Intelligent diagnosis method and system for protection running state of main equipment of new-generation transformer substation

Abstract

The invention discloses a new-generation intelligent diagnosis method and system for the protection operation state of main equipment of a transformer substation. The method comprises the following steps: constructing a diagnosis index of a new-generation main equipment protection device of the transformer substation; the network communication architecture based on the remote proxy service collects related original data of each diagnostic index of a new generation of transformer substation main equipment protection device; the diagnosis indexes are divided, and the divided indexes are processed respectively; and based on the related original data of each diagnosis index and the processed index data, judging whether each diagnosis index is abnormal or not, and completing diagnosis. Full-link monitoring and intelligent analysis are carried out on the protection function state of the main equipment based on multi-source information, diagnosis indexes of a new-generation transformer substation main equipment protection device are comprehensively selected, the collected indexes are respectively processed according to the characteristics of the indexes, effective processing of the indexes is achieved, and the diagnosis accuracy of the transformer substation main equipment protection device is improved. And meanwhile, the dynamically changing weight is set, so that the diagnosis result is more practical, and the monitoring effect of the operation and maintenance personnel on the protection state of the main equipment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system operation and maintenance, and more specifically, to an intelligent diagnosis method and system for the operation status of main equipment protection in a new generation of substations. Background Art

[0002] The self - controllable new generation of substation secondary systems rely on domestically self - developed chips and operating systems. Through means such as system design innovation, acquisition method optimization, and network structure simplification, the number of devices and the complexity of operation and maintenance have been effectively reduced, and the integration and operation and maintenance efficiency of the system have been improved. Main equipment protection, which can cut off the faults of protected equipment and lines selectively at the fastest speed to meet the requirements of system stability and equipment safety, is the key to the safe and stable operation of the power grid. Aiming at the problem of insufficient monitoring ability of the function status of main equipment in the new generation of substations, it is necessary to study a technology based on multi - source information to monitor all links of the main equipment protection function status and perform intelligent analysis, improve the monitoring effect of operation and maintenance personnel on the main equipment protection status, and prevent the occurrence of protection refusal due to the failure of operation and maintenance personnel to accurately and timely grasp the main equipment protection status.

[0003] There are still the following technical problems in the intelligent diagnosis of main equipment in the new generation of substations in the prior art:

[0004] 1. It is only applied to the technical field of fault diagnosis, unable to realize the full - link monitoring and multi - dimensional diagnosis of the main equipment protection status. The monitoring indicators for the main equipment in the new generation of substations are not comprehensive enough, and there is no reasonable processing process for the index data, or only simple data processing methods are used, which cannot make the processed data well reflect the actual situation and diagnosis requirements. The acquisition method of monitoring indicators is single, resulting in inaccurate index data, thus affecting the diagnosis result;

[0005] 2. The application service is not in the form of an APP and cannot be deployed in the integrated application host of the new generation of substations. The present invention APP - enables the application functions, meets the requirements of on - demand customization and flexible expansion of the APP, supports the development of advanced applications, and can well solve the problem of remote operation and maintenance of the diagnosis system. Summary of the Invention

[0006] To solve the deficiencies in the prior art, the present invention provides an intelligent diagnosis method and system for the operation status of main equipment protection in a new generation of substations.

[0007] The present invention adopts the following technical solutions.

[0008] An intelligent diagnosis method for the operation status of main equipment protection in a new generation of substations includes the following steps:

[0009] Step 1, based on the network communication architecture of the remote proxy service, construct the diagnostic indicators of the new-generation main equipment protection device for substations;

[0010] Step 2, collect the original data of each diagnostic indicator of the new-generation main equipment protection device for substations;

[0011] Step 3, divide the diagnostic indicators and process the original data of the divided indicators;

[0012] Step 4, based on the original data related to the diagnostic indicators and the processed data, determine whether each diagnostic indicator is abnormal to obtain the diagnostic result.

[0013] Preferably, the diagnostic indicators include: detection-type indicators, risk-type indicators, and failure-type indicators;

[0014] Among them, the detection-type indicators include power supply voltage offset, power supply voltage fluctuation amplitude, power supply temperature, SFP operating temperature, SFP operating voltage, bias current, optical fiber power, and optical fiber channel;

[0015] The risk-type indicators include the device operation years, the correct operation rate of the device, and the communication interruption frequency;

[0016] The failure-type indicators include protection function input status information, protection function blocking status information, protection trip circuit status information, control circuit open-circuit information, outlet hard pressing plate status information, protection function trip sending pressing plate verification information, and main transformer protection trip matrix setting value verification information.

[0017] Preferably, the network communication architecture of the remote proxy service specifically includes: RGS network communication layer, exchange protocol layer, RPC server architecture layer, and service layer;

[0018] Among them, the RGS network communication layer is used to complete the network communication between the public services of the system platform and the APP running in the container;

[0019] The exchange protocol layer is used to complete the generation and parsing of JSON messages for data interaction;

[0020] The RPC server architecture layer includes a responsive server architecture and a subscription-based server architecture;

[0021] The service layer includes the public services running on the host and the user operation interface of the intelligent diagnosis APP for the operation status of the main equipment protection running in the container.

[0022] Preferably, the division of the diagnostic indicators specifically includes:

[0023] Divide the detection-type indicators into two-way degradation indicators and one-way degradation indicators;

[0024] The two-way degradation indicators include: power supply voltage fluctuation range, SFP operating voltage, and fiber channel.

[0025] The one-way degradation indicators include: power supply voltage offset, power supply temperature, SFP operating temperature, bias current, and optical fiber power.

[0026] Preferably, the processing of the divided original index data includes: respectively performing normalization processing on the original data of the two-way degradation indicators and the one-way degradation indicators to obtain the normalized data of each indicator;

[0027] The normalization processing of the two-way degradation indicators is calculated as follows:

[0028]

[0029] In the formula, d i represents the normalized data of the i-th two-way degradation indicator, x i is the original data of the i-th two-way degradation indicator, x a , x b are respectively the upper and lower limits of the reference range of the good value of this two-way degradation indicator, max{x i}, min{x i} respectively represent the upper and lower limits of the threshold value of each two-way degradation indicator;

[0030] The normalization processing of the one-way degradation indicators is calculated as follows:

[0031]

[0032] In the formula, x i is the original data of the i-th one-way degradation indicator, x a is the upper limit of the reference range of the good value of the i-th one-way degradation indicator, max{x i} represents the upper limit of the threshold value of each one-way degradation indicator.

[0033] Preferably, the processing of the divided original index data respectively further includes: performing weighted fusion on the normalized data to obtain the fused detection-type index data, and the weighted fusion calculation formula is as follows:

[0034]

[0035] Among them, w i is the weight of the i-th detection-type indicator at time t, d i is the normalized data of the i-th detection-type indicator, and D is the weighted fusion data of this detection-type indicator.

[0036] Preferably, the weight is dynamically adjusted according to the performance value and influence factors of the detection-type index data. The influence factors of the detection-type index data include a time decay factor, a performance sensitivity factor, and a historical data influence factor. Among them, the time decay factor represents the attention degree of the diagnostic system to the recent performance value, the performance sensitivity factor represents the attention degree of the diagnostic system to the performance value fluctuation condition, and the historical data influence factor represents the dependence degree of the diagnostic system on historical data.

[0037] The present invention also proposes a new-generation intelligent diagnostic system for the operation state of main equipment protection in a substation, which is used to implement the new-generation intelligent diagnostic method for the operation state of main equipment protection in a substation, and includes: an interaction module, an index construction module, a data processing module, and a diagnostic module.

[0038] Among them, the index construction module is used to construct diagnostic indexes for the main equipment protection device of the new-generation substation, including detection indexes, risk indexes, and failure indexes.

[0039] The interaction module collects the original data of each index of the main equipment protection device of the new-generation substation to be diagnosed.

[0040] The data processing module is used to process the collected diagnostic index data and obtain the processed data.

[0041] The diagnostic module is used to judge whether each diagnostic index is abnormal based on the original data related to the diagnostic index and the processed data, and obtain a diagnostic result.

[0042] The present invention also proposes a terminal, including a processor and a storage medium.

[0043] The storage medium is used to store instructions.

[0044] The processor is used to operate according to the instructions to execute the steps of the new-generation intelligent diagnostic method for the operation state of main equipment protection in a substation.

[0045] The present invention also proposes a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the new-generation intelligent diagnostic method for the operation state of main equipment protection in a substation are implemented.

[0046] The beneficial effects of the present invention are as follows. Compared with the prior art, the present invention monitors the protection function status of the main equipment in all links based on multi-source information and conducts intelligent analysis. It comprehensively selects the diagnostic indicators for the protection device of the main equipment in the new generation substation, and processes the collected indicators separately according to their characteristics, realizing the effective processing of the indicators. At the same time, dynamically changing weights are set, and the weights are reasonably calculated and adjusted according to the historical conditions and diagnostic requirements of the indicators, making the diagnostic results more accurate and in line with the actual situation, improving the diagnostic and monitoring effects of the maintenance personnel on the protection status of the main equipment, and preventing the occurrence of protection refusal due to the failure of the maintenance personnel to accurately and timely grasp the protection status of the main equipment. Based on the basic platform of the new generation substation station control system, the present invention APP-izes the multi-dimensional intelligent diagnosis function of the operation status of the main equipment protection, deploys it on the comprehensive application host, and can effectively monitor the protection status of the main equipment in all links in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of the intelligent diagnosis method for the operation status of the main equipment protection in the new generation substation of the present invention;

[0048] Figure 2 It is a hierarchical structure diagram of the digital twin of the main equipment protection status in the present invention;

[0049] Figure 3 It is a schematic diagram of the common communication mode of the RGS network in the present invention;

[0050] Figure 4 It is a structure diagram of the intelligent diagnosis APP and the host of the operation status of the main equipment protection in the new generation substation of the present invention;

[0051] Figure 5 It is a structure diagram of the intelligent diagnosis system for the operation status of the main equipment protection in the new generation substation of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only a part of the embodiments of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0053] Such as Figure 1As shown in the figure, the present invention provides a method for intelligent diagnosis of the operation status of the main equipment protection in a new generation of substations. This method is applicable to the intelligent diagnosis of the operation status of the main equipment protection in a new generation of substations. Among them, a new generation of substations refers to intelligent substations that are based on domestic chips, operating systems, and communication protocols, and through reconstructing the secondary system architecture, achieve full domestic production and independent controllability of hardware and software. Compared with traditional intelligent substations, a new generation of substations adopts a brand-new networking architecture, cancels the process layer network, and the original combined intelligent device is transformed into an acquisition and execution unit. Digital and intelligent technologies are used to integrate device functions, optimize the network structure, improve system reliability and operation and maintenance efficiency, and meet the requirements of grid security and energy supply. Typical features include integrated monitoring of main and auxiliary equipment, intensive and efficient design, enhanced anti-interference ability, etc., to support the construction of a new power system. This method includes:

[0054] Step 1, construct diagnostic indicators for the main equipment protection device in a new generation of substations;

[0055] The diagnostic indicators include: detection-type indicators, risk-type indicators, and failure-type indicators; as shown in Table 1 below:

[0056] Table 1: Diagnostic Indicator Table for Discriminating the Status of Main Equipment Protection

[0057]

[0058] Among them, the detection-type indicators include power supply voltage offset, power supply voltage fluctuation amplitude, power supply temperature, SFP (Small Form-factor Pluggable) operating temperature, SFP operating voltage, bias current, optical fiber power, and optical fiber channel;

[0059] The risk-type indicators include device operation years, correct action rate of the device, and communication interruption frequency;

[0060] The failure-type indicators include protection function input status information, protection function blocking status information, protection trip circuit status information, control circuit open circuit information, outlet hard pressure plate status information, protection function trip sending pressure plate verification information, and main transformer protection trip matrix setting value verification information.

[0061] Step 2, collect the original data related to each diagnostic indicator of the main equipment protection device in a new generation of substations based on the network communication architecture of the remote proxy service;

[0062] As Figure 2 shown, the network communication architecture based on the remote proxy service (RGS) includes four layers: the RGS network communication layer, the exchange protocol layer, the RPC server architecture layer, and

[0063] Specifically, the first layer is the RGS network communication layer, whose main function is to complete the network communication between the public services of the system platform and the APP running in the container.

[0064] The second layer is the exchange protocol layer, whose main function is to complete the generation (serialization) and parsing (deserialization) of JSON messages for data interaction.

[0065] The third layer is the RPC server architecture layer: the system platform provides a unified response server architecture (supporting multi-threading) and subscription server architecture (supporting multi-threading). The unified service architecture supports concurrent access by multiple clients and simplifies the coding complexity of public service programs.

[0066] The fourth layer is the service layer, which includes: public services running on the host machine and the main device running in the container to protect the running status of the multi-dimensional intelligent diagnosis APP user-level operation interface.

[0067] Based on the RGS network communication architecture, the host and container communicate through a virtual network, achieving complete security isolation. The RGS-based network communication module uses a broker communication middleware mechanism, providing point-to-point, point-to-multipoint, and event subscription and publishing communication methods, solving the problem of cross-platform and cross-system network security interaction.

[0068] Figure 3 This is a common communication mode for RGS, where the RGS network middleware (rgs_server) acts as a broker to forward messages between the RGS client and the RGS server.

[0069] Compared with traditional smart substations, the new generation of substations adopts a brand-new networking architecture, cancels the process layer network, and transforms the original intelligent device into an acquisition and execution unit. For the status diagnosis of the main equipment protection, in the traditional substation main equipment protection operation status diagnosis method, the process layer data is the key diagnosis criterion. Therefore, the new generation of substation main equipment protection operation status diagnosis cannot adopt the traditional diagnosis method. Based on the networking and equipment information characteristics of the new generation of substations, the present invention proposes a method for all-round monitoring and diagnosis of the data of the acquisition and execution unit using the SV / GOOSE subscription method combined with the station control layer CMS message.

[0070] Furthermore, the outlet pressure plate is used to transmit protection device decisions to the actual equipment or system. Traditional substations cannot directly obtain the status of the outlet pressure plate. This invention uses a "dual pressure plate + GOOSE position signal" method to obtain this information, providing data support for the monitoring module and diagnostic module. Specifically, the outlet pressure plate signal is emitted through the dual pressure plate's output node and transmitted as a GOOSE position signal to the next-generation substation main equipment protection operation status intelligent diagnosis system.

[0071] The original data of the detected indicators collected include the power supply voltage offset, the power supply voltage fluctuation amplitude, the power supply temperature, the SFP operating temperature, the SFP operating voltage, the bias current, the optical fiber power, and the actual operating data of the optical fiber channel;

[0072] The risk indicators collected include the actual data of the device operation years, the correct operation rate of the device, and the communication interruption frequency;

[0073] The failure indicators are obtained by abnormal analysis of the status discrimination information of each link. The original data of the failure indicators collected include the primary equipment switch and disconnecting switch information, the secondary equipment remote signal, self-check, setting value information, the port optical intensity status, the disconnection alarm status, the soft pressure plate status, and the outlet hard pressure plate information;

[0074] Step 3: Divide the diagnostic indicators and process the divided indicators separately;

[0075] Specifically, for the risk indicators and failure indicators, in the present invention, diagnosis is performed based on the original data of each risk indicator and failure indicator collected, without going through the processing of Step 3;

[0076] For the detected indicators, in order to avoid the excessive difference in the order of magnitude of each input variable affecting the diagnostic effect, the input data is first normalized so that the data model can converge quickly, and the present invention adopts different data normalization methods for different types of indicator data.

[0077] The detected indicators are divided into two-way degradation indicators and one-way degradation indicators;

[0078] The two-way degradation indicators include: the power supply voltage fluctuation amplitude, the SFP operating voltage, and the optical fiber channel.

[0079] The one-way degradation indicators include: the power supply voltage offset, the power supply temperature, the SFP operating temperature, the bias current, and the optical fiber power.

[0080] Process the original data of each detected indicator collected respectively, specifically as follows:

[0081] For the two-way degradation indicators, the normalization formula is as shown in Equation (1).

[0082]

[0083] In the above formula, d i represents the normalized data of the i-th two-way degradation indicator, x i is the original data of the i-th two-way degradation indicator, x a , x b are respectively the upper and lower limits of the reference range of the good value of this two-way degradation indicator, max{xi} and min{x i} respectively represent the upper and lower limits of the threshold values of each two-way degradation index;

[0084] For a unidirectional degradation index with a warning as an upper limit, the normalization formula is shown in Equation (2).

[0085]

[0086] In the above formula, x i is the original data of the i-th unidirectional degradation index, x a is the upper limit of the reference range of the good value of the i-th unidirectional degradation index, and max{x i} represents the upper limit of the threshold value of each unidirectional degradation index.

[0087] Furthermore, the normalized data is weighted and fused to obtain the data processing result of each detection index, and diagnosis is performed based on the processed data to improve the reliability of the evaluation result of the main equipment operating state. The fusion formula is:

[0088]

[0089] Among them, w i (t) is the weight of the i-th detection index at time t, and d i is the normalized data of the i-th detection index, and D is the weighted fusion data of this detection index.

[0090] Aiming at the problem that the traditional weighted fusion method cannot adapt to the changing operating conditions of the main equipment, the present invention proposes a fusion method for dynamically adjusting the weight w i (t) of each data source for real-time monitoring data and historical alarm data.

[0091] The weight is dynamically adjusted according to the performance value and influence factors of the detection index data. The influence factors of the detection index data include a time decay factor, a performance sensitivity factor, and a historical data influence factor; among them, the time decay factor represents the attention degree of the diagnosis system to the recent performance value, the performance sensitivity factor represents the attention degree of the diagnosis system to the performance value fluctuation situation, and the historical data influence factor represents the dependence degree of the diagnosis system on historical data.

[0092] Furthermore, the dynamic adjustment calculation formula of the weight of each data source satisfies:

[0093]

[0094] In the formula, P i (t) is the performance value of the i-th detection index at time t, and P i,avgis the historical average performance value of the i-th detection index, Δt is the time interval for index data collection, α is the time decay factor, and 0 < α < 1, β is the performance sensitivity factor, and 0 < β < 1, γ is the historical data influence factor, and 0 < γ < 1.

[0095] Preferably, the time decay factor α reflects the attention of the diagnostic system to the recent performance value. When the performance value of the detection index fluctuates or changes greatly within the set historical time, the time decay factor α is increased to help the system respond to these changes faster; when the performance value of the detection index is relatively stable within the set historical time, the time decay factor α is decreased to help the system reduce the overreaction to short-term fluctuations;

[0096] The performance sensitivity factor β represents the attention of the diagnostic system to the performance value fluctuation. When the performance value of the detection index fluctuates greatly within the set historical time, the performance sensitivity factor β is increased to help the system detect these fluctuations more sensitively; when the performance value of the detection index is relatively stable within the set historical time, the performance sensitivity factor β is decreased to help the system reduce the overreaction to small fluctuations.

[0097] The historical data influence factor γ represents the degree of dependence of the diagnostic system on historical data. When the system has a high requirement for the continuity of historical data and needs a longer-term average effect, the value of the historical data influence factor γ is increased to improve the dependence on historical data; when the system has a high requirement for real-time performance and needs to quickly respond to new performance data, the historical data influence factor γ is decreased to improve the sensitivity to the latest data.

[0098] When a certain data source shows high reliability within a specific time period, its weight can be increased, otherwise it can be decreased. This dynamic adjustment strategy can better adapt to the changes in the operating state of the main equipment and improve the real-time performance and accuracy of the operating state diagnosis results.

[0099] Step 4, based on the original data related to each diagnostic index and the processed index data, determine whether there are abnormalities in each diagnostic index and output the diagnostic results.

[0100] Diagnose according to the risk-type index, detection-type index, and failure-type index obtained after collection and processing to obtain the operating state of the main equipment protection of the new-generation substation, as follows:

[0101] Evaluate the abnormal probability of the main equipment protection through the risk-type index. For example, if the operation years of the device exceed 20 years, the abnormal probability of the device is evaluated as high;

[0102] Monitor the detection-type index in real time. When an index abnormality occurs, it is considered that the device is in an abnormal state;

[0103] The abnormal diagnosis of detection-type indicators can refer to the evaluation content, reference range of good values, and threshold values in the deteriorated state of each detection-type indicator shown in Table 2 below. When the processed detection-type indicator data exceeds the threshold value, it is determined that there is an abnormality.

[0104] Table 2: Reference Range and Threshold Values of Detection-Type Indicators

[0105]

[0106]

[0107] By analyzing the input state of the main equipment protection for the failure-type indicator, when an abnormal indicator appears, it is considered that the device is in a state of loss of main protection. Combining the first two types of indicators, a comprehensive analysis is carried out on whether the main equipment protection is in an abnormal state. Specifically as follows:

[0108] (1) Information on the input state of protection functions

[0109] The information on the input state of protection functions is obtained through the analysis of the input of protection functions. The information on the input state of protection functions is used to reflect whether the protection function is input, including protection function soft pressure plates and control words.

[0110] For the analysis of the input of protection functions, it can be determined whether the protection function is input by judging the protection function input signal; when the input state of the protection function exits, it is necessary to judge the states of the protection function soft pressure plate and the control word.

[0111] The protection monitoring adopts a real-time calculation mode, and the state of the soft pressure plate will be updated in real time, while for the fixed value, it needs to be actively summoned. Therefore, only when it is judged that the protection function input signal is not input, it is necessary to summon the fixed value of the protection device to determine whether the control word of the protection function is input.

[0112] The analysis of the input of protection functions for various types of main equipment is shown in Table 3.

[0113] Table 3: Analysis of the Input of Protection Functions for Various Types of Main Equipment

[0114]

[0115]

[0116] (2) Information on the blocked state of protection functions

[0117] Analysis of the blocked state of protection functions

[0118] The blocked state of protection functions: reflects the information generated when the input protection function fails, including the state information of the failure of main protection, backup protection, and other functions.

[0119] When the abnormal state of the main protection blocking is monitored, it is necessary to further analyze the reasons for blocking. The reasons for the main protection blocking judgment and their corresponding bases are shown in Table 4.

[0120] Table 4: Analysis and Judgment Criteria for Protection Function Blocking

[0121]

[0122]

[0123] (3) Analysis of the Verification of the Trip Sending Pressure Plate for Protection Functions

[0124] For the protection device in the intelligent substation, the protection function trip is controlled by the trip sending soft pressure plate. Therefore, verifying the trip sending soft pressure plate is also part of the protection function monitoring. The specific verification method is to call up the protection setting values of the protection device, obtain the trip sending soft pressure plate, and verify whether the sending soft pressure plate is put into operation.

[0125] The verification of the trip sending pressure plates for the three main equipment functions of line, transformer, and bus is as follows.

[0126] ① For line protection, there are multiple sending soft pressure plates such as trip, reclosing, and blocking reclosing, and it is impossible to determine the verification reference. Only verify the trip sending soft pressure plate.

[0127] ② For transformer protection, it is necessary to verify whether the sending soft pressure plate corresponding to the setting value of the main protection trip matrix is put into operation.

[0128] ③ For bus protection, it is necessary to take the interval input soft pressure plate as the reference and verify whether the trip sending soft pressure plate of the interval with the interval input soft pressure plate of 1 is put into operation.

[0129] (4) Analysis of the Verification of the Trip Matrix Setting Value of the Main Transformer Protection

[0130] The trip matrix setting value in the main transformer protection device determines the trip settings of various protection functions of the main transformer protection. For this scheme, the input situation of the main protection trip in the trip matrix setting value can be verified.

[0131] Verification method: Call up the protection setting values of the main transformer protection device, obtain the main protection trip setting value in the trip matrix setting value. If the main protection trip matrix setting value is 0, it is judged as abnormal. Since the probability of the trip matrix of the main transformer protection being modified is relatively low, consider calling up the main transformer protection setting values once every 12 hours.

[0132] (5) Analysis of the Status of the Protection Trip Circuit

[0133] The correctness of the protection trip circuit directly affects whether the protection function is correctly realized. Therefore, the abnormality of the protection trip circuit should also be included in the main equipment protection status discrimination index set.

[0134] In a new generation of substations, the acquisition and execution unit is responsible for receiving protection trip signals, and regards whether the protection trip link subscribed by the acquisition and execution unit is disconnected as an abnormal state of the sending-end protection status.

[0135] Associate the protection trip link status signal subscribed by the acquisition and execution unit with the corresponding sending-end protection device, so that the corresponding protection trip link status can be directly monitored when monitoring and analyzing the protection device.

[0136] (6) Analysis of the status of the outlet hard pressure plate

[0137] As an important node in the trip circuit, adding monitoring of the outlet hard pressure plate is a necessary task for judging whether the protection status is abnormal. Based on the traditional pressure plate, the intelligent pressure plate realizes real-time acquisition of the pressure plate's on / off status through an added monitoring circuit, and realizes remote monitoring of the pressure plate status.

[0138] (7) Analysis of the control circuit disconnection information

[0139] For the monitoring of the control circuit disconnection, there is a virtual terminal for the control circuit disconnection signal in the acquisition and execution unit. The measurement and control can receive the control circuit disconnection signal of the acquisition and execution unit of the new generation substation and forward it to the monitoring system.

[0140] Furthermore, according to whether each diagnostic index is abnormal, the output intelligent diagnostic results are divided into two output methods: alarm signal output and diagnostic result file output. The alarm signal is used to prompt that the protection operation status of the main equipment is in an abnormal state, and the diagnostic result file is used to show the specific reasons for the protection operation status of the main equipment being in an abnormal state.

[0141] As Figure 4 、 5 shown, the present invention also proposes an intelligent diagnostic system for the protection operation status of the main equipment in a new generation substation. The above method can operate based on this system. The system includes: an interaction module, an index construction module, a data acquisition module, a monitoring module, a diagnostic module, and a result output module;

[0142] The intelligent diagnostic system for the protection operation status of the main equipment in the new generation substation constructed by the present invention is a system APP running on the basic platform of the new generation substation station control system. It separates the station control system platform from the application, forming a software architecture of platform + application (APP). The present invention preferably deploys the intelligent diagnostic system APP for the protection operation status of the main equipment in the new generation substation on the integrated application host.

[0143] Furthermore, the WebAssembly sandbox virtual machine technology is introduced, and a network security isolation technology that innovatively combines containers with the WebAssembly sandbox is adopted. It shares the operating system kernel with the host machine, and the APP deployed inside the container cannot directly interact with the external system platform of the container. While ensuring the running speed, it has a strong security isolation function.

[0144] Among them, the interaction module is used to implement data interaction between the intelligent diagnosis system for the operation status of the main equipment protection of the new-generation substation and the main equipment protection device of the new-generation substation to be diagnosed. In the present invention, the interaction module includes a remote proxy service (RGS) network communication architecture, and realizes data interaction through the remote proxy service network communication architecture;

[0145] The index construction module is used to construct diagnosis indexes for the main equipment protection device of the new-generation substation, including detection indexes, risk indexes, and failure indexes.

[0146] The data acquisition module is used to collect the original data of each diagnosis index of the main equipment protection device of the new-generation substation;

[0147] The data processing module is used to process the collected data and obtain the data of each detection index;

[0148] The monitoring module analyzes based on the collected data to obtain failure indexes;

[0149] The diagnosis module is used to diagnose according to the index data obtained by the data acquisition module, the data processing module, and the monitoring module;

[0150] The diagnosis result output module is used to output the diagnosis result.

[0151] The intelligent diagnosis results are divided into two output methods: alarm signal output and diagnosis result file output. The alarm signal is used to prompt that the operation status of the main equipment protection is in an abnormal state, and the diagnosis result file is used to show the specific reasons for the operation status of the main equipment protection being in an abnormal state.

[0152] The beneficial effects of the present invention are as follows. Compared with the prior art, the present invention adopts a multi-source data fusion technology to comprehensively analyze the data from different sensors and monitoring devices, improving the accuracy and reliability of the diagnosis of the operation status of the main equipment. In order to more comprehensively grasp the protection status of the main equipment, on the basis of detection-type indexes, the present invention adds some risk-type indexes and failure-type indexes as supplements to achieve multi-dimensional and accurate discrimination of the protection status of the main equipment.

[0153] This disclosure can be a system, a method, and / or a computer program product. The computer program product may include a computer-readable storage medium having thereon computer-readable program instructions for causing a processor to implement various aspects of this disclosure.

[0154] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. A computer-readable storage medium may be, for example - but not limited to - an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device such as a punched card or raised structures in grooves having instructions stored thereon, and any suitable combination of the foregoing. The computer-readable storage medium as used herein is not construed as being a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0155] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to respective computing / processing devices, or can be downloaded to an external computer or an external storage device through a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include a copper transmission cable, an optical fiber transmission, a wireless transmission, a router, a firewall, a switch, a gateway computer, and / or an edge server. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0156] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state-setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider). In some embodiments, by using the state information of the computer-readable program instructions to customize an electronic circuit, such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present disclosure.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent substitutions can still be made to the specific embodiments of the present invention, and any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. An intelligent diagnosis method for the operation status of main equipment protection in a new generation of substations, characterized in that, It includes the following steps: Step 1: Based on the network communication architecture of the remote proxy service, construct the diagnostic indicators of the new-generation substation main equipment protection device; Step 2: Collect the original data of each diagnostic indicator of the new-generation substation main equipment protection device; Step 3: Divide the diagnostic indicators and process the original data of the divided diagnostic indicators; Step 4: Based on the original data related to the diagnostic indicators and the processed data, judge whether there are abnormalities in each diagnostic indicator to obtain the diagnostic result.

2. The intelligent diagnostic method for the operating state of the new-generation substation main equipment protection according to claim 1, characterized in that the diagnostic indicators include: detection-type indicators, risk-type indicators, and failure-type indicators; Among them, the detection-type indicators include power supply voltage offset, power supply voltage fluctuation amplitude, power supply temperature, SFP operating temperature, SFP operating voltage, bias current, optical fiber power, and optical fiber channel; The risk-type indicators include device operation years, device correct operation rate, and communication interruption frequency; The failure-type indicators include protection function input status information, protection function blocking status information, protection trip circuit status information, control circuit open circuit information, outlet hard pressure plate status information, protection function trip sending pressure plate verification information, and main transformer protection trip matrix setting value verification information.

3. The intelligent diagnostic method for the operating state of the new-generation substation main equipment protection according to claim 1, characterized in that the network communication architecture of the remote proxy service includes: RGS network communication layer, exchange protocol layer, RPC server architecture layer, and service layer; Among them, the RGS network communication layer is used to complete the network communication between the public services of the system platform and the APP running in the container; The exchange protocol layer is used to complete the generation and parsing of JSON messages for data interaction; The RPC server architecture layer includes a responsive server architecture and a subscription server architecture; The service layer includes the public services running on the host and the intelligent diagnostic APP user operation interface for the operating state of the main equipment protection running in the container.

4. The intelligent diagnostic method for the operating state of the new-generation substation main equipment protection according to claim 2, characterized in that the division of the diagnostic indicators specifically includes: Dividing the detection-type indicators into two-way degradation indicators and one-way degradation indicators; The two-way degradation indicators include: power supply voltage fluctuation amplitude, SFP operating voltage, and optical fiber channel. The one-way degradation indicators include: power supply voltage offset, power supply temperature, SFP operating temperature, bias current, and optical fiber power.

5. The intelligent diagnostic method for the operating state of the new-generation substation main equipment protection according to claim 4, characterized in that processing the original data of the divided diagnostic indicators includes: respectively performing normalization processing on the original data of the two-way degradation indicators and the one-way degradation indicators to obtain the normalized data of each indicator; The calculation formula for performing normalization processing on the two-way degradation indicators is as follows: where d i represents the normalized data of the i-th two-way degradation index, and x i is the original data of the i-th two-way degradation index. x a , x b are respectively the lower and upper limits of the reference range of the good value of the two-way degradation index. max{x i}, min{x i} respectively represent the upper and lower limits of the threshold value of each two-way degradation index; The calculation formula for performing normalization processing on the one-way degradation indicators is as follows: where d i represents the normalized data of the i-th unidirectional deterioration index, and x i is the original data of the i-th unidirectional deterioration index, and x a is the lower limit of the reference range of the good value of the i-th unidirectional deterioration index, and max{x i} represents the upper limit of the threshold value of each unidirectional deterioration index.

6. The intelligent diagnostic method for the operating state of the new-generation substation main equipment protection according to claim 5, characterized in that The processing of the original data of the divided indicators respectively further includes: performing weighted fusion on the normalized data to obtain the fused detection-type indicator data, and the weighted fusion calculation formula is as follows: Among them, w i (t) is the weight of the i-th detection index at time t, d i is the normalized data of the i-th detection index, D is the weighted fusion data of this detection index, and n is the total number of detection indexes.

7. The intelligent diagnosis method for the operation state of the main equipment protection of a new-generation substation according to claim 6, wherein the weight is dynamically adjusted according to the performance value and influence factors of the detection-type indicator data. The influence factors of the detection-type indicator data include a time decay factor, a performance sensitivity factor, and a historical data influence factor; among them, the time decay factor represents the attention degree of the diagnosis system to the recent performance value, the performance sensitivity factor represents the attention degree of the diagnosis system to the fluctuation of the performance value, and the historical data influence factor represents the dependence degree of the diagnosis system on historical data.

8. A new-generation intelligent diagnosis system for the operation status of main equipment protection in a substation, which is used to implement the new-generation intelligent diagnosis method for the operation status of main equipment protection in a substation according to any one of claims 1-7, is characterized in that, It includes: an interaction module, an indicator construction module, a data processing module, and a diagnosis module; wherein, the indicator construction module is used to construct the diagnosis indicators of the main equipment protection device of the new-generation substation, including detection indicators, risk indicators, and failure indicators; the interaction module collects the original data of each indicator of the main equipment protection device of the new-generation substation to be diagnosed; the data processing module is used to process the collected diagnosis indicator data and obtain the processed data; the diagnosis module is used to judge whether each diagnosis indicator is abnormal based on the original data related to the diagnosis indicators and the processed data, and obtain the diagnosis result.

9. A terminal, including a processor and a storage medium; wherein the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the steps of the method according to any one of claims 1-7 are implemented.

Images