Power system cloud platform design method, system, equipment and medium

Abstract

The invention relates to the technical field of electric power systems, and discloses an electric power system cloud platform design method, system and device and a medium, and the method comprises the step of effectively solving the problem that the version change of a bottom-layer component influences an upper-layer application. By establishing the public resource packaging model, the change of a bottom-layer component version is shielded, a uniform interface is provided for an upper-layer application, and the stability and reliability of the upper-layer application when the upper-layer application uses public resource services are ensured. Meanwhile, the business basic service platform carries out unified management on public functions of all advanced applications, efficient integration and deployment of the functions are achieved, and the operation efficiency and the management level of the whole electric power system cloud platform are improved. The electric power system cloud platform design has remarkable innovation and practicability in the technical field of electric power systems, and can provide powerful guarantee for stable operation and efficient management of the electric power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, and particularly relates to a power system cloud platform design method, system, device and medium. BACKGROUND

[0002] In the operation and management process of the power system, the traditional platform design method exposes many significant problems. Specifically, the version of the underlying component is updated frequently, and such frequent changes often have an adverse impact on the upper application, which is specifically manifested as a significant decrease in the stability and compatibility of the application, thereby affecting the normal operation of the entire system. In addition, the functional modules common to each high-level application lack a unified and effective management mechanism, and this lack of management makes the post-maintenance and functional expansion of the system extremely difficult, which not only greatly increases the cost required in the operation process, but also increases the implementation difficulty of the technical level.

[0003] Furthermore, when the system faces different device health states and complex and variable environmental factors, the traditional platform design method is difficult to quickly and accurately generate the most optimized platform service configuration scheme in a short time, which directly affects the overall operation efficiency and reliability of the power system, and becomes a bottleneck restricting the efficient and stable operation of the power system. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a power system cloud platform design method, system, device and medium, which can solve the problem of the influence of the version change of the underlying component on the upper application, realize the unified management of the public functions of each high-level application, and quickly generate the optimal platform service configuration according to different device health states and environmental factors, thereby improving the operation efficiency and reliability of the power system.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a power system cloud platform design method, comprising:

[0008] obtaining device data and environmental data of a target power system, and preprocessing the device data and the environmental data;

[0009] establishing a public resource packaging model according to the preprocessed device data and environmental data;

[0010] The public resource encapsulation model is used for shielding the influence of bottom component version change on upper application, providing unified interface for providing application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service for upper application;

[0011] The business basic service platform is constructed based on the public resource encapsulation model;

[0012] The business basic service platform is used for uniformly managing public functions of each high-level application, and the public functions include model splicing, graphic interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management and permission service;

[0013] The business basic service platform is called through a preset platform service function, optimal platform service configuration is generated, and corresponding lower execution function is triggered to implement platform configuration operation.

[0014] As a preferred scheme of the power system cloud platform design method, the method further comprises the following steps:

[0015] The platform configuration operation execution result data is obtained;

[0016] The platform configuration operation execution result data is fed back to the public resource encapsulation model and the business basic service platform for parameter iterative updating;

[0017] Until the iteration condition is met.

[0018] As a preferred scheme of the power system cloud platform design method, the method further comprises the following steps:

[0019] A preset public resource service index set is included, and the public resource service index set includes a plurality of public resource service indexes for evaluating the target power system cloud platform;

[0020] The public resource service indexes are selected based on the preprocessed equipment data and environment data;

[0021] The selected public resource service indexes are characterized by a scoring formula, and the public resource service score of the target power system cloud platform is calculated according to the scoring formula;

[0022] The public resource service demand of the platform is classified according to the public resource service score, and the public resource encapsulation model is formed.

[0023] The preferred scheme can comprehensively and specifically evaluate the public resource service of the target power system cloud platform by presetting a public resource service index set. The selected indexes are more in line with the actual situation and can accurately reflect the real service state of the platform based on the preprocessed equipment data and environmental data. The selected indexes are characterized by a scoring formula and the score is calculated, which provides a quantitative evaluation standard for the public resource service of the platform, facilitating intuitive understanding of the platform service level. According to the score, the public resource service demand is classified to form an encapsulation model, which can not only clearly distinguish the service demand levels of different platforms, but also provide more accurate and adaptive services for upper-layer applications. In this way, in the subsequent platform management and service provision process, resources can be flexibly allocated according to different classification situations, improving resource utilization efficiency and reducing resource waste. At the same time, this classification and encapsulation model can effectively shield the influence of bottom component version changes on upper-layer applications, ensuring the stability and reliability of upper-layer applications when using public resource services. In addition, for developers, the unified interface design makes development and testing work more efficient, enabling rapid construction and deployment of applications, reducing development cost and time. Moreover, the business basic service platform constructed in this way can better unify the public functions of various high-level applications, further improving the operation efficiency and management level of the entire power system cloud platform.

[0024] As a preferred scheme of the power system cloud platform design method of the present application, wherein:

[0025] A set of business basic service optimization strategies is preset, and the set of business basic service optimization strategies includes several optimization strategies for different public resource service classifications;

[0026] According to the platform public resource service classification result obtained from the public resource encapsulation model, an adaptive optimization strategy is selected from the set of business basic service optimization strategies;

[0027] The selected optimization strategy is parameterized and configured, and the business basic service platform for optimizing and adjusting basic public resource service demand is constructed in combination with the public resource service indexes and scores in the public resource encapsulation model.

[0028] As a preferred scheme of the power system cloud platform design method of the present application, wherein:

[0029] Different platform service strategy rules under the combination of different equipment health states and environmental factors are preset;

[0030] The platform service function selects corresponding rules from preset platform service policy rules according to the current obtained device health status and environmental factors;

[0031] The selected rules are transmitted to the business basic service platform as input conditions;

[0032] The different platform service behaviors are comprehensively evaluated to obtain the platform service configuration with the optimal efficiency reliability ratio under the current state.

[0033] As a preferred scheme of the power system cloud platform design method, the trigger corresponding lower layer execution function implementation platform configuration operation includes:

[0034] When the optimal platform service configuration is determined, the platform service function triggers the corresponding lower layer execution function;

[0035] The lower layer execution function generates specific platform configuration instructions according to the optimal platform service configuration;

[0036] The platform configuration instructions include but are not limited to the setting and adjustment of application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service;

[0037] The platform configuration instructions are sent to the corresponding execution equipment or personnel to implement specific platform configuration operations.

[0038] As a preferred scheme of the power system cloud platform design method, the iteration condition includes:

[0039] When the feedback iteration number of platform configuration operation execution result data reaches the preset maximum iteration number, and the parameter change rate of the public resource packaging model and the business basic service platform is less than the preset threshold value;

[0040] Or the platform performance index reflected by the platform configuration operation execution result data exceeds the preset performance target value.

[0041] Secondly, the application provides a power system cloud platform design system, which includes:

[0042] A data acquisition and processing module is configured to acquire device data and environmental data of a target power system and pre-process the device data and environmental data;

[0043] A first model establishing module is configured to establish a public resource packaging model according to the pre-processed device data and environmental data;

[0044] The public resource encapsulation model is used for shielding the influence of bottom component version change on upper application, providing unified interface for providing application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service for upper application;

[0045] The platform establishment module is used for constructing a business basic service platform based on the public resource encapsulation model;

[0046] The business basic service platform is used for uniformly managing public functions of each high-level application, and the public functions include model splicing, graphic interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management and permission service.

[0047] The operation module is used for calling the business basic service platform through a preset platform service function, generating optimal platform service position, and triggering corresponding lower execution function to implement platform configuration operation.

[0048] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method as described above when executing the computer program.

[0049] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the method as described above when executed by a processor.

[0050] Compared with the prior art, the present application has the following beneficial effects: the present application proposes a power system cloud platform design method, which effectively solves the problem of the influence of bottom component version change on upper application. By establishing a public resource encapsulation model, the change of the bottom component version is shielded, a unified interface is provided for the upper application, and the stability and reliability of the upper application when using the public resource service are ensured. At the same time, the business basic service platform uniformly manages the public functions of each high-level application, realizes efficient integration and deployment of functions, and improves the operation efficiency and management level of the entire power system cloud platform. The power system cloud platform design of the present application has significant innovation and practicality in the field of power system technology, and can provide strong guarantee for the stable operation and efficient management of the power system. It not only solves many problems in the prior art, but also provides a new idea and direction for the future development of the power system, and is expected to achieve good economic and social benefits in practical application. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description only represent some of the embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0052] Figure 1 A method flow chart of a power system cloud platform design method provided by an embodiment of the present application.

[0053] Figure 2 An internal structure diagram of an electronic device of a power system cloud platform design method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned objects, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort should fall within the scope of protection of the present application.

[0055] Embodiment 1, refer to Figure 1 For the first embodiment of the present application, the embodiment provides a power system cloud platform design method, which comprises:

[0056] In the prior art, there are some problems, such as the traditional platform design method is difficult to cope with the frequent update of the underlying component version, which leads to the decline of the stability and compatibility of the upper application; the lack of unified management of the public functions of each senior application increases the difficulty and cost of system maintenance and expansion; when facing different device health states and environmental factors, the optimal platform service configuration cannot be generated quickly, which affects the operation efficiency and reliability of the power system.

[0057] The present application provides a method that can effectively solve the above-mentioned problems. Next, how to realize the power system cloud platform design method will be described in detail in combination with multiple embodiments.

[0058] Figure 1 A method flow chart of a power system cloud platform design method is shown, which comprises:

[0059] S101, obtaining device data and environmental data of a target power system, and preprocessing the device data and the environmental data, wherein:

[0060] It should be noted that in order to realize the power system cloud platform design, the device data and the environmental data of the target power system must be obtained first.

[0061] In some specific embodiments, the device data covers the operating parameters and state information of various devices in the power system, such as the power, voltage, and temperature of the generator, the load condition of the transformer, etc., which can intuitively reflect the real-time operating conditions of the devices. The environmental data includes external environmental factors such as temperature, humidity, air pressure, and light intensity, which often have an important impact on the performance and operating stability of the devices.

[0062] It should be noted that when the device data and environmental data of the target power system are obtained, considering the diversity and complexity of these data, directly using them for subsequent platform design may result in inaccurate or inefficient results. Therefore, it is necessary to preprocess the device data and environmental data.

[0063] In some specific embodiments, preprocessing these data is a key step, which includes data cleaning to remove noise, outliers, and duplicate data to ensure the accuracy and consistency of the data; data normalization to unify different magnitudes and ranges of data to the same scale for subsequent analysis and processing; and data encoding to convert non-numeric data into numeric data to facilitate better recognition and processing by computers.

[0064] It should be noted that through these preprocessing operations, the quality of the data can be improved, providing a solid data foundation for subsequent model establishment and platform construction.

[0065] In the embodiments of the present application, raw operating data is collected from various sensors, SCADA systems, log systems, dispatching platforms, etc. of the target power system, including device state data (such as voltage, current, temperature, and load rate) and external environmental data (such as air temperature, humidity, wind speed, and rainfall). The raw data is cleaned, normalized, and feature extracted to provide high-quality input for subsequent modeling.

[0066] Specifically, data cleaning and outlier processing can use the following operations:

[0067]

[0068] where x represents a certain item of raw collected value, for example, the real-time temperature of a transformer winding, unit: Celsius (℃), or the real-time current of a line, unit: ampere (A). x cleanis the effective data value after cleaning. μ is the average value of the index in the historical period, used to determine whether the current value deviates from the normal range. σ is the historical standard deviation of the index, reflecting the degree of data fluctuation. If the current value exceeds μ ± 3σ, it is considered an abnormal value, and the historical median of the index is used instead to enhance robustness. If the data is missing, the historical mean of the index is used The missing data is filled in.

[0069] It should be noted that this method can effectively filter out dirty data caused by sensor false positives, communication interruptions, etc.

[0070] For example, the reading of a certain substation voltage monitoring point is 132 kV, and the historical mean is 110 kV, and the standard deviation is 5 kV. Then 132 > 110 + 3 × 5 = 125, it is determined to be abnormal, and replaced with the median 111 kV.

[0071] Furthermore, data normalization is performed;

[0072]

[0073] where x' is the normalized data, with a value range of [0, 1] and dimensionless. x clean is the original value after cleaning. x min and x max are the minimum and maximum values of the index in the historical data, respectively.

[0074] It should be noted that the purpose of normalization is to eliminate the dimensional differences between different indicators, facilitating subsequent multi-index fusion and scoring calculation.

[0075] For example, the load rate of a certain device is 75%, with a historical minimum of 0% and a maximum of 100%. The normalized value is (750) / (1000) = 0.75.

[0076] In some specific embodiments, a device health index is designed to comprehensively evaluate the current operating state of the device, and the calculation steps are as follows:

[0077]

[0078] where EHI is the device health index, used to comprehensively evaluate the current operating state of the device, with a value closer to 0 being healthier, and greater than 1 indicating a serious anomaly. T is the current device temperature, in ℃. T norm is the rated operating temperature of the device, in ℃. ΔT max is the maximum temperature rise allowed by the device, in ℃. V actual is the current voltage actual value, in kV. V rated is the rated voltage of the device, in kV. Irms is the current effective value, unit: A. I rated is the device rated current, unit: A. w1, w2, w3 are weight coefficients, which satisfy w1+w2+w3=1, and can be set according to the device type or historical fault data, for example, w1=0.5 (temperature weight is the highest), w2=0.3, w3=0.2.

[0079] For example, the current temperature of a transformer is 85℃, the rated temperature is 65℃, the allowed temperature rise is 30℃, the voltage deviation is 2kV (rated 110kV), and the current is 800A (rated 1000A), then:

[0080]

[0081] It indicates that the device is in a mild overheating state, but is still within the controllable range.

[0082] It should be noted that obtaining the device data and environmental data of the target power system and preprocessing the device data and environmental data provide high-quality, standardized data support for subsequent establishment of a public resource packaging model and construction of a business basic service platform. High-quality data can make the public resource packaging model more accurately shield the influence of bottom component version changes on the upper application, and provide more stable and reliable unified interfaces. Because accurate, consistent and normalized data can make the model better capture the characteristics and change rules of the bottom component, thereby providing more accurate application management, application logs and other types of services for the upper application.

[0083] S102, establishing a public resource packaging model according to the preprocessed device data and environmental data, wherein:

[0084] It should be noted that when the preprocessed device data and environmental data are obtained, it is considered that the frequent changes of the bottom component version will bring many unstable factors to the upper application, such as compatibility problems, function failure, etc. The establishment of the public resource packaging model is to effectively solve these difficult problems. The model will deeply analyze the preprocessed data and mine the characteristics and change rules of the bottom component. Through a series of complex algorithms and logical designs, it can shield the changes of the bottom component version.

[0085] In some specific embodiments, the public resource packaging model integrates and abstracts various information of the underlying components, and uniformly describes and manages different versions of the underlying components. It is like an intermediate layer that builds a stable bridge between the upper-layer application and the underlying components. The upper-layer application does not need to care about the specific version and changes of the underlying components, but only needs to obtain the required services through the unified interface provided by the public resource packaging model. For example, when the version of the underlying component is updated, the public resource packaging model automatically handles these changes to ensure that the upper-layer application can continue to run normally and is not affected by version changes.

[0086] In some specific embodiments, the unified interface covers a variety of important services, such as application management, which can comprehensively manage the life cycle of the upper-layer application, including operations such as deployment, startup, stop, update, etc. of the application; application log service can record various information during the running of the application, facilitating subsequent troubleshooting and performance analysis; application cluster scheduling can reasonably allocate cluster resources according to the load and resource requirements of the application, improving the running efficiency of the application; application warehouse is used to store and manage various application programs, facilitating the distribution and sharing of applications; the management console provides an interface for administrators to centrally manage the entire platform, facilitating configuration and monitoring of the entire platform; the development and testing environment provides a safe and stable environment for developers to develop and test new applications; the object storage service can store various types of data to provide reliable data storage support for applications; and the general authentication service can verify and authorize the identity of users to ensure that only legitimate users can access applications and resources.

[0087] In the embodiments of the present application, the public resource packaging model is used to shield the influence of version changes of the underlying components on the upper-layer application, and provides a unified interface for the upper-layer application to provide application management, application log, application cluster scheduling, application warehouse, management console, development and testing environment, object storage service, and general authentication service.

[0088] In the embodiments of the present application, establishing the public resource packaging model according to the preprocessed device data and environment data comprises:

[0089] A preset public resource service index set is provided, and the public resource service index set includes a plurality of public resource service indexes for evaluating the target power system cloud platform;

[0090] The public resource service indexes are selected based on the preprocessed device data and environment data;

[0091] The selected public resource service indexes are represented by a scoring formula, and the public resource service score of the target power system cloud platform is calculated according to the scoring formula;

[0092] According to the public resource service score, the public resource service demand of the platform is classified, and a public resource encapsulation model is formed.

[0093] Specifically, a public resource encapsulation model is constructed, which is used to shield the influence of version changes of the underlying components on the upper layer application and provide unified interface services.

[0094] Further, a set of public resource service indicators is preset A set of indicators for evaluating the public resource service capability of the cloud platform is defined, which can include the following contents: Among them, m1 represents the average response delay, the unit is millisecond (ms), which reflects the service response speed. m2 represents the resource utilization rate, the unit is percentage (%), which refers to the comprehensive utilization rate of CPU, memory, storage, etc. m3 represents the service availability, the unit is percentage (%), which represents the monthly service uptime ratio. m4 represents the fault recovery time, the unit is minute (min), which is MTTR (Mean Time To Repair). m5 represents the security authentication strength, which is a scoring system (0-5 points), which reflects the complexity and security of the identity authentication mechanism.

[0095] Further, based on the data, a subset of key indicators is selected The Pearson correlation coefficient is used to select indicators that are strongly related to the quality of platform services. The Pearson correlation coefficient can be calculated as follows:

[0096]

[0097] Among them, r i is the correlation between indicator m i and comprehensive service quality Q, the value range is [-1, 1], the larger the absolute value, the stronger the correlation. Q is the comprehensive score of platform service quality, which can be obtained through user feedback, SLA achievement rate or operation and maintenance event statistics. Cov(m i ,Q) is the covariance of m i and Q. And σ Q are the standard deviations of m i and Q.

[0098] It should be noted that a threshold τ r = 0.5 can be set, if |r i |> τ r , the indicator is retained into M sel .

[0099] For example, if r1 = 0.8 (delay is strongly negatively correlated with service quality), it is retained;

[0100] If r5 = 0.1, it is removed.

[0101] Further, the selected public resource service indicators are scored by a scoring formula, each retained indicator is quantitatively scored (0-1), and the total score is obtained by weighted summation. Each single indicator scoring function can be expressed as follows (taking response delay as an example):

[0102]

[0103] Where S1 is the delay service quality score, and the value closer to 1 indicates lower delay and higher service quality. m1 is the current average response delay, with a unit of ms. m0 is the ideal delay threshold, for example 100 ms. λ is the steepness coefficient, which controls the scoring decline speed, for example λ = 0.05.

[0104] For example, if m1 = 200 ms, then S1 ≈ 1 / (1+e 0.05×100 ) = 1 / (1+e 5 ) ≈ 0.0067, the score is extremely low.

[0105] Further, the public resource service score of the target power system cloud platform is calculated according to the scoring formula, and the comprehensive service score is represented as follows:

[0106]

[0107] Where G is the total score of the public resource service, with a value range of [0, 1], and the higher the score, the stronger the platform service capability. k' is the number of retained indicators in . w i is the weight of the i-th indicator, which satisfies ∑w i = 1, and can be determined by entropy weight method, AHP or machine learning method. S i (m i ) is the score value of the i-th indicator.

[0108] For example, w1 = 0.4, w2 = 0.3, w3 = 0.3, S1 = 0.9, S2 = 0.7, S3 = 0.8, then G = 0.4 x 0.9 + 0.3 x 0.7 + 0.3 x 0.8 = 0.81.

[0109] Further, the service demand classification is performed according to the score G. The specific service level classification rules are as follows:

[0110]

[0111] It should be noted that the high security level is suitable for critical business, requiring high availability, low delay and strong fault tolerance. The standard level is suitable for general business, balancing efficiency and cost. The energy-saving level is suitable for non-critical tasks, giving priority to reducing energy consumption and resource consumption.

[0112] Further, the public resource encapsulation model is represented as

[0113] It should be noted that the establishment of the public resource encapsulation model based on the pre-processed device data and environment data is of great significance for the subsequent construction of the business basic service platform. It provides a stable and unified underlying resource support for the business basic service platform. The public resource encapsulation model shields the version changes of the underlying components, allowing the business basic service platform to focus on the implementation of business logic without worrying about the instability of the underlying factors.

[0114] S103, constructing a business basic service platform based on the public resource encapsulation model, wherein:

[0115] It should be noted that after obtaining the public resource encapsulation model, the business basic service platform will take this model as the cornerstone and carry out a series of construction work. The construction goal of the business basic service platform is to provide a stable, efficient and function-rich basic support environment for various business applications in the upper layer.

[0116] In some specific embodiments, the business basic service platform will access various underlying resources according to the unified interface provided by the public resource encapsulation model. These resources include but are not limited to computing resources, storage resources, network resources, etc. The platform will dynamically allocate and manage these resources according to the needs of different businesses to ensure the rational use and efficient operation of resources. For example, for computing-intensive business applications, the platform will preferentially allocate more computing resources to ensure their running efficiency; for business with large storage requirements, sufficient storage space will be provided, and data will be safely stored and backed up.

[0117] In some specific embodiments, the business basic service platform will use the application management function of the public resource encapsulation model to manage the upper-layer business applications throughout their life cycle. This includes application deployment, monitoring, maintenance and updating operations. The platform will select the appropriate deployment method, such as containerized deployment or virtual machine deployment, according to the type and needs of the application. During the application running process, the performance indicators of the application are monitored in real time, such as response time, throughput, resource utilization, etc. Once the application has abnormal or performance degradation, timely adjustment and optimization are made. At the same time, the platform will regularly update the application to fix vulnerabilities, improve functionality and performance.

[0118] In some specific embodiments, the business basic service platform will record detailed information during the running of business applications by means of the application log service of the public resource encapsulation model. These log information is of great value for troubleshooting, performance analysis and security audit. The platform will classify and store logs and provide powerful query and analysis functions. Administrators can easily view and analyze application logs through the management console, quickly locate problems and take appropriate measures. For example, when an application error occurs, administrators can quickly find the root cause of the problem and fix it by viewing error information and stack traces in the logs.

[0119] In some specific embodiments, the business basic service platform will utilize the application cluster scheduling function of the public resource encapsulation model to reasonably allocate cluster resources according to the load and resource requirements of business applications. When the load of a certain business application is too high, the platform will automatically distribute part of the request to other idle nodes to achieve load balancing. At the same time, the platform will reasonably allocate and schedule resources according to the priority and importance of the application to ensure the normal operation of critical business. For example, for high-guarantee-level business applications, the platform will preferentially allocate more resources to ensure high availability and low latency.

[0120] In some specific embodiments, the business basic service platform will utilize the application warehouse function of the public resource encapsulation model to store and manage various business application programs. The platform will control and manage application versions to facilitate application distribution and sharing. Developers can upload their own developed applications to the application warehouse for use and testing by others. At the same time, the platform will conduct security checks and audits to ensure the security and reliability of the application.

[0121] In some specific embodiments, the business basic service platform will utilize the general authentication service of the public resource encapsulation model to verify and authorize the identity of users. Only authenticated users can access business applications and platform resources. The platform will use multiple authentication methods such as username and password authentication, digital certificate authentication, etc. to ensure the authenticity and security of user identity. At the same time, the platform will authorize user operations according to user roles and permissions to ensure that users can only access resources and functions they are authorized to access. For example, ordinary users can only access and operate their own business data, while administrators can configure and manage the entire platform.

[0122] It should be noted that through the above series of construction work, the business basic service platform can provide a stable, efficient, secure and functionally rich basic support environment for upper-layer business applications, thereby promoting the smooth development and development of various business applications of the power system cloud platform.

[0123] In the embodiments of the present application, the business basic service platform is used for uniformly managing public functions of each advanced application, and the public functions include model splicing, graphic interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management and permission service.

[0124] In the embodiments of the present application, the business basic service platform is constructed based on the public resource encapsulation model, and the business basic service platform includes:

[0125] A preset business basic service optimization strategy set, the business basic service optimization strategy set including several optimization strategies for different public resource service levels;

[0126] According to a platform public resource service level result obtained based on the public resource encapsulation model, an adaptive optimization strategy is selected from the business basic service optimization strategy set;

[0127] The selected optimization strategy is parameterized configured, and the business basic service platform for optimizing and adjusting basic public resource service requirements is constructed in combination with public resource service indexes and scores in the public resource encapsulation model.

[0128] Specifically, the business basic service platform is constructed based on the encapsulation model, and a preset optimization strategy set A group of optimization strategies for different service levels are defined:

[0129] ①The high-guarantee-level strategy is automatic expansion, dual-active deployment, real-time full-quantity log collection and high-frequency monitoring.

[0130] ②The standard-level strategy is dynamic load balancing, on-demand expansion, log sampling and timing backup.

[0131] ③The energy-saving-level strategy is low-power mode, batch processing scheduling, log degradation and resource recycling.

[0132] Further, the strategy selection and parameterized configuration are performed according to Level(G) to select a corresponding strategy.

[0133] The strategy mapping function is designed as follows:

[0134] s * =StrategyMap(Level)

[0135] Wherein, s * is the selected optimization strategy, such as “automatic expansion”. The strategy is parameterized configured to adapt to the current platform state.

[0136] Further, the parameterized configuration formula is designed as follows:

[0137] θ j =α j ·G+β j

[0138] where θ j is the adjustable parameter of the strategy, such as the capacity expansion trigger threshold, log sampling frequency, etc. α j and β j are linear coefficients, which are fitted by historical data.

[0139] For example, if G = 0.85, α = -2, and β = 2, then θ = -2 x 0.85 + 2 = 0.3, indicating that capacity expansion is triggered when resource utilization exceeds 30%.

[0140] It should be noted that the parameterized business basic service platform is denoted as

[0141] It should be further noted that StrategyMap can be a Level output by the public resource packaging model, and is an arbitrary function for selecting the most suitable optimization strategy from a preset set of optimization strategies.

[0142] It should be further noted that the construction of the business basic service platform based on the public resource packaging model plays a crucial role in the performance improvement and business development of the subsequent power system cloud platform. The completed business basic service platform can flexibly adjust and optimize its own operation strategy according to different business demands and public resource service levels, thereby better meeting the diversified needs of upper-layer business applications.

[0143] S104, calling the business basic service platform through a preset platform service function, generating an optimal platform service configuration, and triggering the corresponding lower-layer execution function to implement platform configuration operations, wherein:

[0144] It should be noted that when the business basic service platform is obtained, it can be called by means of a preset platform service function. The preset platform service function is designed according to the business needs and functional characteristics of the power system cloud platform, and it can flexibly call the functions of the business basic service platform according to different business scenarios and requirements.

[0145] In some specific embodiments, the platform service function can generate different platform service configuration schemes according to the needs of different business scenarios. For example, for a power monitoring business with extremely high real-time requirements, the platform service function will call the fast response function of the business basic service platform, and preferentially allocate high-priority computing resources and network bandwidth to ensure that monitoring data can be transmitted and processed in a timely and accurate manner. At the same time, the function will dynamically adjust the service configuration according to the current state and resource usage of the business basic service platform to achieve optimal performance and resource utilization.

[0146] In some embodiments, after generating the platform service configuration scheme, the platform service function triggers the corresponding lower layer execution function to implement the platform configuration operation. The lower layer execution function is responsible for converting the configuration scheme into specific system instructions and sending them to the corresponding underlying resources and components. These instructions include but are not limited to resource allocation, task scheduling, service start and stop, etc. For example, when the platform service function decides to allocate more computing resources for a certain business application, the lower layer execution function will send instructions to the computing resource management module to increase the computing resource quota of the application.

[0147] In embodiments of the present application, the business basic service platform is called by the preset platform service function, including:

[0148] Different platform service policy rules under the combination of preset device health status and environmental factors are preset;

[0149] The platform service function selects the corresponding rule from the preset platform service policy rule according to the current obtained device health status and environmental factors;

[0150] The selected rule is passed to the business basic service platform as an input condition;

[0151] The different platform service behaviors are comprehensively evaluated to obtain the platform service configuration with the optimal efficiency and reliability ratio under the current state.

[0152] In embodiments of the present application, triggering the corresponding lower layer execution function to implement the platform configuration operation includes:

[0153] When the optimal platform service configuration is determined, the platform service function triggers the corresponding lower layer execution function;

[0154] The lower layer execution function generates specific platform configuration instructions according to the optimal platform service configuration;

[0155] The platform configuration instructions include but are not limited to the setting and adjustment of application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service;

[0156] The platform configuration instructions are sent to the corresponding execution device or personnel to implement the specific platform configuration operation.

[0157] Specifically, the platform service function calls the business platform, and presets the platform service policy rule library A set of rules based on device health status H and environmental factors E are defined:

[0158] If H = normal and E = normal, the current configuration is maintained.

[0159] If H = warning and E = high temperature, start the heat dissipation plan and increase the monitoring frequency.

[0160] If H = failure and E = heavy rain, switch to the backup line and enable the disaster recovery cluster.

[0161] Furthermore, the design rule activation function is designed:

[0162] R * = MatchRule(H, E)

[0163] where H is the current device health status, taking values "normal", "warning" or "failure". E is the current environment state, such as "normal", "high temperature", "heavy rain", etc. R * is the matched rule, which is passed as input to the business base service platform

[0164] Furthermore, the optimal configuration is comprehensively evaluated, and in a multi-objective optimization is run to find the optimal platform service configuration. The efficiency and reliability objective functions can be designed as follows:

[0165]

[0166] where C is the candidate configuration scheme, such as the number of replicas, QoS level, scheduling strategy, etc. η(C) is the efficiency indicator, defined as the throughput divided by the resource consumption, and the higher the value, the more efficient the resource utilization. is the reliability indicator, such as MTBF or failure recovery success rate, and the higher the value, the more stable the system. γ is the reliability weight coefficient, used to adjust the priority of efficiency and reliability, for example, γ = 2 means more emphasis on reliability.

[0167] For example, compare two configuration schemes and select the one with the highest comprehensive score as the optimal configuration C * .

[0168] Furthermore, the platform configuration operation is executed, triggering the lower-level execution function when the optimal configuration C * is determined. The platform service function triggers the lower-level execution function. Instruction generation can use the following function:

[0169] I = GenCommand(C * )

[0170] where I is the generated specific platform configuration instruction, which can include, for example: start or stop a certain application instance. Adjust the log level to DEBUG. Increase the number of Kubernetes Pod replicas to 5. Switch object storage to cold storage mode to reduce costs. Enable two-factor authentication to enhance security.

[0171] Further, the instruction I is sent to a corresponding execution unit, which can include a container orchestration system, a log and monitoring system, a storage gateway or an authentication service, and a key operation needs to be pushed to an operation and maintenance personnel terminal for manual confirmation.

[0172] In the embodiment of the application, platform configuration operation execution result data is acquired;

[0173] The platform configuration operation execution result data is fed back to the public resource packaging model and the business basic service platform for parameter iterative updating;

[0174] Until the iteration condition is met.

[0175] In the embodiment of the application, the iteration condition includes:

[0176] When the feedback iteration number of the platform configuration operation execution result data reaches the preset maximum iteration number, and the parameter change rate of the public resource packaging model and the business basic service platform is less than the preset threshold value;

[0177] Or the platform performance index reflected by the platform configuration operation execution result data exceeds the preset performance target value.

[0178] In summary, the application proposes a power system cloud platform design method, which effectively solves the problem of the influence of bottom component version change on upper application. By establishing a public resource packaging model, the change of the bottom component version is shielded, a unified interface is provided for the upper application, and the stability and reliability of the upper application when using the public resource service are ensured. At the same time, the business basic service platform uniformly manages the public functions of each senior application, realizes efficient integration and deployment of functions, and improves the operation efficiency and management level of the entire power system cloud platform. The power system cloud platform design of the application has significant innovation and practicality in the field of power system technology, and can provide strong guarantee for the stable operation and efficient management of the power system. It not only solves many problems in the prior art, but also provides a new idea and direction for the future development of the power system, and is expected to achieve good economic benefits and social benefits in practical application.

[0179] In one preferred embodiment, the specific operation of the iteration condition can be designed as follows in Embodiment 2:

[0180] The execution result feedback is acquired, the system continuously monitors the performance data after configuration execution, and a new service score Gnew is recalculated.

[0181] Further, the iteration termination condition is designed, and the convergence termination condition can be designed as follows:

[0182]

[0183] where IterCount is the current iteration number, starting from 1 and increasing. T max is the preset maximum iteration number, for example, 10 times. G (t) and G (t-1) are the service scores of the current and last iterations, respectively. ∈ is the parameter change rate threshold, for example, 0.01 (i.e., 1%), indicating that the model has tended to be stable.

[0184] Furthermore, a performance target termination condition can also be designed, which is specifically represented as follows:

[0185] Stop2: P actual ≥ P target

[0186] where P actual is the actual platform performance indicator achieved after the configuration is executed, such as request success rate, average delay, etc. P target is the preset performance target value, such as 99.9% availability.

[0187] It should be noted that as long as any of the above conditions is met, the system stops iteration and maintains the current configuration; otherwise, it returns to the first stage and re-optimizes based on new data.

[0188] In this embodiment, a power system cloud platform design system is also provided, which includes: Figure 2 A data acquisition and processing module is configured to acquire device data and environment data of a target power system and pre-process the device data and environment data.

[0189] A first model establishment module is configured to establish a common resource packaging model based on the pre-processed device data and environment data.

[0190] The common resource packaging model is configured to shield the influence of bottom component version changes on upper layer applications, and provide a unified interface for the upper layer applications to provide application management, application logs, application cluster scheduling, application warehouse, management console, development test environment, object storage service, and general authentication service.

[0191] A platform establishment module is configured to construct a business basic service platform based on the common resource packaging model.

[0192] The business basic service platform is configured to uniformly manage public functions of each high-level application, and the public functions include model splicing, graphical interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management, and permission service.

[0193]

[0194] ​The configuration module is used to call the business basic service platform through preset platform service functions, generate the optimal platform service configuration, and trigger the corresponding lower-level execution function to perform platform configuration operations.

[0195] The above-mentioned unit modules can be embedded in the processor of the electronic device in hardware form or independent of it, or they can be stored in the memory of the electronic device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0196] This embodiment also provides an electronic device, which can be a terminal, and its internal structure diagram can be as follows: Figure 2 As shown, the electronic device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores 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 medium. 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. When the computer program is executed by the processor, it implements a power system cloud platform design method. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0197] This embodiment also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, it performs the following steps:

[0198] Acquire equipment and environmental data of the target power system, and preprocess the equipment and environmental data.

[0199] A public resource encapsulation model is established based on the preprocessed equipment data and environmental data.

[0200] The public resource encapsulation model is used to shield the impact of underlying component version changes on upper-layer applications, and provides a unified interface for upper-layer applications to provide application management, application logs, application cluster scheduling, application repository, management console, development and testing environment, object storage service and general authentication service;

[0201] A business infrastructure service platform is built based on a public resource encapsulation model.

[0202] The business base service platform is used for uniformly managing public functions of various high-level applications, and the public functions include model splicing, graphic interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management and permission service.

[0203] The business base service platform is called through a preset platform service function, an optimal platform service configuration is generated, and a corresponding lower layer execution function is triggered to implement a platform configuration operation.

[0204] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and all modifications and replacements should be covered in the scope of the claims of the present application.

[0205] Although the preferred embodiments of the present application have been described, those skilled in the art can make further changes and modifications to the embodiments once they know the basic inventive concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0206] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A design method for a power system cloud platform, characterized in that, The method comprises the following steps: Obtain device data and environment data of a target power system, and preprocess the device data and environment data; Establish a common resource encapsulation model based on the preprocessed device data and environment data; The common resource encapsulation model is used to shield the influence of bottom component version changes on upper applications, and provides a unified interface for the upper applications to provide application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service; Construct a business basic service platform based on the common resource encapsulation model; The business basic service platform is used to uniformly manage public functions of each high-level application, and the public functions include model splicing, graphic interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management and permission service; The business basic service platform is called through a preset platform service function, an optimal platform service configuration is generated, and a corresponding lower execution function is triggered to implement platform configuration operation.

2. The power system cloud platform design method of claim 1, wherein, Further comprising: Obtain platform configuration operation execution result data; Feed back the platform configuration operation execution result data to the common resource encapsulation model and the business basic service platform for parameter iterative updating; Until the iteration condition is met.

3. The power system cloud platform design method of claim 2, wherein, The common resource encapsulation model is established based on the preprocessed device data and environment data, which comprises the following steps: A set of common resource service indexes is preset, and the set of common resource service indexes comprises a plurality of common resource service indexes for evaluating the cloud platform of the target power system; Select common resource service indexes based on the preprocessed device data and environment data; The selected common resource service indexes are represented by a scoring formula, and the common resource service score of the cloud platform of the target power system is calculated according to the scoring formula; According to the common resource service score, the common resource service demand of the platform is classified to form a common resource encapsulation model.

4. The power system cloud platform design method of claim 3, wherein, The business basic service platform is constructed based on the common resource encapsulation model, which comprises the following steps: A set of business basic service optimization strategies is preset, and the set of business basic service optimization strategies comprises a plurality of optimization strategies for different common resource service classifications; According to the platform common resource service classification result obtained from the common resource encapsulation model, an adaptive optimization strategy is selected from the set of business basic service optimization strategies; The selected optimization strategy is parameterized configured, and the business basic service platform for optimizing and adjusting the basic common resource service demand is constructed in combination with the common resource service indexes and scores in the common resource encapsulation model.

5. The power system cloud platform design method of claim 4, wherein, The business basic service platform is called through a preset platform service function, which comprises the following steps: Different platform service strategy rules under different combinations of device health status and environmental factors are preset; The platform service function selects corresponding rules from the preset platform service strategy rules according to the currently obtained device health status and environmental factors; The selected rules are input conditions and are passed to the business basic service platform; The different platform service behaviors are comprehensively evaluated to obtain the platform service configuration with the optimal efficiency and reliability ratio under the current state.

6. The power system cloud platform design method of claim 5, wherein, The corresponding lower execution function is triggered to implement platform configuration operation, which comprises the following steps: When the optimal platform service configuration is determined, the platform service function triggers the corresponding lower layer execution function; The lower layer execution function generates specific platform configuration instructions according to the optimal platform service configuration; The platform configuration instructions include but are not limited to the setting and adjustment of application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service; The platform configuration instructions are sent to the corresponding execution equipment or personnel to implement specific platform configuration operations.

7. The power system cloud platform design method of claim 6, wherein, The iteration conditions include: When the feedback iteration number of platform configuration operation execution result data reaches the preset maximum iteration number, and the parameter change rate of the common resource packaging model and the business basic service platform is less than the preset threshold value; Or the platform performance index reflected by the platform configuration operation execution result data exceeds the preset performance target value.

8. A power system cloud platform design system, applying the method according to any one of claims 1 to 7, characterized in that, The data acquisition and processing module is configured to acquire device data and environment data of a target power system and pre-process the device data and environment data; The first model establishing module is configured to establish a common resource packaging model according to the pre-processed device data and environment data; The common resource packaging model is used to shield the influence of bottom layer component version change on upper layer application, and provides a unified interface to provide application management, application log, application cluster scheduling, application warehouse, management console, development test environment, object storage service and general authentication service for the upper layer application; The platform establishing module is configured to construct a business basic service platform based on the common resource packaging model; The business basic service platform is used to uniformly manage the public functions of each high-level application, and the public functions include model splicing, graphic interaction, picture calling, notification sending and receiving, alarm event, geographic information, CASE management and permission service; The platform operation module is configured to call the business basic service platform through a preset platform service function, generate an optimal platform service configuration, and trigger the corresponding lower layer execution function to implement platform configuration operations. The processor executes the computer program to realize the steps of the power system cloud platform design method in any one of claims 1-7. 9.An electronic device comprising a memory and a processor, the memory storing a computer program, wherein, The computer program is executed by the processor to realize the steps of the power system cloud platform design method in any one of claims 1-7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, ​

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