CN117194550A - Full-path data display method for multi-energy circulation - Google Patents

Abstract

The application discloses a full-path data display method of multi-energy circulation, which comprises the following steps: s1: acquiring position information of a user side and energy equipment, and constructing a spatial position model; s2: constructing an energy flow path according to the spatial position model and an energy flow mechanism; s3: acquiring historical user side and energy equipment monitoring data, performing energy flow reproduction according to an energy flow path, and analyzing through a neural network algorithm to acquire a path loss rule; s4: constructing a digital twin path display model according to the spatial position model, the energy source streaming path and the path loss rule; s5: and acquiring the demand information, and displaying full-path data of the energy circulation by the digital twin path display model according to the demand information. The application has the beneficial effects that: the method can obtain the actual energy loss condition according to the path loss rule, ensure the actual lamination of the displayed energy circulation full-path data, meanwhile, the real-time monitoring data is not required to be relied on, the simulation accuracy is improved, and meanwhile, the simulation instantaneity is improved.

Description

A full-path data display method for multi-energy circulation

Technical field

This application relates to the field of data visualization technology, and in particular to a full-path data display method for multi-energy circulation.

Background technique

Multi-energy system refers to a new energy system view formed by the coupling of multiple energy systems such as cold, heat, electricity, and gas in energy production, transmission, and use. Multi-energy systems make full use of the mutual aid and complementarity of different forms of energy to improve system economy, enhance system flexibility, increase system reliability, and tap system complementarity. Through the display of energy consumption, energy production and unit energy flow paths among various industries, we can understand the energy and energy resource use efficiency and energy structure among multiple industries. Based on this, we can guide the optimization and adjustment of energy allocation among multiple industries and establish a reasonable energy balance. structure.

Digital twins make full use of data such as physical models, sensor updates, and operation history to integrate multi-disciplinary, multi-physical quantities, multi-scale, and multi-probability simulation processes to complete mapping in virtual space to reflect the full life of the corresponding physical equipment. cyclic process. However, in related technologies, the statistics of multi-energy flow data are limited to the monitoring data of each energy point, and the losses in the actual flow of energy are ignored, resulting in discrepancies between the multi-energy flow situation simulated by the digital twin and the actual situation.

Chinese patent "A Data Visualization Interaction Method for Digital Twins of Multi-Energy Systems", Publication Number: CN113591173A, Publication Date: November 2, 2021, specifically disclosed including building a visualization model based on a digital twin of a multi-energy system and conducting Generate; display the generated visual model; users interact with the displayed visual model by clicking the mouse, display specific content based on the object of interest, and obtain different display content and effects. This solution builds a visual model through the topology and operating data of the multi-energy system, but its operating data is only based on the measurement results of the equipment and does not take into account the losses in the actual energy flow process.

Chinese patent "New energy multi-type data allocation method and system based on localized structure", publication number: CN115757569A, publication date: March 07, 2023, specifically discloses the data in the system that separates new energy power plants from each other through ETL technology After data extraction, data cleaning, in-database conversion, rule checking, and data loading, the data is stored in the corresponding data table according to the data collection terminal and data type, so that each data can be unified and can be called across systems; use the data display module Diversify the display and make it easy to expand. This solution also simply stores all the data and uses the data display module to display the data. It does not disclose how to make the full path data of multi-energy circulation fit the actual circulation situation.

Contents of the invention

This application aims at the problem that the data display of multi-energy flow in the existing technology is limited to monitoring data and cannot show the actual energy flow situation and loss. This application provides a full-path data display method of multi-energy flow, through the spatial position model, Energy flow path and path loss rules build a digital twin path display model, add path loss rules to the display model, and the path loss rules are obtained by simulating and reproducing the energy flow path, and the loss on this path is obtained through the historical energy flow path. , the path loss rules are obtained through statistical analysis, so that when simulating actual multi-energy flow, the actual energy loss can be obtained according to the path loss rules, ensuring that the full path data of energy flow displayed by the digital twin path display model is realistic, and there is no need to rely on real-time monitoring. Data can be used to improve simulation accuracy while improving real-time simulation and improving user perception.

In order to achieve the above technical objectives, a technical solution provided by this application is a full-path data display method for multi-energy circulation, which is characterized by: including the following steps: S1: Obtain the location information of the user terminal and energy equipment, and construct a space Location model; S2: Build an energy circulation path based on the spatial location model and energy circulation mechanism; S3: Obtain historical user terminal and energy equipment monitoring data, reproduce energy circulation according to the energy circulation path, and obtain path loss rules through neural network algorithm analysis ; S4: Construct a digital twin path display model based on the spatial location model, energy flow path and path loss rules; S5: Obtain demand information, and the digital twin path display model displays the full path data of energy flow based on the demand information.

Further, S2 includes: building an energy flow path with energy conversion rules based on the spatial location model and energy flow mechanism.

Further, S5 includes: S51: Obtain demand information, and determine the display demand based on the demand information. If the display demand is the optimal solution for displaying the energy flow path, execute S52; if the display demand is the feasible solution for displaying the energy flow path, execute S53; S52: The digital twin path display model calculates the optimal solution of the energy flow path according to the energy conversion rules and path loss rules, and displays the full path data of the optimal solution of the energy flow path; S53: The digital twin path display model calculates the optimal solution of the energy flow path based on the energy conversion rules and path loss. Rules calculate feasible solutions for energy flow paths and display the full path data of feasible solutions for all energy flow paths.

Further, S53 also includes: marking the optimal solution among the feasible solutions of the energy flow path.

Further, S53 includes: obtaining the number of paths for demand display, the digital twin path display model calculating feasible solutions for energy flow paths based on energy conversion rules and path loss rules, optimizing the feasible solutions for energy flow paths, and filtering the number of paths based on the optimal ranking. Feasible solution of the energy flow path, showing the full path data corresponding to the feasible solution of the energy flow path.

Further, S3 includes: obtaining historical user terminal and energy equipment monitoring data, reproducing energy flow according to the energy flow path, and obtaining path loss rules and energy equipment operation rules through neural network algorithm analysis.

Further, S4 includes: building a digital twin path display model based on the spatial location model, energy flow path, path loss rules and energy equipment operation rules.

Further, the energy equipment operation rules are correlation rules between energy equipment usage time and operating costs.

Furthermore, S5 also includes: setting the dynamic change time, obtaining demand information, and the digital twin path display model displays the full path data of energy flow within the dynamic time based on the demand information.

Further, S6: Obtain the actual user terminal and energy equipment monitoring data, build the full path data of actual energy flow, compare the full path data of actual energy flow with the displayed full path data of energy flow, calculate the feedback fluctuation value, and update the numbers. Twin path display model.

The beneficial effects of this application: construct a digital twin path display model through the spatial location model, energy flow path and path loss rules, add path loss rules to the display model, and the path loss rules are obtained by simulating and reproducing the energy flow path, and through historical energy The loss on this path is obtained from the circulation path, and the path loss rules are obtained through statistical analysis, so that when simulating actual multi-energy circulation, the actual energy loss can be obtained according to the path loss rules, ensuring that the energy circulation displayed by the digital twin path display model is complete. The path data is close to reality and does not need to rely on real-time monitoring data. This improves simulation accuracy while improving real-time simulation and improving user perception.

Description of the drawings

Figure 1 is a schematic flowchart of a full-path data display method for multi-energy circulation in this application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in conjunction with the drawings and examples. It should be understood that the specific implementation described here is only one of the best embodiments of the present application. The embodiments are only used to explain the present application and do not limit the scope of protection of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

As shown in Figure 1, as the first embodiment of the present application, a full-path data display method for multi-energy circulation is provided, including the following steps:

S1: Obtain the location information of the user terminal and energy equipment, and build a spatial location model;

S2: Build an energy flow path based on the spatial location model and energy flow mechanism;

S3: Obtain historical user terminal and energy equipment monitoring data, reproduce energy flow according to the energy flow path, and obtain path loss rules through neural network algorithm analysis;

S4: Build a digital twin path display model based on the spatial location model, energy flow path and path loss rules;

S5: Obtain demand information, and the digital twin path display model displays the full path data of energy flow based on the demand information.

In this embodiment, the energy flow mechanism is the conversion relationship between multiple energy sources. For example, electric energy and thermal energy can be converted into each other. The energy flow path between each energy device can be obtained based on the spatial position model and the energy flow mechanism. Historical user end and energy equipment monitoring data at least include user end energy reception data, energy equipment energy reception data and energy equipment energy output data. Energy flow is reproduced according to the energy flow path, path loss during the flow process is calculated, and path loss rules are obtained. At this time, a digital twin path display model is constructed through the spatial location model, energy flow path and path loss rules. When the user submits demand information, the digital twin path display model automatically generates the current demand energy flow path based on the user's geographical location information, and based on the path The loss rules calculate the energy flow loss on each path, generate path loss data, and display the full path data of energy flow based on the energy flow path of the current demand. This makes multi-energy flow more intuitive, and takes into account the path loss during the energy flow process, making the data displayed by the digital twin path display model more consistent with the actual situation. Real-time display of energy flow in actual situations requires monitoring equipment to continuously send monitoring data to the display platform. However, in a multi-energy situation, more monitoring equipment is inevitably involved. To receive data in real time and eliminate interfering data, a display platform server is required. A large amount of data is received and calculated at every moment, which will obviously put great computing pressure on the server of the display platform. Moreover, the delay caused by real-time data transmission will also bring delay to the path display, which is not conducive to the visual experience. The construction of a digital twin path display model is not only constructed through actual physics, geometry, and rule mechanisms, but also fits the actual energy At the same time, the display platform does not need to bear heavy computing pressure at all times, and there is no delay in data transmission. It can improve the viewing experience while meeting the user's demand for energy flow display.

In this embodiment, the neural network algorithm analysis in step S3 includes: using the spatial autocorrelation function and the correlation function as neurons respectively, using the positional relationship between the user terminal and the energy device as input, and using the spatial autocorrelation function neuron to output the user The spatial correlation degree between terminals and energy equipment, energy equipment and energy equipment, taking the spatial correlation degree and the energy flow process reproduced according to the energy flow path as input, the correlation function neuron outputs the correlation between energy loss and energy flow path , which is the path loss rule.

As the second embodiment of this application, the energy flow mechanism also includes the conversion ratio between multiple energy sources. The energy conversion ratios between different energy sources are bound to be different, and the energy conversion rules are constructed based on the energy conversion ratios. Step S2 includes: building an energy flow path with energy conversion rules based on the spatial location model and energy flow mechanism. Therefore, when obtaining demand information and displaying data on the entire energy flow path, the optimal solution of the energy flow path is calculated based on the energy conversion rules, and the optimal solution of the energy flow path is displayed. In this way, the actual situation of energy flow can be judged more intuitively, and the actual situation can be adjusted according to the digital twin path display model.

In this embodiment, step S5 includes:

S51: Obtain the demand information, and determine the display demand based on the demand information. If the display demand is the optimal solution for displaying the energy flow path, execute S52. If the display demand is the feasible solution for displaying the energy flow path, execute S53;

S52: The digital twin path display model calculates the optimal solution of the energy flow path based on the energy conversion rules and path loss rules, and displays the full path data of the optimal solution of the energy flow path;

S53: The digital twin path display model calculates feasible solutions for energy flow paths based on energy conversion rules and path loss rules, and displays the full path data of feasible solutions for all energy flow paths.

In this embodiment, the demand information at least includes demand energy data and display requirements. Based on the demand information, the user's display requirements for the energy path are judged, so that different calculations are performed, and the optimal solution or feasible solution is output corresponding to the display requirements, so that when the user only needs The optimal solution of energy flow path reduces the display of useless data, improves the clarity of data display, improves user perception, while reducing the difficulty of model simulation rendering and reducing computer load.

In this embodiment, step S53 also includes: marking the optimal solution among the feasible solutions of the energy flow path. In this way, the user can obtain the optimal solution of the energy flow path while viewing the feasible solution of the energy flow path. This reduces the display of useless data when the user only needs the optimal solution. However, when the user needs a feasible solution, it provides the user with a reference to enable the user to understand the energy flow path. The difference in feasible solution data for global energy flow paths is clearer.

In other embodiments, step S53 includes: obtaining the number of paths for demand display, the digital twin path display model calculating feasible solutions for the energy flow path according to the energy conversion rules and path loss rules, and optimizing the feasible solutions for the energy flow path, according to Preferably sort and screen the feasible solutions of the energy flow path by the number of paths, and display the full path data corresponding to the feasible solutions of the energy flow path. The displayed requirements include at least the optimal solution and feasible solution requirements and the number of paths displayed by the requirements. According to the energy conversion rules, the energy conversion situation between energy devices can be obtained, and the energy conversion loss rate can be calculated. According to the path loss rules, the energy transfer loss situation between energy equipment can be obtained, and the energy transfer loss rate can be calculated. Based on the energy conversion The minimum sum of the loss rate and the energy transfer loss rate is used as the objective function, and the cost in the user demand information is used as the constraint condition. Optimization calculations can be performed to obtain all feasible solutions that satisfy the constraint conditions. At this time, the corresponding value of each feasible solution is The sum of the energy conversion loss rate and the energy transfer loss rate is sorted from small to large, which is the preferred sorting. The feasible solutions of the energy flow path are screened according to the number of paths displayed according to the demand, and the full path data corresponding to the feasible solution of the energy flow path is displayed. When the user has a requirement for the number of paths displayed, the corresponding number of optimal solutions among the feasible solutions will be displayed to the user.

As the third embodiment of the present application, step S3 includes: obtaining historical user end and energy equipment monitoring data, reproducing energy flow according to the energy flow path, and obtaining path loss rules and energy equipment operation rules through neural network algorithm analysis; step S4 Including: building a digital twin path display model based on the spatial location model, energy flow path, path loss rules and energy equipment operation rules.

In this embodiment, the energy equipment operation rules are correlation rules between energy equipment usage time and operating costs. Energy equipment operating costs include: additional energy losses, energy equipment repair losses, and energy equipment maintenance losses. The additional energy loss is the additional energy loss generated when the energy equipment is running compared with the initial operation. The initial operation means that the energy equipment has just started to be put into use. At this time, the energy equipment should be in the best working condition. As the energy equipment continues to operate, the energy equipment The conversion rate of As the running time of energy equipment increases. Similarly, energy equipment repair loss and energy equipment maintenance loss are the repair and maintenance losses that need to be carried out during the operation of energy equipment. The longer the energy equipment runs, the greater the probability of repairs and the more frequent maintenance. Therefore, based on historical energy equipment detection data Carry out learning and training to obtain the rules of energy equipment maintenance loss and energy equipment maintenance loss as the equipment operating time increases. Based on the calculated rules, the correlation rules between energy equipment usage time and operating costs are established, that is, energy equipment operation rules. The digital twin path display model can simulate the additional operating costs caused by the operating time of the energy equipment according to the energy equipment operating rules, thereby outputting the additional operating costs of the corresponding equipment when simulating the energy flow path. At the same time, in some embodiments, the additional operating costs are also As a consideration of feasible and optimal solutions for energy flow paths, it makes the full path data of energy flow closer to the actual situation.

In this embodiment, step S5 also includes: setting the dynamic change time, obtaining demand information, and the digital twin path display model displays the full path data of energy flow within the dynamic time according to the demand information. By setting the dynamic change time, users are provided with the full path data of energy flow within a period of time, thereby preventing users from being unable to intuitively feel the changes in the full path data of energy flow due to changes in equipment running time.

As the fourth embodiment of this application, a full-path data display method for multi-energy circulation also includes:

S6: Obtain the actual user terminal and energy equipment monitoring data, build the full path data of actual energy flow, compare the full path data of actual energy flow with the displayed full path data of energy flow, calculate the feedback fluctuation value, and update the digital twin path display Model.

Since there may be some influencing factors that cannot be displayed intuitively in actual situations, but will cause deviations in the full path data of energy flow, the feedback fluctuation value is calculated through the difference between the actual value and the simulated value, and the digital twin is updated based on the feedback fluctuation value. Path display model.

In this embodiment, a feedback model can also be established based on historical feedback fluctuation values, and a digital twin path display model and a feedback model can be combined to construct a digital twin feedforward path display model, thereby making the simulation display information more accurate.

The above specific implementation mode is a preferred implementation mode of a full-path data display method for multi-energy circulation in this application. This does not limit the specific implementation scope of this application. The scope of this application includes but is not limited to this specific implementation mode. Equivalent changes made according to the shape and structure of the present application are within the protection scope of the present application.

Claims (10)

1. A full-path data display method for multi-energy circulation, which is characterized by: including the following steps: S1: Obtain the location information of the user terminal and energy equipment, and build a spatial location model; S2: Build an energy flow path based on the spatial location model and energy flow mechanism; S3: Obtain historical user terminal and energy equipment monitoring data, reproduce energy flow according to the energy flow path, and obtain path loss rules through neural network algorithm analysis; S4: Build a digital twin path display model based on the spatial location model, energy flow path and path loss rules; S5: Obtain demand information, and the digital twin path display model displays the full path data of energy flow based on the demand information. 2. A full-path data display method for multi-energy circulation as claimed in claim 1, characterized by: The S2 includes: building an energy flow path with energy conversion rules based on the spatial location model and energy flow mechanism. 3. A full-path data display method for multi-energy circulation as claimed in claim 2, characterized by: The S5 includes: S51: Obtain the demand information, and determine the display demand based on the demand information. If the display demand is the optimal solution for displaying the energy flow path, execute S52. If the display demand is the feasible solution for displaying the energy flow path, execute S53; S52: The digital twin path display model calculates the optimal solution of the energy flow path based on the energy conversion rules and path loss rules, and displays the full path data of the optimal solution of the energy flow path; S53: The digital twin path display model calculates feasible solutions for energy flow paths based on energy conversion rules and path loss rules, and displays the full path data of feasible solutions for all energy flow paths. 4. A full-path data display method for multi-energy circulation as claimed in claim 3, characterized by: The S53 also includes: marking the optimal solution among the feasible solutions of the energy flow path. 5. A full-path data display method for multi-energy circulation as claimed in claim 3, characterized by: The S53 includes: obtaining the number of paths for demand display, the digital twin path display model calculating feasible solutions for energy circulation paths based on energy conversion rules and path loss rules, optimizing the feasible solutions for energy circulation paths, and screening the number of paths based on the optimal ranking. Feasible solution of energy flow path, showing the full path data corresponding to the feasible solution of energy flow path. 6. A full-path data display method for multi-energy circulation as claimed in claim 1, characterized by: The S3 includes: obtaining historical user terminal and energy equipment monitoring data, reproducing energy flow according to the energy flow path, and obtaining path loss rules and energy equipment operation rules through neural network algorithm analysis. 7. A full-path data display method for multi-energy circulation as claimed in claim 6, characterized by: The S4 includes: constructing a digital twin path display model based on the spatial location model, energy flow path, path loss rules and energy equipment operation rules. 8. A full-path data display method for multi-energy circulation as claimed in claim 7, characterized by: Energy equipment operation rules are correlation rules between energy equipment usage time and operating costs. 9. A full-path data display method for multi-energy circulation as claimed in claim 7, characterized by: The S5 also includes: setting the dynamic change time, obtaining demand information, and the digital twin path display model displays the full path data of energy flow within the dynamic time based on the demand information. 10. A full-path data display method for multi-energy circulation as claimed in claim 1, characterized by: S6: Obtain the actual user terminal and energy equipment monitoring data, build the full path data of actual energy flow, compare the full path data of actual energy flow with the displayed full path data of energy flow, calculate the feedback fluctuation value, and update the digital twin path display Model.