AMI simulation test methods, apparatus, computer equipment and storage media

Abstract

This invention relates to the field of power Internet of Things (IoT) technology, and particularly to an AMI (Automatic Machine Injection) simulation testing method, apparatus, computer equipment, and storage medium. The method utilizes several configuration tools as AMI simulation meters to establish information interaction between the AMI simulation meters and the data acquisition system, storing the interaction information. It configures connections for the AMI simulation meters, and based on preset test requirements and connection configuration information, issues invocation commands to the AMI simulation meters. According to the invocation commands, it retrieves the corresponding test information from the information repository, and executes the AMI simulation test based on the test information. Alternatively, by acquiring port information from the data acquisition system, several configuration tools are constructed as AMI simulation meters. Based on the information repository, connections are configured for the AMI simulation meters to obtain connection configuration information, and the corresponding test information from the information repository is retrieved to execute the AMI simulation test. This automates the connection interaction with the AMI simulation meters for AMI testing.

Description

Technical Field

[0001] This invention relates to the field of power Internet of Things (IoT) technology, and in particular to an AMI simulation test method, apparatus, computer equipment, and storage medium. Background Technology

[0002] Advanced Metering Infrastructure (AMI), a key component of the smart grid, enables two-way communication and data exchange between power suppliers and users, improving the operational efficiency and management level of the power system. However, many problems still exist in the deployment and maintenance of AMI systems.

[0003] Currently, most AMI simulation testing methods involve developing basic simulation programs to mimic the communication process between meters and data acquisition systems. These programs generate preset test data, send it to the data acquisition system according to certain rules, and receive responses to check the system's basic functionality. However, this approach struggles to simulate the complex behavior and diverse operating scenarios of real meters. For complex communication protocols and data processing logic, simulation programs often fail to accurately simulate them, resulting in low accuracy and reliability of test results. Furthermore, the functionality and test scenarios of simulation programs are relatively fixed, making it difficult to flexibly expand and customize them to meet different testing needs, thus increasing the difficulty and cost of testing.

[0004] In real-world applications, a region may have tens of thousands or even more smart meters that need to be connected to an AMI system for real-time monitoring and management of electricity usage. This requires the system to have robust device access capabilities. With the connection of a large number of devices, the AMI system needs to process massive amounts of device information. This information is not only large in volume but also has high real-time requirements, demanding that the system be able to transmit and process it quickly and accurately. Existing analog meters are typically designed for small-scale testing or specific scenarios, and their ability to simulate the number of connected devices is limited, failing to meet the scale requirements of large-scale device access in real-world AMI system applications. Current testing tools have performance bottlenecks when it comes to transmitting and processing massive amounts of device information. They may not be able to effectively simulate scenarios where a large number of devices transmit information simultaneously, nor can they process and analyze such large-scale information quickly and accurately. As the scale and complexity of AMI systems continue to increase, there may be more devices connected and more complex information processing needs in the future. Existing analog meters and testing tools often lack scalability, making it difficult to flexibly adjust and upgrade as the system develops, and thus unable to adapt to the ever-changing testing requirements of AMI systems.

[0005] Therefore, how to automatically connect and interact with AMI analog meters, so as to test AMI through AMI analog meters, has become an urgent problem to be solved. Summary of the Invention

[0006] This invention provides an AMI simulation testing method, apparatus, computer device, and storage medium to solve the problem of how to automatically connect and interact with AMI simulation meters, thereby testing AMIs through AMI simulation meters.

[0007] In a first aspect, embodiments of the present invention provide an AMI simulation testing method, comprising: Obtain the port information of the acquisition system, call the configuration tools in the preset programming framework, and use several of the configuration tools as AMI analog meters; Based on the port information, the interaction address is determined, and based on the interaction address, the information interaction between the AMI analog meter and the acquisition system is constructed. The interaction information is then stored to obtain an information storage repository. For any of the AMI analog meters, configure the connection for the AMI analog meter, obtain the connection configuration information of the AMI analog meter, and issue a call command to the AMI analog meter according to the preset test requirements and the connection configuration information. According to the invocation instruction, the test information corresponding to the test requirement is retrieved from the information repository, and the AMI simulation test is executed based on the test information.

[0008] Secondly, embodiments of the present invention provide an AMI simulation testing device, the AMI simulation testing device comprising: The tool calling module is used to obtain port information of the acquisition system, call the configuration tools in the preset programming framework, and use several of the configuration tools as AMI analog meters; The information interaction module is used to determine the interaction address based on the port information, construct the information interaction between the AMI analog meter and the acquisition system based on the interaction address, and store the interaction information to obtain an information storage repository. The instruction issuing module is used to configure the connection of any AMI simulated meter, obtain the connection configuration information of the AMI simulated meter, and issue a call instruction to the AMI simulated meter according to the preset test requirements and the connection configuration information. The testing module is used to call the test information corresponding to the test requirements in the information repository according to the calling instruction, and to execute AMI simulation test according to the test information.

[0009] Thirdly, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described AMI simulation test method.

[0010] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described AMI simulation test method.

[0011] The beneficial effects of this invention compared to existing technologies are as follows: By acquiring port information of the acquisition system, calling configuration tools in a preset programming framework, using several configuration tools as AMI simulated meters, determining the interaction address based on the port information, constructing information interaction between the AMI simulated meters and the acquisition system based on the interaction address, and storing the interaction information to obtain an information repository, for any AMI simulated meter, configuring the connection of the AMI simulated meter to obtain the connection configuration information of the AMI simulated meter, issuing a call command to the AMI simulated meter according to preset test requirements and the connection configuration information, calling the corresponding test information in the information repository according to the call command, and executing the AMI simulation test according to the test information. By acquiring port information of the acquisition system, constructing several configuration tools as AMI simulated meters, configuring the connection of the AMI simulated meters according to the information repository to obtain the connection configuration information, and calling the corresponding test information in the information repository to execute the AMI simulation test, the invention automatically connects and interacts with the AMI simulated meters to test AMIs through the AMI simulated meters. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the application environment of an AMI simulation test method provided in Embodiment 1 of the present invention; Figure 2 This is a flowchart illustrating an AMI simulation testing method provided in Embodiment 2 of the present invention; Figure 3 This is a flowchart illustrating an AMI simulation testing method provided in Embodiment 3 of the present invention; Figure 4 This is a flowchart illustrating an AMI simulation testing method provided in Embodiment 4 of the present invention; Figure 5 This is a flowchart illustrating an AMI simulation testing method provided in Embodiment 5 of the present invention; Figure 6This is a schematic diagram of the structure of an AMI simulation test device provided in Embodiment Six of the present invention; Figure 7 This is a schematic diagram of the structure of a computer device provided in Embodiment 7 of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] like Figure 1 The diagram illustrates an application environment for an AMI simulation testing method according to Embodiment 1 of the present invention. The AMI simulation testing method is applied to a television terminal. The client and server communicate with each other, and the user can provide conditions, requirements, and operational instructions for AMI simulation testing through the client. The client includes, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be a standalone server or a server cluster consisting of multiple servers.

[0016] like Figure 2 The diagram shown is a flowchart of an AMI simulation testing method provided in Embodiment 2 of the present invention. The AMI simulation testing method may include the following steps: Step S201: Obtain the port information of the acquisition system, call the configuration tool in the preset programming framework, and use several of the configuration tools as AMI analog meters.

[0017] Port information can include port number, port type (e.g., TCP port, UDP port), and port communication status (whether it is open or in use). This port information is fundamental for communication between the AMI analog meter and the data acquisition system. Different ports correspond to different communication protocols and functions. By obtaining port information, the specific port used by the analog meter and the data acquisition system for information interaction can be identified, ensuring the accuracy and stability of communication. Port information of the data acquisition system can be obtained in various ways, such as using the system's built-in network management tools, programming interfaces (e.g., Python's socket library), or dedicated port scanning tools. In practical applications, the appropriate acquisition method can be selected based on the type and configuration of the data acquisition system. The pre-defined programming framework is a program architecture pre-designed and implemented by developers to facilitate AMI simulation testing. The programming framework encapsulates some commonly used functions and operations, providing unified interfaces and specifications, enabling developers to perform test development more efficiently. The programming framework can reduce repetitive work and improve code maintainability and scalability.

[0018] The configuration tool, part of the programming framework, has the ability to simulate various functions and features of AMI meters. Through the configuration tool, meter parameters (such as measurement accuracy, communication protocol, data format, etc.) can be set, meter operating states (such as normal operation, fault state, etc.) can be simulated, and simulated metering data can be generated. For example, at startup, based on the scanned available ports, the address and port information of the Netty server-side ServerBootstrap can be configured, and ServerBootstraps can be started in batches, with each ServerBootstrap acting as a simulated meter.

[0019] Using the configuration tool as an AMI (Automatic Management Interface) simulated meter allows for the flexible creation of multiple simulated meters, and each simulated meter can be customized according to testing requirements. This enables the simulation of different types and parameters of meters interacting with the data acquisition system, thus providing a more comprehensive test of the system's compatibility and performance.

[0020] Step S202: Determine the interaction address based on the port information, construct the information interaction between the AMI analog meter and the acquisition system based on the interaction address, and store the interaction information to obtain an information storage repository.

[0021] Optionally, step S202 above may include the following steps: The connection status of the port information is detected. If the connection status is empty, the interaction address in the port information is extracted. Based on the interaction address, the analog meter is configured with interaction information, the information interaction between the analog meter and the data acquisition system is constructed based on the interaction information, and the interaction information is stored to obtain an information storage repository.

[0022] The interaction address is a key identifier for communication between the AMI analog meter and the data acquisition system, and includes an IP address and a port number. The IP address is used to locate the device where the data acquisition system is located on the network, while the port number specifies the specific interface used for communication on that device.

[0023] Port information contains the IP address and port number required for interaction, or it can be derived from the port information through certain rules and configurations. For example, in some network environments, port information is bound to specific IP addresses and port numbers, and the interaction address can be determined by parsing the port information.

[0024] Once the interaction address is determined, the AMI analog meter and the data acquisition system can establish a communication connection based on that address. This involves using specific communication protocols (such as TCP, UDP, etc.) to transmit information by sending and receiving data packets. For example, the analog meter can send metering data to the data acquisition system according to an agreed-upon protocol format. After receiving the data, the data acquisition system processes it accordingly and can return confirmation information or other instructions. The interaction information can include various metering-related data, such as measured values ​​of electricity, voltage, and current, as well as equipment status information and configuration parameters. Storing the interaction information to form an information repository can be used for subsequent data analysis and statistics to evaluate the performance and operating status of the AMI system; furthermore, it can serve as a basis for tracing and troubleshooting when problems occur.

[0025] Information storage can be a database (such as MySQL, Oracle, etc.), a file system (such as CSV files, JSON files, etc.), or other storage media. When storing data, the organization and format of the data need to be considered to facilitate subsequent retrieval and use. Connection status reflects whether the port is currently available, i.e., whether normal communication is possible. Connection status can have various states, such as connected, disconnected, or connection error.

[0026] Checking the connection status of port information before determining the interaction address can prevent invalid operations from being performed when the port is unavailable. If the port connection status is empty, it means that a valid connection may not have been established on the port.

[0027] Based on the specific format and content of the port information, the corresponding parsing method is used to extract the interaction address. For example, if the port information is stored in a specific string format, string processing functions can be used to extract the IP address and port number. The configuration of the interaction information includes setting the communication protocol, data format, transmission rules, etc. For example, specifying the use of the TCP protocol for communication, setting data to be transmitted in JSON format, and specifying the data sending frequency and retransmission mechanism, etc.

[0028] By configuring the interactive information of the analog meters, it can be ensured that the analog meters and the data acquisition system follow the same rules during communication, thereby achieving accurate and reliable information exchange. After the interactive information is configured, the AMI analog meters and the data acquisition system can exchange information according to the configured rules and store the information generated during the interaction in the information repository.

[0029] Step S203: For any of the AMI analog meters, configure the connection of the AMI analog meter to obtain the connection configuration information of the AMI analog meter, and issue a call command to the AMI analog meter according to the preset test requirements and the connection configuration information.

[0030] Optionally, the connection configuration information includes communication information, protocol information, and parameter information; the step of configuring a connection for any of the AMI analog meters to obtain the connection configuration information of the AMI analog meter includes: According to the preset connection rules, the AMI analog meters are configured with communication connections, protocol connections and parameter connections respectively; Based on the communication connection, the communication information of the AMI analog meter is obtained; Based on the protocol connection, the protocol information is obtained; The parameter information is obtained by connecting the parameters.

[0031] The connection configuration information includes communication information, protocol information, and parameter information. The communication information concerns the method and channel for data transmission between the analog meter and external systems. The protocol information specifies the rules and standards followed for data transmission and interaction. The parameter information consists of various parameters related to the analog meter's own functions and operating status.

[0032] The pre-defined test requirements clearly define the objectives and specific requirements of this simulation test, such as testing transmission stability under different communication protocols and verifying the metering accuracy under specific parameter settings. By combining the connection configuration information and the pre-defined test requirements, appropriate call commands can be accurately sent to the AMI simulated meter, enabling the simulated meter to perform corresponding operations and responses according to the test requirements, thereby completing various test tasks.

[0033] The main task is to determine the communication method between the analog meter and external devices, such as whether Ethernet, wireless communication (e.g., ZigBee, LoRa), or other communication methods are used, as well as the communication port, speed, and other related settings. It also involves clarifying the protocol followed by the analog meter during data transmission, such as Modbus or DL / T 645. Different protocols have different data formats, command sets, and interaction flows. Finally, various parameters of the analog meter are set, which may include metering accuracy, sampling period, alarm thresholds, etc., to simulate different real-world working scenarios.

[0034] By configuring the communication connection, information such as the analog meter's communication port, communication rate, and communication method can be determined. This information is fundamental to ensuring correct data transmission. After configuring the protocol connection, information such as the protocol type, protocol version, and specific parameters used by the analog meter can be obtained, ensuring compatibility between the analog meter and external devices at the protocol level. During the parameter connection configuration process, various functional parameters of the analog meter, such as range, resolution, and calibration coefficient, are determined. These parameters directly affect the measurement and operational results of the analog meter.

[0035] Step S204: According to the calling instruction, call the test information corresponding to the test requirements in the information repository, and execute the AMI simulation test according to the test information.

[0036] The invocation command serves as a bridge connecting test requirements and the information repository. It is generated based on preset test requirements and the connection configuration information of the AMI simulated meters, containing key information about the test, such as the functional modules to be tested, specific test conditions, and expected data types. This command allows for precise location of the required test information in the information repository.

[0037] The information repository, constructed in step S202, stores data generated during previous information interactions between the AMI simulated meters and the data acquisition system. This data may include various metering data (such as electricity consumption, voltage, and current), equipment status information, and interaction records under different configurations. This data is stored according to certain rules and structures to facilitate querying and retrieval. The system searches and selects data from the information repository based on key information in the call command. For example, if the call command requests voltage data from a specific simulated meter within a specific time period, the system will find voltage data matching these conditions from the information repository as test information, based on meter identification and time range. The acquired test information provides basic data and reference for AMI simulation testing, used to simulate different real-world scenarios, such as simulating peak and off-peak electricity consumption, or simulating equipment malfunctions.

[0038] After receiving test information, the system will use this information to test the AMI simulated meters or the entire AMI system according to the preset test procedures and rules. The metering data from the test information is injected into the AMI simulated meters, which will then process and respond accordingly, just like receiving real metering data during actual operation. The system checks whether the various functions of the AMI system are normal after receiving simulated data, such as whether the data transmission is accurate, whether the acquisition system can correctly process and store data, and whether alarm information can be issued in a timely manner. By analyzing the data and system response time during the test, the performance of the AMI system is evaluated, including data transmission latency and system throughput.

[0039] In this embodiment, by acquiring the port information of the acquisition system, a configuration tool in a preset programming framework is invoked. Several configuration tools are used as AMI simulation meters. Based on the port information, the interaction address is determined. Based on the interaction address, information interaction between the AMI simulation meter and the acquisition system is constructed, and the interaction information is stored to obtain an information repository. For any AMI simulation meter, a connection is configured for the AMI simulation meter, obtaining the connection configuration information of the AMI simulation meter. Based on preset test requirements and the connection configuration information, a call command is issued to the AMI simulation meter. According to the call command, the corresponding test information in the information repository is retrieved, and the AMI simulation test is executed based on the test information. By acquiring the port information of the acquisition system, constructing several configuration tools as AMI simulation meters, configuring the connection for the AMI simulation meters based on the information repository, obtaining the connection configuration information, and retrieving the corresponding test information in the information repository to execute the AMI simulation test, the connection interaction with the AMI simulation meters is automatically performed to test the AMI through the AMI simulation meters.

[0040] Compared to existing technologies, this application addresses the issue that most meter simulators on the market currently operate as standalone machines. This means they typically exist as individual devices or systems, lacking the ability to work collaboratively with multiple machines. Standalone simulators have relatively limited resource utilization and processing power, and can only run simulation tasks in an isolated environment. Insufficient concurrency support indicates that these simulators struggle to handle multiple tasks or connections simultaneously. In real power systems, a large number of meters may communicate with the data acquisition system simultaneously, requiring simulators capable of simulating such high concurrency. However, existing standalone simulators cannot meet this requirement, potentially leading to slow processing speeds, untimely responses, or even crashes.

[0041] Furthermore, existing meter simulators have limited functionality, mainly focusing on simulating the communication process between the meter and other devices. They simply simulate the process of the meter sending and receiving data, but cannot simulate other complex behaviors of the meter in actual operation, such as metering, billing, and fault handling.

[0042] Furthermore, existing large-scale high-concurrency stress tests in the market are interface tests, which cannot meet the testing requirements of electricity meters and terminals. Currently, testing for large-scale high-concurrency scenarios mainly uses interface testing. Interface testing primarily focuses on whether the interfaces between systems can function properly, checking whether data transmission and interaction conform to specified protocols and standards. However, the communication mode of electricity meters and terminals involves not only interface-level issues but also interactions at multiple layers, including the physical layer, data link layer, and application layer. The communication mode of electricity meters and terminals has unique characteristics, such as the diversity of communication protocols and the complexity of the communication environment. Interface testing cannot fully simulate these actual communication scenarios and cannot accurately reflect the operation of electricity meters and terminals in a real environment. Therefore, existing large-scale high-concurrency stress tests cannot meet the testing requirements of electricity meter and terminal communication modes.

[0043] Furthermore, in power systems, different meters and terminals may use different communication protocols for data transmission, such as Modbus and DL / T 645. To simulate different types of meters and terminals, meter simulators need to have multi-protocol adaptation capabilities, meaning they must support multiple different communication protocols. Currently available meter simulators cannot meet the diverse communication needs of power systems in terms of protocol support. This often leads to the need to use multiple different simulators to simulate meters with different protocols during meter testing and verification, increasing the complexity and cost of testing.

[0044] Preferably, this application utilizes a large-scale high-concurrency AMI meter simulation method and apparatus implemented using the Netty framework. This addresses the shortcomings of traditional data acquisition systems in verifying high-concurrency performance by constructing a distributed event-driven architecture, achieving dynamic simulation of millions of device connections per second, thus meeting the power system's requirements for high-concurrency communication simulation testing of a large number of meters.

[0045] Netty is a high-performance network programming framework based on Java NIO. Its asynchronous non-blocking I / O model allows for efficient use of system resources without blocking threads when handling a large number of connections. When new connection requests or data arrive, Netty can handle them in an event-driven manner, without needing to create a separate thread for each connection.

[0046] Traditional methods often struggle to handle a large number of concurrent connections from analog meters in a master station data acquisition system. A multi-level session manager, designed based on Netty's asynchronous non-blocking I / O model, can efficiently manage sessions from a large number of analog meters. It can process sessions in layers according to different business logic and connection states, and rationally allocate system resources, thereby solving the problem of the master station data acquisition system being unable to concurrently access analog meters for stress testing.

[0047] SQLite is a lightweight embedded database that requires no separate server process, consumes few resources, and is suitable for use in resource-constrained environments. It boasts good performance and reliability, efficiently handling data read and write operations. In simulating electricity meters, a large amount of meter data needs to be stored, and this data grows continuously over time, just like real electricity meters constantly generating new metering data during operation. Using SQLite to implement data storage for the simulated meter can simulate this data growth process of real electricity meters, providing a more realistic data environment for testing.

[0048] In power systems, different meters and terminals may use different communication protocols for data transmission, such as Modbus and DL / T645. This simulation method and device can adapt to multiple protocol modes, meaning it can simulate meter communication under different protocols, meeting the needs of different users and scenarios.

[0049] Different power systems or users have different standards and requirements for stress testing. This device can provide corresponding stress test responses according to different standards, such as testing the system's performance and stability under different concurrent connection numbers, data transmission rates, and other conditions.

[0050] Actual testing has shown that this AMI simulation testing method and device can stably simulate continuous communication of 1 million devices on a single machine, with latency controlled within 1 second. It can meet the requirements of meter simulation testing in large-scale, high-concurrency scenarios, providing a reliable solution for verifying the high-concurrency performance of power systems.

[0051] like Figure 3 The diagram shown is a flowchart of an AMI simulation testing method provided in Embodiment 3 of the present invention. Step S203, which involves issuing a call command to the AMI simulation meter based on preset test requirements and the connection configuration information, may include the following steps: Step S301: Establish the connection relationship between the AMI analog meter and the acquisition system according to the connection configuration information.

[0052] Step S302: According to the test requirements, connect the AMI analog meter using the connection relationship and issue a call command to the AMI analog meter.

[0053] The system configures the communication port, speed, and other parameters according to the communication method (such as Ethernet or wireless communication) specified in the connection configuration information. It also adheres to the protocol standards (such as Modbus or DL / T645) defined in the protocol information to complete the handshake and establish the communication link between the AMI analog meter and the data acquisition system. For example, if the communication method is Ethernet, the system configures the IP address, subnet mask, and other information, and then connects to the data acquisition system via network protocols; if it is wireless communication, it sets the frequency band, channel, and other parameters to ensure normal communication between the two.

[0054] The pre-defined test requirements clearly define the specific objectives and requirements of this test, such as testing the metering accuracy at different time periods and verifying the data transmission stability of the system under a specific protocol. These test requirements determine the types of call commands that need to be issued to the AMI simulated meter.

[0055] After establishing the connection between the AMI analog meter and the data acquisition system, the system sends a call command to the AMI analog meter through the established connection channel, following the format and rules specified in the protocol, according to the testing requirements. The call command may include various operational requirements for the meter, such as reading the meter's real-time data, modifying the meter's parameter settings, or initiating a specific test process. For example, if the test requirement is to verify the meter's measurement accuracy during peak hours, the call command might require the meter to upload electricity data at regular intervals during the specified peak hours.

[0056] In this embodiment of the application, the functions and performance of the AMI system are verified by controlling and testing the AMI analog meters.

[0057] like Figure 4 The diagram shown is a flowchart of an AMI simulation testing method provided in Embodiment 4 of the present invention. Step S204, which involves calling the test information corresponding to the test requirement in the information repository according to the calling instruction, and executing the AMI simulation test according to the test information, may include the following steps: Step S401: Determine the requirement parameters according to the test requirements; Step S402: Based on the requirement parameters, filter the test information in the information repository that corresponds to the requirement parameters.

[0058] Step S403: Perform an AMI simulation test based on the test information.

[0059] Based on testing requirements, these requirements are transformed into specific, quantifiable demand parameters. These parameters are the key basis for subsequent screening of test information. For example, if the testing requirement is to evaluate the system's performance during peak electricity consumption periods, then the demand parameters may include the specific time range of peak periods (e.g., 18:00-22:00) and the expected power load range (e.g., 5000-8000 kW).

[0060] The information repository is constructed in step S202. It stores various types of data generated during the interaction between the AMI analog meters and the data acquisition system, covering metering data, equipment status information, communication records, etc. Using the determined requirement parameters, targeted filtering is performed in the information repository. The system will find matching test information from the massive amount of data based on the conditions of the requirement parameters. For example, if the requirement parameters are a communication rate of 9600bps and a time range of 9:00-10:00 AM, the system will search the repository for data records that meet these two conditions as test information.

[0061] The selected test information forms the basis for conducting simulation tests. It simulates various situations in real-world scenarios, providing realistic data support for the tests. Based on the test information, simulation tests are performed on the AMI system. This may involve injecting the test information into the AMI simulated meter or related system and observing the system's response and processing results. For example, electricity data for a specific time period selected from the test information can be injected into the simulated meter to check whether the data acquisition system can accurately receive, process, and store this data, while simultaneously evaluating the system's performance indicators in this scenario, such as the accuracy of data transmission and the system's response time.

[0062] In this embodiment of the application, by utilizing data in the information repository, targeted AMI simulation tests are conducted to identify potential problems in the system and optimize it.

[0063] like Figure 5 The diagram shown is a flowchart of an AMI simulation testing method provided in Embodiment 5 of the present invention. After step S203, the AMI simulation testing method may further include the following steps: Step S501: Use the test information to determine the delivery parameters.

[0064] Step S502: Use the AMI device to provide feedback on the transmission parameters and obtain feedback information.

[0065] Step S503: Obtain the equipment detection result based on the feedback information.

[0066] Optionally, after obtaining the device detection result based on the feedback information, the process may further include the following steps: A test report is generated based on the test results from the equipment. Based on the test report, an optimization strategy for the AMI device is generated.

[0067] Based on test information and considering the working principles and actual operational requirements of the AMI system, the transmission parameters used to test the AMI equipment are determined. These transmission parameters can be data transmission rate, frequency, power, or simulated electrical load, signal strength, etc. For example, if test information shows high electrical load during a specific time period, the transmission parameters can be set to simulate the data transmission rate and power under that high load to verify the equipment's performance under such conditions.

[0068] Once the predetermined transmission parameters are input into the AMI device, the AMI device will perform corresponding operations and responses based on these parameters. For example, when specific data transmission rate and power parameters are input, the AMI device will send and receive data according to that rate and power, and adjust its own operating status accordingly.

[0069] Feedback Information Acquisition: During the AMI device's response to transmission parameters, the system collects various feedback information from the device. This feedback information may include the device's operating status (e.g., whether it is working normally, whether a fault has occurred), the accuracy of data transmission (e.g., whether data is lost, whether the error rate is within acceptable limits), and the device's energy consumption. For example, by monitoring the device's communication interface, feedback information such as data transmission success rate and latency can be obtained.

[0070] The obtained feedback information is analyzed in depth and compared with preset standards and indicators. These preset standards and indicators are formulated based on the design requirements and performance specifications of the AMI equipment; for example, the data transmission error rate should be less than 1%, and the equipment's energy consumption should be within a certain range.

[0071] Based on the analysis results, determine whether the AMI equipment meets the requirements and obtain the equipment test results. The test results can be: the equipment is normal, the equipment has minor issues requiring adjustment, or the equipment has serious faults requiring repair or replacement. For example, if the feedback information shows that the data transmission error rate exceeds 1%, the test results may indicate that the equipment has a problem with data transmission. Organize and summarize the equipment test results to form a detailed test report. The test report should include the purpose of the test, the test methods, the transmission parameters used, the analysis results of the feedback information, and the equipment test results. Relevant data charts and statistical information can also be attached to more intuitively demonstrate the equipment's performance status.

[0072] The test report is a comprehensive summary of the AMI equipment's testing results, providing a reference for equipment maintenance, management, and optimization. Based on the issues identified in the test report, the causes of these problems are further analyzed. For example, if the test report shows significant data transmission latency under high load, it may indicate insufficient processing power or a bottleneck in the communication line. Corresponding optimization strategies are developed to address the identified problems and causes. Optimization strategies may include software upgrades, adjusting equipment parameter settings, replacing hardware with higher-performance components, and optimizing communication lines. For instance, for data transmission latency issues, upgrading the equipment's communication module or increasing buffer capacity can improve data processing speed.

[0073] In this embodiment of the application, by evaluating the performance of the AMI device, problems are identified and corresponding optimization measures are taken to improve the reliability and stability of the device.

[0074] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0075] like Figure 6 The diagram shown is a schematic of an AMI simulation testing device provided in Embodiment Six of the present invention. This AMI simulation testing device corresponds one-to-one with the AMI simulation testing methods in the above embodiments. The AMI simulation testing device includes a tool invocation module 61, an information interaction module 62, an instruction issuance module 63, and a testing module 64. Detailed descriptions of each functional module are as follows: The tool calling module 61 is used to obtain the port information of the acquisition system, call the configuration tools in the preset programming framework, and use several of the configuration tools as AMI analog meters; The information interaction module 62 is used to determine the interaction address based on the port information, construct the information interaction between the AMI analog meter and the acquisition system based on the interaction address, and store the interaction information to obtain an information storage repository. The instruction issuing module 63 is used to configure the connection of any AMI analog meter, obtain the connection configuration information of the AMI analog meter, and issue a call instruction to the AMI analog meter according to the preset test requirements and the connection configuration information. The test module 64 is used to call the test information corresponding to the test requirements in the information repository according to the call instruction, and to execute AMI simulation test according to the test information.

[0076] Optionally, the aforementioned information interaction module 62 includes: The address extraction unit is used to detect the connection status of the port information. If the connection status is empty, the interaction address in the port information is extracted. An information storage unit is used to configure interaction information for the analog meter according to the interaction address, construct information interaction between the analog meter and the acquisition system according to the interaction information, and store the interaction information to obtain an information storage repository.

[0077] Optionally, the instruction issuing module 63 includes: The connection unit is used to configure communication connection, protocol connection and parameter connection for the AMI analog meter according to the preset connection rules; A communication acquisition unit is used to obtain the communication information of the AMI analog meter based on the communication connection. The protocol acquisition unit is used to obtain the protocol information based on the protocol connection. A parameter acquisition unit is used to obtain the parameter information based on the parameter connection.

[0078] Optionally, the instruction issuing module 63 includes: The relationship establishment unit is used to establish the connection relationship between the AMI analog meter and the acquisition system based on the connection configuration information. The calling unit is used to connect to the AMI analog meter using the connection relationship according to the test requirements, and to issue a calling instruction to the AMI analog meter.

[0079] Optionally, the test module 64 includes: The requirement parameter determination unit is used to determine the requirement parameters based on the test requirements. A filtering unit is used to filter test information in the information repository that corresponds to the requirement parameters according to the requirement parameters; The test execution unit is used to execute AMI simulation tests based on the test information.

[0080] Optionally, the test module 64 includes: A delivery parameter determination unit is used to determine delivery parameters using the test information; An information feedback unit is used to use the AMI device to feed back the transmission parameters and obtain feedback information; The equipment detection unit is used to obtain equipment detection results based on the feedback information.

[0081] Optionally, the test module 64 further includes: The report generation unit is used to generate a test report based on the equipment test results obtained based on the feedback information. The strategy generation unit is used to generate an optimization strategy for the AMI device based on the detection report.

[0082] Specific limitations regarding the AMI simulation test apparatus can be found in the limitations of the AMI simulation test method described above, and will not be repeated here. The aforementioned AMI simulation test apparatus and its modules can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the computer device, or stored in the memory of the computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0083] like Figure 7 The diagram shown is a schematic representation of a computer device structure according to Embodiment 7 of the present invention. The computer device includes a processor, a memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an AMI simulation testing method.

[0084] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the AMI simulation test method described in the above embodiments, for example... Figures 2 to 5 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of the AMI simulation test apparatus or the various modules / units in this embodiment of the AMI simulation test apparatus, for example... Figure 6 The functions of the tool call module 61, information interaction module 62, instruction issuance module 63, and test module 64 shown are not described again here to avoid repetition.

[0085] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the AMI simulation test method described in the above embodiments, such as... Figures 2 to 5 As shown, to avoid repetition, it will not be described again here. Alternatively, when the computer program is executed by the processor, it implements the functions of each module / unit in this embodiment of the AMI simulation test apparatus, for example... Figure 6The tool invocation module 61, information interaction module 62, instruction issuance module 63, and testing module 64 shown are not described again here to avoid repetition. The computer-readable storage medium can be non-volatile or volatile.

[0086] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0087] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0088] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. An AMI simulation test method, characterized in that, include: Obtain the port information of the acquisition system, call the configuration tools in the preset programming framework, and use several of the configuration tools as AMI analog meters; Based on the port information, the interaction address is determined, and based on the interaction address, the information interaction between the AMI analog meter and the acquisition system is constructed. The interaction information is then stored to obtain an information storage repository. For any of the AMI analog meters, configure the connection for the AMI analog meter, obtain the connection configuration information of the AMI analog meter, and issue a call command to the AMI analog meter according to the preset test requirements and the connection configuration information. According to the invocation instruction, the test information corresponding to the test requirement is retrieved from the information repository, and the AMI simulation test is executed based on the test information.

2. The AMI analog test method of claim 1, wherein, The step involves determining the interaction address based on the port information, constructing the information interaction between the analog meter and the data acquisition system based on the interaction address, and storing the interaction information to obtain an information storage repository, including: The connection status of the port information is detected. If the connection status is empty, the interaction address in the port information is extracted. Based on the interaction address, the analog meter is configured with interaction information, the information interaction between the analog meter and the data acquisition system is constructed based on the interaction information, and the interaction information is stored to obtain an information storage repository.

3. The AMI analog test method of claim 1, wherein, The connection configuration information includes communication information, protocol information, and parameter information; The step of configuring a connection for any of the AMI analog meters to obtain the connection configuration information of the AMI analog meter includes: According to the preset connection rules, the AMI analog meters are configured with communication connections, protocol connections and parameter connections respectively; Based on the communication connection, the communication information of the AMI analog meter is obtained; Based on the protocol connection, the protocol information is obtained; The parameter information is obtained by connecting the parameters.

4. The AMI simulation test method according to claim 1, characterized in that, The step of issuing a call command to the AMI analog meter based on preset test requirements and connection configuration information includes: Based on the connection configuration information, establish the connection relationship between the AMI analog meter and the data acquisition system; According to the test requirements, the AMI analog meter is connected using the connection relationship, and a call command is issued to the AMI analog meter.

5. The AMI simulation test method according to claim 1, characterized in that, The step of calling the test information corresponding to the test requirement from the information repository according to the calling instruction, and executing the AMI simulation test according to the test information, includes: Based on the aforementioned test requirements, determine the required parameters; Based on the required parameters, filter the test information in the information repository that corresponds to the required parameters; Based on the test information, perform an AMI simulation test.

6. The AMI simulation test method according to claim 1, characterized in that, The step of performing AMI simulation testing based on the test information includes: Use the test information to determine the delivery parameters; The AMI device is used to feed back the transmission parameters to obtain feedback information; Based on the feedback information, the equipment test results are obtained.

7. The AMI simulation test method according to claim 6, characterized in that, After obtaining the device detection result based on the feedback information, the process further includes: A test report is generated based on the test results from the equipment. Based on the test report, an optimization strategy for the AMI device is generated.

8. An AMI simulation test apparatus, characterized in that, The AMI simulation test device includes: The tool calling module is used to obtain port information of the acquisition system, call the configuration tools in the preset programming framework, and use several of the configuration tools as AMI analog meters; The information interaction module is used to determine the interaction address based on the port information, construct the information interaction between the AMI analog meter and the acquisition system based on the interaction address, and store the interaction information to obtain an information storage repository. The instruction issuing module is used to configure the connection of any AMI simulated meter, obtain the connection configuration information of the AMI simulated meter, and issue a call instruction to the AMI simulated meter according to the preset test requirements and the connection configuration information. The testing module is used to call the test information corresponding to the test requirements in the information repository according to the calling instruction, and to execute AMI simulation test according to the test information.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the AMI simulation test method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the AMI simulation test method according to any one of claims 1 to 7.

Images