CN118860668B - Intelligent ammeter data processing method and system based on regional management - Google Patents
Intelligent ammeter data processing method and system based on regional management Download PDFInfo
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Abstract
本发明涉及一种基于区域化管理的智能电表数据处理方法和系统，涉及电表技术领域，该方法包括：将整个供电区域划分为多个独立的管理区，每个管理区内设立区域节点服务器；将电力使用数据传输至所在区域的区域节点服务器进行初步处理得到区域内总电力使用量；通过中间节点服务器处理和分析区域内总电力使用量，得到整合数据；对每个智能电表的电力使用数据进行异常检测，修复异常数据，得到处理后数据；对处理后数据进行最终存储和综合分析，得到目标数据；根据目标数据，确定各区域节点服务器和各区域节点服务器的负载，并根据负载动态调整各区域节点服务器和各区域节点服务器的区域范围。本发明能够提升智能电表数据处理的准确性、安全性和效率。
The present invention relates to a smart meter data processing method and system based on regional management, and relates to the technical field of electric meters. The method comprises: dividing the entire power supply area into multiple independent management areas, and setting up a regional node server in each management area; transmitting the power usage data to the regional node server in the area for preliminary processing to obtain the total power usage in the area; processing and analyzing the total power usage in the area through the intermediate node server to obtain integrated data; performing abnormal detection on the power usage data of each smart meter, repairing the abnormal data, and obtaining processed data; performing final storage and comprehensive analysis on the processed data to obtain target data; determining the load of each regional node server and each regional node server according to the target data, and dynamically adjusting each regional node server and each regional node server's regional range according to the load. The present invention can improve the accuracy, security and efficiency of smart meter data processing.
Description
Technical Field
The invention relates to the technical field of electric meters, in particular to a smart electric meter data processing method, a smart electric meter data processing system, electronic equipment and a non-transitory computer readable storage medium based on regional management.
Background
Today, smart meter data processing methods rely mainly on centralized data acquisition and management systems. These systems periodically collect power usage data through smart meters installed at each user's home or business, and then transmit the data to a central server through a network for storage and processing. The centralized system has the advantage that the centralized system can uniformly manage and analyze a large amount of data, thereby providing accurate electricity consumption analysis and real-time monitoring. In addition, the centralized system can also support advanced functions such as remote meter reading, abnormal electricity behavior detection and load prediction.
However, as the number of users and the amount of data continue to increase, the processing pressure and storage requirements of central servers rapidly rise, easily resulting in system performance bottlenecks and response time extension. Secondly, problems such as network delay, transmission interruption or data loss can be encountered in the data transmission process, and the real-time performance and accuracy of the data are affected. In addition, centralized systems also face challenges in terms of data security and privacy protection, and once user data stored centrally is attacked, it may lead to large-scale information leakage. Finally, the maintenance and expansion costs of the centralized system are high, which is not beneficial to large-scale deployment and application popularization.
Therefore, the smart meter data processing method based on regional management gradually becomes a hot spot for research and application.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a smart meter data processing method, a smart meter data processing system, electronic equipment and a non-transitory computer readable storage medium based on regional management, which can improve the accuracy, safety and efficiency of smart meter data processing.
The technical scheme for solving the technical problems is as follows:
The invention provides a smart meter data processing method based on regional management, which comprises the following steps:
Dividing the whole power supply area into a plurality of independent management areas, and setting up an area node server in each management area;
each intelligent ammeter periodically transmits the power usage data to an area node server of the area where the intelligent ammeter is located, and the area node server performs preliminary processing on the received power usage data to obtain the total power usage in the area;
Each regional node server periodically gathers and transmits the processed total power usage in the region to an intermediate node server, the intermediate node server further processes and analyzes the power usage data, and data integration among regions is carried out to obtain integrated data;
Performing anomaly detection on the power usage data of each intelligent ammeter according to the integrated data, and repairing the anomaly data to obtain processed data;
Transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data;
and determining the loads of the regional node servers and the regional node servers according to the target data, and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
Optionally, the preliminary processing, by the regional node server, the received power usage data to obtain a total power usage in the region includes:
a first adjustment coefficient and a second adjustment coefficient are obtained,
Acquiring the electric power usage amount acquired by each intelligent electric meter and the error correction value corresponding to each intelligent electric meter;
And determining the total power consumption in the area according to the quantity of the intelligent electric meters in the area, the first adjustment coefficient, the second adjustment coefficient, the power consumption collected by each intelligent electric meter and the error correction value corresponding to each intelligent electric meter.
Optionally, the total power usage in the area is expressed as:
Wherein, Is the total power usage in the area, N is the number of smart meters in the area,Is the firstThe amount of power usage of the smart meter,And beta is a first adjustment factor and a second adjustment factor respectively,Is the firstError correction value of each intelligent ammeter.
Optionally, the further processing and analyzing, by the intermediate node server, the power usage data, and integrating data between areas to obtain integrated data, including:
acquiring the number of the areas to be integrated;
Acquiring a first weight and a total power usage amount of each area;
acquiring a third adjustment coefficient;
and determining the integrated data according to the third adjustment coefficient, the number of areas, the first weight of each area and the total power usage.
Optionally, the integrated data is expressed as:
Wherein, Is integrated data representing a weighted average power usage of a plurality of regions, M is the number of regions,Is the first weight of the j-th region,Is the total power usage of the jth zone,Is the third adjustment coefficient.
Optionally, the anomaly detection for the power usage data of each smart meter according to the integrated data includes:
Acquiring the power usage amount of each intelligent ammeter and the integration data;
acquiring standard deviation of the power consumption in the area;
Obtaining a fourth adjustment coefficient
Determining an anomaly detection value according to the power usage amount of each intelligent ammeter, the integrated data, the standard deviation of the power usage amount in the area and the fourth adjustment coefficient, and performing anomaly detection on the integrated data based on the anomaly detection value
Alternatively, the abnormality detection value is expressed as:
Wherein, Is an anomaly detection value, represents a standard deviation value of data points of the ith smart meter,Is the power usage of the i-th smart meter,Is the data of the integration of the data,Is the standard deviation of the amount of power usage in the area,Is the fourth adjustment coefficient.
Optionally, the transmitting the processed data to a central server for final storage and comprehensive analysis includes:
Calculating a hash value of the processed data, and carrying out hash check on the processed data; wherein the hash value of the processed data is expressed as:
Where H represents a hash value of data transmission verification, Representing the processed data to be transmitted,The time stamp is indicated as such,Represents the key, salt represents the Salt value,Representing the connection operation.
Optionally, the dynamically adjusting each regional node server and the regional scope of each regional node server according to the load includes:
Processing initial weights of load distribution of the regional node servers and the regional node servers according to the current load, the maximum load, the current response time, the optimal response time and the fifth adjustment coefficient of the regional node servers and the regional node servers to obtain corresponding second weights; wherein the second weight is expressed as:
Wherein, Is the second weight after the initial weight adjustment,Is the initial weight of the weight to be added,Is the current load of the node and,Is the maximum load of the node and,Is the current response time of the device,Is the optimal response time for the device to be used,Is the fifth adjustment coefficient.
The invention also provides a smart meter data processing system based on regional management, which comprises:
the regional division module is used for dividing the whole power supply region into a plurality of independent management regions, and a regional node server is arranged in each management region;
The first processing module is used for periodically transmitting the power usage data to an area node server of the area where each intelligent ammeter is located, and performing preliminary processing on the received power usage data through the area node server to obtain the total power usage in the area;
The second processing module is used for periodically summarizing the processed total power usage in the area by each area node server, transmitting the summarized total power usage to an intermediate node server, further processing and analyzing the power usage data by the intermediate node server, and integrating the data among the areas to obtain integrated data;
the third processing module is used for carrying out anomaly detection on the power use data of each intelligent ammeter according to the integrated data, repairing the anomaly data and obtaining processed data;
The fourth processing module is used for transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data;
and the fifth processing module is used for determining the loads of the regional node servers and the regional node servers according to the target data and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
In addition, to achieve the above object, the present invention also proposes an electronic device including: a memory for storing a computer software program; and the processor is used for reading and executing the computer software program so as to realize the intelligent ammeter data processing method based on regional management.
In addition, in order to achieve the above object, the present invention also proposes a non-transitory computer readable storage medium, in which a computer software program is stored, which when executed by a processor, implements a smart meter data processing method based on regional management as described above.
The beneficial effects of the invention are as follows:
(1) The invention distributes the data processing task to a plurality of Regional Node Servers (RNS) and Intermediate Node Servers (INS) through regional management, thereby greatly reducing the load pressure of the central server. Each RNS and INS is responsible for data acquisition and preliminary processing in the jurisdiction area, so that the performance bottleneck problem caused by overlarge data volume of a central server is effectively avoided, and the overall response speed of the system is remarkably improved.
(2) The Regional Node Server (RNS) and the Intermediate Node Server (INS) reduce the times of long-distance data transmission in the data processing process, reduce the risks of network delay and data transmission interruption, and improve the real-time performance and accuracy of data transmission. By performing preliminary processing and verification of data at the RNS and INS levels, errors and losses that may occur during data transmission are reduced.
(3) The invention effectively reduces the exposure opportunity of the data in the transmission process and reduces the risks of attack and leakage through regional management and distributed data processing. Meanwhile, each regional node only stores and processes the data in the management range, even if a certain node is attacked, the influence range is limited to the region managed by the node, and the overall safety of the system and the user privacy protection capability are improved.
In summary, the intelligent ammeter data processing method based on regional management can effectively solve various defects in the existing centralized processing method, remarkably improves the performance, safety, expandability and service level of the system, and provides a more efficient and reliable solution for power management and user service.
Drawings
FIG. 1 is a scene diagram of a smart meter data processing method based on regional management, which is provided by the invention;
FIG. 2 is a flow chart of a method for processing data of a smart meter based on regional management;
FIG. 3 is a schematic structural diagram of a data processing system of a smart meter based on regional management according to the present invention;
Fig. 4 is a schematic hardware structure of one possible electronic device according to the present invention;
fig. 5 is a schematic hardware structure of a possible computer readable storage medium according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the description of the present invention, the term "for example" is used to mean "serving as an example, instance, or illustration. Any embodiment described as "for example" in this disclosure is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes have not been described in detail so as not to obscure the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Referring to fig. 1, fig. 1 is a schematic diagram of a smart meter data processing method based on regional management according to the present invention. As shown in fig. 1, the terminal and the server are connected through a network, for example, a wired or wireless network connection. The terminal may include, but is not limited to, mobile terminals such as mobile phones and tablets, and fixed terminals such as computers, inquiry machines and advertising machines, where applications of various network platforms are installed. The server provides various business services for the user, including a service push server, a user recommendation server and the like.
It should be noted that, the scenario diagram of the smart meter data processing method based on regional management shown in fig. 1 is only an example, and the terminal, the server and the application scenario described in the embodiment of the present invention are for more clearly describing the technical solution of the embodiment of the present invention, and do not generate a limitation on the technical solution provided by the embodiment of the present invention, and as a person of ordinary skill in the art can know that, with the evolution of the system and the appearance of a new service scenario, the technical solution provided by the embodiment of the present invention is applicable to similar technical problems.
Wherein the terminal may be configured to:
Dividing the whole power supply area into a plurality of independent management areas, and setting up an area node server in each management area;
each intelligent ammeter periodically transmits the power usage data to an area node server of the area where the intelligent ammeter is located, and the area node server performs preliminary processing on the received power usage data to obtain the total power usage in the area;
Each regional node server periodically gathers and transmits the processed total power usage in the region to an intermediate node server, the intermediate node server further processes and analyzes the power usage data, and data integration among regions is carried out to obtain integrated data;
Performing anomaly detection on the power usage data of each intelligent ammeter according to the integrated data, and repairing the anomaly data to obtain processed data;
Transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data;
and determining the loads of the regional node servers and the regional node servers according to the target data, and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
Referring to fig. 2, a flowchart of a smart meter data processing method based on regional management according to the present invention is provided, including the following steps:
step 201, dividing the whole power supply area into a plurality of independent management areas, and setting up an area node server in each management area.
Wherein the area node server may be RNS (Regional Node Server). In some embodiments, the partitioning purpose of the regional node servers may be:
Dispersing load: by dividing the whole power supply area into a plurality of smaller independent management areas, the load of data acquisition and processing is dispersed, and the overload problem of a single central server is avoided. Efficiency is improved: the independent management area can independently process and store data, reduce delay of data transmission and improve response speed and instantaneity of the system. Enhancing reliability: node servers are arranged in different areas, and once a server in a certain area fails, the data acquisition and management of the whole power supply area cannot be affected, so that the stability and reliability of the system are improved.
In some embodiments, its partitioning criteria may be: geographic location: the data acquisition and management can be facilitated by dividing the area based on the geographic position. Number of users: and the load of each area is ensured to be balanced relatively according to the uniform division of the number of users. Electricity consumption requirements: and dividing the areas according to the difference of the power consumption demands, so that the areas with high power consumption demands and the areas with low power consumption demands are managed in a targeted manner.
In some embodiments, the setting purpose of the area node server may be: local data processing: the regional node server is responsible for collecting and processing all intelligent ammeter data in the management area, and reduces the requirement of data transmission to the central server. And (3) data storage: the regional node server locally stores data, provides quick access and processing capacity of the data, and ensures real-time performance and reliability. Pretreatment and analysis: and data preprocessing and preliminary analysis are carried out locally, so that the calculation load of a central server is reduced, and the overall efficiency of the system is improved.
In some embodiments, the primary functions of the regional node server may be: and (3) data acquisition: and periodically collecting the power use data of the user through the intelligent ammeter in the area, and summarizing the power use data to the area node server. And (3) data processing: and executing local data processing tasks such as data cleaning, checking, aggregation and the like, and ensuring the accuracy and the effectiveness of the data. Abnormality detection: abnormal electricity behavior is monitored and detected in real time, early warning and processing are performed in time, and power supply safety and legal rights and interests of users are ensured. And (3) data transmission: and uploading the processed data to a central server periodically or in real time for further analysis and management.
By way of example only, assume that a city is divided into four management areas: east, west, south and north regions. And setting up a regional node server in each region, and uploading the power use data to the corresponding node server by the intelligent ammeter in each region at regular intervals.
East region: and the east region node server is responsible for collecting data of all intelligent electric meters in the east region, and carrying out local processing and storage. When a user in the east region is found to have abnormal electricity utilization behaviors, the node server immediately gives an alarm and records related data. South region: the south area node server periodically uploads the processed data to the central server, and simultaneously stores local data for power use analysis and anomaly detection in the area.
By the above way, the present invention can alleviate the burden of the central server by dividing a plurality of regional node servers: each regional node server shares the work of data acquisition and processing, and the central server only needs to process the summarized data, so that the burden of the central server is greatly reduced. The data processing speed can be improved: because the data is processed and stored locally, the delay of data transmission is reduced, and the real-time performance of data processing is improved. The system reliability can be improved: the distributed regional node server structure does not influence the normal operation of other regions even if a certain regional server fails, and improves the overall reliability of the system. Data security may be enhanced: the data is locally stored and processed in the areas, so that the security risk in the long-distance transmission process is reduced, and meanwhile, the node server of each area can independently take security measures, so that the security and privacy protection of the data are enhanced.
Through the intelligent ammeter data processing mode of regional management, a power supply company can manage large-scale power user data more efficiently and reliably, and the overall power supply service quality is improved.
And 202, each intelligent ammeter periodically transmits the power usage data to an area node server in the area, and the area node server performs preliminary processing on the received power usage data to obtain the total power usage in the area.
In some embodiments, step 202 may include:
a first adjustment coefficient and a second adjustment coefficient are obtained,
Acquiring the electric power usage amount acquired by each intelligent electric meter and the error correction value corresponding to each intelligent electric meter;
And determining the total power consumption in the area according to the quantity of the intelligent electric meters in the area, the first adjustment coefficient, the second adjustment coefficient, the power consumption collected by each intelligent electric meter and the error correction value corresponding to each intelligent electric meter.
In some embodiments, the total power usage within a region is expressed as:
Wherein, Is the total power usage in the area, N is the number of smart meters in the area,Is the firstThe amount of power usage of the smart meter,And beta is a first adjustment factor and a second adjustment factor respectively,Is the firstError correction value of each intelligent ammeter.
In a specific implementation of the present invention,The total power usage in the area is a target value representing the total power consumption of all users in a specific area.
N is the number of smart meters in an area and indicates how many individual smart meters are recording and reporting power usage data in that area.
Is the firstThe power consumption of each intelligent ammeter is specific power consumption data of each user (or equipment).
And β is a first adjustment coefficient and a second adjustment coefficient, respectively, which are used to adjust the calculation of the power usage and the error correction value. They can be adjusted according to the system requirements to optimize the calculation results.
Is the firstError correction values of the smart meters, since each smart meter may have a certain measurement error,For correcting these errors, ensuring a more accurate calculation result.
In particular, the method comprises the steps of,When the square of the power consumption is large and the base of the correction term is ensured to be large, the correction value is increased correspondingly.The power consumption and the error correction value are combined to adjust the coefficientThe extent of influence of the error correction value is determined. Taking the square root makes the increase speed of the error correction value more gentle, and avoids overcorrection. Finally multiplying by the adjustment coefficientThe final value of the error correction term is further adjusted, so that the reasonable ratio of the correction term to the actual power consumption is ensured.
And 203, each regional node server periodically gathers and transmits the processed total power usage in the region to an intermediate node server, and the intermediate node server further processes and analyzes the power usage data and integrates the data among the regions to obtain integrated data.
In some embodiments, step 203 may comprise:
acquiring the number of the areas to be integrated;
Acquiring a first weight and a total power usage amount of each area;
acquiring a third adjustment coefficient;
and determining the integrated data according to the third adjustment coefficient, the number of areas, the first weight of each area and the total power usage.
In some embodiments, the consolidated data is represented as:
Wherein, Is integrated data representing a weighted average power usage of a plurality of regions, M is the number of regions,Is the first weight of the j-th region,Is the total power usage of the jth zone,Is the third adjustment coefficient.
Wherein the intermediate node server may be INS (Intermediate Node Server).The integrated data represents the weighted average power usage of a plurality of areas, and reflects the overall power usage.
M is the number of regions, indicating how many independent regions are present, each region having its own independent data acquisition and processing node.
Is the first weight of the j-th region for adjusting the relative importance of each region in calculating the weighted average. The weight may be determined based on factors such as the size of the electricity used, the number of users, etc. of the area.
The total power usage of the jth zone is indicative of the total power usage of all users in the jth zone.
Is a third adjustment coefficient for adjusting the degree of influence of the logarithmic transformation so that the contribution of the total power usage in the calculation is smoother.
In particular, the method comprises the steps of,Is the weighted total power usage of each region multiplied by its logarithmic transformation term. By logarithmic transformation, the effect of large values is reduced, making the contribution of each region smoother and more stable.
Is the accumulated value of the weighted logarithmic transformation term for all regions. The integrated weight of each region on the logarithmic transformation term is reflected.
In summary, the invention calculates the weighted average power usage by the ratio of the numerator to the denominator of the formula. Ensuring that the total power usage and weight of each zone are properly considered.
And 204, performing anomaly detection on the power usage data of each intelligent ammeter according to the integrated data, repairing the anomaly data, and obtaining processed data.
In some embodiments, step 204 may include:
Acquiring the power usage amount of each intelligent ammeter and the integration data;
acquiring standard deviation of the power consumption in the area;
Acquiring a fourth adjustment coefficient;
And determining an abnormality detection value according to the power usage amount of each intelligent ammeter, the integrated data, the standard deviation of the power usage amount in the area and the fourth adjustment coefficient, and performing abnormality detection on the integrated data based on the abnormality detection value.
In some embodiments, the anomaly detection value is expressed as:
Wherein, Is an anomaly detection value, represents a standard deviation value of data points of the ith smart meter,Is the power usage of the i-th smart meter,Is the data of the integration of the data,Is the standard deviation of the amount of power usage in the area,Is the fourth adjustment coefficient.
In a specific implementation of the present invention,Is the standard deviation of the ith data point and is used for representing the power usage of the ith smart meter relative to the average valueIs not limited by the degree of deviation.
Is the power usage amount of the ith smart meter, and represents the power usage data actually recorded by each smart meter.
Is the integrated data representing the weighted average power usage of the plurality of regions. Is a representative value of overall power usage.
The standard deviation of the amount of power usage in the area represents the degree of dispersion of the power usage data.
Is a fourth adjustment coefficient for adjusting the degree of influence of the deviation value in the calculation.
In particular, the method comprises the steps of,And a deviation value of the power usage amount of the ith smart meter from the average power usage amount is indicated.Is an adjustment term for the deviation, and the influence of the deviation value is controlled by adjusting the coefficient lambda.
It will be appreciated that the present invention will deviate from the valuesDivided by standard deviation adjustment termObtaining standard deviation and dispersion valueThe degree of normalized deviation of the power usage amount of each smart meter from the average value is reflected. In some embodiments, if|, I.eIf the absolute value of (a) exceeds a certain threshold, then the data point is considered likely to be abnormal.
And 205, transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data.
In some embodiments, step 205 may comprise:
Calculating a hash value of the processed data, and carrying out hash check on the processed data; wherein the hash value of the processed data is expressed as:
Where H represents a hash value of data transmission verification, Representing the processed data to be transmitted,The time stamp is indicated as such,Represents the key, salt represents the Salt value,Representing the connection operation.
In a specific implementation, H represents a hash value of data transmission verification, and is used for verifying the integrity of data and preventing tampering in the transmission process.
Representing processed data to be transmitted, representing power usage data or other related data that needs to be transmitted.
And the time stamp is expressed and used for recording the specific time of data generation or transmission, ensuring the timeliness of the data and preventing replay attacks.
A key is represented for enhancing the security of data transmission, and only secret information known to both communication parties.
Salt represents a Salt value for increasing the randomness of the hash function and preventing hash collision attacks.
Representing a join operation, representing the joining together of the individual data portions as an input to a hash function.
In particular, the present invention uses a join operatorProcessed data to be transmittedThe time stamp t, the key k and the Salt value Salt are concatenated together to form a new string or data block.
In some embodiments, a Hash function Hash () may be applied to the concatenated data blocks. The hash function may be a conventional cryptographic hash function such as MD5, SHA-256, etc. A hash value H of a fixed length is generated for data verification.
And 206, determining the loads of the regional node servers and the regional node servers according to the target data, and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
In some embodiments, step 206 may include:
Processing initial weights of load distribution of the regional node servers and the regional node servers according to the current load, the maximum load, the current response time, the optimal response time and the fifth adjustment coefficient of the regional node servers and the regional node servers to obtain corresponding second weights; wherein the second weight is expressed as:
Wherein, Is the second weight after the initial weight adjustment,Is the initial weight of the weight to be added,Is the current load of the node and,Is the maximum load of the node and,Is the current response time of the device,Is the optimal response time for the device to be used,Is the fifth adjustment coefficient.
In a specific implementation of the present invention,The second weight is the adjusted weight of the initial weight and is used for distributing the load of the nodes, so that the load balance of each node is ensured;
the initial weight is a value preset by the system according to the capacity, the position and other initial conditions of each node;
is the load of the current node, and represents the actual load condition of the current node, such as the current processed data quantity or the user request number;
the maximum load of the node is represented by the maximum load which the node can bear theoretically or in design;
the current response time is the response time of the current node to the request, and is an important index for measuring the performance of the node;
is the optimal response time, and represents the expected or set ideal response time of the system as the reference standard of the performance;
is a fifth adjustment coefficient for controlling the degree of influence of the response time difference on the weight adjustment.
In particular, the method comprises the steps of,Representing the ratio of the current node load to the maximum load.Representing the ratio of load remaining capacity. The higher the load, the lower the residual capacity and vice versa. The weight is initially adjusted by multiplying the initial weight omega by the ratio of the residual capacity, so that the node weight with higher load is ensured to be reduced, and the load is reduced.
Indicating the degree of deviation of the current response time from the optimal response time. If the current response time isHigher than optimal response time，Positive values.
The weights are adjusted by an exponential function, so that the node weight with longer response time is further reduced, and the load is lightened. Adjustment coefficientThe adjustment amplitude is controlled.
In some embodiments, the initial weight adjustment and the response time adjustment may be combined to obtain a final adjusted weight. This ensures that nodes with higher loads and longer response times are weighted down, distributing less load and vice versa, thus achieving load balancing.
In some embodiments, when the load ratioWhen a certain threshold is exceeded, a load adjustment mechanism may be triggered. For example, some of the data processing tasks may be transferred to a less loaded node server.
In some embodiments, the management area may be further subdivided, and the management area of a node server may be enlarged or reduced. When the overload of a certain node server is detected, the management area is divided again, so that the area range of the node server with lighter adjacent load is enlarged, and the load of an overload node is reduced; or the area range of the overload node is reduced, and partial users and data are distributed to adjacent nodes.
The method can ensure the load balance of the node servers in each region by dynamically adjusting the region range, and improves the data processing efficiency and the system reliability.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a smart meter data processing system based on regional management according to the present invention.
As shown in fig. 3, a smart meter data processing system based on regional management according to an embodiment of the present invention includes:
the regional division module 301 is configured to divide an entire power supply region into a plurality of independent management regions, and each management region is internally provided with a regional node server;
the first processing module 302 is configured to periodically transmit the power usage data to an area node server in the area where each smart meter is located, and perform preliminary processing on the received power usage data by using the area node server to obtain a total power usage in the area;
The second processing module 303 is configured to periodically collect and transmit the processed total power usage amount in the area to an intermediate node server, further process and analyze the power usage data by using the intermediate node server, and integrate data between areas to obtain integrated data;
The third processing module 304 is configured to perform anomaly detection on the power usage data of each smart meter according to the integrated data, repair the anomaly data, and obtain processed data;
A fourth processing module 305, configured to transmit the processed data to a central server for final storage and comprehensive analysis, to obtain target data;
and a fifth processing module 306, configured to determine loads of the regional node servers and the regional node servers according to the target data, and dynamically adjust regional ranges of the regional node servers and the regional node servers according to the loads.
Referring to fig. 4, fig. 4 is a schematic diagram of an embodiment of an electronic device according to an embodiment of the invention. As shown in fig. 4, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420, wherein the processor 420 executes the computer program 411 to implement the following steps:
Dividing the whole power supply area into a plurality of independent management areas, and setting up an area node server in each management area;
each intelligent ammeter periodically transmits the power usage data to an area node server of the area where the intelligent ammeter is located, and the area node server performs preliminary processing on the received power usage data to obtain the total power usage in the area;
Each regional node server periodically gathers and transmits the processed total power usage in the region to an intermediate node server, the intermediate node server further processes and analyzes the power usage data, and data integration among regions is carried out to obtain integrated data;
Performing anomaly detection on the power usage data of each intelligent ammeter according to the integrated data, and repairing the anomaly data to obtain processed data;
Transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data;
and determining the loads of the regional node servers and the regional node servers according to the target data, and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
Referring to fig. 5, fig. 5 is a schematic diagram of an embodiment of a computer readable storage medium according to an embodiment of the invention. As shown in fig. 5, the present embodiment provides a computer-readable storage medium 500 having stored thereon a computer program 411, which computer program 411, when executed by a processor, performs the steps of:
Dividing the whole power supply area into a plurality of independent management areas, and setting up an area node server in each management area;
each intelligent ammeter periodically transmits the power usage data to an area node server of the area where the intelligent ammeter is located, and the area node server performs preliminary processing on the received power usage data to obtain the total power usage in the area;
Each regional node server periodically gathers and transmits the processed total power usage in the region to an intermediate node server, the intermediate node server further processes and analyzes the power usage data, and data integration among regions is carried out to obtain integrated data;
Performing anomaly detection on the power usage data of each intelligent ammeter according to the integrated data, and repairing the anomaly data to obtain processed data;
Transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data;
and determining the loads of the regional node servers and the regional node servers according to the target data, and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
In the foregoing embodiments, the descriptions of the embodiments are focused on, and for those portions of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (2)
1. The utility model provides a smart electric meter data processing method based on regional management, which is characterized in that the method comprises the following steps:
Dividing the whole power supply area into a plurality of independent management areas, and setting up an area node server in each management area;
Each smart meter periodically transmits power usage data to an area node server of an area where the smart meter is located, performs preliminary processing on the received power usage data through the area node server to obtain total power usage in the area, and comprises the following steps: acquiring a first adjustment coefficient and a second adjustment coefficient, and acquiring the power usage amount acquired by each intelligent electric meter and an error correction value corresponding to each intelligent electric meter; determining the total power consumption in the area according to the number of intelligent electric meters in the area, the first adjustment coefficient, the second adjustment coefficient, the power consumption collected by each intelligent electric meter and the error correction value corresponding to each intelligent electric meter; the total power usage in the area is expressed as: wherein P total is the total power consumption in the area, N is the number of intelligent electric meters in the area, P i is the power consumption of the ith intelligent electric meter, alpha and beta are a first adjustment coefficient and a second adjustment coefficient respectively, and E i is the error correction value of the ith intelligent electric meter;
Each regional node server periodically gathers and transmits the processed total power usage in the region to an intermediate node server, the intermediate node server further processes and analyzes the power usage data, and integrates the data among the regions to obtain integrated data, and the method comprises the following steps: acquiring the number of the areas to be integrated; acquiring a first weight and a total power usage amount of each area; acquiring a third adjustment coefficient; determining the integrated data according to the third adjustment coefficient, the number of areas, the first weight of each area and the total power usage; the integrated data is expressed as: Wherein P avg is integration data representing a weighted average power usage amount of a plurality of regions, M is a region number, ω j is a first weight of a j-th region, P total,j is a total power usage amount of the j-th region, and γ is a third adjustment coefficient;
performing anomaly detection on the power usage data of each intelligent ammeter according to the integrated data, repairing the anomaly data to obtain processed data, wherein the method comprises the following steps: acquiring the power usage amount of each intelligent ammeter and the integration data; acquiring standard deviation of the power consumption in the area; acquiring a fourth adjustment coefficient; determining an anomaly detection value according to the power usage amount of each intelligent ammeter, the integrated data, the standard deviation of the power usage amount in the area and the fourth adjustment coefficient, and performing anomaly detection on the integrated data based on the anomaly detection value; the abnormality detection value is expressed as: wherein Z i is an anomaly detection value, represents a standard deviation difference value of data points of the ith smart meter, P i is a power usage amount of the ith smart meter, P avg is integrated data, σ is a standard deviation of power usage amount in the area, and λ is a fourth adjustment coefficient;
Transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data, wherein the method comprises the following steps of: calculating a hash value of the processed data, and carrying out hash check on the processed data; wherein the hash value of the processed data is expressed as: h=hash (P The position of the part || t k Salt); wherein H represents a hash value of data transmission verification, P The position of the part represents processed data to be transmitted, t represents a time stamp, k represents a key, salt represents a Salt value, and l represents a connection operation;
Determining the load of each intermediate node server and each regional node server according to the target data, and dynamically adjusting the regional scope of each regional node server according to the load, wherein the method comprises the following steps: processing initial weights of load distribution of the regional node servers and the regional node servers according to the current load, the maximum load, the current response time, the optimal response time and the fifth adjustment coefficient of the regional node servers and the regional node servers to obtain corresponding second weights; wherein the second weight is expressed as: Where ω' is the second weight after initial weight adjustment, ω is the initial weight, L current is the current load of the node, L max is the maximum load of the node, T response is the current response time, T optimal is the optimal response time, and δ is the fifth adjustment coefficient.
2. A smart meter data processing system based on regional management for executing the smart meter data processing method based on regional management as claimed in claim 1, the system comprising:
the regional division module is used for dividing the whole power supply region into a plurality of independent management regions, and a regional node server is arranged in each management region;
The first processing module is used for periodically transmitting the power usage data to an area node server of the area where each intelligent ammeter is located, and performing preliminary processing on the received power usage data through the area node server to obtain the total power usage in the area;
The second processing module is used for periodically summarizing the processed total power usage in the area by each area node server, transmitting the summarized total power usage to an intermediate node server, further processing and analyzing the power usage data by the intermediate node server, and integrating the data among the areas to obtain integrated data;
the third processing module is used for carrying out anomaly detection on the power use data of each intelligent ammeter according to the integrated data, repairing the anomaly data and obtaining processed data;
The fourth processing module is used for transmitting the processed data to a central server for final storage and comprehensive analysis to obtain target data;
and the fifth processing module is used for determining the loads of the regional node servers and the regional node servers according to the target data and dynamically adjusting the regional scope of the regional node servers and the regional scope of the regional node servers according to the loads.
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