Information processing method and system of distributed energy operation and maintenance standardization model

Abstract

The application discloses an information processing method and system for a distributed energy operation and maintenance standardization model, relates to the technical field of distributed energy intelligence, and comprises the following steps: a distributed energy intelligent operation and maintenance role class is constructed, similar objects in inherent attributes are extracted, the similar objects are assembled into a business scene, a business process complying with a standardization model is formed, and the business process is processed through the operation and maintenance standardization model to verify a point-to-point operation and maintenance business of the distributed energy. The application verifies the point-to-point operation and maintenance business of the distributed energy, improves operation and maintenance scalability and flexibility, improves operation and maintenance efficiency and data accuracy of the energy, reduces operation and maintenance cost, promotes business mode innovation, and improves the safety of the energy.

Description

Technical Field

[0001] This invention relates to the field of distributed energy technology, and in particular to an information processing method and system for a standardized model of distributed energy operation and maintenance. Background Technology

[0002] With the rapid development of distributed energy, the demand for energy operation and maintenance is increasing. However, the development of distributed energy operation and maintenance is still insufficient, and there is a lack of replicable and referable application business models. Due to the lack of standardized data interaction and processing mechanisms, traditional energy operation and maintenance services suffer from problems such as unreliable information and low operation and maintenance efficiency. Therefore, developing a standardized model for distributed energy operation and maintenance has significant application value. It standardizes business descriptions and enables the verification of point-to-point operation and maintenance services of distributed energy under conditions of unreliable information and low operation and maintenance efficiency. Summary of the Invention

[0003] In view of the problems existing in the existing standardized information model methods and systems based on intelligent operation and maintenance of distributed energy, this invention is proposed.

[0004] Therefore, the purpose of this invention is to provide an information processing method and system for a standardized model of distributed energy operation and maintenance, which can verify point-to-point operation and maintenance services of distributed energy using a standardized model of distributed energy operation and maintenance under conditions of unreliable information and low operation and maintenance efficiency.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] In a first aspect, embodiments of the present invention provide an information processing method for a standardized model of distributed energy operation and maintenance, comprising: establishing a distributed energy operation and maintenance package; organizing distributed energy participants according to enumeration types; constructing a distributed energy operation and maintenance role class; defining role class rules; determining role class requirements through rules; establishing a standardized data processing mechanism; assessing core inherent attributes; extracting similar objects from inherent attributes; assembling similar objects into a business scenario to form a business process that follows the standardized model; processing the process through the standardized operation and maintenance model; and verifying the point-to-point operation and maintenance business of distributed energy.

[0007] As a preferred embodiment of the information processing method for the standardized distributed energy operation and maintenance model of the present invention, the following is provided: the establishment of the distributed energy operation and maintenance package includes defining basic model elements, defining basic model elements includes pre-setting basic operation and maintenance functions using object-oriented technology, the enumeration type organization includes customizing a unified interface based on the pre-set basic operation and maintenance functions, setting core services for the basic operation and maintenance functions, when a function in the basic operation and maintenance functions uploads running data, the device monitoring interface is accessed, when a function in the basic operation and maintenance functions issues a scheduling instruction, the scheduling management interface is accessed, and when distributed energy participants inherit the corresponding enumeration type, they need to implement some of the unified interfaces in the operation and maintenance package;

[0008] The unified interface includes verifying the interface monitoring mechanism through unit test cases in the device monitoring interface, using a preset threshold for the coverage of each unit test case, and the test case coverage includes evaluating the number of different coverage granularities through statement coverage data and branch coverage data, training the number of different coverage granularities based on machine learning algorithms, and dynamically adjusting the overall coverage.

[0009] Evaluation is performed based on a preset threshold T = B + (S × F), where T is the preset threshold, B is the baseline coverage, S is the project size, and F is the coverage adjustment factor. When the statement coverage data is lower than T, the current unit test case does not cover the statement granularity. When the branch coverage data is lower than T, the current unit test case does not cover the branch granularity. Training is performed on the number of test cases under different coverage granularities. When the statement coverage data and branch coverage data are equal to or higher than T, role class construction is performed directly.

[0010] As a preferred embodiment of the information processing method for the distributed energy operation and maintenance standardization model of the present invention, the training of the quantity under different coverage granularities includes evaluating the quantity under different coverage granularities using independent test data. The evaluation includes determining the overall coverage rate based on the calculation ratio and performing normalization processing. The overall coverage rate includes statement coverage rate and branch coverage rate. The specific steps are as follows:

[0011] The formula for statement coverage is:

[0012]

[0013] Among them, C s T represents the number of statements covered. s y represents the total number of statements, and y represents the statement coverage rate.

[0014] The formula for branch coverage is:

[0015]

[0016] Among them, C bFor branch coverage data, T b Here, f represents the total branch coverage data, and f represents the branch coverage rate.

[0017] The normalization formula is:

[0018]

[0019] Where y' is the raw value of statement coverage, f' is the raw value of branch coverage, and Z... min Given the minimum coverage value, Z max Given the maximum known coverage value, g is the normalized overall coverage.

[0020] The role classes include different types of role classes built based on dynamically adjusted overall coverage planning. When g > B, it means that the test case coverage is higher than the baseline coverage, and a high coverage role class is built.

[0021] When g = B, it means that the test case coverage is within the baseline coverage, and a role class with medium coverage is constructed.

[0022] When g < B, it means that the test case coverage is lower than the baseline coverage, and a low coverage role class is constructed.

[0023] The role classes include different types of role classes built based on the dynamic adjustment of overall coverage planning. When g > B, it means that the test case coverage is higher than the baseline coverage, and a high coverage role class is built.

[0024] As a preferred embodiment of the information processing method for the distributed energy operation and maintenance standardization model of the present invention, the definition of role class rules includes making decisions on paths based on low coverage. When the test case coverage is lower than the average level of low coverage role classes, all paths in the role class are not tested.

[0025] When the test case coverage is equal to the average level of the low-coverage role class, then some paths in the role class are tested;

[0026] When the test case coverage is higher than the average level of low coverage role classes, then all paths in the role class are tested;

[0027] The rule-based determination of role class requirements includes identifying test cases based on the weak links in the path. When all paths in a role class are not tested, they are identified as weak links, zero requirements are obtained, and all paths are evaluated through different coverage granularities to identify abnormal paths.

[0028] When all paths in a role class have been tested, they are identified as strong links. User experience tests are then conducted on all paths, and corresponding user experience test cases are designed.

[0029] When some paths in a role class are tested, abnormal paths are identified according to the defined role class rules, judged as weak links, zero requirements are obtained, and abnormal paths are evaluated through different coverage granularities.

[0030] The processing mechanism includes collecting abnormal paths to standardize the coverage. The standardization process includes analyzing external and internal anomalies under abnormal paths. External anomalies include inputs and outputs of the external environment, and internal anomalies include inputs and outputs of the internal environment. The core inherent attributes of the assessment include establishing a comparison framework and listing the external and internal outputs under different input conditions.

[0031] In the internal environment, when the actual output is inconsistent with the expected output, the input condition is judged to be abnormal; when the actual output is consistent with the expected output, the input condition is judged to be normal.

[0032] In the external environment, when the actual output is inconsistent with the expected output, the input condition is judged to be normal; when the actual output is inconsistent with the expected output, the input condition is judged to be abnormal.

[0033] The similar objects include paths with abnormal input conditions, and the classification includes local anomalies and all anomalies. When there is a local anomaly, similar objects in the inherent attributes are extracted. When there is an all anomaly, the processing mechanism is suspended.

[0034] As a preferred embodiment of the information processing method for the distributed energy operation and maintenance standardization model of the present invention, the business process includes verifying similar objects according to the standardization model and comparing the inherent attributes of the similar objects with the inherent attributes defined in the standardization model.

[0035] The attributes include matching based on the inherent attribute similarity class in the creation of similar objects and the inherent attribute range defined in the normalization pattern. If the match is consistent, the object is in the inherent attribute similarity class; if the match is inconsistent, the object is in the non-inherent attribute similarity class; if the match is redundant, the object is in the special attribute similarity class.

[0036] When the inherent attribute values ​​of similar objects are not within the range of inherent attributes defined in the standardized model, the validation fails, and the similarity class of the inherent attributes of the similar objects is selected.

[0037] When the inherent attribute values ​​of similar objects are within the range of inherent attributes defined in the standardized model, the validation is successful, and a similarity class for the inherent attributes of the similar objects is created.

[0038] The process of creating a similar class for inherent attributes in similar objects involves comparing the value of the new attribute with the range of inherent attributes defined in the standardization model. If the value of the new attribute is within the range of inherent attributes defined in the standardization model, the new attribute is added to the similar class for inherent attributes in the similar objects. If the value of the new attribute is not within the range of inherent attributes defined in the standardization model, additional processing is required.

[0039] As a preferred embodiment of the information processing method of the distributed energy operation and maintenance standardization model of the present invention, the processing includes defining the similarity class of inherent attributes in similar objects, obtaining the comparison value of the new attribute and the inherent attribute defined in the standardization model, and if there is a new attribute in the similar objects, then the value of the new attribute is compared with the range of inherent attributes defined in the standardization model.

[0040] If the value of the new attribute is within the range of inherent attributes defined in the normalization pattern, the new attribute will be added to the inherent attribute similarity class of similar objects;

[0041] If the value of the new attribute is not within the range of inherent attributes defined in the standardized pattern, the enumeration type is inconsistent. The inconsistent enumeration values ​​are mapped to the range of inherent attributes, and the inherent attributes in similar objects are checked again to ensure consistency between the inherent attributes in similar objects and the new attribute pattern.

[0042] If the validation is successful, a new attribute relationship is established; if the validation fails, the scope of the inherent attributes defined in the standardized model is expanded.

[0043] As a preferred embodiment of the information processing method of the distributed energy operation and maintenance standardization model of the present invention, the verification of the distributed energy point-to-point operation and maintenance business includes establishing a standardized data interaction mechanism within the extended range of the inherent attributes defined in the standardized model. The interaction mechanism includes participants interacting with data according to the standardized model and verifying whether the received data conforms to the new attribute relationship.

[0044] If the conditions are met, it proves that there is no offset in the distributed point-to-point operation. At this time, the operation and maintenance business is normal, and distributed energy operation and maintenance can be carried out.

[0045] If it does not meet the requirements, it proves that there is an offset in the distributed point-to-point connection. At this time, the operation and maintenance business is abnormal, and the manual fault diagnosis stage is entered. The offset distributed point is extracted and manual operation and maintenance is carried out.

[0046] Secondly, embodiments of the present invention provide a distributed energy intelligent operation and maintenance standardized information model system, which includes: a construction module, which establishes a distributed energy operation and maintenance package, organizes distributed energy participants according to enumeration types, and constructs distributed energy operation and maintenance role classes; an extraction module, which defines role class rules, determines role class requirements through rules, establishes a standardized data processing mechanism, assesses core inherent attributes, and extracts similar objects from inherent attributes; and a verification module, which assembles similar objects into business scenarios to form a business process that follows the standardized model, processes the data through the operation and maintenance standardized model, and verifies the point-to-point operation and maintenance business of distributed energy.

[0047] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any step of the information processing method of the above-described distributed energy operation and maintenance standardization model.

[0048] Fourthly, embodiments of the present invention provide 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 information processing method of the above-described distributed energy operation and maintenance standardization model.

[0049] The beneficial effects of this invention are as follows: By constructing a distributed energy intelligent operation and maintenance role class, extracting similar objects from inherent attributes, assembling similar objects into business scenarios, forming a business process that follows a standardized model, processing through the standardized operation and maintenance model, verifying the point-to-point operation and maintenance business of distributed energy, improving the scalability and flexibility of operation and maintenance, improving the efficiency and accuracy of energy operation and maintenance, reducing operation and maintenance costs, promoting business model innovation, and improving energy security. Attached Figure Description

[0050] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0051] Figure 1 A flowchart of a standardized information model for a method and system based on a standardized information model for intelligent operation and maintenance of distributed energy, provided as an embodiment of the present invention.

[0052] Figure 2 This invention provides a business block diagram of intelligent operation and maintenance of distributed energy based on a standardized information model method and system for intelligent operation and maintenance of distributed energy, as an embodiment of the present invention.

[0053] Figure 3 This is an internal structure diagram of a computer device based on a standardized information model method and system for intelligent operation and maintenance of distributed energy, provided as an embodiment of the present invention. Detailed Implementation

[0054] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0055] 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.

[0056] 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.

[0057] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0058] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0059] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0060] Example 1

[0061] Reference Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method based on a standardized information model for intelligent operation and maintenance of distributed energy resources, including:

[0062] S1: Establish a distributed energy operation and maintenance package, organize distributed energy participants according to the enumeration type, and construct a distributed energy operation and maintenance role class.

[0063] The establishment of the distributed energy operation and maintenance package includes defining basic model elements, which includes using object-oriented technology to pre-configure basic operation and maintenance functions. The enumeration type organization includes customizing a unified interface based on the pre-configured basic operation and maintenance functions, setting core services for the basic operation and maintenance functions, and connecting to the device monitoring interface when a function in the basic operation and maintenance functions uploads running data and connecting to the scheduling management interface when a function in the basic operation and maintenance functions issues a scheduling instruction. When distributed energy participants inherit the corresponding enumeration type, they need to implement some of the unified interfaces in the operation and maintenance package.

[0064] Some unified interfaces include verifying the interface monitoring mechanism through unit test cases in the device monitoring interface, using the coverage of each unit test case to preset a threshold, and the test case coverage includes evaluating the number of different coverage granularities through statement coverage data and branch coverage data, training the number of different coverage granularities based on machine learning algorithms, and dynamically adjusting the overall coverage.

[0065] Evaluation is performed based on a preset threshold T = B + (S × F), where T is the preset threshold, B is the baseline coverage, S is the project size, and F is the coverage adjustment factor. When the statement coverage data is lower than T, the current unit test case does not cover the statement granularity. When the branch coverage data is lower than T, the current unit test case does not cover the branch granularity. Training is performed on the number of test cases under different coverage granularities. When the statement coverage data and branch coverage data are equal to or higher than T, role class construction is performed directly.

[0066] Furthermore, for a relatively simple small-scale distributed energy project, the threshold T can be set between 60% and 70%. When the statement coverage and branch coverage of the interface reach 60% to 70%, the interface monitoring mechanism is considered to have sufficient coverage, and role classes can be constructed. For medium-sized distributed energy projects, the threshold T needs to be set between 70% and 80%. Medium-sized projects are relatively large, involving more modules and complex business logic, requiring higher interface coverage to ensure system stability and reliability. In large-scale distributed energy projects, very high interface coverage is required, so the threshold T is set between 80% and 90% or even higher. Large projects usually have complex architectures, diverse participants, and numerous business processes, requiring a higher level of interface monitoring coverage. The interface coverage threshold selection is shown in Table 1 below.

[0067] Table 1. Interface Coverage Threshold Selection Table

[0068] Small projects 60％-70％ medium-sized projects 70％-80％ Large projects 80%-90% or higher

[0069] For small projects, 60% to 70% interface coverage can meet basic needs, covering the main business paths and ensuring the correctness of basic functions. Medium-sized projects require a higher interface coverage of 70% to 80% to cover multiple modules and complex business logic, improving system stability. In large projects, 80% to 90% or even higher interface coverage is crucial to fully cover numerous modules, complex business processes, and diverse participants, improving system robustness and maintainability.

[0070] S1.1: Training the quantity at different coverage granularities includes evaluating the quantity at different coverage granularities using independent test data. The evaluation includes determining the overall coverage rate based on the calculation ratio and performing normalization processing. The overall coverage rate includes statement coverage rate and branch coverage rate. The specific steps are as follows:

[0071] The formula for statement coverage is:

[0072]

[0073] Among them, C s T represents the number of statements covered. s y represents the total number of statements, and y represents the statement coverage rate.

[0074] The formula for branch coverage is:

[0075]

[0076] Among them, C b Tb is the branch coverage data, Tb is the total branch coverage data, and f is the branch coverage rate;

[0077] The normalization formula is:

[0078]

[0079] Where y' is the raw value of statement coverage, f' is the raw value of branch coverage, and Z... min Given the minimum coverage value, Z max Given the maximum known coverage value, g is the normalized overall coverage.

[0080] Role classes include different types of role classes built based on dynamically adjusted overall coverage planning. When g > B, it means that the test case coverage is higher than the baseline coverage, and a high coverage role class is built.

[0081] When g = B, it means that the test case coverage is within the baseline coverage, and a role class with medium coverage is constructed.

[0082] When g < B, it means that the test case coverage is lower than the baseline coverage, and a low coverage role class is constructed.

[0083] S2: Define role class rules including making decisions on paths based on low coverage. When the test case coverage is lower than the average level of low coverage role classes, then all paths in the role class are not tested.

[0084] When the test case coverage is equal to the average level of the low-coverage role class, then some paths in the role class are tested;

[0085] When the test case coverage is higher than the average level of low coverage role classes, then all paths in the role class are tested;

[0086] Determining role-class requirements through rules includes identifying test cases based on weak links in the path. When all paths in a role class are not tested, they are identified as weak links, and zero requirements are obtained. All paths are evaluated through different coverage granularities to identify abnormal paths.

[0087] When all paths in a role class have been tested, they are identified as strong links. User experience tests are then conducted on all paths, and corresponding user experience test cases are designed.

[0088] When some paths in a role class are tested, abnormal paths are identified according to the defined role class rules, judged as weak links, zero requirements are obtained, and abnormal paths are evaluated through different coverage granularities.

[0089] S2.1: The processing mechanism includes collecting abnormal paths and standardizing the coverage. The standardization process includes analyzing external and internal anomalies under the abnormal paths. External anomalies include the input and output of the external environment, and internal anomalies include the input and output of the internal environment. The assessment of core inherent attributes includes establishing a comparison framework and listing the external and internal outputs under different input conditions.

[0090] In the internal environment, when the actual output is inconsistent with the expected output, the input condition is judged to be abnormal; when the actual output is consistent with the expected output, the input condition is judged to be normal.

[0091] In the external environment, when the actual output is inconsistent with the expected output, the input condition is judged to be normal; when the actual output is inconsistent with the expected output, the input condition is judged to be abnormal.

[0092] Similar objects include categorizing paths with abnormal input conditions. The categories include local anomalies and all anomalies. When there is a local anomaly, similar objects in the inherent attributes are extracted. When there is an all anomaly, the processing mechanism is suspended.

[0093] S3: Assemble similar objects into business scenarios to form business processes that follow standardized models. Process them through standardized operation and maintenance models to verify the point-to-point operation and maintenance business of distributed energy.

[0094] The business process includes verifying similar objects according to a standardized model, and comparing the inherent attributes of similar objects with the inherent attributes defined in the standardized model.

[0095] The attributes include matching based on the inherent attribute similarity class in the creation of similar objects and the inherent attribute range defined in the normalization pattern. If the match is consistent, they are in the inherent attribute similarity class; if the match is inconsistent, they are in the non-inherent attribute similarity class; if the match is redundant, they are in the special attribute similarity class.

[0096] When the inherent attribute values ​​of similar objects are not within the range of inherent attributes defined in the standardized model, the validation fails, and the similarity class of the inherent attributes of the similar objects is selected.

[0097] When the inherent attribute values ​​of similar objects are within the range of inherent attributes defined in the standardized model, the validation is successful, and a similarity class for the inherent attributes of the similar objects is created.

[0098] Creating a similar class for inherent attributes in similar objects involves comparing the value of the new attribute with the range of inherent attributes defined in the standardization model. If the value of the new attribute is within the range of inherent attributes defined in the standardization model, the new attribute is added to the similar class for inherent attributes in the similar objects. If the value of the new attribute is not within the range of inherent attributes defined in the standardization model, additional processing is required.

[0099] S3.1: The processing includes defining similarity classes of inherent attributes in similar objects, obtaining comparison values ​​between new attributes and inherent attributes defined in the standardization model, and if new attributes exist in similar objects, comparing the value of the new attributes with the range of inherent attributes defined in the standardization model.

[0100] If the value of the new attribute is within the range of inherent attributes defined in the normalization pattern, the new attribute will be added to the inherent attribute similarity class of similar objects;

[0101] If the value of the new attribute is not within the range of inherent attributes defined in the standardized pattern, the enumeration type is inconsistent. The inconsistent enumeration values ​​are mapped to the range of inherent attributes, and the inherent attributes in similar objects are checked again to ensure consistency between the inherent attributes in similar objects and the new attribute pattern.

[0102] If the validation is successful, a new attribute relationship is established; if the validation fails, the scope of the inherent attributes defined in the standardized model is expanded.

[0103] Furthermore, verifying the point-to-point operation and maintenance business of distributed energy includes establishing a standardized data interaction mechanism within the scope of the inherent attributes defined in the standardized model. The interaction mechanism includes participants interacting with data according to the standardized model and verifying whether the received data conforms to the new attribute relationship.

[0104] If the conditions are met, it proves that there is no offset in the distributed point-to-point operation. At this time, the operation and maintenance business is normal, and distributed energy operation and maintenance can be carried out.

[0105] If it does not meet the requirements, it proves that there is an offset in the distributed point-to-point connection. At this time, the operation and maintenance business is abnormal, and the manual fault diagnosis stage is entered. The offset distributed point is extracted and manual operation and maintenance is carried out.

[0106] In a preferred embodiment, a distributed energy intelligent operation and maintenance standardized information model system is provided. This system includes a construction module, which establishes a distributed energy operation and maintenance package, organizes distributed energy participants according to enumeration types, and constructs distributed energy operation and maintenance role classes; an extraction module, which defines role class rules, determines role class requirements through rules, establishes a standardized data processing mechanism, assesses core inherent attributes, and extracts similar objects from the inherent attributes; and a verification module, which assembles similar objects into business scenarios to form business processes that follow the standardized model, processes them through the operation and maintenance standardized model, and verifies the point-to-point operation and maintenance business of distributed energy.

[0107] The above-mentioned unit modules can be embedded in the processor of the computer device in hardware form or independent of it, or they can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0108] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes 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.

[0109] In summary, this invention constructs a distributed energy intelligent operation and maintenance role class, extracts similar objects from inherent attributes, assembles these similar objects into business scenarios, forms a business process that follows a standardized model, processes the data through the standardized operation and maintenance model, verifies the point-to-point operation and maintenance business of distributed energy, improves the scalability and flexibility of operation and maintenance, enhances the efficiency and accuracy of energy operation and maintenance data, reduces operation and maintenance costs, promotes business model innovation, and improves energy security.

[0110] Example 2

[0111] Reference Figure 1 and Figure 2 This is the second embodiment of the present invention, which provides a multi-source power grid information fusion method based on the Internet of Things. In order to verify the beneficial effects of the present invention, a simulation experiment is conducted for scientific demonstration.

[0112] First, a distributed energy intelligent operation and maintenance package was established. Participants were organized using enumeration types, basic model elements were defined, and core services were set. By setting a threshold T, unit test cases were used to evaluate the statement and branch coverage data of the interface, dynamically adjusting the overall coverage. Based on the coverage, different types of role classes were constructed. In business scenarios, similar objects were assembled into business processes. The business processes were filtered and verified through smart contracts to ensure they conformed to standardized patterns. Through a standardized data interaction mechanism, new attribute relationships were handled, ensuring data consistency and accuracy. The complete process ensured the efficient and stable operation of the intelligent operation and maintenance of the large-scale distributed energy system. The information model implementation steps are shown in Table 2 below:

[0113] Table 2: Correspondence Table for Information Model Implementation Steps

[0114]

[0115] The table contains detailed descriptions of each step, such as establishing a distributed energy intelligent operation and maintenance package and defining role-based rules. The second column provides detailed operations for each step, such as defining basic model elements and verifying the interface monitoring mechanism through unit test cases in the device monitoring interface. The third column lists the corresponding operation numbers, indicating the sequence of each specific operation in the entire implementation process. This table provides a clear operational guide, ensuring that each step in the implementation process is correctly identified and executed, thus guaranteeing the smooth implementation of the overall project. A comparison with existing technologies is shown in Table 3 below.

[0116] Table 3 Comparison with Existing Technologies

[0117] Data standardization Highly standardized, conforming to the model Not necessarily standardized Surveillance coverage It can be dynamically adjusted to improve stability. Fixed coverage Distributed consensus mechanism Highly distributed, point-to-point communication Centralized or hybrid Smart contract applications Effectively applied to business processes Narrow application range flexibility Highly flexible and adaptable to multiple scenarios Usually more fixed Data processing efficiency Efficiently process large-scale data Limited demand for big data processing abnormal path handling Automated processing mechanism Manual intervention is usually required. Overall stability Improve overall system stability Stability is highly dependent on the specific implementation.

[0118] Compared with existing technologies, this invention has significant advantages in data standardization, monitoring coverage, distributed consensus mechanism, smart contract application, flexibility, data processing efficiency, abnormal path handling, and overall stability. Through highly standardized data processing, dynamically adjusted monitoring coverage, distributed peer-to-peer communication, multi-scenario application of smart contracts, and automated abnormal path handling, this invention provides a more efficient, flexible, and stable solution suitable for distributed energy of various scales, bringing revolutionary progress to the field of intelligent operation and maintenance.

[0119] 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. An information processing method for a standardized model of distributed energy operation and maintenance, characterized in that: include, Establish a distributed energy operation and maintenance package, organize distributed energy participants according to enumeration types, and construct a distributed energy operation and maintenance role class; Define role class rules, determine role class requirements through rules, establish a standardized data processing mechanism, assess core inherent attributes, and extract similar objects from inherent attributes; Based on similar objects, they are assembled into business scenarios to form business processes that follow standardized models. These processes are then processed through standardized operation and maintenance models to verify the point-to-point operation and maintenance business of distributed energy. The establishment of the distributed energy operation and maintenance package includes defining basic model elements. The definition of basic model elements includes pre-setting basic operation and maintenance functions using object-oriented technology. The enumeration type organization includes customizing a unified interface based on the pre-set basic operation and maintenance functions, setting core services for the basic operation and maintenance functions, and connecting to the device monitoring interface when a function in the basic operation and maintenance functions uploads running data, and connecting to the scheduling management interface when a function in the basic operation and maintenance functions issues a scheduling instruction. When distributed energy participants inherit the corresponding enumeration type, they need to implement some of the unified interfaces in the operation and maintenance package. The unified interface includes verifying the interface monitoring mechanism through unit test cases in the device monitoring interface, using a preset threshold for the coverage of each unit test case, and the test case coverage includes evaluating the number of different coverage granularities through statement coverage data and branch coverage data, training the number of different coverage granularities based on machine learning algorithms, and dynamically adjusting the overall coverage. According to the preset threshold An assessment was conducted, in which For the preset threshold, As the baseline coverage, For project scale, This is a coverage adjustment factor; it is used when the statement covers less than [a certain amount of data]. At this point, the current unit test case does not cover the statement granularity, and the branch coverage data is lower than... When the current unit test case does not cover the branch granularity, training is performed on the number of test cases under different coverage granularities. When the statement coverage data and branch coverage data are equal to or higher than the specified values, the training continues. At that time, the character class is constructed directly.

2. The information processing method for the standardized model of distributed energy operation and maintenance as described in claim 1, characterized in that: The training of the quantity at different coverage granularities includes evaluating the quantity at different coverage granularities using independent test data. The evaluation includes determining the overall coverage rate based on the calculated ratio and performing normalization processing. The overall coverage rate includes statement coverage rate and branch coverage rate. The specific steps are as follows: The formula for statement coverage is: in, For the number of statements covered, y represents the total number of statements, and y represents the statement coverage rate. The formula for branch coverage is: in, To cover data for branches, Here, f represents the total branch coverage data, and f represents the branch coverage rate. The normalization formula is: in, This is the raw numerical value for statement coverage. This is the original value for branch coverage. Given the minimum coverage value, Given the maximum coverage value, This represents the normalized overall coverage rate; The role classes include different types of role classes constructed based on dynamically adjusted overall coverage planning. When the test case coverage is higher than the baseline coverage, a high coverage role class is constructed. when When the test case coverage is within the baseline coverage, a role class with medium coverage is constructed. when When the test case coverage is lower than the baseline coverage, a low coverage role class is created.

3. The information processing method for the standardized model of distributed energy operation and maintenance as described in claim 2, characterized in that: The defined role class rules include making decisions about paths based on low coverage. When the test case coverage is lower than the average level of low coverage role classes, then all paths in the role class are not tested. When the test case coverage is equal to the average level of the low-coverage role class, then some paths in the role class are tested; When the test case coverage is higher than the average level of low coverage role classes, then all paths in the role class are tested; The rule-based determination of role class requirements includes identifying test cases based on the weak links in the path. When all paths in a role class are not tested, they are identified as weak links, zero requirements are obtained, and all paths are evaluated through different coverage granularities to identify abnormal paths. When all paths in a role class have been tested, they are identified as strong links. User experience tests are then conducted on all paths, and corresponding user experience test cases are designed. When some paths in a role class are tested, abnormal paths are identified according to the defined role class rules, judged as weak links, zero requirements are obtained, and abnormal paths are evaluated through different coverage granularities. The processing mechanism includes collecting abnormal paths to standardize the coverage. The standardization process includes analyzing external and internal anomalies under abnormal paths. External anomalies include inputs and outputs of the external environment, and internal anomalies include inputs and outputs of the internal environment. The core inherent attributes of the assessment include establishing a comparison framework and listing the external and internal outputs under different input conditions. In the internal environment, when the actual output is inconsistent with the expected output, the input condition is judged to be abnormal; when the actual output is consistent with the expected output, the input condition is judged to be normal. In the external environment, when the actual output is inconsistent with the expected output, the input condition is judged to be normal; when the actual output is inconsistent with the expected output, the input condition is judged to be abnormal. The similar objects include paths with abnormal input conditions, and the classification includes local anomalies and all anomalies. When there is a local anomaly, similar objects in the inherent attributes are extracted. When there is an all anomaly, the processing mechanism is suspended.

4. The information processing method for the standardized model of distributed energy operation and maintenance as described in claim 3, characterized in that: The business process includes verifying similar objects according to a standardized model, and comparing the inherent attributes of the similar objects with the inherent attributes defined in the standardized model; The attributes include matching based on the inherent attribute similarity class in the creation of similar objects and the inherent attribute range defined in the normalization pattern. If the match is consistent, the object is in the inherent attribute similarity class; if the match is inconsistent, the object is in the non-inherent attribute similarity class; if the match is redundant, the object is in the special attribute similarity class. When the inherent attribute values ​​of similar objects are not within the range of inherent attributes defined in the standardized model, the validation fails, and the similarity class of the inherent attributes of the similar objects is selected. When the inherent attribute values ​​of similar objects are within the range of inherent attributes defined in the standardized model, the validation is successful, and a similarity class for the inherent attributes of the similar objects is created. The process of creating a similar class for inherent attributes in similar objects involves comparing the value of the new attribute with the range of inherent attributes defined in the standardization model. If the value of the new attribute is within the range of inherent attributes defined in the standardization model, the new attribute is added to the similar class for inherent attributes in the similar objects. If the value of the new attribute is not within the range of inherent attributes defined in the standardization model, additional processing is required.

5. The information processing method for the standardized model of distributed energy operation and maintenance as described in claim 4, characterized in that: The process includes defining similarity classes of inherent attributes in similar objects, obtaining comparison values ​​between new attributes and inherent attributes defined in the standardization model, and if new attributes exist in similar objects, comparing the value of the new attributes with the range of inherent attributes defined in the standardization model. If the value of the new attribute is within the range of inherent attributes defined in the normalization pattern, the new attribute will be added to the inherent attribute similarity class of similar objects; If the value of the new attribute is not within the range of inherent attributes defined in the standardized pattern, the enumeration type is inconsistent. The inconsistent enumeration values ​​are mapped to the range of inherent attributes, and the inherent attributes in similar objects are checked again to ensure consistency between the inherent attributes in similar objects and the new attribute pattern. If the validation is successful, a new attribute relationship is established; if the validation fails, the scope of the inherent attributes defined in the standardized model is expanded.

6. The information processing method for the standardized operation and maintenance model of distributed energy as described in claim 5, characterized in that: The verification of the point-to-point operation and maintenance business of distributed energy includes establishing a standardized data interaction mechanism within the scope of the inherent attributes defined in the standardized model. The interaction mechanism includes participants interacting with data according to the standardized model and verifying whether the received data conforms to the new attribute relationship. If the conditions are met, it proves that there is no offset in the distributed point-to-point operation. At this time, the operation and maintenance business is normal, and distributed energy operation and maintenance can be carried out. If it does not meet the requirements, it proves that there is an offset in the distributed point-to-point connection. At this time, the operation and maintenance business is abnormal, and the manual fault diagnosis stage is entered. The offset distributed point is extracted and manual operation and maintenance is carried out.

7. A system based on a standardized information model for intelligent operation and maintenance of distributed energy resources, and an information processing method based on the standardized operation and maintenance model for distributed energy resources as described in any one of claims 1 to 6, characterized in that: include, The module builds a distributed energy operation and maintenance package, organizes distributed energy participants according to enumeration types, and constructs distributed energy operation and maintenance role classes. The extraction module defines role class rules, determines role class requirements through rules, establishes a standardized data processing mechanism, assesses core inherent attributes, and extracts similar objects from inherent attributes. The verification module assembles similar objects into business scenarios to form business processes that follow standardized models. These processes are then processed through standardized operation and maintenance models to verify the point-to-point operation and maintenance business of distributed energy.

8. 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 information processing method for the standardized model of distributed energy operation and maintenance as described in any one of claims 1 to 6.

9. 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 information processing method for the standardized model of distributed energy operation and maintenance as described in any one of claims 1 to 6.

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