Method and system for counting continuous operation duration of electrical equipment in new energy station

Abstract

The invention discloses a method and system for counting the continuous operation duration of electrical equipment in a new energy station. The method comprises the following steps: acquiring at least two switching value operation signals of specified electrical equipment from a time sequence database through an interface program; merging the plurality of switching value operation signals according to the timestamps of the switching value operation signals, generating a uniform state change time sequence queue, and sorting the state change time sequence queue according to the sequence of sampling time; on the basis of the state change time sequence queue, calculating the continuous duration of the opening and closing state through traversal, and obtaining the continuous operation duration of the electrical equipment; returning the continuous operation duration through a calling interface, and sending the continuous operation duration to a front-end interface for display; according to the invention, full-process automatic processing from data acquisition to result output is realized, low efficiency and errors of traditional manual statistics are avoided, and the accuracy and efficiency of statistics are remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of operation and maintenance technology of electrical equipment in new energy power stations, and particularly relates to a method and system for calculating the continuous operating time of electrical equipment in new energy power stations. Background Technology

[0002] As the global energy structure shifts towards cleaner and lower-carbon energy sources, the construction and grid connection of new energy power plants, primarily wind, solar, and energy storage, are experiencing explosive growth. These power plants are typically located in remote areas and are widely distributed, with a large number and variety of electrical equipment, and their operating conditions are profoundly affected by the intermittency and volatility of natural resources. Against this backdrop, achieving refined and intelligent operation and maintenance of power plant equipment to ensure the safe and stable operation of the power system has become a core requirement and a common consensus in the development of the new energy industry.

[0003] In existing technologies, the monitoring and data acquisition of the operating status of electrical equipment has formed a relatively mature system. A common implementation plan is to build a monitoring system that integrates hardware sensing, data transmission, and software platform. For example, by deploying various sensors, measurement and control devices, or intelligent terminals on the field equipment side, real-time data such as voltage, current, power, and switch status of the equipment are collected; this data is transmitted to the site monitoring system via fieldbus or industrial Ethernet, and further aggregated into a time-series database or real-time database for storage. Some advanced applications integrate data visualization, historical query, and basic alarm functions at the platform layer, providing maintenance personnel with a visual display of the real-time operating status of the equipment.

[0004] However, existing technical solutions have a significant drawback: their functional focus is generally placed on monitoring the real-time status of equipment and recording basic data, lacking the ability to automatically and accurately statistically analyze the key cumulative state quantity of continuous equipment operation. Existing systems typically only provide discrete moment-by-moment status or segmented event records. When it is necessary to know how long a piece of equipment has been running since the last shutdown for maintenance, or the longest continuous operation record within a historical period, maintenance personnel often need to manually search through historical event logs, correlate multiple switch change records, and perform manual calculations. This method is not only inefficient and error-prone, but also difficult to scale up with a large number of devices. It cannot proactively and intuitively warn of potential overload, fatigue, or lifespan reduction risks caused by prolonged continuous equipment operation, thus hindering the effective implementation of preventative maintenance strategies. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a method and system for calculating the continuous operating time of electrical equipment in new energy power plants. This method can automatically and accurately calculate the continuous operating time of electrical equipment in new energy power plants, thereby overcoming the shortcomings of existing technologies that rely on manual labor, are inefficient, and cannot provide proactive early warnings.

[0006] Technical solution: The method for calculating the continuous operating time of electrical equipment in new energy power plants according to the present invention includes the following steps:

[0007] S1: Obtain at least two switching operation signals of a specified electrical device from a timing database through an interface program, each of the switching operation signals containing a time-stamped sequence of open and closed states;

[0008] S2: Merge the aforementioned switching operation signals according to their timestamps to generate a unified state change timing queue and sort them according to the order of sampling time;

[0009] S3: Based on the state change time sequence queue, the continuous operating time of the electrical equipment is obtained by traversing and calculating the continuous duration of the open and closed states;

[0010] S4: Return the continuous runtime through the API call and send it to the front-end interface for display.

[0011] This invention automatically acquires multiple switching operation signals from electrical equipment in new energy power plants through an interface program, realizing automated data collection of equipment operation status. It then merges and sorts these multiple signals by timestamp, constructing a unified and time-sequentially clear queue of status changes, effectively solving the problem of inconsistent timing among multi-source data. Subsequently, it iterates and calculates the continuous duration of open and closed states, accurately analyzing equipment start-up and shutdown cycles and achieving precise statistics on continuous operating time. Finally, the results are automatically returned and pushed to the front-end interface for display. The entire process requires no manual intervention, significantly improving statistical efficiency and providing reliable data support for equipment status monitoring and proactive early warning through real-time and accurate data output.

[0012] Preferably, step S1, which involves obtaining at least two switching operation signals of a specified electrical device from a timing database via an interface program, includes:

[0013] The query parameters are composed of a set of unique identifiers of electrical equipment. The timing database interface is called to obtain the timing data of the corresponding switch operation signal. Each piece of timing data includes the electrical equipment identifier, timestamp, and running or stopped status.

[0014] This preferred solution achieves accurate and automated acquisition of multiple switching signals of a specified device by constructing query parameters based on the unique identifier set of electrical equipment and calling the interface, ensuring the integrity and relevance of the data source. At the same time, each time-series data clearly includes the device identifier, timestamp, and operating status, laying a solid foundation for accurate data alignment and reliable analysis in the future.

[0015] Preferably, step S2, which involves merging the plurality of switching operation signals according to their timestamps, includes:

[0016] Each switch operation signal is merged and sorted according to its timestamp. When multiple switch operation signals have the same timestamp, the corresponding operation status of the switch operation signal is generated by logical OR operation and the corresponding time is recorded. When the timestamps of the switch operation signals are different, the earlier time of the switch operation signal is used as the merge time, and the corresponding operation status of the switch operation signal is generated by logical OR operation.

[0017] This preferred solution achieves time synchronization and state fusion of heterogeneous signal sources by merging, sorting, and performing logical OR operations on multiple switching signals according to their timestamps. This effectively solves the problems of data timing conflicts and state inconsistencies caused by asynchronous signal acquisition or scattered points. At the same time, its processing mechanism can accurately capture the device state transition represented by any signal change, ensuring that the generated state change timing queue has high integrity and logical consistency, providing a reliable data foundation for the accurate calculation of subsequent continuous running time.

[0018] Preferably, the method for calculating the continuous running time in step S3 includes:

[0019] Traverse the state change time sequence queue, record the start time of the run when the start of the run is detected, record the end time of the run when the end of the run is detected, and calculate the duration of a continuous run based on the start time and end time of the run.

[0020] This preferred solution achieves automatic identification and accurate segmentation of each continuous operating cycle of electrical equipment by accurately capturing the start and end times of the operation in the state change time sequence queue. Its calculation method has clear logic and reliable judgment, and can effectively eliminate interference caused by brief start-stop of equipment or signal fluctuations, thereby calculating the true and complete continuous operating time, providing accurate core data indicators for equipment reliability analysis and early warning decision-making.

[0021] Preferably, step S3 further includes storing the calculated continuous runtime in a runtime set in chronological order, and outputting a preset number of the most recent continuous runtime results.

[0022] This preferred solution not only constructs a traceable history of continuous equipment operation by storing the continuous runtime calculated each time in sequence and pre-outputting the results of the most recent few times, providing a data foundation for trend analysis and long-term performance evaluation, but also, by focusing on the latest operating cycle data, can efficiently support real-time monitoring and rapid judgment of the recent operating status of the equipment, significantly improving the timeliness and pertinence of status warnings and operation and maintenance decisions.

[0023] Preferably, the process of calling the interface in step S4 is as follows:

[0024] Organize the unique identifier skey of the electrical equipment to be queried into query parameters in JSON format, and initiate a query request through the REST interface;

[0025] The system receives a query response, which is JSON format data containing the continuous operating time of the electrical equipment. The JSON format data includes at least the start time, end time, and duration of each continuous operation.

[0026] This preferred solution achieves a high degree of structure and standardization of query parameters and response data by using a standardized JSON format and REST interface for data interaction, ensuring the efficiency and universality of data transmission between the front-end and back-end. Its response data clearly includes key information such as the start and end times and duration of each continuous run, which not only makes the data content clear, complete and easy to parse, but also significantly improves the system integration capabilities and the flexibility of the front-end display.

[0027] Preferably, the front-end interface described in step S4 is designed and implemented using the Vue framework, and displays the received continuous runtime data in a graphical manner.

[0028] This preferred solution uses the Vue framework to build the front-end interface and graphically display the data of continuous runtime. This not only enables dynamic and interactive visualization of the data, improving users' intuitive understanding and perception of the device's operating history and trends, but also leverages Vue's efficient responsiveness to ensure real-time synchronization between data updates and interface rendering, thereby significantly enhancing the user experience and information transmission efficiency of the monitoring system.

[0029] Secondly, the system for calculating the continuous operating time of electrical equipment in new energy power stations according to the present invention includes:

[0030] The data acquisition module is used to acquire at least two switching operation signals of a specified electrical device from a time-series database through an interface program, each of the switching operation signals containing an open / closed state sequence with a time stamp;

[0031] The signal merging and processing module is used to merge the several switching operation signals according to their timestamps, generate a unified state change timing queue, and sort them according to the order of sampling time.

[0032] The duration calculation module is used to calculate the continuous operating time of the electrical equipment by traversing and calculating the continuous duration of the open and closed states based on the state change time sequence queue.

[0033] The result output and display module is used to return the continuous runtime through the API call and send it to the front-end interface for display.

[0034] Preferably, the signal merging processing module is configured to perform a logical OR operation on the running state when multiple running signals have the same time, and to generate a state change timing queue using the running state corresponding to the earlier time as the merging benchmark when the running signals have different times.

[0035] This preferred scheme ensures the logical rigor and timing accuracy of the state change timing queue by using logical OR operations and unified processing of multiple signals with different timings. It effectively avoids misjudgment of the actual operating status of the equipment due to the dispersion of signal acquisition points or the asynchronous state of instantaneous states, thus providing a highly reliable and consistent data sequence foundation for the accurate calculation of subsequent continuous running time.

[0036] Preferably, the system further includes a runtime storage unit for storing the calculated continuous runtime of the electrical equipment into a real-time database to support historical queries and statistical analysis.

[0037] This preferred solution, by adding a runtime storage unit and persistently storing the calculation results in a real-time database, not only achieves the accumulation and efficient management of historical data on the continuous runtime of the equipment, providing a solid data foundation for trend analysis, reliability assessment, and statistical mining based on long-term data, but also enhances the system's ability to quickly backtrack on historical operating status and conduct multi-dimensional comparative analysis, thereby significantly improving the intelligence and decision support level of operation and maintenance management.

[0038] Thirdly, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed for the method of statistically analyzing the continuous operating time of electrical equipment in new energy power stations.

[0039] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for statistically analyzing the continuous operating time of electrical equipment in new energy power stations.

[0040] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: 1. This invention obtains time-stamped switch operation signals from a time-series database and performs automated merging, sorting, and traversal calculations to directly generate the continuous operating time of electrical equipment. This achieves fully automated processing from data acquisition to result output, avoiding the inefficiency and errors of traditional manual statistics and significantly improving the accuracy and efficiency of statistics; 2. By accurately statistically analyzing historical data on the continuous operating time of equipment, the system can provide a reliable basis for equipment status assessment and potential fault warning, helping maintenance personnel to promptly detect equipment overload or abnormal operating trends, thereby... 3. Based on accurate continuous operating time statistics, enterprises can reasonably arrange equipment maintenance plans to avoid unnecessary repairs and downtime, which saves maintenance costs and ensures the continuous and stable operation of equipment, thereby reducing power generation losses and improving the power generation efficiency and operational benefits of new energy power plants; 4. The system returns standardized format duration data through interfaces and displays it graphically through the front-end interface, making the runtime information more intuitive and easy to access. At the same time, the modular design and data storage function of the system facilitate integration with existing operation and maintenance platforms, support historical queries and statistical analysis, and improve the overall informatization level of operation and maintenance management. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0042] Figure 2 This is a flowchart illustrating the merging and processing of multiple signals according to the present invention.

[0043] Figure 3 This is a flowchart illustrating the continuous operating time of electrical equipment according to the present invention. Detailed Implementation

[0044] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0045] like Figure 1 As shown, the method for statistically analyzing the continuous operating time of electrical equipment in a new energy power station, as described in this invention, includes a complete data acquisition, calculation, transmission, storage, and display process. First, the operating signals of the electrical equipment with time stamps are acquired from a time-series database. Then, several switching signals of the electrical equipment are merged to form a new queue. Based on the on / off state and duration of the operating signals in the new queue, the continuous operating time of the electrical equipment in the new energy power station is calculated and statistically analyzed. Finally, the continuous operating time of the electrical equipment is displayed on a web monitoring interface through an interface call. The method includes the following steps:

[0046] S10. Obtain the operating signals of electrical equipment. Obtain the operating signals of electrical equipment with time stamps from the time-series database, including both running and stopped states. This includes the following steps.

[0047] S11. Obtain the time-stamped operating signals of electrical equipment from the time-series database, including several switching signals that affect the operating status of the electrical equipment. Each signal contains the equipment ID number, two states: running and stopped, and the time point of occurrence.

[0048] The data format for electrical equipment operation signals is as follows:

[0049] {

[0050] "statusCode": 200,

[0051] "successful": true,

[0052] "resultData": {

[0053] "tb_di:234456755:value": [

[0054] {

[0055] "time": "2025-04-24 23:00:00",

[0056] value: "0"

[0057] },

[0058] {

[0059] "time": "2025-04-24 23:05:53",

[0060] value: "1"

[0061] },

[0062] {

[0063] "time": "2025-04-24 23:15:54",

[0064] value: "0"

[0065] },

[0066] {

[0067] "time": "2025-04-24 23:25:56",

[0068] value: "1"

[0069] },

[0070] {

[0071] "time": "2025-04-24 23:30:00",

[0072] "value": "1"

[0073] }

[0074] ],

[0075] "tb_di: 234376100:value": [

[0076] {

[0077] "time": "2025-04-24 23:00:00",

[0078] "value": "0"

[0079] },

[0080] {

[0081] "time": "2025-04-24 23:05:56",

[0082] "value": "1"

[0083] },

[0084] {

[0085] "time": "2025-04-24 23:15:58",

[0086] "value": "0"

[0087] },

[0088] {

[0089] "time": "2025-04-24 23:25:59",

[0090] "value": "1"

[0091] },

[0092] {

[0093] "time": "2025-04-24 23:30:00",

[0094] "value": "1"

[0095] } ]

[0097] },

[0098] "resultHint": null,

[0099] "addition": null

[0100] }

[0101] S12. Transmit the operating signals of electrical equipment to a system that calculates the continuous operating time of electrical equipment in new energy power stations through a historical data call interface.

[0102] S20. Merge and process multiple signals. Merge and process several switching operation signals of electrical equipment to form a new queue, and sort them according to the order of sampling time. This includes the following steps.

[0103] S21, such as Figure 2 As shown, the running signals are reordered and merged according to the sampling time. Assume there are two queues of switching signals, queue A and queue B. Starting with the earliest record, if the timestamps of records in queues A and B are equal, a bitwise OR operation is performed on the states of these two records, and the time is taken from that moment. The merged result is placed in a new queue C. Next, the next record in queues A and B is taken in chronological order. If the two timestamps of two records are equal, the same algorithm is used to update queue C. If the two timestamps of two records are not equal, a bitwise OR operation is performed between the state of the earlier record and the state of the later record from the previous moment, and the time is taken from the earlier moment. The merged result is placed in a new queue C. This process continues until the last record of queue A. If there are remaining records in queue B, a bitwise OR operation is performed between the state of the remaining records in queue B and the state of the last record in queue A, and the time is taken from the moment recorded in queue B. The merged result is placed in a new queue C.

[0104] S22. The new queue is sorted according to the order of sampling time to prepare for further work.

[0105] S30. Design an algorithm for the continuous operating time of electrical equipment. Substitute the data from the new queue into the algorithm, and calculate the continuous operating time of the electrical equipment using a computer. The specific steps include the following.

[0106] S31, such as Figure 3As shown, a continuous runtime algorithm is designed. First, the timestamp is read, and it is determined whether the time exceeds the statistical time range. If found, the calculation exits. If it does not exceed the range, the current value is checked for 0. If it is 0, the current time t0 is recorded, the next time value is retrieved, and the process returns to the previous step. If it is not 0, the current time t1 is recorded, the next time value is retrieved, and the process continues to check if the current value is 0. If it is 0, the device runtime t = t1 - t0 is calculated, stored in an array, the current time t0 is recorded, the next time value is retrieved, and the process returns to the initial condition. If it is not 0, the current time t1 is recorded, the next time value is retrieved, and the process returns to the previous step. This method is used to calculate the device runtime for the most recent 10 times.

[0107] S40. Obtain the continuous operating time of the electrical equipment through interface calls. This includes the following steps.

[0108] S41. Organize the unique identifier skey of the electrical equipment to be queried into JSON format data as query parameters.

[0109] The query parameter format is as follows:

[0110] {

[0111] "skeys": [

[0112] "tb_di: 234456755:value",

[0113] "tb_di: 234376100:value" ]

[0115] }

[0116] S42. Compile the most recent 10 consecutive operating times of all queried electrical devices into JSON format data.

[0117] The returned data format is as follows:

[0118] {

[0119] "statusCode": null,

[0120] "successful": true,

[0121] "resultData": { [

[0123] {

[0124] "startTime": "2025-04-29 11:23:45",

[0125] "endTime": "2025-04-29 11:24:09",

[0126] "duration": "24"

[0127] },

[0128] {

[0129] "startTime": "2025-04-29 10:26:06",

[0130] "endTime": "2025-04-29 10:26:59",

[0131] "duration": "53"

[0132] },

[0133] {

[0134] "startTime": "2025-04-29 09:28:19",

[0135] "endTime": "2025-04-29 09:29:10",

[0136] "duration": "51"

[0137] },

[0138] {

[0139] "startTime": "2025-04-29 05:34:14",

[0140] "endTime": "2025-04-29 05:35:03",

[0141] "duration": "49"

[0142] },

[0143] {

[0144] "startTime": "2025-04-29 04:34:52",

[0145] "endTime": "2025-04-29 04:35:43",

[0146] "duration": "51"

[0147] },

[0148] {

[0149] "startTime": "2025-04-29 03:35:16",

[0150] "endTime": "2025-04-29 03:36:07",

[0151] "duration": "51"

[0152] },

[0153] {

[0154] "startTime": "2025-04-28 22:26:26",

[0155] "endTime": "2025-04-28 22:27:19",

[0156] "duration": "53"

[0157] },

[0158] {

[0159] "startTime": "2025-04-28 22:07:44",

[0160] "endTime": "2025-04-28 22:09:01",

[0161] "duration": "77"

[0162] },

[0163] {

[0164] "startTime": "2025-04-28 12:50:12",

[0165] "endTime": "2025-04-28 17:25:58",

[0166] "duration": "16546"

[0167] },

[0168] {

[0169] "startTime": "2025-04-27 20:11:53",

[0170] "endTime": "2025-04-28 12:34:45",

[0171] "duration": "58972"

[0172] } ]

[0174] },

[0175] "resultHint": null,

[0176] "addition": null

[0177] }

[0178] S43. Provide the continuous operating time of electrical equipment in JSON format to the queryer via a REST interface.

[0179] S50. Design an interface to display the continuous operating time of electrical equipment, and present the obtained continuous operating time of electrical equipment in a graphical manner. This includes the following steps.

[0180] S51. Design a monitoring interface for the continuous operation of electrical equipment using the Vue framework.

[0181] S52. Display the continuous operating time of the queried electrical equipment on the front-end interface.

[0182] Based on a similar inventive concept, this invention also provides a system for calculating the continuous operating time of electrical equipment in new energy power stations, corresponding to the method for calculating the continuous operating time of electrical equipment in new energy power stations, comprising:

[0183] The data acquisition module is used to acquire at least two switching operation signals of a specified electrical device from a time-series database through an interface program, each of the switching operation signals containing an open / closed state sequence with a time stamp;

[0184] The signal merging and processing module is used to merge the several switching operation signals according to their timestamps, generate a unified state change timing queue, and sort them according to the order of sampling time.

[0185] The duration calculation module is used to calculate the continuous operating time of the electrical equipment by traversing and calculating the continuous duration of the open and closed states based on the state change time sequence queue.

[0186] The result output and display module is used to return the continuous runtime through the API call and send it to the front-end interface for display.

[0187] The present invention also discloses an electronic device.

[0188] Specifically, the electronic device can be a desktop computer, laptop computer, handheld computer, or cloud server, etc. This computer device may include, but is not limited to, a processor and memory. The processor and memory can be connected via a bus or other means. The processor can be a Central Processing Unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, graphics processing units (GPUs), embedded neural network processing units (NPUs) or other dedicated deep learning coprocessors, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0189] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules. The processor executes various functional applications and data processing by running non-transitory software programs, instructions, and modules stored in memory. Memory may include a program storage area and a data storage area. The program storage area may store the control unit and the application program required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, memory may include high-speed random access memory and non-transitory memory. In some embodiments, memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0190] The present invention also discloses a computer-readable storage medium.

[0191] Specifically, the computer-readable storage medium is used to store a computer program, which, when executed by a processor, implements the methods described in the above method implementation.

[0192] Those skilled in the art will understand that all or part of the processes in the methods described above can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

Claims

1. A method for statistically analyzing the continuous operating time of electrical equipment in new energy power plants, characterized in that, Includes the following steps: S1: Obtain at least two switching operation signals of a specified electrical device from a timing database through an interface program, each of the switching operation signals containing a time-stamped sequence of open and closed states; S2: Merge the aforementioned switching operation signals according to their timestamps to generate a unified state change timing queue and sort them according to the order of sampling time; S3: Based on the state change time sequence queue, the continuous operating time of the electrical equipment is obtained by traversing and calculating the continuous duration of the open and closed states; S4: Return the continuous runtime through the API call and send it to the front-end interface for display.

2. The method according to claim 1, characterized in that, Step S1, which involves obtaining at least two switching operation signals of a specified electrical device from a timing database via an interface program, includes: The query parameters are composed of a set of unique identifiers of electrical equipment. The timing database interface is called to obtain the timing data of the corresponding switch operation signal. Each piece of timing data includes the electrical equipment identifier, timestamp, and running or stopped status.

3. The method according to claim 1, characterized in that, Step S2, which involves merging the plurality of switching operation signals according to their timestamps, includes: Each switch operation signal is merged and sorted according to its timestamp. When multiple switch operation signals have the same timestamp, the corresponding operation status of the switch operation signal is generated by logical OR operation and the corresponding time is recorded. When the timestamps of the switch operation signals are different, the earlier time of the switch operation signal is used as the merge time, and the corresponding operation status of the switch operation signal is generated by logical OR operation.

4. The method according to claim 1, characterized in that, The method for calculating the continuous running time in step S3 includes: Traverse the state change time sequence queue, record the start time of the run when the start of the run is detected, record the end time of the run when the end of the run is detected, and calculate the duration of a continuous run based on the start time and end time of the run.

5. The method according to claim 4, characterized in that, Step S3 also includes storing the calculated continuous runtime in a runtime set in chronological order and outputting a preset number of the most recent continuous runtime results.

6. The method according to claim 1, characterized in that, The process of calling the interface described in step S4 is as follows: Organize the unique identifier skey of the electrical equipment to be queried into query parameters in JSON format, and initiate a query request through the REST interface; The system receives a query response, which is JSON format data containing the continuous operating time of the electrical equipment. The JSON format data includes at least the start time, end time, and duration of each continuous operation.

7. The method according to claim 1, characterized in that, The front-end interface described in step S4 is designed and implemented using the Vue framework, and displays the received continuous runtime data in a graphical manner.

8. A system for statistically analyzing the continuous operating time of electrical equipment in new energy power plants, characterized in that, include: The data acquisition module is used to acquire at least two switching operation signals of a specified electrical device from a time-series database through an interface program, each of the switching operation signals containing an open / closed state sequence with a time stamp; The signal merging and processing module is used to merge the several switching operation signals according to their timestamps, generate a unified state change timing queue, and sort them according to the order of sampling time. The duration calculation module is used to calculate the continuous operating time of the electrical equipment by traversing and calculating the continuous duration of the open and closed states based on the state change time sequence queue. The result output and display module is used to return the continuous runtime through the API call and send it to the front-end interface for display.

9. The system according to claim 8, characterized in that, The signal merging processing module is configured to perform a logical OR operation on the running state when multiple running signals are at the same time, and to generate a state change timing queue using the running state corresponding to the earlier time as the merging benchmark when the running signals are at different times.

10. The system according to claim 8, characterized in that, It also includes a runtime storage unit, which stores the calculated continuous runtime of electrical equipment into a real-time database to support historical queries and statistical analysis.

Images