Remote meter reading method and system of intelligent electric energy meter

Abstract

This invention discloses a remote meter reading method and system for smart meters, specifically relating to the field of electricity meter reading. It addresses the problems of poor communication link stability, frequent re-convergence of automatic gain control, and low meter reading success rate in existing power line carrier remote meter reading processes. By collecting carrier signal strength values ​​and automatic gain control parameters, a two-dimensional profile of the target electricity meter's time period and receiving link status is established. The temporal change slope and gain lock drift corresponding to each time period unit are calculated, constructing a historical stable distribution and identifying stable receiving link periods. Furthermore, by combining gain level migration, the target pre-locked gain level is determined. Before sending the meter reading request, pre-locking control is performed on the concentrator carrier receiving link, achieving remote meter reading time period optimization and receiving link stability control. This increases the stability of remote meter reading and the data acquisition success rate, improving power operation management efficiency and user service levels.

Description

Technical Field

[0001] This invention relates to the field of electricity meter reading technology, and more specifically, to a remote meter reading method and system for smart electricity meters. Background Technology

[0002] With the continuous development of smart grids and remote centralized meter reading technology, power operators are gradually adopting smart energy meter remote meter reading systems based on power line carrier communication to automate data collection, centralized storage, and remote management of distributed energy metering equipment, thereby reducing the cost of manual meter reading and improving the efficiency of electricity data collection.

[0003] Existing remote meter reading systems typically send meter reading requests periodically to target energy meters via a concentrator and transmit the electricity metering data back through a power line carrier network. Simultaneously, the collected data undergoes time synchronization, integrity verification, centralized aggregation, and standardization to meet the needs of electricity billing, grid dispatching, and user electricity management. However, in actual operation, the power line communication link is susceptible to factors such as grid load fluctuations, switching power supply connections, motor operation, and harmonic noise. This results in significant differences in communication quality at different times, leading to decreased stability of carrier communication between the concentrator and smart meters during certain periods. Problems such as failed response frame reception, data loss, increased communication retransmissions, and fluctuations in equipment online rates are common.

[0004] With the continuous expansion of remote meter reading, a large number of electricity meters are simultaneously connected to the same power line carrier network. The communication link status changes continuously over time. Most existing technologies rely solely on fixed communication parameters or simple signal strength statistics for meter reading scheduling, lacking the ability to continuously analyze the historical stable state of the receiving link and the automatic gain control process. This makes it difficult to dynamically adjust the concentrator's receiving link operating state according to the link stability in different time periods, leading to frequent re-convergence of the receiving gain, affecting the meter reading success rate and data acquisition continuity. This fails to meet the requirements for communication reliability, operational stability, and long-term adaptive optimization capabilities in large-scale remote meter reading scenarios. Therefore, how to achieve remote, efficient, and accurate collection of electricity meter data in this scenario, significantly reducing the cost of manual meter reading and improving the efficiency of power operation and management and the level of user service, is an urgent problem to be solved. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a remote meter reading method and system for smart energy meters to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A remote meter reading method for a smart energy meter includes the following steps: S1. When the concentrator receives the response frame of the target energy meter via power line carrier, it extracts the carrier signal strength value and records the automatic gain control parameters. S2. Map the precise time of meter reading to the preset time period unit, merge the carrier signal strength value and automatic gain control parameters into the receiving link status sampling point within the time period unit, and establish a two-dimensional file of the target energy meter's time period-receiving link status. S3. Retrieve the two-dimensional file of the time period-receive link status of the target energy meter, calculate the temporal change slope of the carrier signal strength of each time period unit, and generate the gain lock-on drift amount according to the automatic gain control parameters. S4. Construct a historical stable distribution of the time-series variation slope and gain-locked drift based on the carrier signal strength, and identify and mark the stable periods of the receiving link; S5. Extract the gain level migration amount of each successful meter reading during the stable period, and determine the target pre-locked gain level by combining the number of gain adjustments. S6. Allocate the current meter reading time to a stable period according to the meter reading deadline, and preset the concentrator carrier receiving link to the target pre-locked gain level before sending the meter reading request.

[0008] As a further aspect of the present invention, in step S1, recording the automatic gain control parameters specifically includes: During the process of receiving the response frame from the target energy meter, the current gain level in the automatic gain control register is read periodically, and a gain change trajectory is formed according to the acquisition time sequence. Record the first gain level in the gain change trajectory as the initial gain level, and record the gain level corresponding to the completion of the response frame verification as the final locked gain level. The number of times the gain level changes in the statistical gain change trajectory is taken as the number of gain adjustments; The process of increasing and decreasing the gain level in the gain change trajectory is recorded as a gain callback if the magnitude of the increase and decrease exceeds the preset callback monitoring threshold. The initial gain level, the final locked gain level, the number of gain adjustments, and the number of gain callbacks are encapsulated as automatic gain control parameters.

[0009] As a further aspect of the present invention, in step S2, establishing a two-dimensional file of the target energy meter's time period-receiver link status specifically includes: A two-dimensional archive storage structure for time period-receive link status is established, using the communication address of the target energy meter as the first index and the time period identifier of the preset time period unit as the second index. The carrier signal strength value and automatic gain control parameters are integrated into a single receiver link status sampling point, and then appended to the sampling point record set under the corresponding second index according to the time period unit to which the accurate meter reading time belongs. The carrier signal strength values ​​of all received link status sampling points within the corresponding time period are statistically analyzed. The historical average value of the carrier signal strength and the fluctuation envelope width of the corresponding time period are calculated to construct the channel fluctuation baseline corresponding to that time period.

[0010] As a further aspect of the present invention, in step S3, calculating the temporal variation slope of the unit carrier signal strength in each time period and generating the gain-locked drift amount based on the automatic gain control parameters specifically includes: Extract all receiving link status sampling points within each time period unit of the target energy meter from the two-dimensional archive of time period-receiving link status, and sort them in ascending order according to the accurate meter reading time corresponding to the sampling points; Within each time period unit, the ratio of the change in carrier signal strength between adjacent sampling points to the corresponding time interval is calculated, and the average of all ratios is taken as the slope of change for that time period unit. Extract the number of gain callbacks and the number of gain adjustments for each sampling point. The proportion of gain callbacks to gain adjustments is used as the proportion of callback bursts. The channel fluctuation baseline of the current time period unit is envelope normalized and transformed to generate a gain correction coefficient, which is multiplied by the proportion of callback bursts. The result is used as the burst disturbance intensity of the sampling point. The average value of the sudden disturbance intensity of all sampling points within each time period is used as the gain lock-off drift of that time period.

[0011] As a further aspect of the present invention, in step S4, identifying and marking the stable periods of the receiving link specifically includes: The slope of the time series change and the absolute value of the gain lock drift of all time period units of the target energy meter are converted to the same dimension, and the range of the two values ​​is stretched to the same dimension range. The absolute value of the slope after the range is converted to the same level within each time unit and the drift amount are used to form the link stability feature points, and a historical stable distribution is constructed. In the historical stable distribution, the link stable feature point of each time period unit is taken as the center, and the preset neighborhood radius is taken as the search radius. The number of adjacent link stable feature points falling within the search radius is counted as the point density of that time period unit. After traversing all time period units, a high-density cluster area is selected in the region where the link stable feature points with the highest point density are located. The arithmetic mean of the coordinate values ​​of all link stable feature points in each dimension is calculated in the high-density cluster area, and the coordinate point corresponding to the arithmetic mean is taken as the center of the time period cluster. Calculate the distance from the stable feature point of the link corresponding to each time period unit to the center of the time period cluster, and mark the time period units whose distance is less than the preset stable range as locked stable time periods.

[0012] As a further aspect of the present invention, in step S5, determining the target pre-locked gain level specifically includes: From the two-dimensional archive of time period-receive link status, retrieve all receive link status sampling points contained in all time period units marked as locked stable time periods; Extract the initial gain level and the final locked gain level corresponding to each receiving link state sampling point, and calculate the level shift amount that the initial gain level undergoes to converge to the final locked gain level. All sampling points were grouped according to the final locked gain level, and the average level shift and the average number of gain callbacks were calculated for each final locked gain level. The final locked gain gear with the smallest average gear shift amount is selected as the target candidate gear. When there are multiple target candidate gears with the same gear shift amount, the final locked gain gear with the lowest average gain callback number is selected as the target pre-locked gain gear.

[0013] As a further aspect of the present invention, in S6, allocating the current meter reading time to a stable period according to the meter reading deadline, and presetting the concentrator carrier receiving link to the target pre-locked gain level before sending the meter reading request specifically includes: Obtain the deadline for this meter reading task, and filter out the time period units marked as locked stable time periods. The time span completely covers the time required for a complete meter reading interaction and the end time is no later than the deadline, and use them as candidate execution time periods. Retrieve the channel fluctuation baseline of each candidate execution period from the two-dimensional file of time period-receive link status, extract the fluctuation envelope width in the corresponding channel fluctuation baseline, and select the candidate execution period with the smallest fluctuation envelope width as the execution period for this meter reading. Before the start time of the meter reading execution period arrives, the gain register of the concentrator carrier receiving link is written to the target pre-locked gain level, and a meter reading request frame is sent to the target energy meter when the start time arrives.

[0014] On the other hand, the present invention provides a remote meter reading system for smart energy meters, comprising: The communication acquisition module is used to perform periodic remote meter reading communication with smart meters in the target area through the power line carrier network. It collects the carrier signal strength value and automatic gain control parameters corresponding to the response frames of each meter through a preset query interface, and performs time synchronization and integrity verification. The data aggregation module is used to centrally store and standardize the collected electricity metering data, receiving link status sampling points and communication operation records, and to establish a two-dimensional file of the time period-receiving link status corresponding to the target electricity meter. The link analysis module is used to dynamically monitor the communication quality, online status of equipment, and receiving link during the remote meter reading process, and generate the time sequence change slope and gain lock-on drift corresponding to each time period unit. The pre-locking control module is used to identify the stable periods of the receiving link based on historical stable distribution, determine the target pre-locking gain level according to the gain level shift, and perform pre-locking control on the concentrator carrier receiving link before sending the meter reading request. The operation management module is used to identify meter reading failures, communication interruptions, and data loss, and trigger supplementary collection or retransmission control. At the same time, it continuously updates the pre-locking control strategy based on historical operation data.

[0015] The technical effects and advantages of the remote meter reading method and system for smart energy meters of this invention are as follows: This invention establishes a two-dimensional archive of the time period and receiving link status corresponding to the target energy meter. It continuously records and analyzes the carrier signal strength variation trend and automatic gain control process during different time periods in remote meter reading, enabling long-term learning and dynamic evaluation of the stable state of the power line carrier communication link. By constructing a historical stable distribution based on the time-series change slope and gain lock drift, it can accurately identify long-term stable periods of the receiving link. Combined with gain level shift, it determines the target pre-locked gain level, allowing the concentrator to enter the vicinity of the historical stable operating point before sending the meter reading request. This reduces the level shift distance and gain callback times during automatic gain control, lowers the time required for receiving link reconvergence, and improves the stability of response frame reception and the success rate of remote meter reading.

[0016] Meanwhile, this invention can continuously monitor communication quality, link stability and abnormal communication status, and continuously optimize the stable period identification strategy and pre-locking control strategy under the conditions of communication environment changes, power grid load fluctuations or equipment aging, improve the adaptability of the remote meter reading system to complex power line communication environment, and ensure the continuity, accuracy and long-term stable operation of power metering data collection. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a remote meter reading method for a smart energy meter according to the present invention; Figure 2 This is a schematic diagram of the structure of a remote meter reading system for a smart energy meter according to the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 Figure 1 The present invention provides a remote meter reading method for a smart energy meter, which includes the following steps: S1. When the concentrator receives the response frame of the target energy meter via power line carrier, it extracts the carrier signal strength value and records the automatic gain control parameters. S2. Map the precise time of meter reading to the preset time period unit, merge the carrier signal strength value and automatic gain control parameters into the receiving link status sampling point within the time period unit, and establish a two-dimensional file of the target energy meter's time period-receiving link status. S3. Retrieve the two-dimensional file of the time period-receive link status of the target energy meter, calculate the temporal change slope of the carrier signal strength of each time period unit, and generate the gain lock-on drift amount according to the automatic gain control parameters. S4. Construct a historical stable distribution of the time-series variation slope and gain-locked drift based on the carrier signal strength, and identify and mark the stable periods of the receiving link; S5. Extract the gain level migration amount of each successful meter reading during the stable period, and determine the target pre-locked gain level by combining the number of gain adjustments. S6. Allocate the current meter reading time to a stable period according to the meter reading deadline, and preset the concentrator carrier receiving link to the target pre-locked gain level before sending the meter reading request.

[0020] In step S1, the automatic gain control parameters are recorded.

[0021] During the reception of the target energy meter's response frame, the automatic gain control unit (AGU) in the concentrator's carrier receiving link continuously and dynamically adjusts the input signal amplitude. After the concentrator completes the transmission of the meter reading request frame, it initiates the gain status acquisition process in the receiving link. The front end of the receiving link includes a low-noise amplifier circuit, an analog-to-digital converter circuit, and an AGI register. The AGI register is used to store the current receiving gain level in real time. After the carrier response frame arrives, the current gain level in the AGI register is periodically read at a fixed sampling period. The sampling period is set according to the carrier baseband processing period, using 2 milliseconds as the single sampling period, so that a continuous gain change record can be formed during the reception of a single response frame. Each time it is read, the corresponding sampling time is recorded synchronously, and the read gain level is written into the buffer in the order of sampling time to form a gain change trajectory. Because power line carrier communication is easily affected by switching power supplies, motor loads, and harmonic noise, the AGI control unit will exhibit dynamic adjustment behaviors such as adjusting the level upwards, maintaining, or falling back during signal reception. Therefore, the gain change trajectory can truly reflect the stability of the receiving link during the current period. Gain levels are divided into discrete levels, for example, from level 1 to level 16, where a higher level value indicates a higher amplification factor in the receiving link. If the gain level obtained from two consecutive samples is the same, the current trajectory record remains unchanged; if the gain level of the subsequent sample is different from the previous sample result, a new level change node is recorded in the trajectory.

[0022] After the CRC check of the response frame is completed and the data integrity is confirmed, the current gain level value in the automatic gain control register is read as the final locked gain level. Since the automatic gain control process is essentially an adaptive convergence process of the receiving link to the dynamic amplitude of the input signal, the change between the initial gain level and the final locked gain level reflects the adjustment process the receiving link undergoes to reach a stable state. The adjacent sampling results are traversed node by node along the gain change trajectory. When the gain level of the next node differs from that of the previous node, it is counted as a gain adjustment event, and the total number of gain adjustment events is taken as the gain adjustment count. For example, in a certain response frame reception process, if the gain trajectory is sequentially 3, 4, 5, 5, 4, 5, then the transitions from 3 to 4, 4 to 5, 5 to 4, and 4 to 5 are each counted as a gain adjustment event, corresponding to a gain adjustment count of 4 times. Based on this, a preset callback monitoring threshold is further applied. In this embodiment, the default increase and decrease range are both set to 2 levels. The system detects whether there is a change in the gain level in the trajectory, where the gain level first increases and then decreases again. For example, if the trajectory increases from level 3 to level 6 and then decreases back to level 3, it is determined that a gain callback has occurred in the receiving link at the current stage. Gain callback reflects the behavior of the automatic gain control unit in correcting overshoot during the convergence process. Therefore, it can be used to identify whether there is sudden noise or short-term disturbance in the current power line communication environment. Only when the gain level falls back to a previously observed level is it counted as a valid gain callback, avoiding misjudging normal unidirectional convergence processes as callback behavior.

[0023] After receiving a single response frame, the corresponding initial gain level, final locked gain level, number of gain adjustments, and number of gain callbacks are written into the receiving link status record area in a fixed field order, forming the automatic gain control parameters corresponding to the current meter reading process. The initial gain level and final locked gain level are stored as single-byte integers, while the number of gain adjustments and the number of gain callbacks are stored as counter values, and are synchronously associated with the current meter reading time and the target energy meter address.

[0024] In step S2, a two-dimensional file of the target energy meter's time period and receiving link status is established.

[0025] After receiving a response frame from a target energy meter, the concentrator reads the communication address of the energy meter corresponding to the current meter reading task and uses this address as a unique index identifier for the target energy meter in the two-dimensional file of time period-receive link status. The communication address is identified using the energy meter's own carrier communication address or the concentrator's internal mapping address, and uses a 12-bit hexadecimal address code as the energy meter's communication address. Internally, the concentrator divides the entire day into time periods according to a preset time division method, dividing 24 hours into 48 time period units. Each time period unit corresponds to a continuous 30-minute time interval, and the time period number is written into the two-dimensional file as a second index. After each meter reading is completed, the concentrator reads the precise time of the current meter reading, determines the corresponding time period unit number based on the time interval to which the time belongs, and then encapsulates the carrier signal strength value and automatic gain control parameters obtained from this meter reading into a receive link status sampling point. The receive link status sampling point includes at least the carrier signal strength value, initial gain level, final locked gain level, number of gain adjustments, number of gain callbacks, and the corresponding sampling time. The carrier signal strength value is recorded in decibels and milliwatts (dW) using the signal strength detection result output from the concentrator carrier receiver chip. Automatic gain control parameters are encapsulated in a fixed field order to avoid field misalignment during subsequent readings. When the target energy meter has no historical sampling records for the corresponding time period unit, a new sampling point record set is directly established; when historical sampling records already exist, the newly generated receiver link status sampling points are appended to the end of the sampling point record set for the corresponding time period unit in sampling time order. To avoid the statistical results being interfered with by premature historical data due to an excessively large number of historical sampling points in a single time period unit after long-term operation, a maximum buffer length is set for the sampling point record set under each time period unit, using the most recent 120 valid meter reading records as the retention limit.

[0026] For sampling results indicating meter reading failure, CRC check failure of the response frame, or abnormal sudden changes in carrier signal strength, no data will be written to the corresponding sampling point record set. The method for determining abnormal sudden changes in carrier signal strength is as follows: if the deviation between the current carrier signal strength value and the average of the last 10 valid samples from the same time period exceeds a preset abnormal fluctuation threshold, the sampling is considered abnormal. The abnormal fluctuation threshold is set based on the historical operational statistics of the concentrator, taking three times the average carrier signal fluctuation of similar energy meters over the last 30 days as the abnormal fluctuation threshold. For example, if the historical average fluctuation amplitude is 4 dB / mW, the corresponding abnormal fluctuation threshold is set to 12 dB / mW.

[0027] The concentrator periodically traverses the two-dimensional archive of the time period-receiver link status corresponding to each target energy meter, reads the carrier signal strength values ​​from all valid receiver link status sampling points within the corresponding time period unit, and arranges them in chronological order to form a historical signal sequence. To avoid individual abnormal sampling values ​​affecting the overall statistical results, boundary removal processing is performed on the historical signal sequence. All carrier signal strength values ​​are reordered by numerical value, and abnormal boundary values ​​located in the highest and lowest 5% after sorting are deleted, retaining only the middle 90% of valid sampling results for subsequent statistics. For example, if 100 valid samples are accumulated within a certain time period unit, the highest 5 and lowest 5 carrier signal strength values ​​are deleted, and only the remaining 90 sampling results are used for mean and fluctuation analysis. Subsequently, the average result of all retained carrier signal strength values ​​is calculated as the historical mean of carrier signal strength for that time period unit. The historical mean of carrier signal strength is used to reflect the average communication signal level between the concentrator and the target energy meter under long-term stable conditions during the current time period. Furthermore, the difference between the maximum and minimum values ​​in the retained carrier signal strength sequence is calculated, and this difference is used as the fluctuation envelope width of the corresponding time period unit. The fluctuation envelope width reflects the overall fluctuation degree of the communication link under environmental interference during a given time period. For example, if the carrier signal strength corresponding to a certain time period unit remains between -63 dBmW and -66 dBmW for a long period, the corresponding fluctuation envelope width is 3 dBmW, indicating that the link environment is stable during that time period. If the carrier signal strength corresponding to a certain time period unit fluctuates between -55 dBmW and -74 dBmW for a long period, the corresponding fluctuation envelope width reaches 19 dBmW, indicating that there is significant power line background interference during that time period. The historical average carrier signal strength and the fluctuation envelope width are encapsulated together to form the channel fluctuation baseline corresponding to that time period unit, and synchronously correlated with the most recent update time.

[0028] In step S3, the temporal change slope of the unit carrier signal strength in each time period is calculated, and the gain lock drift amount is generated based on the automatic gain control parameters.

[0029] After the concentrator enters the link stability analysis phase, because the sampling records under the same time period unit will continue to accumulate over long-term meter reading operations, before performing trend analysis, all sampling points are first sorted in ascending order of time according to the precise meter reading time to ensure that the carrier signal strength change process conforms to the actual time evolution sequence. If the number of valid sampling points in a certain time period unit is less than the preset minimum analysis number, it will not participate in the change slope calculation. The minimum analysis number is set based on the concentrator's historical operating cycle, taking 15 consecutive valid meter reading records as the minimum analysis number to avoid distortion of the change trend due to a small number of samples. After completing the time sorting, adjacent sampling points within the same time period unit are traversed sequentially, and the carrier signal strength value and sampling time corresponding to the two sampling points are read. The change in carrier signal strength between adjacent sampling points is calculated, and the corresponding time interval is calculated. Then, the change in carrier signal strength is divided by the time interval to obtain the change rate within the corresponding time interval. The absolute value of the change rate corresponding to all adjacent sampling points is taken before participating in the statistics to avoid mutual cancellation due to different signal enhancement or weakening directions. After traversing all adjacent sampling points, the average of all obtained change rates is calculated, and this average is used as the change slope corresponding to that time period. The change slope is used to characterize the long-term stability of the power line communication environment within the corresponding time period. When the change slope is consistently small, it indicates that the carrier signal strength changes smoothly over a long period, and the receiving link is highly stable; when the change slope is consistently large, it indicates that the communication environment within the corresponding time period is easily affected by external load fluctuations or transient noise.

[0030] The concentrator further extracts the number of gain adjustments and the number of gain callbacks from each receiving link status sampling point. Since the number of gain adjustments reflects the overall convergence process of the automatic gain control unit reaching its stable operating point, while the number of gain callbacks reflects the number of times overshoot occurs and corrections are made during convergence, the proportion of gain callbacks in the number of gain adjustments directly reflects whether there are sudden disturbances in the current receiving link. Dividing the number of gain callbacks by the number of gain adjustments yields the callback burst proportion for the corresponding sampling point. For example, if there are 8 gain adjustments and 2 gain callbacks in a sampling process, the corresponding callback burst proportion is 0.25. Subsequently, the fluctuation envelope width in the channel fluctuation baseline corresponding to the current time period unit is read, and envelope normalization is performed. The concentrator calculates the maximum and minimum fluctuation envelope widths in all time period units of the current target energy meter, maps the fluctuation envelope width of the current time period unit to a normalized interval between 0 and 1, and obtains the corresponding gain correction coefficient. For example, if the minimum fluctuation envelope width across all time periods is 2 dB / mW and the maximum fluctuation envelope width is 20 dB / mW, while the fluctuation envelope width corresponding to the current time period is 11 dB / mW, the corresponding normalized result is approximately 0.5. Subsequently, the gain correction coefficient is multiplied by the callback burst proportion to obtain the burst disturbance intensity at the corresponding sampling point. Since the gain correction coefficient reflects the overall background fluctuation level within the current time period, and the callback burst proportion reflects the instantaneous disturbance behavior during automatic gain control, the combination of the two can simultaneously reflect both long-term link fluctuations and transient interference levels. After completing the calculation for all sampling points, the average burst disturbance intensity corresponding to all sampling points within the current time period is calculated, and the resulting average is used as the gain lock-up drift for that time period.

[0031] In step S4, the stable periods of the receiving link are identified and marked.

[0032] Since the slope of change reflects the long-term trend of carrier signal strength, while the gain-locked drift reflects the degree of disturbance in the automatic gain control process, and there are significant differences between the two in their original numerical range and physical magnitude, a uniform range transformation is performed on both types of data before joint stability analysis. The maximum and minimum values ​​of the slope of change and the maximum and minimum values ​​of the gain-locked drift for all time periods are statistically analyzed, and the original values ​​for each time period are mapped to a uniform dimension range between 0 and 1. For example, if the minimum slope of change for a target energy meter is 0.02 and the maximum is 0.31, then when the slope of change for the current time period is 0.11, the normalized result is approximately 0.31. Similarly, if the minimum gain-locked drift is 0.08 and the maximum is 0.72, then when the drift for the current time period is 0.24, the normalized result is approximately 0.25. After the uniform dimension transformation, the normalized slope and normalized drift for the same time period are used to form a two-dimensional link stability feature point. In this system, the horizontal coordinate of the two-dimensional feature points characterizes the long-term variation of the carrier signal within that time period, while the vertical coordinate characterizes the degree of lock-in disturbance during automatic gain control. Subsequently, the link stability feature points corresponding to all time period units are mapped to a unified two-dimensional distribution plane, forming the historical stability distribution corresponding to the target energy meter. Only when the number of valid sampling points within the corresponding time period unit reaches the preset number of valid analysis points are the corresponding link stability feature points allowed to participate in the construction of the historical stability distribution.

[0033] After constructing the historical stable distribution, the concentrator further performs neighborhood density statistics on each link stable feature point. Specifically, the link stable feature point corresponding to each time period unit is used as the current analysis center point, and a corresponding search area is established within the two-dimensional stable distribution plane. The search area adopts a circular neighborhood range, and the search radius is set based on the historical operational stability of the target electricity meter. For residential electricity meters with long-term stable operation, a default search radius of 0.12 is used; for electricity meters in industrial areas or areas with significant load fluctuations, a default search radius of 0.18 is used. These default values ​​are empirically set based on historical data of actual electricity meters to adapt to the link fluctuation characteristics under different power line communication environments. Subsequently, the number of other link stable feature points falling within the neighborhood range of the current search area is counted, and the statistical result is used as the point density corresponding to the current time period unit. For example, if there are 14 other feature points within the neighborhood range around a certain link stable feature point, the point density corresponding to the current time period unit is recorded as 14. Since the slope of change and gain lock-up drift typically remain close to each other during stable periods, the corresponding stable feature points will form a clear clustering region within the two-dimensional stable distribution plane. During periods of high disturbance, however, due to significant link fluctuations, the corresponding feature points usually exhibit a discrete distribution. Therefore, the point density directly reflects the degree of stability concentration during the long-term operation of the corresponding period. To avoid the search radius being too small, preventing the formation of clusters during normal stable periods, or the search radius being too large, causing multiple independent stable regions to be incorrectly merged, the concentrator automatically verifies the validity of the search radius based on the target energy meter's operating records for the past 30 days.

[0034] After completing the point density statistics for all stable link feature points, the concentrator sorts them according to the point density results, selects the stable link feature point with the highest point density as the core point of the high-density cluster, and divides all stable link feature points falling within the search neighborhood of this core point into a high-density cluster. Then, the coordinate values ​​of all stable link feature points within the high-density cluster are calculated in both the slope of change and gain lock-in drift dimensions, and the arithmetic mean of both dimensions is taken. For example, if there are 12 stable link feature points in the high-density cluster, the average of the horizontal and vertical coordinate values ​​corresponding to the 12 feature points is calculated, and the resulting two-dimensional average coordinates are used as the time period cluster center. The time period cluster center is used to characterize the most stable link operating area of ​​the target energy meter during long-term operation. Subsequently, the concentrator traverses all stable link feature points corresponding to all time period units, calculating the distance from each feature point to the time period cluster center. The distance is calculated using two-dimensional Euclidean distance and uniformly retained to three decimal places. When the distance between a feature point corresponding to a time period unit and the time period cluster center is less than a preset stable range, that time period unit is marked as a locked stable time period. The preset stable range is set comprehensively based on the concentration of historical stable distribution and communication stability requirements. The default value is 1.2 times the average distance of all feature points in the high-density cluster area.

[0035] In step S5, the target pre-locked gain level is determined.

[0036] After identifying the stable locking period, the concentrator reads all time period units marked as stable locking periods from the two-dimensional file of time period-receiver link status and extracts all received link status sampling points stored under the corresponding time period unit. Since the carrier signal corresponding to the stable locking period changes gradually over a long period and the automatic gain control process is stable, these sampling points can accurately reflect the receive link convergence behavior of the target energy meter under a stable communication environment. The initial gain level and the final locked gain level stored in each received link status sampling point are read one by one, and the corresponding level shift is calculated according to the gain change process within the same sampling point. The level shift reflects the overall convergence distance experienced by the automatic gain control unit from starting reception to achieving stable locking. The level shift is expressed as the absolute value of the level difference between the initial gain level and the final locked gain level. For example, if the initial gain level is 3 and the final locked gain level is 7 in a certain sampling, the corresponding level shift is 4; if the initial gain level is 6 and the final locked gain level is 5, the corresponding level shift is 1. Since the automatic gain control unit needs to gradually approach the stable operating point through multiple gain adjustments during actual operation, the smaller the gain shift, the closer the receiving link is to the target stable operating state, and the shorter the corresponding automatic gain control convergence process. For sampling points with zero gain adjustments and the same initial and final locked gain levels, the gain shift is directly recorded as 0, and these sampling points are marked as directly locked sampling points. When the proportion of directly locked sampling points in a certain time period unit is consistently higher than the preset direct locking ratio, the corresponding time period number is recorded synchronously for subsequent priority participation in the target pre-locked gain level selection. The direct locking ratio is set based on the historical operation statistics of the concentrator, with 60% taken as the direct locking ratio. For example, if a certain time period unit has a total of 50 valid samples, of which 32 are directly locked sampling points, the corresponding direct locking ratio reaches 64%, meeting the direct locking time period determination condition.

[0037] After calculating the range shift for all valid sampling points, the concentrator categorizes and statistically analyzes all sampling points according to the final locked gain level. For example, sampling points with a final locked gain level of 5 are grouped into one group, and those with a final locked gain level of 6 are grouped into another. Then, the average range shift and the average gain callback count for all sampling points within each group are calculated. The average range shift represents the overall convergence distance required for the automatic gain control unit to converge to the corresponding final locked gain level; the average gain callback count indicates the frequency of overshoot corrections during meter convergence. If the average range shift for a certain final locked gain level is significantly smaller, it indicates that the receiving link is more likely to converge quickly to the vicinity of that level during stable periods, thus prioritizing the corresponding final locked gain level as a target candidate level. For example, if the average range shift for a target energy meter is 1.2 for level 5 and 2.8 for level 6, then level 5 is prioritized as the target candidate level. When multiple final locked gain levels correspond to the same average shift amount, the average gain callback count is further compared, and the final locked gain level with the lowest average gain callback count is selected as the target pre-locked gain level. For example, the average shift amount for levels 5 and 6 is 1.5, but the average gain callback count for level 5 is 0.4, while the average gain callback count for level 6 is 1.1. Therefore, level 5 is ultimately selected as the target pre-locked gain level.

[0038] In step S6, the meter reading time is allocated to a stable period according to the meter reading deadline, and the concentrator carrier receiving link is preset to the target pre-locked gain level before sending the meter reading request.

[0039] After receiving the remote meter reading task, the concentrator first reads the target meter address and the task deadline. The deadline is determined by the meter reading cycle requirements issued by the main station and is uniformly configured according to the centralized meter reading cycle. Then, the concentrator reads all the locked stable time periods corresponding to the target meter and analyzes the time span of each locked stable time period. The concentrator internally records the average duration required for a single complete meter reading interaction, which is obtained based on statistics from the target meter's recent historical meter reading records. For example, if the average time from sending the meter reading request frame to the completion of the response frame verification in the last 30 successful meter readings of a target meter is 18 seconds, then 18 seconds is taken as the complete meter reading interaction duration for that target meter. All locked stable time periods are traversed, and time period units with a duration greater than 18 seconds and an end time no later than the current task deadline are selected as candidate execution time periods.

[0040] After selecting candidate execution periods, the channel fluctuation baseline of each candidate execution period is read from the two-dimensional file of time period-receive link status, and the corresponding fluctuation envelope width is extracted. The fluctuation envelope width reflects the long-term fluctuation of the carrier signal strength within the time period; therefore, the smaller the fluctuation envelope width, the more stable the power line communication environment corresponding to the time period. The fluctuation envelope widths corresponding to all candidate execution periods are sorted in ascending order, and the candidate execution period with the smallest fluctuation envelope width is selected as the current meter reading execution period. For example, a target energy meter may have three candidate execution periods. When multiple candidate execution periods correspond to the same fluctuation envelope width, the average gain callback count of the most recent 10 meter readings within the corresponding time period is further compared, and the time period with the lowest average gain callback count is selected as the final execution period, thereby further reducing the risk of lock-in disturbances in the automatic gain control process. In addition, to avoid local centralized communication congestion caused by long-term fixed execution of meter readings in the same time period, the number of consecutive reuses is limited. For example, if the same execution period is selected more than 5 times consecutively, it automatically switches to the next priority candidate execution period to reduce link contention caused by the concentrator repeatedly occupying the same time period in a short period.

[0041] Before the official start of the meter reading period, the concentrator enters the receive link pre-locking phase. A fixed lead time of 5 seconds is reserved before the start of the period. When 5 seconds remain before the start of the period, the concentrator pauses the automatic gain dynamic learning process in the current carrier receive link and directly writes the determined target pre-locked gain level into the automatic gain control register. The target pre-locked gain level is derived from the convergence results statistics over a long historical stable period; therefore, the corresponding level is usually close to the actual receiving operating point of the target energy meter under stable communication conditions. The automatic gain control register uses hardware latching to maintain the current preset gain level, ensuring stable receive link operating gain before the meter reading request frame is sent, and avoiding frequent re-convergence of the automatic gain control unit during request frame transmission. Subsequently, when the start of the meter reading period arrives, the concentrator immediately sends a meter reading request frame to the target energy meter and initiates the response frame reception process. Since the receive link has already entered the historical stable operating gain range before the request frame is sent, the automatic gain control only needs minor adjustments to complete the final lock after the target energy meter's response frame returns. When the number of gain adjustments during the reception of a response frame remains below the preset fast convergence threshold, this meter reading record is marked as a fast-lock sampling result. The fast convergence threshold is set based on the concentrator's historical operating results, using three gain adjustments as the fast convergence threshold. For example, if the number of gain adjustments during the reception of this response frame is only two, then the current pre-locked gain level is determined to be very close to the actual stable operating point. For target pre-locked gain levels that are repeatedly identified as fast-lock sampling results, their subsequent priority level is simultaneously increased, thereby enabling the concentrator to gradually converge to a stable operating point of the receiving link that is more suitable for the current power line communication environment.

[0042] Example 2 The difference between Embodiment 2 and Embodiment 1 is that this embodiment introduces a remote meter reading system for a smart energy meter.

[0043] Figure 2 A schematic diagram of a remote meter reading system for a smart energy meter is provided according to the present invention. The remote meter reading system for a smart energy meter includes: The communication acquisition module is used to perform periodic remote meter reading communication with smart meters in the target area through the power line carrier network. It collects the carrier signal strength value and automatic gain control parameters corresponding to the response frames of each meter through a preset query interface, and performs time synchronization and integrity verification. The data aggregation module is used to centrally store and standardize the collected electricity metering data, receiving link status sampling points and communication operation records, and to establish a two-dimensional file of the time period-receiving link status corresponding to the target electricity meter. The link analysis module is used to dynamically monitor the communication quality, online status of equipment, and receiving link during the remote meter reading process, and generate the time sequence change slope and gain lock-on drift corresponding to each time period unit. The pre-locking control module is used to identify the stable periods of the receiving link based on historical stable distribution, determine the target pre-locking gain level according to the gain level shift, and perform pre-locking control on the concentrator carrier receiving link before sending the meter reading request. The operation management module is used to identify meter reading failures, communication interruptions, and data loss, and trigger supplementary collection or retransmission control. At the same time, it continuously updates the pre-locking control strategy based on historical operation data.

[0044] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0045] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0046] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0047] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only 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; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0048] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0049] In addition, the functional modules in the various embodiments of this application 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.

[0050] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a 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 described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0051] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0052] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A remote meter reading method for a smart energy meter, characterized in that, Includes the following steps: S1. When the concentrator receives the response frame of the target energy meter via power line carrier, it extracts the carrier signal strength value and records the automatic gain control parameters. S2. Map the precise time of meter reading to a preset time period unit, merge the carrier signal strength value and automatic gain control parameters into the receiving link status sampling point within the time period unit, and establish a two-dimensional file of the target energy meter's time period-receiving link status. S3. Retrieve the two-dimensional file of the time period-receiver link status of the target energy meter, calculate the temporal change slope of the carrier signal strength of each time period unit, and generate the gain lock-on drift amount according to the automatic gain control parameters. S4. Construct a historical stable distribution of the time-series variation slope and gain-locked drift based on the carrier signal strength, and identify and mark the stable periods of the receiving link; S5. Extract the gain level migration amount of each successful meter reading during the stable period, and determine the target pre-locked gain level by combining the number of gain adjustments. S6. Allocate the current meter reading time to a stable period according to the meter reading deadline, and preset the concentrator carrier receiving link to the target pre-locked gain level before sending the meter reading request.

2. The remote meter reading method for a smart energy meter according to claim 1, characterized in that, In step S1, recording the automatic gain control parameters specifically includes: During the process of receiving the response frame from the target energy meter, the current gain level in the automatic gain control register is read periodically, and a gain change trajectory is formed according to the acquisition time sequence. Record the first gain level in the gain change trajectory as the initial gain level, and record the gain level corresponding to the completion of the response frame verification as the final locked gain level. The number of times the gain level changes in the statistical gain change trajectory is taken as the number of gain adjustments; The process of increasing and decreasing the gain level in the gain change trajectory is recorded as a gain callback if the magnitude of the increase and decrease exceeds the preset callback monitoring threshold. The initial gain level, the final locked gain level, the number of gain adjustments, and the number of gain callbacks are encapsulated as automatic gain control parameters.

3. The remote meter reading method for a smart energy meter according to claim 2, characterized in that, In step S2, establishing the two-dimensional profile of the target energy meter's time period-receiver link status specifically includes: A two-dimensional archive storage structure for time period-receive link status is established, using the communication address of the target energy meter as the first index and the time period identifier of the preset time period unit as the second index. The carrier signal strength value and automatic gain control parameters are integrated into a single receiver link status sampling point, and then appended to the sampling point record set under the corresponding second index according to the time period unit to which the meter reading time belongs. The carrier signal strength values ​​of all received link status sampling points within the corresponding time period are statistically analyzed. The historical average value of the carrier signal strength and the fluctuation envelope width of the corresponding time period are calculated to construct the channel fluctuation baseline corresponding to that time period.

4. The remote meter reading method for a smart energy meter according to claim 3, characterized in that, In step S3, calculating the temporal variation slope of the unit carrier signal strength in each time period and generating the gain-locked drift amount based on the automatic gain control parameters specifically includes: Extract all receiving link status sampling points within each time period unit of the target energy meter from the two-dimensional archive of time period-receiving link status, and sort them in ascending order according to the accurate meter reading time corresponding to the sampling points; Within each time period unit, the ratio of the change in carrier signal strength between adjacent sampling points to the corresponding time interval is calculated, and the average of all ratios is taken as the slope of change for that time period unit. Extract the number of gain callbacks and the number of gain adjustments for each sampling point. The proportion of gain callbacks to gain adjustments is used as the proportion of callback bursts. The channel fluctuation baseline of the current time period unit is envelope normalized and transformed to generate a gain correction coefficient, which is multiplied by the proportion of callback bursts. The result is used as the burst disturbance intensity of the sampling point. The average value of the sudden disturbance intensity of all sampling points within each time period is used as the gain lock-off drift of that time period.

5. The remote meter reading method for a smart energy meter according to claim 1, characterized in that, In step S4, identifying and marking the stable periods of the receiving link specifically includes: The slope of the time series change and the absolute value of the gain lock drift of all time period units of the target energy meter are converted to the same dimension, and the range of the two values ​​is stretched to the same dimension range. The absolute value of the slope after the range is converted to the same level within each time unit and the drift amount are used to form the link stability feature points, and a historical stable distribution is constructed. In the historical stable distribution, the link stable feature point of each time period unit is taken as the center, and the preset neighborhood radius is taken as the search radius. The number of adjacent link stable feature points falling within the search radius is counted as the point density of that time period unit. After traversing all time period units, a high-density cluster area is selected in the region where the link stable feature points with the highest point density are located. The arithmetic mean of the coordinate values ​​of all link stable feature points in each dimension is calculated in the high-density cluster area, and the coordinate point corresponding to the arithmetic mean is taken as the center of the time period cluster. Calculate the distance from the stable feature point of the link corresponding to each time period unit to the center of the time period cluster, and mark the time period units whose distance is less than the preset stable range as locked stable time periods.

6. The remote meter reading method for a smart energy meter according to claim 1, characterized in that, In step S5, determining the target pre-locked gain level specifically includes: From the two-dimensional archive of time period-receive link status, retrieve all receive link status sampling points contained in all time period units marked as locked stable time periods; Extract the initial gain level and the final locked gain level corresponding to each receiving link state sampling point, and calculate the level shift amount that the initial gain level undergoes to converge to the final locked gain level. All sampling points were grouped according to the final locked gain level, and the average level shift and the average number of gain callbacks were calculated for each final locked gain level. The final locked gain gear with the smallest average gear shift amount is selected as the target candidate gear. When there are multiple target candidate gears with the same gear shift amount, the final locked gain gear with the lowest average gain callback number is selected as the target pre-locked gain gear.

7. The remote meter reading method for a smart energy meter according to claim 3, characterized in that, In step S6, allocating the current meter reading time to a stable period according to the meter reading deadline, and presetting the concentrator carrier receiving link to the target pre-locked gain level before sending the meter reading request specifically includes: Obtain the deadline for this meter reading task, and filter out the time period units marked as locked stable time periods. The time span completely covers the time required for a complete meter reading interaction and the end time is no later than the deadline, and use them as candidate execution time periods. Retrieve the channel fluctuation baseline of each candidate execution period from the two-dimensional file of time period-receive link status, extract the fluctuation envelope width in the corresponding channel fluctuation baseline, and select the candidate execution period with the smallest fluctuation envelope width as the execution period for this meter reading. Before the start time of the meter reading execution period arrives, the gain register of the concentrator carrier receiving link is written to the target pre-locked gain level, and a meter reading request frame is sent to the target energy meter when the start time arrives.

8. A remote meter reading system for a smart energy meter, used to implement the remote meter reading method for a smart energy meter as described in any one of claims 1-7, characterized in that, include: The communication acquisition module is used to perform periodic remote meter reading communication with smart meters in the target area through the power line carrier network. It collects the carrier signal strength value and automatic gain control parameters corresponding to the response frames of each meter through a preset query interface, and performs time synchronization and integrity verification. The data aggregation module is used to centrally store and standardize the collected electricity metering data, receiving link status sampling points and communication operation records, and to establish a two-dimensional file of the time period-receiving link status corresponding to the target electricity meter. The link analysis module is used to dynamically monitor the communication quality, online status of equipment, and receiving link during the remote meter reading process, and generate the time sequence change slope and gain lock-on drift corresponding to each time period unit. The pre-locking control module is used to identify the stable periods of the receiving link based on historical stable distribution, determine the target pre-locking gain level according to the gain level shift, and perform pre-locking control on the concentrator carrier receiving link before sending the meter reading request. The operation management module is used to identify meter reading failures, communication interruptions, and data loss, and trigger supplementary collection or retransmission control. At the same time, it continuously updates the pre-locking control strategy based on historical operation data.

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