A steel enterprise energy flow network simulation system and method

Abstract

This invention belongs to the field of energy simulation technology and relates to an energy flow network simulation system and method for steel enterprises. It includes: a system configuration module for configuring parameters based on user-inputted information and forming a structured configuration data package; a front-end operation module for configuring a visual interactive interface based on the configuration data package; generating a Gantt chart based on pre-set production and maintenance plans; and drawing a dynamic energy flow diagram based on user-defined equipment and energy nodes; and a back-end service module for calculating energy prediction results based on the Gantt chart, dynamic energy flow diagram, and configuration data package using a pre-set production and consumption model, and performing scheduling optimization when energy prediction results are unbalanced to obtain an energy scheduling balance result. This invention achieves collaborative simulation of production and energy, more intuitively displays the energy balance process, provides a more comprehensive simulation platform for the steel industry, and facilitates systematic management by enterprises.

Description

Technical Field

[0001] This invention relates to the field of energy simulation technology, and in particular to an energy flow network simulation system and method for steel enterprises. Background Technology

[0002] The steel production process is complex, involving multiple steps such as sintering, ironmaking, steelmaking, and rolling. Changes in the production rhythm of equipment at each step, planned maintenance, and unplanned downtime can cause imbalances in energy media. Material and energy flows under different operating conditions are coupled and mutually restrictive. During production, energy planning varies significantly under different production plans and operating conditions. Furthermore, when abnormal operating conditions occur, changes in equipment status directly cause fluctuations in energy production and consumption, and the underlying mechanisms of this impact are extremely complex. These factors make it difficult for data modeling methods to describe such a complex, multifaceted, and nonlinear system.

[0003] To systematically address the aforementioned issues, it is necessary to build an energy simulation system for steel enterprises capable of simulating and extrapolating under different scenarios. Current energy simulation technologies primarily focus on constructing theoretical mathematical models of energy flow networks to analyze the static structure and energy efficiency bottlenecks in the generation, conversion, distribution, and consumption of energy. Building upon this, to address the impact of production plan fluctuations on the energy system, process network simulation technology has been introduced. By constructing event models of the entire production process, it is possible to pre-simulate and optimize production scheduling schemes for steelmaking, continuous casting, and other processes in a single steel enterprise, thereby predicting future energy demand. However, these technologies still suffer from several problems, including limited applicability, reliance on static data tables for technical analysis, insufficient granularity in model construction, difficulty in accurately describing the dynamic transmission and interaction relationships of energy flow, and a lack of unified models and system support. Summary of the Invention

[0004] Based on the above analysis, the embodiments of the present invention aim to provide an energy flow network simulation system and method for steel enterprises, in order to solve the problems that the existing technology cannot systematically manage simulation projects of various steel enterprises, the models and configuration parameters are not replaceable, and there is a lack of dynamic energy flow diagrams to show the energy balance process.

[0005] On one hand, embodiments of the present invention provide an energy flow network simulation system for steel enterprises, comprising: The system configuration module is used to configure parameters based on user-input parameters and generate a structured configuration data package. The front-end operation module is used to configure a visual interactive interface based on the configuration data package; generate a Gantt chart of operating conditions according to the pre-set production and maintenance plan; and draw a dynamic energy flow diagram based on user-defined equipment and energy nodes. The backend service module is used to calculate the energy prediction results based on the operating condition Gantt chart, the dynamic energy flow diagram and the configuration data package through a pre-set production and consumption model, and to perform scheduling optimization when the energy prediction results are unbalanced, so as to obtain the energy scheduling balance result.

[0006] Furthermore, the system configuration module includes: The project configuration unit is used to define the process equipment nodes, energy media, and operating conditions in steel production, and to form a project parameter package; The scenario parameter configuration unit is used to configure the time period, scenario name, initial scenario value, and simulation process equipment parameters of each simulation scenario in steel production, and to form a scenario parameter package. The model parameter configuration unit is used to configure the baseline parameters, model constraints, and running weights of the production and consumption model, and to form a model parameter package. The dataset configuration unit is used to perform structured processing on the project parameter package, the scene parameter package, and the model parameter package to form the configuration data package and store it in the database.

[0007] Furthermore, the front-end operation module includes: The variable operating condition production planning unit is used to generate the operating condition Gantt chart containing the equipment operating condition sequence according to the production and maintenance plan. The dynamic energy flow compilation unit is used to draw the dynamic energy flow diagram according to the topological relationship of the equipment and energy nodes, and to dynamically configure the production and consumption model and model parameters of each node according to the configuration data package.

[0008] Furthermore, the backend service module includes: The production and consumption model unit is pre-set with production and consumption models corresponding to each node in different processes; it is used to calculate the energy prediction results corresponding to each energy medium based on the equipment operating condition sequence provided by the operating condition Gantt chart and the production and consumption models and model parameters configured for each node in the dynamic energy flow diagram. The optimization algorithm unit is used to optimize and solve the problem based on a pre-set optimization algorithm when the energy prediction results are unbalanced, and generate the energy scheduling balance results corresponding to each energy medium.

[0009] Furthermore, the front-end operation module also includes: a production energy coordination unit; The production energy coordination unit is used for: In response to changes in the equipment operating condition timing in the Gantt chart, and based on the changed equipment operating condition timing, the model parameters of each node in the dynamic energy flow chart are updated synchronously. Based on the changed equipment operating time sequence and model parameters, the corresponding production and consumption model is called and the energy prediction results are recalculated; the optimization algorithm in the optimization algorithm unit is called to optimize and solve the recalculated energy prediction results, and the dynamic energy flow diagram is dynamically updated based on the optimized energy scheduling balance results.

[0010] Furthermore, the backend service module also includes: The simulation analysis unit is used to calculate and analyze the energy dispatch balance results according to the pre-set index calculation rules, and output various analysis indicators; Among them, the various analytical indicators include at least: cost indicators, peak, flat and valley electricity, electricity demand, energy balance rate, pipeline loss rate, energy conversion efficiency, comprehensive energy consumption of processes and unit consumption of media.

[0011] Furthermore, the front-end operation module also includes: The simulation index display unit is used to visualize various analytical indicators calculated by the simulation analysis unit in the form of numbers and curves.

[0012] On the other hand, embodiments of the present invention provide a method for simulating energy flow networks in steel enterprises, including: Configure parameters based on user-input parameters and generate a structured configuration data package; Configure a visual interactive interface based on the configuration data package; generate a working condition Gantt chart according to the pre-set production and maintenance plan, and draw a dynamic energy flow diagram based on user-defined equipment and energy nodes; Based on the operating condition Gantt chart, the dynamic energy flow diagram, and the configuration data package, energy prediction results are calculated using a pre-set production and consumption model. When the energy prediction results are unbalanced, scheduling optimization is performed to obtain energy scheduling balance results.

[0013] Furthermore, the step of calculating energy forecast results through a pre-set production and consumption model, and performing scheduling optimization when the energy forecast results are unbalanced to obtain an energy scheduling balance result, includes: Based on the equipment operating time sequence provided by the operating condition Gantt chart, and the production and consumption model and model parameters configured for each node in the dynamic energy flow diagram, the energy prediction results corresponding to each energy medium are calculated. When the energy forecast results are unbalanced, an optimization algorithm is used to solve the problem and generate the energy scheduling balance results for each energy medium.

[0014] Furthermore, the method also includes: In response to changes in the equipment operating condition timing in the Gantt chart, and based on the changed equipment operating condition timing, the model parameters of each node in the dynamic energy flow chart are updated synchronously. Based on the changed equipment operating time sequence and model parameters, the corresponding production and consumption model is called and the energy prediction results are recalculated; the optimization algorithm is called to optimize the recalculated energy prediction results, and the dynamic energy flow diagram is dynamically updated based on the optimized energy scheduling balance results.

[0015] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects: First, unlike related technologies that struggle to accurately describe the dynamic transmission and interaction of energy flow, this invention constructs an energy flow network for steel enterprises through a collaborative method of programmable Gantt charts and dynamic energy flow diagrams. This achieves, for the first time, a systematic production-energy collaborative simulation adaptable to different enterprises. It can dynamically calculate the production and consumption relationships of various energy sources under various operating conditions and uses dynamic energy flow diagrams to display the calculation results in real time. This solves the problems of existing simulation systems being unable to intuitively view and locate the energy conversion efficiency at each time period and unable to compare and evaluate simulation results. It comprehensively depicts the dynamic transmission characteristics of energy flow and more intuitively presents the key processes of dynamic compensation for different energy media, providing valuable reference for optimizing the operation of actual production processes.

[0016] Secondly, unlike related technologies which have limited applicability and cannot systematically manage simulation projects, this invention provides a decision-making platform that combines theoretical rigor and engineering practicality for energy planning, energy indicator analysis, anomaly early warning, and energy efficiency improvement through the deep integration of dynamic simulation and energy consumption models. It solves problems in existing energy simulation systems such as the inability to simultaneously create multiple projects suitable for different steel companies, the inability to systematically manage simulation projects, and the limited availability of models and non-replaceable model parameters. Furthermore, based on richer analysis of simulation results, it can improve economic, energy-saving, and environmental benefits. As a key infrastructure connecting physical energy systems and digital management, this simulation system is suitable for steel companies, universities, and research institutions, and can promote the transformation of the steel industry from experience-driven to model-driven energy management paradigms, helping steel companies overcome energy conservation and consumption reduction bottlenecks. In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0017] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. Figure 1 is a schematic diagram of the main modules of the energy flow network simulation system for steel enterprises according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the production-energy coupling relationship in an embodiment of the present invention; Figure 3 This is a flowchart of the energy flow network simulation method for steel enterprises according to an embodiment of the present invention. Detailed Implementation

[0018] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0019] A specific embodiment of the present invention discloses an energy flow network simulation system for steel enterprises, such as... Figure 1 As shown, it includes the following modules: The system configuration module is used to configure parameters based on user-input parameters and generate a structured configuration data package. The front-end operation module is used to configure a visual interactive interface based on the configuration data package; generate a Gantt chart of operating conditions according to the pre-set production and maintenance plan; and draw a dynamic energy flow diagram based on user-defined equipment and energy nodes. The backend service module is used to calculate the energy prediction results based on the operating condition Gantt chart, the dynamic energy flow diagram and the configuration data package through a pre-set production and consumption model, and to perform scheduling optimization when the energy prediction results are unbalanced, so as to obtain the energy scheduling balance result.

[0020] During implementation, firstly, the system configuration module configures various user-input parameters. After configuration, based on the pre-defined production and maintenance plans in the front-end operation module, a real-time changing Gantt chart is generated. Then, through user-defined editing, energy nodes and equipment nodes are dragged and dropped to create a dynamic energy flow diagram, connecting the entire energy flow network. Secondly, based on the production and consumption model of the back-end service module and the collaborative relationship between the production and consumption Gantt chart and the dynamic energy flow diagram in the front-end operation module, the energy prediction results for each type of equipment in various simulation scenarios are calculated. This means calculating the production and consumption data related to the input and output of various energy media. The dynamic energy flow diagram is then updated based on the optimized energy scheduling balance results to describe the energy conversion and balancing process, providing a more intuitive presentation of energy flow and real-time changes in flow rate. Finally, the energy scheduling balance results are analyzed and calculated, and the results are displayed in the front-end operation module in the form of numbers and curves.

[0021] In addition, the simulation system supports user-defined simulation scenarios. Once the simulation scenario is defined, it will drive the backend service module to calculate the energy prediction results and perform simulation deduction and optimization solution based on the preset scenario rules and optimization algorithms, so as to display them centrally in the visual interactive interface.

[0022] It is understood that the simulation system of this invention aims to simulate the energy balance process in various scenarios. Its design is based on the simulation and optimization of offline data, specifically by constructing a complete and controllable digital simulation environment through imported configuration data packages and user-defined editing. Within this environment, users can simulate the energy flow network of steel enterprises and pre-assess its impact on the energy system's production and consumption, as well as its balance state. This enables coordinated optimization of production planning and energy dispatching, assisting decision-makers in developing more scientific and efficient plans.

[0023] It should be noted that although the embodiments of the present invention revolve around offline data, the simulation framework and model calculation logic it constructs have good scalability and adaptability. Therefore, without departing from the core principles of the present invention, this system can also be used for online real-time energy flow simulation and prediction, and provide support for real-time energy scheduling or dynamic adjustment.

[0024] Furthermore, the system configuration module includes: a project configuration unit, a scene parameter configuration unit, a model parameter configuration unit, and a dataset configuration unit; and the system configuration module supports the import, export, and parameter replacement functions of various parameters.

[0025] The project configuration unit is used to define the process equipment nodes, energy media, and operating conditions in steel production, and to form a project parameter package; Specifically, the process equipment node definition includes defining the node's name, type, and code. Nodes can be freely added and deleted by users and associated with corresponding energy media and operating conditions. The energy media definition includes defining the energy media's code, name, type, and function. The operating condition type definition includes defining the operating condition's code, name, classification, marking color, whether it is a shutdown, and whether it is a planned operating condition.

[0026] As can be seen, the project configuration unit can define and associate information about common units in the entire steel production process, providing a basic environment for scenario configuration and simulation.

[0027] The scenario parameter configuration unit is used to configure the time period, scenario name, initial scenario value, and simulation process equipment parameters of each simulation scenario in steel production, and form a scenario parameter package.

[0028] For example, scenario parameter configuration specifically includes configuring and setting start / stop for production process units, gas holders, generator sets, venting towers, and purchased / sold energy. Specifically, production process unit configuration includes adding, deleting, and editing equipment and energy nodes, displaying the input and output energy of each node, associating node operating conditions, and configuring flow constraints and duration of energy media under corresponding operating conditions. Gas holder configuration includes adding, deleting, and modifying parameters such as capacity and upper / lower limits for gas holders. Generator set configuration includes adding, deleting, setting unit parameters, setting balance coefficients, and setting input and output energy parameters for generator sets. Venting tower configuration includes adding, deleting, and setting venting coefficients for venting towers. Purchased / sold energy configuration refers to setting the corresponding energy unit price. Furthermore, scenario parameter configuration also includes configuring key energy media, such as entering time-of-use electricity prices, gas calorific value, unit price, minimum adjustment amount, and conversion factor.

[0029] The model parameter configuration unit is used to configure the baseline parameters, model constraints, and running weights of the production and consumption model, and to form a model parameter package.

[0030] For example, the model parameter configuration unit can control the pace and accuracy of simulation optimization, including the time interval for calling the model, prediction duration, number of iterations, and runtime limits; specific model constraints include setting upper and lower limits for gas holders, rate of change of gas holder capacity, and changes in generator load that do not exceed warning thresholds and follow the law of conservation of energy to ensure that the simulation process conforms to the safe operation criteria of actual production; the operation weight configuration facilitates the achievement of cost minimization and multi-objective trade-offs, specifically including setting corresponding weight coefficients for parameters such as purchase costs, power generation benefits, venting costs, sales revenue, and adjustment costs.

[0031] The dataset configuration unit is used to perform structured processing on the project parameter package, the scene parameter package, and the model parameter package to form the configuration data package and store it in the database.

[0032] The dataset configuration unit has the functions of data management and data import. That is, the parameters configured in the system configuration module through the aforementioned units are all imported by the dataset configuration unit and stored in the database in a structured manner for use by the front-end operation module and the back-end service module.

[0033] Preferably, before importing various external data (such as Excel / CSV files) into the dataset configuration unit, data preprocessing operations are performed, specifically including: Data cleaning and verification: Check the completeness and format correctness of various types of data (such as whether the code is unique and whether the value is within a reasonable range), and remove or correct obvious errors and outliers.

[0034] Data transformation and mapping: Transforming and mapping the fields and structure of external data to the data model defined internally by the system.

[0035] It is understandable that the dataset configuration unit can integrate various configuration parameters into a complete, internally self-consistent configuration data package according to the needs of the simulation task. This allows the backend service module to load the configuration data package to complete the solution calculation, and the user can view, edit and modify the configuration data package in the front-end operation module. At the same time, the edited data package needs to be transmitted to the database for storage through the dataset configuration unit.

[0036] Furthermore, the front-end operation module includes: a variable operating condition production planning unit, a dynamic energy flow planning unit, a production energy coordination unit, and a simulation index display unit.

[0037] The variable operating condition production planning unit is used to generate the operating condition Gantt chart containing the equipment operating condition sequence based on the production and maintenance plan.

[0038] Equipment operating condition sequence refers to the sequential arrangement of various operating conditions (such as operation, standby, maintenance, heating, and insulation) experienced by each piece of equipment along the timeline of a Gantt chart. The equipment operating condition sequence can be automatically generated from imported production and maintenance plans using the variable operating condition production planning unit, allowing both types of plans to be presented in the same view. Users can also add, edit, modify, and delete operating conditions individually within the Gantt chart. An interactive timeline is located at the top of the Gantt chart, allowing users to directly adjust the start time, end time, and duration of events by dragging event bars. Furthermore, clicking on a plan or operating condition event in the Gantt chart allows for further configuration of the relevant equipment, scope of influence, associated processes and production lines, simulation time, impact on the production plan, production consumption model and parameters, and related allocation rules.

[0039] The dynamic energy flow compilation unit is used to draw the dynamic energy flow diagram according to the topological relationship of the equipment and energy nodes, and to dynamically configure the production and consumption model and model parameters of each node according to the configuration data package.

[0040] It can be understood that the dynamic energy flow diagram in the embodiments of the present invention is a dynamic Sankey diagram, which is used to dynamically display the input, output and distribution of energy flow or material flow at each stage, and uses the width change to reflect the flow rate, clearly presenting the direction and quantity relationship of energy or material.

[0041] Equipment nodes include physical equipment or process units in the actual production process (such as blast furnaces, converters, rolling mills, heating furnaces, etc.), which are the main entities responsible for energy consumption and conversion. In the energy flow diagram, they represent the starting point, ending point, or conversion point of the energy flow. Energy nodes include various energy media in the transmission and balancing process (such as electricity, blast furnace gas, converter gas, oxygen, steam, nitrogen, etc.), which are the carriers of energy flow. In the energy flow diagram, they are connected to equipment nodes through pipelines to form a complete energy supply, consumption, and recovery network.

[0042] Specifically, users can drag and drop equipment nodes and energy nodes through the dynamic energy flow compilation unit to draw dynamic energy flow diagrams. This includes editing equipment and energy nodes, configuring the energy production and consumption models of each node, dragging nodes to modify upstream and downstream relationships, and changing the layout of the energy flow diagram. Meanwhile, the models and parameters of each node can be customized and modified on the interactive interface, supporting the import and export of models and parameters to adapt to different steel companies.

[0043] During operation, after the user clicks "Run Simulation," the corresponding production and consumption model in the backend service module will be invoked to begin calculations. Combining production plans, energy flow configurations, and scenario rules, a dynamic energy flow network for that time period is generated. The dynamic energy flow diagram displays the dynamic balance process of the energy medium, and the bandwidth of the streamlines visually shows the magnitude and changes in flow, making the entire balance process clearer. Simultaneously, a timeline function is added, allowing users to view the energy flow of the simulation scenario from start to finish. Users can drag the progress bar to freeze at a specific point in time to view various energy indicators and the model calculation status of individual devices at that time. Furthermore, the system will simultaneously display trend charts such as the efficiency curves of key equipment, the cumulative flow curve of the energy medium, and the conversion efficiency curve, helping to observe the dynamic fluctuations of equipment and energy medium during the balance process.

[0044] Furthermore, the production energy coordination unit is used for: In response to changes in the equipment operating condition timing in the Gantt chart, and based on the changed equipment operating condition timing, the model parameters of each node in the dynamic energy flow chart are updated synchronously. Based on the changed equipment operating time sequence and model parameters, the corresponding production and consumption model is called and the energy prediction results are recalculated; the optimization algorithm in the optimization algorithm unit is called to optimize and solve the recalculated energy prediction results, and the dynamic energy flow diagram is dynamically updated based on the optimized energy scheduling balance results.

[0045] The production energy coordination unit can present the real-time linkage effect between the operating condition Gantt chart and the dynamic energy flow chart. After the operating condition and parameters of a single device in the Gantt chart are adjusted and changed, the production consumption model will drive the status and parameters of the corresponding device in the dynamic energy flow chart to change. The production consumption of that device and other devices affected by the production consumption fluctuation will also automatically adjust their status and parameters, and the energy flow will also show the corresponding changes at the same time. That is, the changed energy scheduling balance result calculated by the back-end service module will be updated to the dynamic energy flow chart and operating condition Gantt chart interface in real time.

[0046] refer to Figure 2 As shown, by constructing a collaborative relationship between a working condition Gantt chart and a dynamic energy flow diagram, the digital coupling of production and energy is achieved. Specifically, the Gantt chart represents the time series of discrete events such as equipment start-up and shutdown, and rhythm changes in the production process, driving the production and consumption model to calculate the dynamic production, consumption, storage, and dissipation trajectories of energy media such as gas, steam, and electricity in real time, and outputs key energy efficiency indicators. This process transforms the temporal logic of the production system into a continuous response of energy flow, completing the collaborative simulation of production drive and energy response in virtual space.

[0047] This allows for a direct visualization of the dynamic energy transfer process, such as fluctuations in gas flow and changes in pipeline pressure, as well as the dynamic energy compensation process when various operating scenarios occur. This enables the development of accurate and effective energy plans, providing advanced quantitative data for actual scheduling and facilitating a shift from passive balancing to proactive optimization.

[0048] In the process of energy production coordination, the operating condition Gantt chart plays a decisive role in the dynamic energy flow diagram, mainly in the following three aspects: Time-driven: The generation and disappearance times of each energy medium in the dynamic energy flow diagram are directly determined by the start and end times of the corresponding equipment tasks on the Gantt chart. For example, when the equipment starts up (energy flow changes from 0 to a value) and when it stops (energy flow changes from a value to 0) is entirely determined by the start and end times of the tasks on the operating condition Gantt chart; Spatial correspondence: The operating status of each piece of equipment in the working condition Gantt chart corresponds to the input and output of a specific energy node in the dynamic energy flow chart. For example, the operation of a blast furnace corresponds to the generation of blast furnace gas and the consumption of blast and electricity; the operation of a converter corresponds to the consumption of oxygen and the generation of converter gas. Thus, each flow line in the energy flow chart can be found in the Gantt chart with a specific source node and flow direction. Pattern Mapping: Changes in the operating conditions shown in the Gantt chart directly determine the stepwise changes in energy flow in the energy flow diagram. For example, in the heating state of a steel rolling furnace, gas consumption is close to full load, while in the waiting-to-roll and heat-preserving state, the consumption will be significantly reduced. This allows the state transitions in the Gantt chart to be clearly and intuitively displayed on the energy flow diagram, realizing the coordinated linkage between the equipment status and time information in the operating condition Gantt chart and the energy flow paths and energy flow variables in the dynamic energy flow diagram.

[0049] Furthermore, the simulation index display unit is used to visualize various analysis indicators calculated by the simulation analysis unit in the backend service module in the form of numbers and curves.

[0050] For example, the simulation index display unit can display the analysis indexes of the simulation scenario at each moment in the simulation period. Specifically, it includes the analysis and evaluation of indicators such as cost indicators before and after scenario optimization, peak, flat and valley power, power demand, energy balance rate, pipeline loss rate, energy conversion efficiency, comprehensive energy consumption of processes, and medium unit consumption, and provides better energy planning optimization schemes.

[0051] The analytical metrics are obtained from the backend service module.

[0052] Furthermore, the backend service module includes: a production and consumption model unit, an optimization algorithm unit, a scenario rule unit, and a simulation analysis unit.

[0053] The production and consumption model unit is pre-set with production and consumption models corresponding to each node in different processes; it is used to calculate the energy prediction results corresponding to each energy medium based on the equipment operating condition sequence provided by the operating condition Gantt chart and the production and consumption models and model parameters configured for each node in the dynamic energy flow diagram.

[0054] The production and consumption model unit is equipped with a production and consumption model for calculating the energy input and output of each process and equipment in the steel production process. During implementation, based on the user's preparation of the working condition Gantt chart and dynamic energy flow diagram in the front-end operation module, the corresponding production and consumption model can be dynamically invoked for real-time calculation, thereby generating time-segmented energy supply and demand plans, which are then transmitted to the front-end operation module to update and display the dynamic energy flow diagram.

[0055] The calculation of the production and consumption model depends on the equipment operating condition time sequence provided by the operating condition Gantt chart and the model parameters in the dynamic energy flow diagram. The equipment operating condition time sequence is used to determine at any moment on the simulation time axis and what operating condition stage a specific piece of equipment should be in. The model parameters are the specific variables assigned values ​​in each production and consumption model formula.

[0056] In some implementations, the production consumption model specifically includes a normal steady-state model and a transient operating condition model, and the calculation formulas are shown below: The first type is the production and consumption model under normal steady-state operating conditions. It is applicable to situations where the equipment is operating stably. Specific formulas include: ; : Represents the energy medium flow rate of the current device under normal steady state at time t (unit: m³ / h, kWh / h, etc.). : Indicates the current baseline productivity or throughput of the equipment (unit: t / h, m³ / h, etc.). u: Represents the energy consumption or output coefficient of the current equipment (unit: m³ / t, kWh / t, etc.).

[0057] The second category, the production and consumption model under fluctuating operating conditions, is specifically divided into the following three stages: Phase 1: Transitional state I, from normal to abnormal steady state (such as equipment shutdown).

[0058] This stage is used to describe the energy medium flow rate from its normal value. Steady-state value under abnormal operating conditions The specific formulas include: ; : Represents the dynamic change in energy medium flow rate during the transition from normal production steady state to abnormal production steady state; : Indicates the start time of the operating condition; : Indicates the transition slope (unit: flow rate / time); ,in, It refers to the duration of the transition phase.

[0059] Phase 2: Abnormal steady state (e.g., complete equipment shutdown).

[0060] This stage describes how the equipment maintains a stable production and consumption rate under abnormal operating conditions. Specific formulas include: ; This represents the flow rate of the energy medium in the device under abnormal operating conditions at time t, and is usually a constant; for example, when the device is completely shut down. =0, and during heat preservation, it is a lower constant value.

[0061] Phase 3: Transitional state II, recovering from abnormal steady state to normal.

[0062] This stage is used to describe the flow rate of the energy medium from... Restore to The specific formulas include: ; : Represents the dynamic change in energy medium flow rate during the transition from abnormal production steady state to normal production steady state; : Indicates the start time of the recovery.

[0063] : Indicates the recovery slope, =( ) / .

[0064] The third type is the generalized integrated production and consumption model. This uses a time-based piecewise function to integrate the above stages. Specific formulas include: ; As can be seen from the above, during the simulation calculation, the system first determines the current state stage (normal or fluctuating) based on the working condition Gantt chart; then, it calls the corresponding production and consumption formulas and substitutes the model parameters in the dynamic energy flow diagram, thereby dynamically calculating the predicted value of energy medium flow rate Q(t) at each moment when the working condition changes; that is, the calculation process is driven by the planned timing in the working condition Gantt chart and relies on the model parameters such as output, unit consumption, and various steady-state and transient parameters configured in the dynamic energy flow diagram to achieve the calculation.

[0065] It should be noted that although the production and consumption model is mathematically represented as a deterministic calculation under given input, its essence is a simulation prediction based on production and maintenance plans and user configuration data. The energy prediction results calculated by the system through this model are actually a simulation and deduction of the energy production and consumption that will inevitably accompany the execution of a specific production plan in the future in a virtual environment, thereby realizing the assessment and predictive planning of the synergistic impact of production and energy.

[0066] The optimization algorithm unit is used to optimize and solve the problem based on a pre-set optimization algorithm when the energy prediction results are unbalanced, and generate the energy scheduling balance results corresponding to each energy medium.

[0067] The energy dispatch balance result in this embodiment of the invention refers to the energy medium plan data that has reached a balanced state, generated by the optimization algorithm unit after simulation dispatch calculation when the energy forecast result shows an imbalance between supply and demand. If the energy forecast result is balanced, no optimization dispatch is required, and the energy forecast result can be output as the energy dispatch balance result; if the energy forecast result is unbalanced, the optimization algorithm is triggered, and under the premise of considering various constraints, an adjustment scheme that can make the system reach balance again is simulated and calculated.

[0068] The optimization algorithm unit is pre-set with optimization algorithm models and constraints, supports functions such as optimization algorithm execution engine configuration and model output result testing, and has a variety of different solution algorithms and solvers built in, making it suitable for a wide range of scenarios.

[0069] For example, this involves constructing relevant objective functions and constraints, and setting priorities for energy and equipment usage. The objective functions include, but are not limited to, cost target models, environmental protection target models, and energy-saving target models. The constraint functions include, but are not limited to, constraints on equipment change rate, medium balance, storage equipment capacity, equipment energy consumption, calorific value upper and lower limits, variable non-negativity constraints, equipment efficiency coefficients, and equipment operation penalty coefficients. The energy scheduling is optimized using algorithms and solvers to obtain the optimal energy balance solution. This optimal energy scheduling balance result is then fed back to the dynamic energy flow compilation unit of the front-end operation module for visualization using a dynamic energy flow graph. The specific formulas and construction processes for the objective functions, constraints, and solvers can be found in existing technologies and will not be elaborated upon here.

[0070] Preferably, the scenario rule unit is used to dynamically allocate the energy prediction results output by the production and consumption model unit according to the pre-set energy allocation rules; if the energy prediction results after allocation are unbalanced, they are then sent to the optimization algorithm unit to obtain the energy scheduling balance result.

[0071] Furthermore, the simulation analysis unit is used to calculate and analyze the energy dispatch balance results according to the pre-set index calculation rules, and output a variety of analysis indicators; wherein, the variety of analysis indicators include at least: cost indicators, peak-valley power, power demand, energy balance rate, pipeline loss rate, energy conversion efficiency, comprehensive energy consumption of processes and unit consumption of media.

[0072] Simultaneously, the aforementioned analytical indicators need to be sent to the simulation indicator display unit of the front-end operation module for visualization, enabling users to analyze and evaluate the simulation effect of the entire scene. The indicator calculation rules can refer to existing technologies and can be customized by relevant technical personnel; these details will not be elaborated here.

[0073] It is understood that the above embodiments are for ease of understanding and simplification only, and should not be construed as limitations on the present invention. The present invention does not specifically limit the settings of the system configuration module, front-end operation module, back-end service module, and their internal units, or the model calculation method. Without departing from the core idea of ​​the present invention, the system's scheduling-driven mechanism can be replaced with other equivalent logical units, the evaluation system can be further expanded or its evaluation indicators adjusted, and the types of energy media scheduled can be increased according to actual needs. Furthermore, the names of the functional modules in the system can be adjusted according to the implementation scenario, and their core algorithms and solvers can be replaced with other applicable algorithms and solving tools known to those skilled in the art.

[0074] Therefore, it can be seen that the embodiments of the present invention can achieve at least one of the following beneficial effects: First, production-energy co-simulation. This involves using a user-editable Gantt chart and a dynamic energy flow diagram to dynamically calculate the production and consumption relationships of various energy media under different operating conditions. The dynamic energy flow diagram updates and displays the calculation results in real time. This provides a clearer picture of the entire balancing process, better depicts the dynamic transfer characteristics of energy flow, and intuitively presents the key process of how another energy source dynamically compensates for a decrease in one energy source through the pipeline network.

[0075] Second, systematic management of simulation projects. Through the deep integration of dynamic simulation and energy production and consumption models, a decision-making platform that combines theoretical rigor and engineering practicality is provided for energy planning, energy indicator analysis, anomaly early warning, and energy efficiency improvement. This solves the problems of existing energy simulation systems, such as the inability to simultaneously create multiple projects to adapt to different steel companies, the inability to systematically manage simulation projects, and the limited availability of models and non-replaceable model parameters.

[0076] Third, multi-dimensional analysis of simulation results. A richer analysis of the simulation results, including indicators such as cost, peak / valley electricity consumption, electricity demand, energy balance rate, pipeline loss rate, energy conversion efficiency, comprehensive energy consumption of processes, medium unit consumption, and inversion, can improve economic, energy-saving, and environmental benefits. The simulation system of this invention is suitable for steel enterprises, universities, and research institutions, and can promote the transformation of the steel industry from experience-driven to model-driven energy management paradigms, helping steel enterprises overcome bottlenecks in energy conservation and consumption reduction. In another embodiment of the present invention, a method for simulating energy flow networks in steel enterprises is proposed, such as... Figure 3 As shown, it includes the following steps S1 to S3: Step S1: Configure parameters based on user-input parameters and generate a structured configuration data package; Step S2: Configure a visual interactive interface based on the configuration data package; generate a working condition Gantt chart according to the pre-set production and maintenance plan, and draw a dynamic energy flow diagram based on user-defined equipment and energy nodes; Step S3: Based on the operating condition Gantt chart, the dynamic energy flow diagram, and the configuration data package, the energy prediction result is calculated through a pre-set production and consumption model, and scheduling optimization is performed when the energy prediction result is unbalanced to obtain the energy scheduling balance result.

[0077] Furthermore, the calculation of the energy dispatch balance result specifically includes: Based on the equipment operating time sequence provided by the operating condition Gantt chart, and the production and consumption model and model parameters configured for each node in the dynamic energy flow diagram, the energy prediction results corresponding to each energy medium are calculated. When the energy forecast results are unbalanced, an optimization algorithm is used to solve the problem and generate the energy scheduling balance results for each energy medium.

[0078] Furthermore, the method also includes: responding to changes in the equipment operating condition timing in the operating condition Gantt chart, and synchronously updating the model parameters of each node in the dynamic energy flow chart according to the changed equipment operating condition timing; Based on the changed equipment operating time sequence and model parameters, the corresponding production and consumption model is called and the energy prediction results are recalculated; the optimization algorithm is called to optimize the recalculated energy prediction results, and the dynamic energy flow diagram is dynamically updated based on the optimized energy scheduling balance results.

[0079] The above system and method embodiments are based on the same principles, and their related aspects can be referenced from each other to achieve the same technical effects. For specific implementation processes, please refer to the foregoing embodiments, which will not be repeated here.

[0080] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0081] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A simulation system for energy flow networks in steel enterprises, characterized in that, include: The system configuration module is used to configure parameters based on user-input parameters and generate a structured configuration data package. The front-end operation module is used to configure a visual interactive interface based on the configuration data package; generate a Gantt chart of operating conditions according to the pre-set production and maintenance plan; and draw a dynamic energy flow diagram based on user-defined equipment and energy nodes. The backend service module is used to calculate the energy prediction results based on the operating condition Gantt chart, the dynamic energy flow diagram and the configuration data package through a pre-set production and consumption model, and to perform scheduling optimization when the energy prediction results are unbalanced, so as to obtain the energy scheduling balance result.

2. The simulation system according to claim 1, characterized in that, The system configuration module includes: The project configuration unit is used to define the process equipment nodes, energy media, and operating conditions in steel production, and to form a project parameter package; The scenario parameter configuration unit is used to configure the time period, scenario name, initial scenario value, and simulation process equipment parameters of each simulation scenario in steel production, and to form a scenario parameter package. The model parameter configuration unit is used to configure the baseline parameters, model constraints, and running weights of the production and consumption model, and to form a model parameter package. The dataset configuration unit is used to perform structured processing on the project parameter package, the scene parameter package, and the model parameter package to form the configuration data package and store it in the database.

3. The simulation system according to claim 1, characterized in that, The front-end operation module includes: The variable operating condition production planning unit is used to generate the operating condition Gantt chart containing the equipment operating condition sequence according to the production and maintenance plan. The dynamic energy flow compilation unit is used to draw the dynamic energy flow diagram according to the topological relationship of the equipment and energy nodes, and to dynamically configure the production and consumption model and model parameters of each node according to the configuration data package.

4. The simulation system according to claim 3, characterized in that, The backend service module includes: The production and consumption model unit is pre-set with production and consumption models corresponding to each node in different processes; it is used to calculate the energy prediction results corresponding to each energy medium based on the equipment operating condition sequence provided by the operating condition Gantt chart and the production and consumption models and model parameters configured for each node in the dynamic energy flow diagram. The optimization algorithm unit is used to optimize and solve the problem based on a pre-set optimization algorithm when the energy prediction results are unbalanced, and generate the energy scheduling balance results corresponding to each energy medium.

5. The simulation system according to claim 4, characterized in that, The front-end operation module also includes: a production energy coordination unit; The production energy coordination unit is used for: In response to changes in the equipment operating condition timing in the Gantt chart, and based on the changed equipment operating condition timing, the model parameters of each node in the dynamic energy flow chart are updated synchronously. Based on the changed equipment operating time sequence and model parameters, the corresponding production and consumption model is called and the energy prediction results are recalculated; the optimization algorithm in the optimization algorithm unit is called to optimize and solve the recalculated energy prediction results, and the dynamic energy flow diagram is dynamically updated based on the optimized energy scheduling balance results.

6. The simulation system according to claim 5, characterized in that, The backend service module also includes: The simulation analysis unit is used to calculate and analyze the energy dispatch balance results according to the pre-set index calculation rules, and output various analysis indicators; Among them, the various analytical indicators include at least: cost indicators, peak, flat and valley electricity, electricity demand, energy balance rate, pipeline loss rate, energy conversion efficiency, comprehensive energy consumption of processes and unit consumption of media.

7. The simulation system according to claim 6, characterized in that, The front-end operation module also includes: The simulation index display unit is used to visualize various analytical indicators calculated by the simulation analysis unit in the form of numbers and curves.

8. A simulation method for energy flow networks in steel enterprises, characterized in that, include: Configure parameters based on user-input parameters and generate a structured configuration data package; Configure a visual interactive interface based on the configuration data package; A Gantt chart of operating conditions is generated based on the pre-set production and maintenance plan, and a dynamic energy flow diagram is drawn based on user-defined equipment and energy nodes; Based on the operating condition Gantt chart, the dynamic energy flow diagram, and the configuration data package, energy prediction results are calculated using a pre-set production and consumption model. When the energy prediction results are unbalanced, scheduling optimization is performed to obtain energy scheduling balance results.

9. The simulation method according to claim 1, characterized in that, The process of calculating energy forecast results using a pre-set production and consumption model, and performing scheduling optimization when the energy forecast results are unbalanced to obtain an energy scheduling balance result, includes: Based on the equipment operating time sequence provided by the operating condition Gantt chart, and the production and consumption model and model parameters configured for each node in the dynamic energy flow diagram, the energy prediction results corresponding to each energy medium are calculated. When the energy forecast results are unbalanced, an optimization algorithm is used to solve the problem and generate the energy scheduling balance results for each energy medium.

10. The simulation method according to claim 9, characterized in that, The method further includes: In response to changes in the equipment operating condition timing in the Gantt chart, and based on the changed equipment operating condition timing, the model parameters of each node in the dynamic energy flow chart are updated synchronously. Based on the changed equipment operating time sequence and model parameters, the corresponding production and consumption model is called and the energy prediction results are recalculated; the optimization algorithm is called to optimize the recalculated energy prediction results, and the dynamic energy flow diagram is dynamically updated based on the optimized energy scheduling balance results.

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