Steam turbine and adjusting system network source coordination data information management system thereof

Abstract

The invention discloses a steam turbine and an adjusting system network source coordination data information management system thereof, which comprises a test information module, a model and parameter information module, a modeling report information module and an information report generation module, wherein the test information module acquires test data information of a power generation enterprise in a turbine and its adjusting system network source coordination network-related test and filters the test data information; the model and parameter information module adopts a swarm intelligence algorithm to obtain important parameters of the identified steam turbine model, the adjustment system model and the execution mechanism model; the information report generation module obtains power generation enterprise storage information and fills a report template with the information; and the modeling report information module realizes management of parameter modeling reports of the steam turbine and the adjusting system thereof. According to the invention, the working efficiency of electric power departments and electric power workers is effectively improved, and the grid-related supervision and management support level of the grid-connected unit is improved.

Description

Technical Field

[0001] The present invention relates to the field of power data information management systems, and more particularly to a steam turbine and its regulating system network-source coordination data information management system. Background Art

[0002] Under the new situation where the proportion of new energy is increasing year by year and conventional thermal power units are widely participating in deep peak shaving, the power system has put forward higher requirements for the network-source coordination performance of steam turbines and their regulating systems. In the aspects of parameter modeling experiments and network-source coordination technology supervision of steam turbines and their regulating systems, it is necessary to frequently store and retrieve data information such as test data, test progress, and test modeling reports in real time. For the models of steam turbines and their regulating systems, it is necessary to be able to perform parameter identification, store historical model parameters and updated model parameters, and generate periodic reports according to requirements. This is of great significance for mastering the information of grid-connected tests and improving the support level of grid-connected unit network-source supervision and management.

[0003] At present, for the retrieval of network-source coordination data information of steam turbines and their regulating systems, an artificial and decentralized retrieval mode is still adopted, lacking the strong support of a comprehensive, accurate and efficient data information system. For the identification of model parameters, an artificial comparison method is still used, and parameters are set by comparing simulation curves with actual curves, resulting in poor identification accuracy. Summary of the Invention

[0004] The purpose of the present invention is to establish a network-source coordination data information management system for steam turbines and their regulating systems to standardize the daily information retrieval mode of network-source coordination work of steam turbines and their regulating systems, strengthen the storage and query of network-source information on the source side, and provide data support for network-source coordination technology supervision.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A network-source coordination data information management system for a steam turbine and its regulating system, comprising a test information module and a model and parameter information module, wherein:

[0007] The test information module acquires the test data information of each power generation enterprise in the network-source coordination grid-connected test of the steam turbine and its regulating system, and filters the test measured data based on the sampling rate in the grid-connected test;

[0008] The model and parameter information module uses a swarm intelligence algorithm to obtain the important parameters of the identified steam turbine model, governing system model, and actuator model; for each grid-connected test, the model and parameter information module identifies the model parameters once. The swarm intelligence algorithm selects the most recent model parameter value from the historical model parameters as the initial value, and sets the target optimization function, the number of iterative updates of the parameters, and the boundary values. When the target optimization function is satisfied or the number of iterations is reached, the identification stops and the corresponding model parameter values are generated.

[0009] Furthermore, the filtering algorithm of the test information module is to define the sliding window length n of the filtered data, and the determination method of n is as follows:

[0010]

[0011] In the formula: T is the sampling time, in seconds;

[0012] Sum and average the data before and after the data at position m The number of data to get the filtered value of the data at position m. When the number of data before and after the data at position m is less than , then process according to the actual data length. After the data at position m is filtered, the sliding window moves to filter the data at position m + 1.

[0013] Furthermore, in the model and parameter information module, the set target optimization function S i is as follows:

[0014]

[0015] In the model and parameter information module, the iterative update method of the parameters is as follows:

[0016] x i = x i-1 + α i ·b i ,

[0017] In the formula: y i is the actual value of the test data; is the output value of the model;

[0018] x i is the current parameter value; x i-1 is the parameter value selected in the previous time. When initializing the identification, select the model parameters obtained from the most recent test in the historical model library as the previous parameter value;

[0019] b i is a random number between -1 and 1 generated each time; α iis the impact factor for each time, with a value range between 0 and 1; among them, α i changes correspondingly according to the previous S i value. When the current value of S i is smaller, the value of α i also shrinks correspondingly. The value of α i is determined by the method of α i = S i / S1;

[0020] For the method of parameter selection for each update, it is to compare the objective function. If S i is greater than S i-1 , then the selected x i is the previous parameter x i-1 ; if S i is less than S i-1 , then the selected x i is the x i after this iteration update; when the parameter value exceeds the upper and lower limits, the upper and lower limits are taken as the corresponding parameter values.

[0021] Furthermore, it also includes an information report generation module. The information report generation module obtains the storage information of each power generation enterprise and fills the storage information of each power generation enterprise into a pre-configured report template.

[0022] Furthermore, it also includes a modeling report information module. The modeling report information module manages the parameter modeling report of the steam turbine and its regulating system.

[0023] The system of the present invention establishes four modules: test information, modeling report information, model and parameter information, and information report generation, realizes the storage and retrieval of network-related test information, modeling report information, and model parameters of the steam turbine and its regulating system, and at the same time can realize the filtering of test data and the identification of model parameters. In addition, reports can be generated periodically according to requirements for power workers to consult and report.

[0024] The present invention can realize the real-time sharing of network-source coordination information of the steam turbine and its regulating system, can help the power departments and power workers to realize the collaborative processing and efficient circulation of data information, timely master the test development status and modeling report situation, and is also convenient for querying relevant historical data information. At the same time, it can complete the filtering of test data, the identification of model parameters, and generate the required reports. It effectively improves the work efficiency of power departments and power workers and enhances the support level of network-related supervision and management of grid-connected units. Brief Description of the Drawings

[0025] Figure 1 is the schematic diagram of the system of the embodiment of the present invention.

[0026] Figure 2 This is the distributed storage architecture diagram adopted in the embodiments of the present invention. Detailed implementation manners

[0027] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0028] As Figure 1 shown, this embodiment discloses a steam turbine and its grid-source coordination data information management system for the regulation system, including a test information module, a modeling report information module, a model and parameter information module, and an information report generation module. The access of the four modules uses Django URL routing settings to establish their corresponding path requests. The retrieval, export, generation and other functions in the four modules are implemented by establishing corresponding API interfaces and standardizing and encapsulating them into communication interfaces. The API interfaces of each functional module are standardized and encapsulated in a Restful style. Each module obtains the required data information through each communication interface. Specifically, when establishing multiple API interfaces, all are implemented in the form of functions. Each API interface includes an interface ID, an interface function, input parameters and output parameters. By obtaining the parameter information of each functional module and standardizing and encapsulating the API interface according to the parameter information, a communication interface is formed. Among them:

[0029] (1) The test information module obtains the test data information of each power generation enterprise in the grid-connected test of the steam turbine and its regulation system, including basic information such as plant name, unit name, unit capacity, and generator terminal bus. In addition, it also includes the completion degree of the dynamic and static tests of the grid-connected test and the test data after the dynamic and static tests are completed. And the test information module filters the test measured data based on the sampling rate in the dynamic and static grid-connected tests, suppresses the interference information generated during the test, and can output the filtered test data and draw a data curve.

[0030] The filtering algorithm when the test information module performs filtering is to define the sliding window length n of the filtered data. The determination method of n is as follows:

[0031]

[0032] In the formula: T is the sampling time, and the unit is seconds.

[0033] Sum and average the data before and after the data at position m The number of data, and the obtained average value is the filtered value of the data at position m. When the number of data before and after the data at position m is less than , it is processed according to the actual data length. After the data at position m is filtered, the sliding window moves to filter the data at position m + 1.

[0034] (2) The model and parameter information module uses swarm intelligence algorithms to obtain the important parameters of the identified steam turbine model, governing system model, and actuator model. The important parameters of the steam turbine model include the high-pressure steam chamber volume time constant, the natural overshoot coefficient of the high-pressure cylinder power, and the reheater volume time constant; the important parameters of the governing system model include the actuator PID parameters and the feedforward controller parameters; the important parameters of the actuator model include the opening time constant and closing time constant of the high-pressure control valve.

[0035] Every time a grid-connected test is conducted, the model and parameter information module uses swarm intelligence algorithms. It identifies the important parameters of the actuator model using static test data, the important parameters of the steam turbine model using data under the dynamic test valve position mode, and the important parameters of the governing system model using data under the dynamic test coordination mode, and updates the important parameters of the latest model. At the same time, the model and parameter information module stores the important parameters of the historical model, selects the most recent model important parameter value in the historical model parameters as the initial value through the swarm intelligence algorithm, and sets the target optimization function, the iterative update times and boundary values of the important parameters. It compares and analyzes the updated model parameter values with the historical model parameters in the previous test. When the target optimization function or the number of iterations is satisfied, the identification is stopped, and the corresponding model important parameter values are generated, thereby reflecting the change trend and amplitude of the model parameter values.

[0036] In the model and parameter information module, the set target optimization function S

[0037] is as shown in the following formula: i As shown below:

[0038]

[0039] In the model and parameter information module, the iterative update method of the important parameters is as shown in the following formula:

[0040] x i = x i-1 + α i ·b i ,

[0041] where: y i is the actual value of the test data; is the output value of the model;

[0042] x i is the current important parameter value; x i-1 is the important parameter value selected in the previous time. When initially identifying, the important parameter of the model obtained from the most recent test in the historical model library is selected as the previous important parameter value;

[0043] b i is a random number generated between -1 and 1 each time; αi is the influence factor for each time, and its value range is between 0 and 1; among them, α i changes correspondingly according to the previous S i value. When the current value of S i is smaller, the value of α i also shrinks correspondingly. The value of α i is determined by the method of α i = S i / S1;

[0044] For the method of selecting important parameters updated each time, it is to compare the objective function. If S i is greater than S i-1 , then the selected x i is the previous important parameter x i-1 ; if S i is less than S i-1 , then the selected x i is the x i after the current iteration update; when the important parameter value exceeds the upper and lower limits, the upper and lower limits are taken as the corresponding important parameter values.

[0045] (3) The information report generation module obtains the storage information of each power generation enterprise, including test data information, modeling report information, and model and parameter information, and fills the storage information of each power generation enterprise into a pre-configured report template. This information report generation module can add, delete, and select the required data information sequence according to the needs of power workers, and set it to generate periodic reports and export them on a weekly, monthly, or quarterly basis.

[0046] (4) The modeling report information module realizes the information management of the parameter modeling report of the steam turbine and its regulating system, and is used to obtain the modeling report information of each power generation enterprise, including report writing information, review information, report name, completion unit, etc. The modeling reports of each power generation enterprise are uniformly distributed and stored, and the issue date of the report is recorded. Because tests need to be carried out again and corresponding reports need to be issued every five years, after the report is issued, a reminder to issue a new report will be given when five years are up. When the modeling report of a power generation enterprise is updated, the update date will be recorded, and the new modeling report will be stored.

[0047] The modeling report information module is automatically generated according to the different unit numbers and report version numbers of each power generation enterprise. The report number consists of three parts. The first part is the name of the power generation enterprise, which is composed of the capitalized first pinyin letters of the power generation enterprise's abbreviation. The second part is the unit number, which is composed of Arabic numerals. The third part is the version number of the modeling report, which is composed of the capital letter V plus the update times of the report.

[0048] The above four modules all have the functions of retrieval and query, and can browse the relevant information they need. At the same time, they can make remarks on the problematic data information for the staff to modify in the information input device.

[0049] The steam turbine and its regulating system network-source coordination data information management system described in this embodiment are arranged in each sharded storage database in a distributed storage manner, and a distributed storage cluster is constructed by multiple sharded storage databases. The external client accesses the distributed storage cluster through the server side, and the server side includes an application server, a Web server, and a DNS server.

[0050] Specifically, the client refers to the mobile phone side or the computer side, which is connected to the DNS server through a wireless network, facilitating the client to query relevant information anytime and anywhere.

[0051] The DNS server is connected to the Web server through Ethernet. It is a dedicated server for resolving domain names and obtaining corresponding IP addresses, and also has a load balancing function to distribute client requests to multiple Web servers.

[0052] The Web server is a dedicated server for processing protocol requests and returning the target content. After receiving the client request, it provides the static content required by the client through the HTTP or HTTPS protocol. The Web server is connected to the application server and hands over the complex computing business logic to the application server for processing.

[0053] The application server is a dedicated server for business logic processing and data access. The application program server mainly delivers the dynamic content required by the client, including functions such as the identification operation of model parameters and report generation. At the same time, it is responsible for processing the data in the distributed storage cluster according to the client request and returning the processed data results. The application server is connected to the distributed storage cluster and has an automatic data balancing function, which can automatically monitor the storage capacity of each sharded database. When there is an unbalanced storage capacity state, it automatically gives instructions for data relocation.

[0054] In the distributed storage cluster, each sharded storage database is composed of a database server. The sharded storage database stores data in a replica set manner, mainly including a primary node, two secondary nodes, and an arbiter node. The primary node is used for data reading and writing operations, the secondary nodes are only responsible for data backup and are completely synchronized with the data of the primary node, while the arbiter node does not store data and is only responsible for monitoring the status of other nodes in the replica set. When the primary node fails, the arbiter node can vote to select a new primary node to ensure data security.

[0055] In addition, the sharded storage database in the distributed storage cluster is also connected to an information entry device, through which database operations can be directly performed to enter important data information, including adding and modifying data information.

[0056] The preferred embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. The embodiments described in the present invention are only descriptions of the preferred embodiments of the present invention, and do not limit the concept and scope of the present invention. Among the various specific technical features described in the above specific embodiments, they can be combined in any suitable manner without contradiction. As long as such a combination does not violate the idea of the present invention, it should also be regarded as the content disclosed in this disclosure. To avoid unnecessary repetition, the present invention will not separately describe various possible combination methods.

[0057] The present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention and without departing from the design idea of the present invention, various variations and improvements made by those skilled in the art to the technical solutions of the present invention should all fall within the protection scope of the present invention. The technical content claimed by the present invention has been fully recorded in the claims.

Claims

1. A steam turbine and its regulating system network source coordination data information management system, characterized in that: It includes test information module, model and parameter information module, among which: The test information module obtains the test data information of each power generation enterprise in the grid-related test of the steam turbine and its regulating system network source coordination, and filters the test measured data based on the sampling rate in the grid-related test; The model and parameter information module adopts a swarm intelligence algorithm to obtain the important parameters of the identified steam turbine model, regulation system model, and actuator model; each time a grid-related test is conducted, the model parameters are identified once by the model and parameter information module, and the most recent model parameter value in the historical model parameters is selected as the initial value through the swarm intelligence algorithm, and the target optimization function, the number of iterative updates of the parameters, and the boundary value are set. When the target optimization function or the number of iterations is met, the identification is stopped and the corresponding model parameter values ​​are generated.

2. A steam turbine and its regulating system network source coordination data information management system according to claim 1, characterized in that: The filtering algorithm of the test information module is to define the length n of the sliding window of the filtering data, and the determination method of n is as follows: Where: T is the sampling time, in seconds; The data at position m before and after The data of the number are accumulated and averaged, and the average is the filtered value of the data at position m. When the number of data before and after the position m is less than When , it is processed according to the actual data length. When the data at position m is filtered, the sliding window moves to filter the data at position m+1.

3. A steam turbine and its regulating system network source coordination data information management system according to claim 1, characterized in that: In the model and parameter information module, the target optimization function S is set i As shown below: In the model and parameter information module, the iterative update method of the parameters is shown in the following formula: x i =x i-1 +a i ·b i , Where: y i is the actual value of the test data; is the output value of the model; x i is the parameter value for this time; x i-1 The parameter value obtained in the last selection. When the initial identification is performed, the model parameters obtained in the latest test in the historical model library are selected as the last parameter value; b i is a random number between -1 and 1 generated each time; α i is the impact factor for each time, ranging from 0 to 1; i According to the last S i The value changes accordingly, S i The smaller the current value, the i The value of α is also reduced accordingly. i The value of α i =S i / S1 method is used to determine; The method used for parameter selection for each update is to compare the objective function. If S i Greater than S i-1 , then the selected x i is the last parameter x i-1 If S i Less than S i-1 , then the selected x i is the updated x for this iteration i ; When the parameter value exceeds the upper and lower limits, the upper and lower limits are taken as the corresponding parameter value.

4. A steam turbine and its regulating system network source coordination data information management system according to claim 1, characterized in that: It also includes an information report generation module, which obtains the storage information of each power generation enterprise and fills the storage information of each power generation enterprise into a pre-configured report template.

5. A steam turbine and its regulating system network source coordination data information management system according to claim 1, characterized in that: It also includes a modeling report information module, which implements the management of the modeling report of the steam turbine and its regulating system parameters.

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