Abstract: The water supply network plays a very important role in urban production and life, so it is particularly necessary to ensure its normal operation. This paper will carry out corresponding analysis based on the dynamic hydraulic modeling data of the water supply network and its management, in order to promote the improvement of the operation quality of the urban water supply network and provide some useful references for peers.
1 Overview of dynamic simulation of water supply network
According to the operation characteristics of the water supply network, establishing a corresponding dynamic hydraulic model can not only achieve the purpose of optimal control, but also achieve the effect of scientific management. In the model, the water flow needs to be able to effectively reflect the flow state of the water flow in the real pipe network. In other words, the dynamic model needs to be able to effectively reflect a series of dynamic parameters in the real pipe network.
A reasonable dynamic model of the water supply network has the following functions: effective auxiliary prediction of the leakage of the pipeline network; effective simulation of the operation under the accident state, so as to facilitate the formulation and implementation of fault resolution measures; Predictive analysis of a series of abnormal conditions provides useful reference for scheduling and maintenance personnel; lays the foundation for subsequent optimization of water system operation; facilitates the construction of water quality models and plays an auxiliary role in the process of water quality analysis.
2 Data Analysis of Dynamic Hydraulic Modeling of Water Supply Network
2.1 Data types and sources of dynamic hydraulic modeling
Pipe network attribute data: For the water supply pipe network, its attribute data usually refers to measured values and data obtained from actual surveys. In most cases, such data can be accurately obtained with the help of GIS systems.
Pipe network operation monitoring data: This type of data mainly includes two parts, one is the pressure data of online monitoring, and the other is the flow data of online monitoring. In the process of establishing the hydraulic model, the SCADA system is usually used to realize the delay simulation of the pipe network, and it is also possible to intercept the representative data of certain days for model verification.
Measured data: In the specific modeling process, the measured data mainly includes three parts. One is to accurately measure the uncertain information in the pipeline network attributes on the spot, and the other is to measure the curve of the water pump (especially if the service life is relatively long). Long) to conduct on-site measurement, and the third is to conduct on-site measurement of the user's water consumption curve.
Derived data: The so-called derived data refers to a new type of data formed in the process of analyzing data. Although it is not a necessary part of modeling, it helps to mine the invisible information contained in the existing data to a certain extent. . For example, the burst pipe can be analyzed by using the data mining function, so as to improve the safety factor of the pipe network.
2.2 Data quality analysis of dynamic hydraulic modeling
2.2.1 Data quality evaluation criteria
During the modeling process, the relevant data quality should be effectively analyzed and controlled. The so-called data quality (DQI for short) refers to the characteristics that many data participating in dynamic modeling can meet the actual requirements of modeling.
Only when the data quality is known, can accurate predictions be made on the feasibility of modeling. For dynamic modeling data, its quality level is mainly reflected in the following points: accuracy, precision, uncertainty, inclusiveness, consistency, completeness, ease of use, availability, current situation, etc.
2.2.2 Data quality evaluation method——taking fuzzy comprehensive evaluation method as an example
In the process of adopting the fuzzy comprehensive evaluation method, the following evaluation indicators are involved:
1) Topological attributes, such as node coordinate position accuracy, etc.;
2) Node flow, such as water data accuracy, etc.;
3) Relevant data of the pumping station, such as the extent to which the pump curve conforms to reality;
4) Monitoring data, such as distribution density of monitoring points;
5) Other auxiliary information, such as ground elevation, etc. reflect the true degree.
When evaluating the above indicators, four different grades are divided into excellent, medium and poor: excellent means that the data quality is quite excellent, which can provide ideal data support for modeling work; good means that the data quality is slightly inferior; middle means that the data quality can be basically Meet the modeling needs; Poor refers to the extremely unsatisfactory data quality, unable to support the modeling work.
2.3 Data processing
After the appropriate pipeline network modeling data is selected, it needs to be standardized accordingly, that is, the data in the original form is processed to convert it into a standard form that can participate in actual modeling.
During the pipeline network modeling process, the key data requirements involved and their processing are as follows:
1) Establish and improve the topological structure of the pipe network, and accurately input relevant attribute information - pipe network topology, pipe section and node attributes, elevation data, etc.
2) Scientific allocation of node flow - user water consumption data and water consumption curve.
3) Build an effective pumping station model and check it - pump curves and pumping station operation records.
4) Carry out corresponding simulation calculations and checks—data records of monitoring points, etc.
Comprehensive management of dynamic hydraulic model data
3.1 Model data comprehensive management requirements analysis
3.1.1 Requirements for Data Integrity and Synchronization
Most of the data involved in the water supply system are measured values and field survey data. Therefore, such an efficient data management system should be sought, that is, no matter what type of linkage changes occur, they can be self-maintained with the help of internal functions provided by the system itself , so as to ensure the integrity and synchronization of a series of data.
In addition, in the formal management process, user permissions should be strictly set and managed to ensure the security of relevant data.
3.1.2 The need for convenient data use
In many calculations of the model, comprehensive calculations involving a large amount of data are usually required. Due to different sources and various formats, it is necessary to build a highly unified data management system to facilitate data use.
Not only that, but with the help of views or storage methods, it is possible to obtain purposeful query results based on the corresponding requirements of model computing for data, thus effectively enhancing the work efficiency of filtering model computing data to a certain extent.
3.2 Dynamic data management technology of water supply network - dynamic database of water supply network
The management of this database mainly involves the following points:
1) Data storage, that is, convert all data into data tables and store them;
2) Database connection, that is, the connection between databases, as well as the connection between databases and other systems; comprehensive/joint query, using the query method to collect the data and information that needs to be used, or based on the form of view and storage, for commonly used The query module is effectively saved for later calling;
3) Data update;
4) User management.
3.2.1 Database Design Principles
The principles of database design mainly include: the principle of practicality to meet user needs, the principle of data accuracy, the principle of security and stability, the principle of ease of operation, and the principle of scalability.
3.2.2 Establishment of database
The composition of the database mainly involves the following points:
1) Basic data of the pipe network, such as parameter table, user information table, pressure measuring point information table, water pump information table, water plant information table, valve information table, pressurized pump station information table, clean water pool information table;
2) Dynamic analog data, such as pressure gauges at pressure measuring points, water plant outlet pressure gauges, water pump data tables, water level tables in clear water tanks, pressurized pump station data tables, valve data tables, and cumulative flow data tables.
A data management system with dynamic characteristics can be obtained by coordinating, categorizing, and storing the above data.
There is a certain correlation and restriction between the data tables. This is because the data itself has a certain correlation. The common ones are between pipelines and nodes, between valves and nodes, and between nodes at both ends of the equipment.
When performing important actions such as deletion or editing, special attention should be paid to: when moving a node, the pipeline connected to the node should also change accordingly with the change of the node position; when determining the new coordinates of the node, it is necessary to The length of the pipe is modified; when the pipe segment is moved, the two nodes of the pipe segment will also be moved accordingly. In addition, many pipe segments that are connected to this pipe segment will also appear to a certain extent stretching effect.
With the help of the database management system, the relationship structure between data tables can be clearly and clearly observed, so as to accurately clarify the internal and external relationships between each data table.
Other components of the database:
1) View: For those data that need to be processed in a fixed format, they can be saved with the help of the view, and then extracted when necessary, thus effectively avoiding the occurrence of repeated operations;
2) Stored procedure: For those query modules with relatively high application frequency, it is necessary to compile the corresponding stored procedure to make it a unit with independent characteristics for users to call, so as to prevent multiple compilations of the code, and then Save a lot of manpower and time;
3) Trigger: usually suitable for cascading updates or cascading deletes.
3.2.3 Data Maintenance and Update
After building a new and complete database based on the existing model, the data in different time periods will have corresponding versions in future backups and updates. Apply the excellent update and backup functions of the database system management software itself, and can carry out corresponding backup operations based on the existing database.
During this process, the basic database can be shared, and each version of different time periods can be stored in the form of relatively independent update files. In this way, the version corresponding to any time period can be completely and effectively preserved, not only that , also achieved the goal of minimizing data redundancy, coupled with a relatively high degree of sharing, the file exists in the form of the smallest size, so that the amount of update tasks is relatively small.
When maintaining and updating the dynamic model data of the water supply network, the following tasks are mainly involved:
1) Update the topology and related data of the pipe network model;
2) Update the node flow;
3) Update the operation plan;
4) Update the pipeline roughness coefficient;
5) Update the pump characteristic curve;
6) Regularly check the model.
When the above data changes accordingly, the corresponding data in the database will also be effectively updated accordingly. When updating the pipe network topology and related attribute information, the relevant model data can be re-imported with the help of the interface of the database and the model itself.
For those data with a high degree of complexity and a lot of changes in form, it can be updated manually or in other ways by database managers with modification authority in light of specific changes.
Conclusion:
With the continuous expansion of the scale of the urban water supply network, its operation and management will face greater challenges. Therefore, it is particularly important to do a good job in the dynamic hydraulic modeling data analysis and comprehensive management of the water supply network.
It is believed that with the deepening of the research, the dynamic hydraulic model will achieve greater progress in function and accuracy, thereby providing greater help for the normal and efficient operation of the urban water supply network.