Power utilization information acquisition and transmission method based on multiple networks and multiple channels

Abstract

The invention relates to the technical field of dual-mode communication, in particular to a multi-network multi-channel-based electricity consumption information acquisition and transmission method, which comprises the following steps of: installing electricity counters at a plurality of detection points, monitoring electricity consumption in real time, acquiring the real-time electricity consumption of each detection point, and performing comparative analysis on the real-time electricity consumption and original electricity consumption data of the detection points; and identifying an abnormal power consumption mode through difference analysis. According to the method, the power consumption is monitored in real time, and the abnormal power consumption mode is accurately identified, so that the abnormal data can be quickly responded and efficiently processed, key data can be preferentially processed in an emergency, the coping capacity to emergencies is improved, and the transmission efficiency is improved by dynamically adjusting the transmission power and channel parameters. According to the real-time network condition, the data transmission path is optimized, the energy consumption is reduced, the stability and reliability of data transmission are enhanced, and the function of automatically adjusting network parameters and transmission strategies ensures that efficient data flow and processing can still be kept under the continuously changing network condition.

Description

Technical Field

[0001] The present invention relates to the technical field of dual-mode communication, and in particular to a method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels. Background Art

[0002] The field of dual-mode communication technology mainly involves systems and methods for simultaneously transmitting information through different communication modes or technologies. The core of this field is to use two or more communication methods to enhance the reliability, coverage or speed of data transmission. For example, wired communication (such as high-speed carrier communication) and wireless communication (such as micro-power wireless communication) can be used simultaneously to ensure that even if there is a problem with one communication path in a system, the stability of communication can be maintained through another path. This technology is widely used in scenarios that require high reliability and strong adaptability, such as smart grids, home automation, and remote monitoring systems.

[0003] Among them, the multi-network and multi-channel electricity consumption information collection and transmission method refers to a technical method for collecting and transmitting electricity consumption information through multiple networks and channels. This method combines different communication technologies, such as high-speed carrier communication and micro-power wireless communication, to achieve effective monitoring and management of electricity usage. The main uses include real-time data collection, fault detection, energy management and remote control, etc., to optimize energy efficiency and ensure the safe and stable operation of the power grid. This method is particularly important in smart meter reading, power system monitoring and urban infrastructure management.

[0004] Existing technologies often show insufficient adaptability and low processing efficiency under high data traffic and rapidly changing network conditions. Especially in terms of emergency data processing, existing systems often cannot effectively identify and prioritize key information, resulting in data transmission delays or losses during peak periods of power system demand, affecting the stable operation of the power grid. The lack of the ability to flexibly adjust transmission parameters also makes it impossible to effectively optimize data flow when the network load is large, increasing energy waste and difficulty in system maintenance. For example, when encountering large-scale electricity consumption or communication peaks, due to the lack of an effective dynamic adjustment mechanism, existing technologies fail to optimize communication strategies and network parameters in a timely manner, resulting in obstruction of key data processing, which in turn affects the efficiency and safety of the entire power grid. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings existing in the prior art and to propose a method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels, comprising the following steps: S1: Install power counters at multiple detection points to monitor power consumption in real time. Collect the real-time power consumption of each detection point and compare and analyze it with the original power consumption data of the detection point. Identify abnormal power consumption patterns through difference analysis to obtain abnormal power consumption detection results. S2: Based on the abnormal power consumption detection result, the data is classified according to the urgency, the priority is set according to the urgency of data content processing, the communication channel is allocated, and the data is transmitted to the central processing system through routing to obtain a priority data processing queue; S3: compressing the data in the priority data processing queue, adjusting the transmission power and channel parameters, measuring the signal interference and data packet loss rate, adjusting the error detection threshold according to the measurement results, matching the channel and power parameters, recording the data response of the adjustment operation, and obtaining the transmission optimization configuration; S4: Apply the transmission optimization configuration, monitor the data flow of the transmission path and nodes, continuously monitor the data transmission efficiency and error rate, analyze the real-time network load and signal attenuation, automatically adjust the transmission strategy and network parameters according to the real-time feedback, and generate the network performance adjustment result.

[0007] As a further solution of the present invention, the steps for obtaining the abnormal power consumption detection result are specifically as follows: S111: installing power counters at multiple detection points, monitoring and recording the real-time power consumption of each detection point, and generating real-time power consumption data records; S112: extracting the current power consumption of multiple detection points from the real-time power consumption data record, and comparing it with the original power consumption data of the detection points, and based on the difference analysis, using the formula: ; Identify data points that deviate from normal patterns and obtain electricity usage deviation data; in, Represents the power consumption deviation percentage of the i-th detection point, Represents the real-time power consumption of the current detection point, Represents the normal power consumption of the detection point, It is a small quantity used to stabilize calculations; S113: Using the power consumption deviation data, identifying abnormal power consumption patterns through difference analysis, screening data points whose abnormal deviation values ​​exceed a set threshold, and generating abnormal power consumption detection results.

[0008] As a further solution of the present invention, the step of obtaining the priority data processing queue is specifically as follows: S211: receiving abnormal power consumption detection results, extracting and arranging data on the results, and generating a preliminary arranged abnormal power consumption data record; S212: extracting key features from the preliminarily sorted abnormal power consumption data, including power consumption and time, and calculating the urgency score of each data point based on the key features, using the formula: ; Generate an urgency score for the data point; in, represents the urgency score of the data point, For abnormal power, For the detection time, is the weight parameter, To adjust the threshold of power impact; S213: Analyze the urgency scores of the data points, prioritize the data based on the scores, and generate a data priority list; S214: The high-priority data is securely sent to the central processing system via the data communication network, and the data is integrated according to the data priority list to obtain a priority data processing queue.

[0009] As a further solution of the present invention, the step of acquiring the transmission optimization configuration is specifically as follows: S311: compressing the data in the priority data processing queue to reduce the amount of data during transmission and generate compressed data records; S312: Use the compressed data record to adjust the transmission power and channel parameters, using the formula: ; in, represents the adjusted transmission power, is the original power, is the adjustment factor, and Respectively represent the current and initial signal interference levels, and generate adjusted power and channel parameters; S313: Use the adjusted power and channel parameters to measure signal interference and data packet loss rate, adjust the error detection threshold according to the measurement results, and generate an error adjustment record; S314: Use the error adjustment record to complete the matching and optimization of channel and power parameters to obtain a transmission optimization configuration.

[0010] As a further solution of the present invention, the step of obtaining the network performance adjustment result is specifically: S411: Apply the transmission optimization configuration, monitor the data traffic of multiple nodes, collect data traffic information, and generate traffic monitoring records; S412: Continuously monitor the data transmission efficiency and error rate using the traffic monitoring record, using the formula: ; Adjust transmission efficiency and generate efficiency adjustment records; in, represents the adjusted transmission efficiency, is the original transmission efficiency, is the adjustment factor, represents the observed error rate, is the target error rate; S413: Analyze the real-time network load and signal attenuation based on the efficiency adjustment record, using the formula: ; Automatically adjust network parameters and generate network parameter adjustment records; in, are the adjusted network parameters, is the current parameter, is the adjustment factor, is the current signal attenuation, is the target signal attenuation; S414: Summarize the network parameter adjustment records, update the transmission strategy to match the real-time network load and optimize signal attenuation, and generate a network performance adjustment result.

[0011] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by real-time monitoring of power consumption and accurate identification of abnormal power consumption patterns, rapid response and efficient processing of abnormal data are achieved. This refined abnormal monitoring and data priority classification ensures that key data can be processed first in emergency situations, improving the system's ability to respond to emergencies. In addition, by dynamically adjusting the transmission power and channel parameters and optimizing the data transmission path according to the real-time network conditions, not only energy consumption is reduced, but also the stability and reliability of data transmission are enhanced. This automatic adjustment function of network parameters and transmission strategies ensures that efficient data flow and processing can be maintained under constantly changing network conditions, greatly improving the intelligence and automation level of power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the main steps of the present invention; Figure 2 A flowchart of the steps for obtaining abnormal power consumption detection results of the present invention; Figure 3 A flow chart of the steps for obtaining a priority data processing queue of the present invention; Figure 4 A flow chart of the steps for obtaining the transmission optimization configuration of the present invention; Figure 5 The present invention is a flowchart of the steps for obtaining the network performance adjustment results. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0014] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. Embodiment 1

[0015] See also Figure 1 The present invention provides a technical solution: a method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels, comprising the following steps: S1: Install power counters at multiple detection points to monitor power consumption in real time. Collect the real-time power consumption of each detection point and compare and analyze it with the original power consumption data of the detection point. Identify abnormal power consumption patterns through difference analysis to obtain abnormal power consumption detection results. S2: Based on the abnormal power consumption detection results, the data is classified according to the urgency, the priority is set according to the urgency of data content processing, the communication channel is allocated, and the data is transmitted to the central processing system through routing to obtain the priority data processing queue; S3: compress the data in the priority data processing queue, adjust the transmission power and channel parameters, measure the signal interference and data packet loss rate, adjust the error detection threshold according to the measurement results, match the channel and power parameters, record the data response of the adjustment operation, and obtain the transmission optimization configuration; S4: Apply transmission optimization configuration, monitor the data flow of transmission paths and nodes, continuously monitor data transmission efficiency and error rate, analyze real-time network load and signal attenuation, automatically adjust transmission strategies and network parameters based on real-time feedback, and generate network performance adjustment results.

[0016] The abnormal power consumption detection results include abnormal mode, abnormal index and abnormal degree. The priority data processing queue includes data urgency, priority sorting and channel configuration. The transmission optimization configuration includes channel parameters, transmission power and error detection threshold. The network performance adjustment results include data transmission efficiency, error rate and network parameters.

[0017] See also Figure 2 , the specific steps for obtaining abnormal power consumption detection results are as follows: S111: installing power counters at multiple detection points, monitoring and recording the real-time power consumption of each detection point, and generating real-time power consumption data records; Among them, power counters are installed at multiple detection points to monitor and record the real-time power consumption of each detection point. , calculate the logarithmic transformation of real-time electricity consumption data to reduce the impact of extreme values ​​and simplify the data structure.

[0018] In the formula, represents the logarithmically transformed electricity consumption data of the ith detection point, Represents the real-time power consumption of the ith detection point.

[0019] Detailed explanation of the formula and the process of formula calculation and derivation: When processing real-time power consumption data, directly using power consumption values ​​will affect the analysis of the overall data due to extreme consumption values ​​(including sudden increases or decreases in power consumption). Add 1 to the power consumption of each detection point and take the natural logarithm, which effectively avoids This transformation not only handles extreme values, but also compresses the range of the variable, making it easier to identify patterns and anomalies during data analysis.

[0020] If the real-time power consumption of a detection point is set to 10 kWh, the calculation process is: ; The results show that the electricity consumption data after logarithmic transformation can enter the next step of analysis more smoothly, reduce the impact of extreme values, and facilitate iterative data processing and identification of abnormal electricity consumption patterns.

[0021] S112: extract the current power consumption of multiple detection points from the real-time power consumption data record, compare it with the original power consumption data of the detection points, and use the formula based on difference analysis: ; Identify data points that deviate from normal patterns and obtain electricity usage deviation data; in, Represents the power consumption deviation percentage of the i-th detection point, Represents the real-time power consumption of the current detection point, Represents the normal power consumption of the detection point, It is a small quantity used to stabilize calculations; formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: Calculate the deviation between the power consumption of multiple detection points and the normal power consumption pattern. Formula It is used to measure real-time power consumption and conventional electricity consumption The relative difference between It is a very small positive number used to ensure that the denominator is not zero and takes a very small value, such as 0.01.

[0022] In the formula: Indicates the power consumption deviation ratio of the i-th detection point.

[0023] Represents the real-time power consumption of the current detection point.

[0024] Represents the typical power consumption at the detection point.

[0025] Used to avoid the situation where the denominator is zero.

[0026] Set the real-time power consumption of a detection point is 120 kWh, while the normal electricity consumption For 100 kWh, substitute the value into the formula to calculate the deviation ratio: The results show that the power consumption at the detection point is about 20% higher than the normal pattern, which indicates the existence of some abnormal power consumption pattern.

[0027] S113: Using the power consumption deviation data, identifying abnormal power consumption patterns through difference analysis, screening data points whose abnormal deviation values ​​exceed a set threshold, and generating abnormal power consumption detection results.

[0028] Among them, the abnormal power consumption pattern is identified through difference analysis, and the data points whose abnormal deviation value exceeds the set threshold are screened out. According to the formula , calculate whether each data point exceeds the threshold and determine whether it is recorded as abnormal power consumption data.

[0029] In the formula, Indicates whether the i-th data point is marked as abnormal. Represents the set threshold ratio, Represents the maximum power consumption deviation among all detection points.

[0030] Detailed explanation of the formula and the process of formula calculation and derivation: In this step, a threshold determination method is used to identify and mark abnormal power consumption data. The setting is based on the statistical analysis of the data, for example, the setting is set to the 95% quantile value of the deviation.

[0031] Setting Thresholds A value of 0.15 means focusing on data points that exceed 15% of the maximum deviation, and a maximum deviation of 0.20: ; The results show that any data point with a deviation exceeding 0.03 will be marked as an anomaly.

[0032] See also Figure 3 , the specific steps for obtaining the priority data processing queue are: S211: receiving abnormal power consumption detection results, extracting and arranging data on the results, and generating a preliminary arranged abnormal power consumption data record; Among them, receiving abnormal power consumption detection results and extracting and sorting data, according to the formula , calculate the total amount of data after sorting.

[0033] In the formula, Represents the total amount of data after sorting. represents the amount of data for the ith data point, Represents data weight, which is assigned differentiated weights based on the urgency of the data.

[0034] Detailed explanation of the formula and the process of formula calculation and derivation: In order to calculate the total amount of data after sorting, the weighted sum formula is used. The amount of data for each data point is multiplied by its corresponding weight , weights are assigned based on the urgency of the data, with higher urgency data being given weights. For example, a data point with high urgency has a weight of 0.5, while a data point with low urgency has a weight of 0.1. Then, all weighted data points are added together to get the total .

[0035] For example, there are three data points, the data volumes are 10, 15, and 20, and the corresponding weights are 0.5, 0.3, and 0.2. The calculation of is as follows: ; The results show that after referring to the urgency weight of the data, the total amount of data after sorting is 13.5.

[0036] S212: Extract key features from the preliminarily sorted abnormal power consumption data, including power consumption and time, and calculate the urgency score of each data point based on the key features using the formula: ; Generate an urgency score for the data point; in, represents the urgency score of the data point, For abnormal power, For the detection time, is the weight parameter, To adjust the threshold of power impact; formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: Formula used to calculate the urgency score of abnormal power usage data points ,in represents the abnormal amount of electricity at the ith data point, Represents the detection time of the data point. The parameters are the weight parameters of nonlinear adjustment of power, time and power impact, respectively. It is the threshold value for the power impact adjustment.

[0037] To ensure that the parameters are specific and practical, it is necessary to obtain the parameter values ​​from actual data. ,and If the abnormal power of the data point is 80 and the detection time is 2 hours, the calculation process is as follows: Calculate the contribution of power to urgency: ; Calculate the contribution of time to urgency: ; Calculate the nonlinear adjustment contribution of power impact: ; The urgency scores are: ; The results show that under the given parameters, the urgency score of the data point is 2.997, indicating that it should be given a higher reference in the processing priority.

[0038] S213: analyzing the urgency scores of the data points, prioritizing the data based on the scores, and generating a data priority list; Among them, analyze the urgency score and set the data processing priority according to the formula , calculate the processing priority of each data point.

[0039] In the formula, Represents the processing priority. Score the urgency level. is an adjustment factor used to adjust the sensitivity of the priority according to system needs.

[0040] Detailed explanation of the formula and the process of formula calculation and derivation: To ensure the practicality and accuracy of the formula application, a proportional formula is used to determine the processing priority of each data point. Adjustment coefficient Set the response requirements according to the system processing capacity and urgency. .

[0041] For example, the urgency score of a data point , then the processing priority is calculated as follows: ; The results show that the processing priority of the data point is 4.4955, which means that it is at the front of the processing queue and should be processed first.

[0042] S214: The high-priority data is securely sent to the central processing system through the data communication network, and the data is integrated according to the data priority list to obtain a priority data processing queue.

[0043] Among them, the high-priority data is securely sent to the central processing system through the data communication network, according to the formula , calculate the data transmission efficiency.

[0044] In the formula, Represents the data transmission efficiency, is the data volume, is the transmission time, The network delay time.

[0045] Detailed explanation of the formula and the process of formula calculation and derivation: In order to do this, data transfer must be fast and reliable. Transfer time Seconds, network delay Second.

[0046] The data transmission efficiency is calculated as follows: ; The results show that under current network conditions, the data transmission efficiency is 41.67MB / s.

[0047] See also Figure 4 , the specific steps for obtaining the transmission optimization configuration are: S311: compressing the data in the priority data processing queue to reduce the amount of data in the transmission process and generate compressed data records; Among them, data compression is performed to process the data in the priority data processing queue to reduce the data volume. According to the formula , calculate the compressed data volume.

[0048] In the formula, Represents the data volume, Represents the original data volume, is the compressive strength parameter, Represents the compression ratio.

[0049] Detailed explanation of the formula and the process of formula calculation and derivation: Referring to the effect of reducing the data volume during compression, the compression ratio is introduced and compressive strength parameters ,in, It can be obtained through actual data compression test. For example, if the original data volume is 10MB and the compression ratio is 0.5, it can be obtained through actual measurement. As a constant 1, calculate: ; The results show that by applying the compression strategy, the data size is reduced from 10MB to about 6.065MB, which is beneficial for data transmission optimization and reduces the time and resources required for transmission.

[0050] S312: Use the compressed data record to adjust the transmission power and channel parameters, using the formula: ; in, represents the adjusted transmission power, is the original power, is the adjustment factor, and Respectively represent the current and initial signal interference levels, and generate adjusted power and channel parameters; formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: In this step, the transmission power is adjusted according to the new characteristics of the compressed data. To calculate the transmission power and Represent the current and initial signal interference levels respectively.

[0051] Set the raw transmission power For 100W, the adjustment factor is 0.05, the current signal interference level is 120 units, while the initial signal interference is 100 units. Plugging the values ​​into the formula, calculate the transmitted power: ; The results show that due to the increase in current signal interference, the transmission power needs to be increased to To maintain the quality of communication.

[0052] S313: Use the adjusted power and channel parameters to measure signal interference and data packet loss rate, adjust the error detection threshold according to the measurement results, and generate an error adjustment record; Among them, using the adjusted parameters, measuring signal interference and data packet loss rate, according to the formula , calculate the adjusted packet loss rate.

[0053] In the formula, represents the adjusted packet loss rate, represents the measured packet loss rate, is the attenuation factor, represents the error detection rate.

[0054] Detailed explanation of the formula and the process of formula calculation and derivation: This step focuses on the measurement and adjustment of the signal packet loss rate and error rate. Through actual measurement, set the measured packet loss rate is 0.08 (i.e. 8% packet loss), and by adjusting the error detection rate Increase to 0.25 (25%), set the attenuation factor is 0.5, insert the value to calculate: ; The results show that by adjusting the strategy, the packet loss rate is reduced from 8% to 7%, showing an improvement in signal quality.

[0055] S314: Use the error adjustment record to complete the matching and optimization of channel and power parameters to obtain the transmission optimization configuration.

[0056] Among them, the comprehensive error adjustment record, matching channel and power parameters, according to the formula , calculate the optimized channel configuration. represents the measured signal strength, Represents the target signal strength.

[0057] Detailed explanation of the formula and the process of formula calculation and derivation: In this step, the channel and power are iteratively optimized based on the adjusted error rate and packet loss rate data. Set the initial channel configuration is 100, the target signal strength Set to 50dB, measured signal strength is 55dB, adjustment coefficient Set it to 0.1 and apply the formula for calculation: ; The results show that through adjustment, the channel configuration increases from 100 to 101, and this adjustment helps to better match the channel conditions, thereby improving the overall transmission efficiency and signal quality.

[0058] See also Figure 5 , the specific steps for obtaining the network performance adjustment results are: S411: Apply transmission optimization configuration, monitor data traffic of multiple nodes, collect data traffic information, and generate traffic monitoring records; Among them, the application transmission optimization configuration and monitoring of multi-node data traffic, according to the formula Calculate the average data traffic.

[0059] In the formula, Represents the average data traffic, Represents the total amount of data, Represents a time period.

[0060] Detailed explanation of the formula and the process of formula calculation and derivation: Set in monitoring time period The total amount of data collected within one second (i.e. one hour) The average data flow is 1.8TB, and the average data flow can be calculated as follows: ; Calculations show that the average data flow is 500MB per second, which helps to understand the network load and make iterative optimization adjustments.

[0061] S412: Use traffic monitoring records to continuously monitor data transmission efficiency and error rate using the formula: ; Adjust transmission efficiency and generate efficiency adjustment records; in, represents the adjusted transmission efficiency, is the original transmission efficiency, is the adjustment factor, represents the observed error rate, is the target error rate; formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: Formula used to calculate adjusted data transfer efficiency ,in Represents the original transmission efficiency, is the adjustment factor, represents the observed error rate, is the target error rate.

[0062] Set the original transfer efficiency The observed error rate is 80%. The target error rate is 0.1%. Set to 0.05%, adjustment factor The choice is 2. The calculation process is as follows: ; But because The result must be between 0 and 1, and the maximum value is 1. .

[0063] This shows how the transmission efficiency is adjusted, adaptively adjusting according to changes in error rates to ensure that the network reaches or maintains optimal performance.

[0064] S413: Analyze real-time network load and signal attenuation based on efficiency adjustment records, using the formula: ; Automatically adjust network parameters and generate network parameter adjustment records; in, are the adjusted network parameters, is the current parameter, is the adjustment factor, is the current signal attenuation, is the target signal attenuation; formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: Formulas are used to automatically adjust network parameters , based on the current parameters , adjustment coefficient , the current signal attenuation , and the target signal attenuation .

[0065] Set the current network parameters is 50 units, the current signal attenuation The target signal is attenuated by 10dB. 5dB, adjustment coefficient Set to 0.2. The calculation process is as follows: ; Calculations show that in order to achieve the target signal attenuation level, the network parameters need to be changed from Adjustment , reflecting the automatic adjustment strategy of network parameters based on actual signal attenuation conditions.

[0066] S414: Integrate the network parameter adjustment records, update the transmission strategy to match the real-time network load and optimize signal attenuation, and generate a network performance adjustment result.

[0067] Among them, comprehensive network parameter adjustment records, update transmission strategy to match real-time network load and optimize signal attenuation, according to the formula , calculate the percentage change of transmission strategy, where represents the strategy percentage, is the adjusted network load value, is the network load value before adjustment.

[0068] Detailed explanation of the formula and the process of formula calculation and derivation: Set the network load before adjustment The capacity utilization is 75%, after adjustment due to optimization Reduced to 50%, the calculation process is as follows: ; This indicates that the network load has been reduced by 33.33% due to the optimization measures, showing the efficiency improvement brought about by the transmission strategy and network parameter adjustments.

[0069] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels, characterized in that: The following steps are involved: Install power counters at multiple detection points to monitor power consumption in real time. Collect the real-time power consumption of each detection point and compare and analyze it with the original power consumption data of the detection point. Identify abnormal power consumption patterns through difference analysis to obtain abnormal power consumption detection results. Based on the abnormal power consumption detection results, the data is classified according to the urgency, the priority is set according to the urgency of data content processing, the communication channel is allocated, and the data is transmitted to the central processing system through routing to obtain a priority data processing queue; Implementing compression processing on the data in the priority data processing queue, adjusting transmission power and channel parameters, measuring signal interference and data packet loss rate, adjusting error detection threshold according to the measurement results, matching channel and power parameters, recording data response of the adjustment operation, and obtaining transmission optimization configuration; Apply the transmission optimization configuration, monitor the data flow of the transmission path and nodes, continuously monitor the data transmission efficiency and error rate, analyze the real-time network load and signal attenuation, automatically adjust the transmission strategy and network parameters according to the real-time feedback, and generate the network performance adjustment result.

2. The method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels according to claim 1 is characterized in that: The steps for obtaining the abnormal power consumption detection result are specifically as follows: Install electricity counters at multiple detection points to monitor and record the real-time electricity consumption at each detection point and generate real-time electricity consumption data records; The current power consumption of multiple detection points is extracted from the real-time power consumption data record, and compared with the original power consumption data of the detection points. Based on the difference analysis, the formula is adopted: ； Identify data points that deviate from normal patterns and obtain electricity consumption deviation data; in, Represents the power consumption deviation percentage of the i-th detection point, Represents the real-time power consumption of the current detection point, Represents the normal power consumption of the detection point, It is a small quantity used to stabilize calculations; The power consumption deviation data is used to identify abnormal power consumption patterns through difference analysis, and data points whose abnormal deviation values ​​exceed a set threshold are screened to generate abnormal power consumption detection results.

3. The method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels according to claim 2 is characterized in that: The steps for obtaining the priority data processing queue are specifically as follows: Receiving the abnormal power consumption detection result, extracting and collating the data of the result, and generating a preliminary sorted abnormal power consumption data record; Extract the key features of the abnormal power consumption data records after preliminary sorting, including power consumption and time, and calculate the urgency score of each data point based on the key features, using the formula: ； Generate an urgency score for the data point; in, represents the urgency score of the data point, For abnormal power, For the detection time, is the weight parameter, To adjust the threshold of power impact; Analyze the urgency scores of the data points, prioritize the data based on the scores, and generate a data priority list; The high-priority data is securely sent to the central processing system through the data communication network, and the data is integrated according to the data priority list to obtain a priority data processing queue.

4. The method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels according to claim 3 is characterized in that: The steps for obtaining the transmission optimization configuration are specifically as follows: Compressing the data in the priority data processing queue to reduce the amount of data during transmission and generate compressed data records; The compressed data record is used to adjust the transmission power and channel parameters using the formula: ； in, represents the adjusted transmission power, is the original power, is the adjustment factor, and Respectively represent the current and initial signal interference levels, and generate adjusted power and channel parameters; Using the adjusted power and channel parameters to measure signal interference and data packet loss rate, adjusting the error detection threshold according to the measurement results, and generating an error adjustment record; The error adjustment record is used to complete the matching and optimization of channel and power parameters and record the transmission optimization configuration.

5. The method for collecting and transmitting electricity consumption information based on multiple networks and multiple channels according to claim 4 is characterized in that: The steps of obtaining the network performance adjustment result are specifically as follows: Apply the transmission optimization configuration, monitor the data traffic of multiple nodes, collect data traffic information, and generate traffic monitoring records; The traffic monitoring records are used to continuously monitor the data transmission efficiency and error rate, using the formula: ； Adjust transmission efficiency and generate efficiency adjustment records; in, represents the adjusted transmission efficiency, is the original transmission efficiency, is the adjustment factor, represents the observed error rate, is the target error rate; Based on the efficiency adjustment record analysis of real-time network load and signal attenuation, the formula is used: ； Automatically adjust network parameters and generate network parameter adjustment records; in, are the adjusted network parameters, is the current parameter, is the adjustment factor, is the current signal attenuation, is the target signal attenuation; The network parameter adjustment records are integrated to update the transmission strategy to match the real-time network load and optimize signal attenuation, thereby generating a network performance adjustment result.

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