio and the power consumption ratio, and recording the obtained difference as the power consumption ratio difference;

[0132] reducing the screening standard based on the power consumption ratio difference;

[0133] When the power consumption ratio difference is greater than the second preset power consumption ratio difference Q2, the screening standard is reduced to 0.87 times the initial screening standard, wherein the second preset power consumption ratio difference Q2 in the embodiment of the present invention is 38.92%;

[0134] When the power consumption ratio difference is less than or equal to the second preset power consumption ratio difference Q2 and greater than the first preset power consumption ratio difference Q1, the screening standard is reduced to 0.92 times the initial screening standard, wherein, in the embodiment of the present invention, the first preset power consumption ratio difference Q1=22.78%;

[0135] When the power consumption ratio difference is less than or equal to the first preset power consumption ratio difference Q1, the screening standard is reduced to 0.96 times the initial screening standard.

[0136] Please continue reading Figure 4 As shown, the process of determining whether the collection of the power consumption meets the standard based on the variance of the power consumption in the embodiment of the present invention includes:

[0137] Calculating the variance of each of the power consumptions, and recording the obtained variance as the power consumption variance;

[0138] Determining whether the collection of the power consumption meets the standard based on the power consumption variance;

[0139] When the power consumption variance is less than or equal to a preset power consumption variance C, it is determined that the collection of the power consumption meets the standard, and whether the processing of the power consumption data meets the standard is determined based on the power consumption. In this embodiment of the present invention, the preset power consumption variance C=3.76;

[0140] When the power consumption variance is greater than the preset power consumption variance C, it is determined that the collection of the power consumption does not meet the standard, and a notification of a problematic electric meter is issued.

[0141] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0142] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for analyzing electricity consumption behavior based on an artificial intelligence electric meter, characterized in that: include: Periodically collect electricity consumption data of users; Processing the power consumption data to remove outliers and noise, and normalizing the power consumption data; Determining electricity usage behavior based on the electricity usage; Generate corresponding processing instructions based on the judgment results, or, completing the periodic determination of the electricity usage behavior and determining the electricity usage behavior in the next period; The determination includes determining whether the electricity usage behavior complies with the standards and determining the reasons why the electricity usage behavior does not comply with the standards; Based on the received processing instruction, the preset power consumption difference of the power consumption behavior analysis is re-determined, or the noise reduction ratio is re-determined, or the screening standard is re-determined, or a corresponding notification is issued.

2. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 1, characterized in that: The process of determining whether the electricity usage behavior meets the standard based on the electricity usage includes: Obtaining the power consumption of each item and calculating an average value, and recording the obtained average value as the average power consumption; Calculating the absolute value of the difference between the average power consumption value and the preset average power consumption value, and recording the obtained absolute value as the power consumption difference; determining whether the electricity usage behavior meets the standard based on the electricity usage difference; When the power consumption difference is less than or equal to a first preset power consumption difference, determining that the power consumption behavior meets the standard, completing the periodic determination of the power consumption behavior, and determining the power consumption behavior of the next period; When the power usage difference is greater than the first preset power usage difference and less than or equal to the second preset power usage difference, determining that the power usage behavior does not meet the standard, and determining whether the power usage behavior meets the standard based on the historical average power usage value; When the power usage difference is greater than the second preset power usage difference, it is determined that the power usage behavior does not meet the standard, and the reason why the power usage behavior does not meet the standard is determined based on the power usage difference.

3. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 2, characterized in that: The process of determining whether the electricity usage behavior meets the standard based on the historical average electricity usage includes: Determine the average value of each of the historical electricity consumptions within each historical period; Construct a time-power consumption average curve based on the historical power consumption average and the historical power consumption average; Obtaining the absolute value of the slope of the time-power consumption average value curve at the current cycle node, and recording the obtained absolute value of the slope as the average value slope; determining whether the electricity usage behavior meets the standard based on the average value slope; When the average value slope is less than or equal to a preset average value slope, determining that the electricity usage behavior meets the standard, and correcting the preset electricity usage difference based on the average value slope; When the average value slope is greater than the preset average value slope, it is determined that the electricity usage behavior does not meet the standard, and the reason why the electricity usage behavior does not meet the standard is determined based on the electricity usage difference.

4. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 3, characterized in that: The process of correcting the preset power consumption difference based on the average value slope includes: Calculating the difference between the preset average slope and the average slope, and recording the obtained difference as the slope change value; The preset power consumption difference is increased based on the slope change value, and the increase amplitude of the preset power consumption difference is inversely proportional to the slope change value.

5. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 3, characterized in that: The process of determining the reason why the electricity usage behavior does not meet the standard based on the electricity usage difference includes: Calculating a ratio of the second preset power consumption difference to the power consumption difference, and recording the obtained ratio as the power consumption ratio; Determining the reason why the electricity usage behavior does not meet the standard based on the electricity usage ratio; When the power consumption ratio is less than or equal to a first preset power consumption ratio, determining whether the processing of the power consumption data meets the standard based on the power consumption; When the power consumption ratio is greater than the first preset power consumption ratio and less than or equal to the second preset power consumption ratio, determining whether the collection of the power consumption meets the standard based on the variance of the power consumption; When the power consumption ratio is greater than the second preset power consumption ratio, it is determined that the reason why the power consumption behavior does not meet the standard is that the power consumption behavior is abnormal, and a notification of abnormal power consumption is issued.

6. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 5, characterized in that: The process of determining whether the processing of the power consumption data complies with the standard based on the power consumption includes: sequentially drawing a time-power consumption curve for each of the artificial intelligence electric meters; determining whether the processing of the power consumption data complies with standards according to the time-power consumption curve; For each of the time-power consumption curves, when the frequency ratio of a single type of anomaly is greater than or equal to a preset frequency ratio, determining that a corresponding type of anomaly exists in the processing of the power consumption data, and generating a corresponding processing method based on the determined type of anomaly; When the frequency ratio of a single type of abnormality is less than a preset frequency ratio, whether the collection of the power consumption meets the standard is determined based on the variance of the power consumption.

7. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 6, characterized in that: The process of generating the corresponding processing method based on the determined abnormal type problem includes: When the abnormality problem of the time-power consumption curve is curve jitter, determining that noise removal of the power consumption data does not meet the standard, and correcting the noise reduction factor based on the frequency ratio; When the abnormal type problem of the time-power consumption curve is the power consumption outside the screening standard, it is determined that the power consumption data has an abnormal value, and the screening standard is corrected based on the power consumption ratio.

8. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 7, characterized in that: The process of correcting the noise reduction ratio based on the frequency ratio includes: Calculating a difference between the frequency ratio and the preset frequency ratio, and recording the obtained difference as a frequency ratio difference; The noise reduction factor is increased based on the frequency ratio difference, and the increase amplitude of the noise reduction factor is proportional to the frequency ratio difference.

9. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 7, characterized in that: The process of reducing the screening standard based on the power consumption ratio includes: Calculating a difference between the first preset power consumption ratio and the power consumption ratio, and recording the obtained difference as the power consumption ratio difference; The screening standard is reduced based on the power consumption ratio difference, and the reduction range of the screening standard is proportional to the power consumption ratio difference.

10. The method for analyzing electricity consumption behavior based on an artificial intelligence electric meter according to claim 6, characterized in that: The process of determining whether the collection of the power consumption meets the standard based on the variance of the power consumption includes: Calculating the variance of each of the power consumptions, and recording the obtained variance as the power consumption variance; Determining whether the collection of the power consumption meets the standard based on the power consumption variance; When the power consumption variance is less than or equal to a preset power consumption variance, determining that the collection of the power consumption meets the standard, and determining whether the processing of the power consumption data meets the standard based on the power consumption; When the power consumption variance is greater than the preset power consumption variance, it is determined that the collection of the power consumption does not meet the standard, and a notification of a problematic electric meter is issued.

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