Method and system for remote control joint debugging test based on new energy station

Abstract

The invention discloses a remote control joint debugging test method and system based on a new energy station, and relates to the field of remote centralized control, and the method comprises the steps: exporting a channel point table, a protocol and server resources of a centralized control side and a station side according to the equipment and configuration deployed by the new energy station and a centralized control center, and carrying out the remote control joint debugging test in an isolation network; building a simulated real environment through an independent simulation test platform; instruction transmission and data consistency verification are carried out through the simulation test platform, and a multi-dimensional data verification model is introduced to carry out consistency verification on the communication point table of the new energy station and the centralized control center; according to the simulation data, open-loop instruction verification is carried out in a real environment, after the instruction verification is correct, a remote closed-loop test is carried out, and the consistency verification of the actual action and the adjustment effect of the equipment is carried out; according to the real-time data, a risk prediction model is constructed, risk assessment is carried out, and risk real-time visualization is realized through an automatic report generation method. And the reliability of remote control operation is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of remote centralized control, and in particular to a method and system for remote control and commissioning tests of new energy power stations. Background Technology

[0002] With the rapid growth of new energy installed capacity, the number of distributed power stations has surged, and the power output volatility has increased, leading to stricter requirements from the power grid for coordinated control and voltage support of these stations. To achieve unified operation and optimized scheduling across regions and multiple stations, the industry generally adopts a two-tier architecture of "central control center - power station side".

[0003] Currently, before remote control can be implemented in new energy power plants under the management of a centralized control center, remote control integration testing with the center is required. However, the remote control integration testing process for new energy power plants lacks a systematic approach, the test scenarios are not comprehensive enough, and there is no offline verification step. This can lead to errors in the execution of remote control commands during actual operation. Therefore, developing a phased, full-process remote control experimental method is one of the urgent problems to be solved.

[0004] Traditional remote control and commissioning solutions for new energy power plants suffer from unsystematic and non-reusable processes. Test steps, sequences, and pass / fail criteria lack unified standards, and there is a lack of reusable scenario libraries and templated test cases, making it difficult to support batch deployment across multiple sites. The absence of offline verification steps prevents the formation of a layered, progressive verification chain—"protocol—point table consistency verification—in-loop simulation—on-site connection"—resulting in delayed problem exposure and high location costs. Weak point table mapping consistency and traceability, coupled with multiple vendors and protocols, lead to missing fields, address offsets, inconsistent ranges, and version mismatches in channel point tables on both the central control and power plant sides, causing telemetry deviations, remote signaling errors, and misaligned remote control objects. Summary of the Invention

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a method for remote control and commissioning tests of new energy power plants to solve the problems of traditional new energy remote control and commissioning methods, such as lack of systematic process, insufficient test scenarios, lack of offline verification links, and inability to visualize risks.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for remote control and commissioning testing of new energy power stations, comprising: Based on the equipment and configuration deployed at the new energy power stations and the central control center, the channel point table, protocols, and server resources between the central control side and the power station side are exported, and a simulated real environment is built in an isolated network through an independent simulation test platform. The simulation test platform is used to verify the consistency of command transmission and data, and a multi-dimensional data verification model is introduced to verify the consistency of the communication point table between the new energy power station and the central control center. Based on the simulation data, open-loop command verification is performed in a real environment. After the command verification is correct, a remote closed-loop test is performed to verify the consistency between the actual action of the equipment and the adjustment effect. Based on real-time data, a risk prediction model is built, a risk assessment is conducted, and real-time risk visualization is achieved through automated report generation methods.

[0008] As a preferred embodiment of the method for remote control and commissioning test of new energy power stations described in this invention, the equipment and configuration deployed in the new energy power station and the central control center include an edge integrated machine, a front-end server, a database server, an infrared sensor, and a remote motor; and the channel point table, protocol, and server resources are obtained by viewing the system's configuration file.

[0009] As a preferred embodiment of the method for remote control and commissioning test of new energy power stations described in this invention, the verification command transmission and data includes: simulating control commands issued by the centralized control system on the test platform, and simulating equipment execution of control tasks; acquiring data flow between the monitoring centralized control system and the power station equipment, comparing the data point order and description between the centralized control side and the power station side, and checking the synchronization update of the centralized control side through changes in the measured values ​​of the power station side database; The consistency includes consistency between I / O point sequence and description, consistency between switch quantity change status and change time, and consistency between analog quantity measurement values.

[0010] As a preferred embodiment of the method for remote control and joint commissioning test of new energy power stations described in this invention, the multi-dimensional data verification model includes: importing the channel point table and protocol of the central control side and the power station side into the database temporary storage area, performing data type normalization, generating unified codes, and calculating the coverage rate. When the coverage rate is ≥0.98, the coverage is deemed qualified; when the coverage rate is <0.98, it is returned and a completion mechanism is used to complete it to 0.98; the unified codes are compared in various ways to calculate the consistency degree; when the consistency degree = 1, online consistency comparison is performed, and the inconsistency degree is calculated for each instruction; when the inconsistency degree = 0, the stage verification is deemed passed, and the window error is calculated for the analog quantity; when the window error is ≤0.5%, the stage verification is deemed passed, and the pass rate and median delay are calculated based on the consistency degree and window error; when the pass rate >0.99 and the median delay ≤1.0ms, the overall verification is deemed passed. The coverage formula is expressed as follows: in, Indicates coverage rate; This represents the unified coding set on the centralized control side; This represents the unified coding set on the station side; Represents the cardinality of a set; The completion mechanism includes: when the coverage rate is <0.98, the system will revert to the offline stage, freeze the current channel point table and protocol, and calculate the item gap vector; construct a candidate use case pool based on the gap, and under the constraint of satisfying the comprehensive threshold, select the set of use cases with the lowest cost, execute them first until the coverage rate reaches 1.00, and automatically generate a coverage and evidence report and unfreeze; The gap construction candidate test case pool includes a complete set of test cases automatically generated for uncovered switch quantities, analog quantities, field combinations, and time-scaled boundaries; The minimum cost use case set includes the subset of use cases with the lowest cost and satisfactory coverage selected from the candidate use case pool; The comparisons include comparisons of data type, unit, address, scaling dead zone, and protocol fields; The consistency formula is expressed as follows: in, Indicates consistency; Indicates the number of consistent items; Indicates the total number of items to be compared; The formula for the overall inconsistency is expressed as follows: in, Indicates the inconsistency degree of the k-th instruction; This indicates the time stamp for sending the k-th instruction; This indicates the time stamp for receiving and confirming the receipt of the k-th instruction; Indicates the allowable delay threshold; , Indicates the penalty coefficient; This represents the value received by the k-th instruction; This represents the expected value of the k-th instruction; Indicates the receiving point number of the k-th instruction; Indicates the expected point number for the k-th instruction; Indicates an indicator function; The window error formula is expressed as follows: in, Indicates window error; Indicates the duration of the window; This represents the range normalization coefficient; This indicates centralized control normalized measurement; This indicates normalized measurements at the station; The formula for throughput and median delay is expressed as follows: in, Indicates the pass rate; Indicates the number of samples; Indicates median delay; This represents the confirmation timestamp recorded at the receiving end for the k-th instruction; This represents the timestamp recorded at the sending end for the k-th instruction; This represents the median operator.

[0011] As a preferred embodiment of the method for remote control and commissioning test of new energy power stations described in this invention, the open-loop command verification includes: having the central control center issue a remote control command; after the new energy power station equipment executes the control command, it returns feedback data to the central control center; checking whether the command is accurately transmitted to the equipment; and verifying the transmission path. The remote closed-loop test includes the following steps: after the control center remotely issues a command, the test platform monitors the equipment's response in real time through the infrared sensor and the monitoring terminal; when a deviation is detected, the command execution is automatically adjusted.

[0012] As a preferred embodiment of the method for remote control and commissioning test of new energy power stations described in this invention, the risk prediction model includes: collecting real-time data from power station equipment and centralized control system, establishing a risk assessment model through machine learning algorithm, dynamically assessing the risk of each remote control command execution, calculating the risk index through the model, and providing real-time early warning. The real-time data includes issued instructions, changes in device status, and environmental factors; The risk index formula is expressed as follows: in, Indicates a risk index; This indicates the complexity and danger of the instruction; Indicates the stability of the device's current state; Indicates the impact of environmental factors; The real-time early warning includes setting a risk threshold based on historical data from the station equipment and centralized control system; when the risk coefficient is higher than the risk threshold, the system automatically issues an early warning.

[0013] As a preferred embodiment of the method for remote control and commissioning test of new energy power stations described in this invention, the automated report generation method includes: the test platform automatically records the data and operation steps of each round of test, automatically generates a standardized report according to a preset template, and shares it in real time through a cloud platform to achieve real-time visualization of risks; The test data and operation steps include instruction execution, device response, data consistency verification, and risk assessment; The standardized report includes test procedures, test results, data consistency verification, equipment response status, and risk assessment.

[0014] Secondly, the present invention provides a system based on remote control and commissioning tests of new energy power stations, comprising: The data acquisition unit, based on the equipment and configuration deployed at the new energy power station and the central control center, exports the channel point table, protocols, and server resources between the central control side and the power station side, and builds a simulated real environment in an isolated network through an independent simulation test platform; The data verification unit verifies command transmission and data consistency through the simulation test platform, and introduces a multi-dimensional data verification model to verify the consistency of the communication point table between the new energy power station and the central control center. The instruction experiment unit performs open-loop instruction verification in a real environment based on the simulated data. After the instruction verification is correct, a remote closed-loop test is performed to verify the consistency between the actual action of the equipment and the adjustment effect. The model building unit constructs risk prediction models based on real-time data, conducts risk assessments, and achieves real-time risk visualization through automated report generation methods.

[0015] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the method for remote control and commissioning test of new energy power stations as described in the first aspect of the present invention.

[0016] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the method for remote control and commissioning test of new energy power stations as described in the first aspect of the present invention.

[0017] The beneficial effects of this invention are as follows: The method for remote control and commissioning testing of new energy power plants provided by this invention, through a completely isolated simulation environment, does not occupy production network bandwidth during the testing process and does not affect real-time data transmission, significantly improving system reliability. Multiple rounds of testing can be performed in parallel, quickly verifying the correctness of point tables, protocols, and logic, shortening the testing cycle by more than 50%. For high-risk commands such as AGC, AVC, and switch control, their logic and transmission paths can be fully verified in the simulation environment, avoiding production accidents. The simulation environment is flexibly configurable, adaptable to changes in different power plants or centralized control systems, and supports continuous integration and automated testing. Employing real-time risk assessment technology based on big data and machine learning, it can dynamically assess system risks during testing, providing early warnings and ensuring the safety of the testing process. The use of automated report generation and optimization functions ensures the comprehensiveness and accuracy of test results, reducing errors and omissions caused by manual operation and improving the sharing and reusability of test results. Furthermore, phased testing effectively reduces the risk of on-site commissioning. The use of an open-loop command verification method improves the reliability of remote control operations. The standardized testing process greatly shortens the commissioning cycle of new energy power plants. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. 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.

[0019] Figure 1 This is a flowchart of a method for remote control and commissioning tests of new energy power stations.

[0020] Figure 2 This is a flowchart of the three-step test method for remote control and commissioning of new energy power stations. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0024] Reference Figures 1-2 This is one embodiment of the present invention, which provides a method for remote control and commissioning test of a new energy power station, including the following steps: S1. Based on the equipment and configuration deployed at the new energy power stations and the central control center, export the channel point table, protocols, and server resources between the central control side and the power station side, and build a simulated real environment in an isolated network through an independent simulation test platform.

[0025] The equipment and configurations deployed in the new energy power station and central control center include edge computing units, front-end servers, database servers, infrared sensors, and remote motors; and the channel point table, protocols, and server resources can be obtained by viewing the system's configuration file.

[0026] The edge integrated machine includes a central hub for data acquisition and command execution on the site side, which performs protocol conversion and data forwarding functions in the simulation environment.

[0027] The front-end server includes a communication interface between the simulated central control side and the field station, and processes point table parsing and command issuance.

[0028] The database server includes a configuration point table and test data storage, and the execution of the main program.

[0029] The infrared sensor includes an execution system for on-site verification, used for monitoring temperature rise of station equipment and monitoring personnel intrusion into the work area, as well as for anti-misoperation interlocking.

[0030] The remote control unit includes a tool for verifying the correctness of the communication point table, protocol, and control logic associated with the booster station subsystem.

[0031] It's important to know that other systems also obtain the channel point tables, protocols, and server resources between the central control side and the site side, including: Network architecture diagram: Server resources are usually listed in the system's network architecture diagram or hardware inventory. These can be obtained from project design documents or from the network administrator.

[0032] Server configuration files: By accessing the server's operating system, you can view system resources (such as CPU, memory, storage, network interfaces, etc.) and their configurations. This information can generally be viewed using server management tools (such as Windows Task Manager, Linux's top command, etc.).

[0033] Protocol Standard Documentation: Contact the system provider to obtain the protocol standard documentation.

[0034] Network packet capture tools: Capture communication data packets using network analysis tools (such as Wireshark) to analyze the protocols between the central control side and the field station side.

[0035] S2. Through the simulation test platform, verify the consistency of command transmission and data, and introduce a multi-dimensional data verification model to verify the consistency of the communication point table between the new energy power station and the central control center.

[0036] The verification command transmission and data include, on the test platform, simulating the control commands issued by the centralized control system and simulating the equipment to perform control tasks; acquiring the data flow between the monitoring centralized control system and the field equipment, comparing the data point order and description between the centralized control side and the field side, and checking the synchronization update of the centralized control side through the changes in the measured values ​​of the field side database; The consistency includes consistency between I / O point sequence and description, consistency between switch quantity change status and change time, and consistency between analog quantity measurement values.

[0037] The independent simulation test platform for the simulated production environment includes, in conjunction with virtualization technology, importing and configuring the device communication protocols and channel point tables in the simulated environment through a database management system based on the channel point table, protocols, and server resources of the real environment, so that the simulated environment is consistent with the actual production environment, and verifying the consistency of command transmission and data; and connecting the site equipment and the central control center through an isolated network.

[0038] The virtualization technology includes using physical servers to lay the groundwork for network and host mirroring, and preparing transmission channels by shaping the topology of the virtual network and injecting the channel point table and protocols; generating VMs according to the template and loading the channel point table and protocols.

[0039] The database management system includes the following functions: writing channel point tables and protocol description files into a temporary storage database in batches through a preset import interface; completing a normalized mapping according to data type rules; generating a read-only configuration snapshot; and sending it to the front-end machine, edge integrated machine, and remote machine to complete the joint debugging configuration.

[0040] It is important to know that the virtualization technology includes building a three-tiered resource pool of compute, network, and storage on a physical server using a Type-1 hypervisor (preferably KVM): Computation plane: Allocate memory for "Front-end Machine (FEP) Virtual Machine, Edge Machine Simulation (EDGE) Virtual Machine, Remote Unit Simulation (RTU) Virtual Machine, and Database Virtual Machine (DB)"; enable CPU core binding to reduce jitter for critical real-time virtual machines.

[0041] Network plane: Establish vSwitch using Open vSwitch (OVS); use VXLAN (5001) to implement cross-host Layer 2 overlay when necessary; issue ACLs in OVS to restrict access to only necessary ports.

[0042] Storage plane: Ceph RBD provides virtual disk and snapshot capabilities, and the joint debugging baseline can be reused with one click; all virtual machines are uniformly mounted with clock domain (NTP) to ensure the consistency of time scales such as CP56Time2a.

[0043] Orchestration and monitoring: Ansible is used to deploy images and configurations, and Prometheus + Grafana is used to collect latency, packet loss, and logs to achieve end-to-end observability.

[0044] The multi-dimensional data verification model includes importing the channel point table and protocols of the central control side and the site side into the database temporary storage area, performing data type normalization, generating unified codes, and calculating coverage. When the coverage is ≥0.98, the coverage is deemed qualified; when the coverage is <0.98, it is rolled back and a completion mechanism is used to complete it to 0.98. The unified codes are compared in various ways to calculate the consistency degree; when the consistency degree = 1, online consistency comparison is performed, and the inconsistency degree is calculated for each instruction; when the inconsistency degree = 0, the stage verification is deemed passed, and the window error is calculated for the analog quantity; when the window error ≤0.5%, the stage verification is deemed passed, and the pass rate and median delay are calculated based on the consistency degree and window error. When the pass rate >0.99 and the median delay ≤1.0ms, the overall verification is deemed passed.

[0045] The coverage formula is expressed as follows: in, Indicates coverage rate; This represents the unified coding set on the centralized control side; This represents the unified coding set on the station side; Represents the cardinality of a set.

[0046] The completion mechanism includes: when the coverage rate is <0.98, the system will revert to the offline stage, freeze the current channel point table and protocol, and calculate the sub-item gap vector; construct a candidate use case pool based on the gap, and under the constraint of satisfying the comprehensive threshold, select the set of use cases with the lowest cost, execute them first until the coverage rate reaches 1.00, and automatically generate a coverage and evidence report and unfreeze.

[0047] The gap construction candidate test case pool includes a complete set of test cases automatically generated for uncovered switch quantities, analog quantities, field combinations, and time-stamped boundaries.

[0048] The minimum cost use case set includes the subset of use cases selected from the candidate use case pool that have the lowest cost and meet the coverage requirements.

[0049] The comparisons include comparisons of data type, unit, address, scaling dead zone, and protocol fields.

[0050] The consistency formula is expressed as follows: in, Indicates consistency; Indicates the number of consistent items; This indicates the total number of items to be compared.

[0051] The formula for the overall inconsistency is expressed as follows: in, Indicates the inconsistency degree of the k-th instruction; This indicates the time stamp for sending the k-th instruction; This indicates the time stamp for receiving and confirming the receipt of the k-th instruction; Indicates the allowable delay threshold; , Indicates the penalty coefficient; This represents the value received by the k-th instruction; This represents the expected value of the k-th instruction; Indicates the receiving point number of the k-th instruction; Indicates the expected point number for the k-th instruction; Indicates an indicator function.

[0052] The window error formula is expressed as follows: in, Indicates window error; Indicates the duration of the window; This represents the range normalization coefficient; This indicates centralized control normalized measurement; This indicates the normalized measurement at the station.

[0053] The formula for throughput and median delay is expressed as follows: in, Indicates the pass rate; Indicates the number of samples; Indicates median delay; This represents the confirmation timestamp recorded at the receiving end for the k-th instruction; This represents the timestamp recorded at the sending end for the k-th instruction; This represents the median operator.

[0054] S3. Based on the simulation data, perform open-loop command verification in a real environment. After the command verification is correct, perform a remote closed-loop test to verify the consistency between the actual operation of the equipment and the adjustment effect.

[0055] The open-loop command verification includes having the central control center issue a remote control command, and after the new energy power station equipment executes the control command, it returns feedback data to the central control center to check whether the command is accurately transmitted to the equipment and to verify the transmission path.

[0056] It's important to understand that open-loop verification, without closed-loop feedback, checks each item on the point table mapping, read / write permissions, protocol timing, numerical conversion, network latency, etc., to ensure the correctness of the "command-response-measurement point transition" and prevents process self-adjustment. It only performs atomic operations such as reading, single-point writing, mode switching, and time synchronization; all writes are within a whitelist, amplitude limiting, and interlocking bypass.

[0057] Open-loop verification involves recording the start time, capturing the baseline of the on-site measurement points, and issuing a minimum read request to each channel. Subsequently, the response code is recorded, the test value (within the whitelist and amplitude limit) is written to the i-th point, the readback value is read, and the actual result is compared according to the linear conversion defined in the engineering library. Round-trip delay and jitter are measured for each link, a single anomaly is injected, and the effectiveness of the rejection policy and rollback is verified, forming a "command-response-measurement point trajectory" record.

[0058] The remote closed-loop test includes the following steps: after the control center remotely issues a command, the test platform monitors the equipment's response in real time through the infrared sensor and the monitoring terminal; when a deviation is detected, the command execution is automatically adjusted.

[0059] It's important to understand that closed-loop testing closes the loop of "SP → controller → actuator (MV) → process quantity (PV) → measurement → feedback" in a real environment to verify dynamic performance, steady-state accuracy, disturbance rejection capability, and consistency with "command-actual action-regulation effect." Open-loop testing is then performed using a list of criteria; a step test is executed within the operating condition window, configuring rate limits and backoff thresholds.

[0060] The closed-loop experiment closes the feedback loop by loading the open-loop list and operating condition window, MV rate upper limit and backoff threshold, and records the baseline; a small step is injected into the load side, the error is recorded and the empirical margin is calculated, and finally a closed-loop performance report and consistency conclusions are generated.

[0061] The specific procedure for the verification experiment is as follows: Figure 2As shown, firstly, a simulation environment is set up to migrate the simulation equipment to the central control center; then, the I / O point changes are simulated to verify the consistency of the four remote information. If they are consistent, open-loop command verification is performed; if they are inconsistent, the configuration is corrected to be consistent. In the open-loop command verification, the central control center issues commands and checks the measurement and control devices at the site. If the command verification is correct, remote closed-loop operation is performed; if it is incorrect, the transmission link is checked until it is correct. In the remote closed-loop operation, switches / disconnectors are actually opened and closed, and AGC / AVC control is executed. The actual values ​​are checked to see if they are consistent with the target values. If they are consistent, the experiment ends.

[0062] S4. Based on real-time data, construct a risk prediction model, conduct risk assessment, and achieve real-time risk visualization through automated report generation methods.

[0063] The risk prediction model includes collecting real-time data from site equipment and centralized control systems, establishing a risk assessment model through machine learning algorithms, dynamically assessing the risk of executing each remote control command, calculating a risk index through the model, and providing real-time early warnings.

[0064] The real-time data includes issued instructions, changes in device status, and environmental factors.

[0065] The risk index formula is expressed as follows: in, Indicates a risk index; This indicates the complexity and danger of the instruction; Indicates the stability of the device's current state; This indicates the influence of environmental factors.

[0066] The real-time early warning includes setting a risk threshold based on historical data from the station equipment and centralized control system; when the risk coefficient is higher than the risk threshold, the system automatically issues an early warning.

[0067] The machine learning method includes using an unsupervised autoencoder (AE) for anomaly detection. Without introducing causal weights, it learns a low-dimensional representation of "normal joint debugging behavior" using only historical "pass samples". During joint debugging, it uses reconstruction error to identify soft anomalies that are "morphologically abnormal but have not yet triggered hard failures", which are used as supplementary evidence rather than replacements for rule thresholds.

[0068] In an isolated integration testing environment, the machine learning method constructs a fixed-dimensional feature vector using the running data from each "pass window" and performs zero-mean standardization. An unsupervised autoencoder is trained offline to obtain a low-dimensional representation of normal integration testing behavior. The window reconstruction error is calculated on an independent validation set and a threshold θ is fixed using a preset quantile. During the integration testing period, features are generated in real time according to the sliding window, and the reconstruction error is calculated. The error is compared with the threshold θ to obtain a soft anomaly indication. If the triggering condition is met cumulatively within a predetermined window, the system automatically collects OVS flow tables and packet captures, records configuration and timing evidence, and issues an early warning. The aforementioned soft anomalies are only used as supplementary evidence for rule gates (based on latency thresholds, single-line consistency, and window error criteria) and do not replace the existing "pass or fail" judgment. The entire process is controlled by version numbers and transactions to support rollback and retesting.

[0069] The automated report generation method includes the following steps: the testing platform automatically records the data and operation steps of each round of testing, automatically generates a standardized report based on a preset template, and shares it in real time through a cloud platform to achieve real-time risk visualization.

[0070] The test data and operation steps include instruction execution, device response, data consistency verification, and risk assessment.

[0071] The standardized report includes test procedures, test results, data consistency verification, equipment response status, and risk assessment.

[0072] It is important to understand that the cloud platform is a multi-tenant, versioned, and controlled SaaS integrated platform for remote control of new energy power plants. Its features include: a unified identity and access control module (OIDC, used for tenant and role isolation), an API gateway and message bus (HTTP+AMQP, used for secure access and event-driven configuration and telemetry), a configuration and evidence storage module (Object Storage S3 + Time Series Library, used for versioned storage of point tables, protocol templates, message capture, and judgment results), a workflow orchestration module (used for directed acyclic orchestration), a signature publishing and rollback module (generating read-only configuration snapshots and version switching), and an observability and auditing module (indicators, logs, tracking, and an immutable audit chain).

[0073] The cloud platform receives the channel point tables and protocol descriptions from the central control side and the site side through the API gateway. It triggers a workflow to complete semantic normalization and consistency verification in the database, generates and signs the deployment snapshot of "device-channel-point-protocol template", and sends it to the front-end machine and remote simulation terminal in mTLS push mode. During operation, it aggregates instructions and telemetry through the message bus, calculates the median round-trip delay, success rate, single-line consistency and window error online and stores the evidence. If the threshold is not met, it rolls back to the previous snapshot and replays it with one click according to the difference list. Otherwise, it is fixed as a new version for reuse by peer sites. At the same time, encrypted transmission, least privilege and audit trail are performed throughout the process to ensure controllable release, verifiable evidence and traceable configuration.

[0074] Example 2, an embodiment of the present invention, provides a system based on remote control and commissioning tests of new energy power stations, comprising: The data acquisition unit, based on the equipment and configuration deployed at the new energy power station and the central control center, exports the channel point table, protocols, and server resources between the central control side and the power station side, and builds a simulated real environment in an isolated network through an independent simulation test platform.

[0075] The data verification unit verifies command transmission and data consistency through the simulation test platform, and introduces a multi-dimensional data verification model to verify the consistency of the communication point table between the new energy power station and the central control center.

[0076] The instruction experiment unit performs open-loop instruction verification in a real environment based on the simulated data. After the instruction verification is correct, a remote closed-loop test is conducted to verify the consistency between the actual operation of the equipment and the adjustment effect.

[0077] The model building unit constructs risk prediction models based on real-time data, conducts risk assessments, and achieves real-time risk visualization through automated report generation methods.

[0078] This embodiment also provides a computer device applicable to a method for remote control and commissioning tests of new energy power stations, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the method for remote control and commissioning tests of new energy power stations as proposed in the above embodiment.

[0079] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0080] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements a method for implementing a remote control and commissioning test based on a new energy power station, as proposed in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0081] In summary, this invention, through the integration of a fully isolated network simulation test platform, parallel multi-round testing, open-loop and closed-loop command verification methods, and risk prediction models and real-time visualization technologies, enables energy power plants to be widely used in the field of remote centralized control during remote commissioning. It effectively reduces the risks of on-site commissioning, improves the reliability of remote control operations, and significantly shortens the commissioning cycle of new energy power plants, demonstrating significant application prospects and social value.

[0082] It should be noted that the above 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for remote control and commissioning tests of new energy power stations, characterized in that: This includes exporting the channel point table, protocols, and server resources between the control center and the power station based on the equipment and configuration deployed at the new energy power station and the control center, and building a simulated real environment in an isolated network through an independent simulation test platform; The simulation test platform is used to verify the consistency of command transmission and data, and a multi-dimensional data verification model is introduced to verify the consistency of the communication point table between the new energy power station and the central control center. Based on the simulation data, open-loop command verification is performed in a real environment. After the command verification is correct, a remote closed-loop test is performed to verify the consistency between the actual operation of the equipment and the adjustment effect. Based on real-time data, a risk prediction model is built, a risk assessment is conducted, and real-time risk visualization is achieved through automated report generation methods.

2. The method for remote control and commissioning test of new energy power stations as described in claim 1, characterized in that: The equipment and configurations deployed in the new energy power station and central control center include edge computing units, front-end servers, database servers, infrared sensors, and remote motors; and the channel point table, protocols, and server resources can be obtained by viewing the system's configuration file.

3. The method for remote control and commissioning test of new energy power stations as described in claim 2, characterized in that: The verification command transmission and data include, on the test platform, simulating the control commands issued by the centralized control system and simulating the equipment to perform control tasks; acquiring the data flow between the monitoring centralized control system and the field equipment, comparing the data point order and description between the centralized control side and the field side, and checking the synchronization update of the centralized control side through changes in the measured values ​​of the field side database; The consistency includes consistency between I / O point sequence and description, consistency between switch quantity change status and change time, and consistency between analog quantity measurement values.

4. The method for remote control and commissioning test of new energy power stations as described in claim 3, characterized in that: The multi-dimensional data verification model includes importing the channel point table and protocols of the central control side and the site side into the database temporary storage area, performing data type normalization, generating unified codes, and calculating coverage. When the coverage is ≥0.98, the coverage is deemed qualified; when the coverage is <0.98, it is rolled back and a completion mechanism is used to complete it to 0.

98. The unified codes are compared in various ways to calculate the consistency. When the consistency is 1, an online consistency comparison is performed, and the inconsistency is calculated for each instruction. When the inconsistency is 0, the stage verification is deemed passed, and the window error is calculated for the analog quantity. When the window error is ≤0.5%, the stage verification is deemed passed, and the pass rate and median delay are calculated based on the consistency and window error. When the pass rate is >0.99 and the median delay is ≤1.0ms, the overall verification is deemed passed. The coverage formula is expressed as follows: in, Indicates coverage rate; This represents the unified coding set on the centralized control side; This represents the unified coding set on the station side; Represents the cardinality of a set; The completion mechanism includes: when the coverage rate is <0.98, the system will revert to the offline stage, freeze the current channel point table and protocol, and calculate the item gap vector; construct a candidate use case pool based on the gap, and under the constraint of satisfying the comprehensive threshold, select the set of use cases with the lowest cost, execute them first until the coverage rate reaches 1.00, and automatically generate a coverage and evidence report and unfreeze; The gap construction candidate test case pool includes a complete set of test cases automatically generated for uncovered switch quantities, analog quantities, field combinations, and time-stamped boundaries; The minimum cost use case set includes the subset of use cases with the lowest cost and satisfactory coverage selected from the candidate use case pool; The comparisons include comparisons of data type, unit, address, scaling dead zone, and protocol fields; The consistency formula is expressed as follows: in, Indicates consistency; Indicates the number of consistent items; Indicates the total number of items to be compared; The formula for the overall inconsistency is expressed as follows: in, Indicates the inconsistency degree of the k-th instruction; This indicates the time stamp for sending the k-th instruction; This indicates the time stamp for receiving and confirming the receipt of the k-th instruction; Indicates the allowable delay threshold; , Indicates the penalty coefficient; This represents the value received by the k-th instruction; This represents the expected value of the k-th instruction; Indicates the receiving point number of the k-th instruction; Indicates the expected point number for the k-th instruction; Indicates an indicator function; The window error formula is expressed as follows: in, Indicates window error; Indicates the duration of the window; This represents the range normalization coefficient; This indicates centralized control normalized measurement; This indicates normalized measurements at the station; The formula for throughput and median delay is expressed as follows: in, Indicates the pass rate; Indicates the number of samples; Indicates median delay; This represents the confirmation timestamp recorded at the receiving end for the k-th instruction; This represents the timestamp recorded at the sending end for the k-th instruction; This represents the median operator.

5. The method for remote control and commissioning test of new energy power stations as described in claim 4, characterized in that: The open-loop command verification includes: having the central control center issue a remote control command; after the new energy power station equipment executes the control command, it returns feedback data to the central control center; checking whether the command is accurately transmitted to the equipment; and verifying the transmission path. The remote closed-loop test includes the following steps: after the control center remotely issues a command, the test platform monitors the equipment's response in real time through the infrared sensor and the monitoring terminal; when a deviation is detected, the command execution is automatically adjusted.

6. The method for remote control and commissioning test of new energy power stations as described in claim 5, characterized in that: The risk prediction model includes collecting real-time data from station equipment and centralized control system, establishing a risk assessment model through machine learning algorithm, dynamically assessing the risk of each remote control command execution, calculating a risk index through the model, and providing real-time early warning. The real-time data includes issued instructions, changes in device status, and environmental factors; The risk index formula is expressed as follows: in, Indicates a risk index; This indicates the complexity and danger of the instruction; Indicates the stability of the current state of the device; Indicates the impact of environmental factors; The real-time early warning includes setting a risk threshold based on historical data from the station equipment and centralized control system; when the risk coefficient is higher than the risk threshold, the system automatically issues an early warning.

7. The method for remote control and commissioning test of new energy power stations as described in claim 6, characterized in that: The automated report generation method includes the following steps: the testing platform automatically records the data and operation steps of each round of testing, automatically generates a standardized report based on a preset template, and shares it in real time through a cloud platform to achieve real-time risk visualization. The test data and operation steps include instruction execution, device response, data consistency verification, and risk assessment; The standardized report includes test procedures, test results, data consistency verification, equipment response status, and risk assessment.

8. A system based on remote control and commissioning tests of new energy power stations, based on the file encryption method described in any one of claims 1 to 7, characterized in that: include, The data acquisition unit, based on the equipment and configuration deployed at the new energy power station and the central control center, exports the channel point table, protocols, and server resources between the central control side and the power station side, and builds a simulated real environment in an isolated network through an independent simulation test platform; The data verification unit verifies command transmission and data consistency through the simulation test platform, and introduces a multi-dimensional data verification model to verify the consistency of the communication point table between the new energy power station and the central control center. The instruction experiment unit performs open-loop instruction verification in a real environment based on the simulated data. After the instruction verification is correct, a remote closed-loop test is performed to verify the consistency between the actual action of the equipment and the adjustment effect. The model building unit constructs risk prediction models based on real-time data, conducts risk assessments, and achieves real-time risk visualization through automated report generation methods.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the method for remote control and commissioning test of new energy power stations as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for remote control and commissioning test of new energy power stations as described in any one of claims 1 to 7.

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