Comprehensive energy system modeling method and device based on directed multi-graph

Abstract

The invention relates to the technical field of energy management and control, and relates to a directed multi-graph-based integrated energy system modeling method and device, a computer program product and electronic equipment. The method comprises the following steps: constructing a directed multi-graph according to equipment information of an integrated energy system and energy information in an energy process, wherein the directed multi-graph is used for reflecting a coupling relationship between different energies in the integrated energy system; an adjacent matrix of the integrated energy system is constructed according to the directed multi-graph, the adjacent matrix is of a matrix structure representing the energy conversion relation in the integrated energy system, and directed conversion paths and equipment information between energy are reflected through non-null element information of line and column intersection points; and traversing the adjacent matrix to determine a plurality of energy conversion paths of the integrated energy system, and constructing a target coupling matrix model of the integrated energy system according to element information on each energy conversion path. According to the invention, the accuracy, universality and efficiency of integrated energy system modeling can be improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of energy management, and more particularly, to a comprehensive energy system modeling method based on a directed multigraph, a comprehensive energy system modeling device based on a directed multigraph, a computer program product and an electronic device. BACKGROUND

[0002] With the promotion of energy structure transformation, as a collaborative supply system integrating electricity, heat, cold, gas, water and other forms of energy, comprehensive energy system has gradually become a hot spot in the research of energy system. There are various types of internal devices in the comprehensive energy system, and there are complex conversion, distribution and coupling relationships between energies. In order to realize the optimal scheduling, energy management and structure design of the system, it is particularly important to establish an accurate system-level coupling modeling method.

[0003] Traditional modeling methods mostly construct coupling matrices directly through artificial observation of the energy connection relationship between devices in the system. However, this method lacks universality, and when the system structure is complex or the number of devices is large, it is easy to make mistakes and difficult to maintain. When facing frequent changes in devices, system expansion requirements or introduction of energy storage devices, the method of establishing a topological structure model will lead to problems such as increase in data dimension, confusion in modeling logic, complex programming implementation, large modeling calculation amount and low efficiency, which to some extent affect the automatic control optimization of comprehensive energy system based on modeling.

[0004] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present disclosure is to provide a comprehensive energy system modeling method based on a directed multigraph, a comprehensive energy system modeling device based on a directed multigraph, a computer program product and an electronic device, thereby improving the accuracy, universality and efficiency of comprehensive energy system modeling, and providing model support for the optimal control of comprehensive energy system.

[0006] Other characteristics and advantages of the present disclosure will become apparent from the following detailed description, or will be learned by practice of the present disclosure.

[0007] According to one aspect of the present disclosure, a comprehensive energy system modeling method based on a directed multigraph is provided, comprising: constructing a directed multigraph according to device information of a comprehensive energy system and energy information in an energy process, the directed multigraph being used to reflect coupling relationships between different energies in the comprehensive energy system; constructing an adjacency matrix of the comprehensive energy system according to the directed multigraph, the adjacency matrix being a matrix structure representing energy conversion relationships in the comprehensive energy system, and reflecting a directed conversion path between energies and device information through non-empty element information at a row-column intersection point; traversing the adjacency matrix to determine a plurality of energy conversion paths of the comprehensive energy system, and constructing a target coupling matrix model of the comprehensive energy system according to element information on each energy conversion path.

[0008] In an exemplary embodiment of the present disclosure, the directed multigraph takes energy involved in the comprehensive energy system as an energy node, and a directed edge between the energy nodes is marked with device information and energy information corresponding to the energy nodes, and the directed multigraph is a directed multigraph without self-loop and repeated energy nodes; the adjacency matrix of the comprehensive energy system is constructed according to the directed multigraph, comprising: determining the number of rows and columns of the matrix according to preset virtual inputs and virtual outputs and the number of energy categories involved in the comprehensive energy system, the first row and the first column of the matrix representing the virtual inputs, the last row and the last column representing the virtual outputs, and the rows and columns of the matrix adopting the same energy category sorting manner; for a directed edge in the directed multigraph, determining a target position in the matrix according to energy categories at two ends of the directed edge, and taking corresponding device information and energy information as element information of the target position, to obtain the adjacency matrix.

[0009] In an exemplary embodiment of the present disclosure, if there is no directed edge connecting between target energy nodes in the directed multigraph, the positions corresponding to the target energy nodes in the adjacency matrix are set to zero.

[0010] In one exemplary embodiment of this disclosure, traversing the adjacency matrix to determine multiple energy conversion paths of an integrated energy system includes: starting from the element at the top left corner of the adjacency matrix, searching for the first non-zero element in a preset order, and determining the position of the first non-zero element as the current position; based on the current position, searching in the adjacency matrix for reference non-zero elements whose input devices are the same as the output devices at the current position in a preset order, updating the position of the reference non-zero elements to the current position, and returning to the step of determining the first non-zero element, until the output device corresponding to the current position is a virtual output; determining an energy conversion path based on the first non-zero element, the positions corresponding to each reference non-zero element, device information, and energy information; iteratively updating the adjacency matrix according to the energy conversion path, and returning the updated adjacency matrix to the step of searching for the first non-zero element to determine the energy conversion path, until all elements of the obtained adjacency matrix are zero; and determining multiple energy conversion paths of the integrated energy system based on the obtained energy conversion paths.

[0011] In one exemplary embodiment of this disclosure, searching for reference non-zero elements in the adjacency matrix based on the current position, where the input device is the same as the output device at the current position, in a preset order, includes: determining a starting row based on the column number of the current position; and searching in the adjacency matrix in a preset order, starting from the first element of the starting row, to obtain the reference non-zero elements.

[0012] In one exemplary embodiment of this disclosure, iteratively updating the adjacency matrix according to the energy conversion path includes: deleting or retaining non-zero elements in the adjacency matrix according to the input devices and / or output devices corresponding to the non-zero elements on the energy conversion path, and the output devices and / or input devices corresponding to other elements in the adjacency matrix besides the non-zero elements on the energy conversion path, to obtain an updated adjacency matrix.

[0013] In one exemplary embodiment of this disclosure, iteratively updating the adjacency matrix according to the energy conversion path includes: for any non-zero element in the energy conversion path, if the column number of the input device corresponding to another element in the adjacency matrix is ​​the same as the row number of the output device corresponding to the non-zero element in the adjacency matrix, then the non-zero element is retained; otherwise, the non-zero element is deleted; or, if the column number of the output device corresponding to another element in the adjacency matrix is ​​the same as the row number of the input device corresponding to the non-zero element in the adjacency matrix, then the non-zero element is retained; otherwise, the non-zero element is deleted.

[0014] In one exemplary embodiment of this disclosure, constructing a target coupling matrix model of the integrated energy system based on element information on each energy conversion path includes: constructing a coupling matrix for each energy conversion path based on element information on the energy conversion path, wherein the positions of the elements in the coupling matrix are used to reflect the equipment information and energy information included in the energy conversion path; and fusing the coupling matrices corresponding to each energy conversion path to obtain a target coupling matrix model of the integrated energy system.

[0015] In one exemplary embodiment of this disclosure, the coupling matrices corresponding to each energy conversion path are fused to obtain a target coupling matrix model of the integrated energy system, including: adding the coupling matrices corresponding to each energy conversion path according to the corresponding element positions to obtain the target coupling matrix model.

[0016] In one exemplary embodiment of this disclosure, for each energy conversion path, a coupling matrix is ​​constructed based on the element information on the energy conversion path, including: constructing an empty matrix based on the energy nodes of the directed multigraph, wherein the rows and columns of the empty matrix adopt the same energy category sorting method; for each energy conversion path, determining the target position in the empty matrix based on the element information on the energy conversion path, and determining the elements of the target position based on the energy information on the energy conversion path, so as to obtain the coupling matrix of the energy conversion path.

[0017] In one exemplary embodiment of this disclosure, a directed multigraph is constructed based on equipment information of an integrated energy system and energy information in an energy process, including: determining virtual input nodes and virtual output nodes, and representing the energy involved in the integrated energy system as energy nodes, so as to determine graph nodes based on the virtual input nodes, virtual output nodes, and energy nodes; determining directed edges between graph nodes based on energy information to obtain a first directed multigraph, wherein the directed edges of the first directed multigraph are labeled with equipment information and energy information involved in the graph nodes at both ends of the directed edge; simplifying the first directed multigraph based on energy information to obtain a second directed multigraph; and merging the graph nodes in the second directed multigraph based on energy category to obtain a directed multigraph.

[0018] According to one aspect of this disclosure, a modeling apparatus for an integrated energy system based on a directed multigraph is provided, comprising: a graph construction module for constructing a directed multigraph based on equipment information and energy information in the energy process of the integrated energy system, wherein the directed multigraph reflects the coupling relationship between different energies in the integrated energy system; a matrix construction module for constructing an adjacency matrix of the integrated energy system based on the directed multigraph, wherein the adjacency matrix is ​​a matrix structure representing the energy conversion relationship in the integrated energy system, and the non-empty element information of the row and column intersections reflects the directed conversion path between energies and equipment information; and a model construction module for traversing the adjacency matrix to determine multiple energy conversion paths of the integrated energy system, and constructing a target coupling matrix model of the integrated energy system based on the element information on each energy conversion path.

[0019] According to one aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements any of the above methods.

[0020] According to one aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any of the above methods by executing the executable instructions.

[0021] The exemplary embodiment of this disclosure discloses a method for modeling an integrated energy system based on a directed multigraph. This method constructs a directed multigraph based on equipment information and energy information in the energy processes of the integrated energy system. This directed multigraph reflects the coupling relationships between different energies within the integrated energy system. Then, it constructs an adjacency matrix for the integrated energy system based on the directed multigraph. This adjacency matrix is ​​a matrix structure representing the energy conversion relationships within the integrated energy system. The non-empty element information at the row and column intersections reflects the directed conversion paths between energies and the equipment information. Finally, it traverses the adjacency matrix to determine multiple energy conversion paths of the integrated energy system and constructs a target coupling matrix model of the integrated energy system based on the element information of each energy conversion path.

[0022] On the one hand, by constructing a directed multigraph, various energies and energy flow paths are intuitively presented in graph theory form, clearly expressing complex coupling relationships across energy types. On the other hand, the introduction of the adjacency matrix transforms the graph structure into a matrix form that can be efficiently processed by computers. The non-empty elements at row and column intersections accurately record the direction and parameters of the conversion paths, and matrix traversal allows for automated iterative searching of all energy conversion paths, significantly improving the completeness of complex system analysis. Furthermore, the target coupling matrix model integrates path element information, forming a computable model framework. This facilitates obtaining optimal energy flow allocation through matrix operations, and when new equipment is added, only the matrix dimension needs to be expanded without reconstructing the model architecture, making it adaptable to integrated energy systems of different scales. Therefore, the exemplary embodiments of this disclosure utilize a directed multigraph structure to express the energy conversion paths of the system, and iteratively search for energy paths using the adjacency matrix, thereby constructing a coupling matrix model with clear physical meaning and easy programming implementation. This significantly improves the accuracy, versatility, and efficiency of integrated energy system modeling, providing model support for the planning, real-time scheduling, and benefit evaluation of integrated energy systems.

[0023] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0024] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which: Figure 1 A flowchart illustrating an integrated energy system modeling method based on directed multigraphs, representing an exemplary embodiment of this disclosure, is shown.

[0025] Figure 2 A flowchart illustrating an embodiment of constructing a directed multigraph according to an exemplary embodiment of the present disclosure is shown.

[0026] Figure 3 An input-output block diagram of an exemplary system according to an exemplary embodiment of the present disclosure is shown.

[0027] Figure 4 Exemplary embodiments according to this disclosure are shown. Figure 3 The system corresponds to a first type of directed multigraph.

[0028] Figure 5 A schematic diagram of obtaining a second directed multigraph is shown according to an exemplary embodiment of the present disclosure.

[0029] Figure 6 A flowchart illustrating an embodiment of constructing an adjacency matrix according to the present disclosure is shown.

[0030] Figure 7 An exemplary embodiment according to the present disclosure is shown. Figure 5 The adjacency matrix is ​​constructed from the directed multigraph shown.

[0031] Figure 8 A flowchart illustrating an example of determining an energy conversion path according to an exemplary embodiment of the present disclosure is shown.

[0032] Figure 9 A schematic diagram of a path search based on an adjacency matrix according to an exemplary embodiment of the present disclosure is shown.

[0033] Figure 10 A flowchart illustrating a method for constructing a target coupling matrix model according to an exemplary embodiment of the present disclosure is shown.

[0034] Figure 11 A schematic diagram of a coupling process for obtaining a target coupling matrix model according to an exemplary embodiment of the present disclosure is shown.

[0035] Figure 12 A structural diagram of a university laboratory hall energy supply system according to an exemplary embodiment of the present disclosure is shown.

[0036] Figure 13 A block diagram of a direct-connection structure is shown to represent the structure of a power supply system for a university experimental hall, according to an exemplary embodiment of the present disclosure.

[0037] Figure 14 A schematic diagram of system information for a university laboratory hall energy supply system according to an exemplary embodiment of the present disclosure is shown.

[0038] Figure 15 A schematic diagram of system information for another energy supply system for a university experimental hall according to an exemplary embodiment of the present disclosure is shown.

[0039] Figure 16 A schematic diagram of a directed multigraph according to an exemplary embodiment of the present disclosure is shown.

[0040] Figure 17 A schematic diagram of the adjacency matrix of a university experimental hall energy supply system according to an exemplary embodiment of the present disclosure is shown.

[0041] Figure 18 A flowchart illustrating a first path search based on an adjacency matrix of a university experimental hall energy supply system, according to an exemplary embodiment of the present disclosure, is shown.

[0042] Figure 19 The complete process of path search based on adjacency matrix for a university experimental hall energy supply system according to an exemplary embodiment of the present disclosure is shown.

[0043] Figure 20 This diagram illustrates the path parameters of a university experimental hall energy supply system obtained by path search based on an adjacency matrix according to an exemplary embodiment of the present disclosure.

[0044] Figure 21 The diagram illustrates the load conditions of a university laboratory hall energy supply system based on data from a simulation experiment conducted on a summer and winter day, according to an exemplary embodiment of the present disclosure.

[0045] Figure 22 A graph showing the change of control parameters in a dynamic energy management system for a university experimental hall according to an exemplary embodiment of the present disclosure is provided.

[0046] Figure 23 An energy consumption graph based on dynamic energy management according to an exemplary embodiment of the present disclosure is shown.

[0047] Figure 24 A cost diagram of dynamic energy management based on the present disclosure is shown, according to an exemplary embodiment of the present disclosure.

[0048] Figure 25 An energy flow diagram of electrical energy under dynamic energy management based on the present disclosure is shown, according to an exemplary embodiment of the present disclosure.

[0049] Figure 26 An energy flow diagram of thermal energy under dynamic energy management based on the present disclosure is shown, according to an exemplary embodiment of the present disclosure.

[0050] Figure 27 An energy flow diagram of cold energy under dynamic energy management based on the present disclosure is shown according to an exemplary embodiment of the present disclosure.

[0051] Figure 28 A cost diagram of an optimized control system for a university laboratory hall energy supply system, according to an exemplary embodiment of the present disclosure, is shown.

[0052] Figure 29 A schematic diagram of the composition of an integrated energy system modeling apparatus based on directed multigraphs according to an exemplary embodiment of the present disclosure is shown; Figure 30 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown.

[0053] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0054] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0055] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details described, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0056] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0057] With the advancement of energy structure transformation, integrated energy systems, as collaborative supply systems integrating multiple energy forms such as electricity, heat, cooling, gas, and water, have gradually become a research hotspot in energy systems. Integrated energy systems contain a wide variety of equipment, and there are complex conversion, distribution, and coupling relationships between energy sources. To achieve optimized scheduling, energy management, and structural design of the system, establishing accurate system-level coupling modeling methods is particularly important. Traditional modeling methods often rely on energy flow diagrams or manual experience, directly constructing coupling matrices by observing the energy connections between various devices in the system. However, this method lacks universality and is prone to errors and maintenance when the system structure is complex or the number of devices is large.

[0058] In practical implementation, it was found that establishing adjacency matrices for devices as nodes or topological models for energy as edges can lead to increased data dimensionality, chaotic modeling logic, and complex programming implementation when faced with frequent device changes, system expansion needs, or the introduction of energy storage devices. Furthermore, relying on intermediate variables and using iterative methods to construct augmented matrices requires resetting variables for each iteration, resulting in high computational load and low efficiency in the modeling process, which to some extent affects the optimization of automated control of integrated energy systems based on modeling.

[0059] The exemplary embodiments of this disclosure provide a technical solution for modeling a coupling matrix of an integrated energy system based on a directed multigraph. This method uses a graph structure to clearly express energy flow paths and constructs a coupling matrix through iterative search of adjacency matrices. It achieves a modeling process that is highly versatile, low-dimensional, and easy to program, and is applicable to the modeling of integrated energy systems with different system structures. This provides support for the coordinated analysis, supply, and optimization of multiple energy sources in integrated energy systems.

[0060] It should be noted that the modeling method for integrated energy systems based on directed multigraphs of the exemplary embodiments of this disclosure can be applied to the planning, management and design of regional integrated energy systems (such as parks, communities, and cities); multi-energy flow system collaborative optimization scheduling (such as dynamically adjusting the production and distribution of various energy sources such as electricity, heat, and cooling based on load demand, renewable energy output (such as wind power and photovoltaics) and energy prices according to microgrids or regional energy stations); renewable energy consumption and energy storage system optimization; carbon emission reduction and energy efficiency assessment scenarios, etc., without limiting the specific application scenarios.

[0061] like Figure 1 The diagram shown is a flowchart of an exemplary embodiment of the present disclosure of a comprehensive energy system modeling method based on directed multigraphs, with reference to... Figure 1 As shown, the method includes steps S110 to S130, as detailed below: In step S110, a directed multigraph is constructed based on the equipment information and energy information in the energy process of the integrated energy system. The directed multigraph is used to reflect the coupling relationship between different energies in the integrated energy system.

[0062] In step S120, the adjacency matrix of the integrated energy system is constructed based on the directed multigraph. The adjacency matrix is ​​a matrix structure that represents the energy conversion relationship in the integrated energy system. The non-empty element information of the row and column intersection points reflects the directed conversion path between energy and the equipment information. In step S130, the adjacency matrix is ​​traversed to determine multiple energy conversion paths of the integrated energy system, and the target coupling matrix model of the integrated energy system is constructed based on the element information of each energy conversion path.

[0063] Steps S110 to S130 will be described in more detail below.

[0064] In step S110, a directed multigraph is constructed based on the equipment information and energy information in the energy process of the integrated energy system. The directed multigraph is used to reflect the coupling relationship between different energies in the integrated energy system.

[0065] In the exemplary embodiments of this disclosure, equipment information refers to the specific information of the equipment included in the integrated energy system, including but not limited to equipment type and model, and rated energy information of the equipment (such as rated power of electrical energy used, rated electrical efficiency, and thermal efficiency). Energy process refers to the dynamic behaviors involving energy conversion, transmission, and distribution within the integrated energy system. Its function is to describe the flow and interaction relationships of different forms of energy (such as electricity, heat, cold, and gas) in the system. Energy information is the information describing the energy process, including but not limited to energy type, energy conversion efficiency, and energy distribution parameters. In actual implementation, equipment information and energy information in the energy process of the integrated energy system can be collected. For example, the electrical energy distribution coefficient is implemented by the power electronic controller that distributes electrical energy, referred to as an energy router; the natural gas distribution coefficient is implemented by the valve controller that distributes natural gas; the heat energy distribution coefficient is implemented by the valve controller that controls the flow rate of hot water pipes; the cold energy distribution coefficient is implemented by the valve controller that controls the flow rate of cold air pipes; and the coefficient of performance of a refrigerator, etc. These coefficients can be flexibly determined according to the actual needs of the scenario, and the exemplary embodiments of this disclosure do not impose any limitations on them.

[0066] Directed multigraphs are a core data structure for modeling integrated energy systems, used to formally represent the coupling relationships between different forms of energy (such as electricity, heat, cold, and gas). Their core characteristics are: energy as nodes, energy processes (conversion / transfer / distribution) as edges, and the description of complex energy interaction processes through directionality and multiplicity.

[0067] In some optional embodiments, the directed multigraph uses the energy involved in the integrated energy system as energy nodes, and the directed edges between energy nodes are labeled with the corresponding equipment information and energy information. The directed multigraph is a directed multigraph without self-loops and without repeating energy nodes. Figure 2 The diagram shows a flowchart for constructing a directed multigraph, which includes: Step S210: Determine the virtual input node and the virtual output node, and represent the energy involved in the integrated energy system as energy nodes, so as to determine the graph nodes based on the virtual input node, the virtual output node and the energy nodes.

[0068] The virtual input node serves as the input side (i.e., the source side) and is connected to the energy network of the integrated energy system. The virtual input node may include at least one type of energy, such as natural gas, or it may include both electricity and natural gas. In other words, the integrated energy system may be supplied with electricity and natural gas by the power grid and the natural gas grid. Of course, in some scenarios, it may also include photovoltaic equipment supplying electricity, etc. The exemplary embodiments of this disclosure do not impose any special limitation on the number of virtual input nodes.

[0069] The virtual output node acts as the output side (i.e., the load), serving as the output side of the integrated energy system. For example, the output side of the integrated energy system connects to the experimental hall, providing the necessary energy to the experimental hall. The experimental hall may also include laboratories, control rooms, experimental platforms, power distribution control equipment, and lighting equipment, etc. The exemplary embodiments of this disclosure do not specifically limit the specific composition of the output side.

[0070] As an example, such as Figure 3 The diagram shown is an input-output block diagram of an exemplary system, such as... Figure 3 As shown, this integrated energy system includes a combined heat and power (CHP) unit and a compression electric refrigeration group (CERG), involving four categories of energy: natural gas, electricity, heat, and cold. Virtual input nodes V(I) and virtual output nodes V(O) can be determined, and the energy output from all devices is represented as energy nodes. Based on the virtual input nodes, virtual output nodes, and energy nodes, the graph nodes of the directed multigraph are determined.

[0071] Step S220: Determine the directed edges between graph nodes based on the energy information to obtain a first directed multigraph. The directed edges of the first directed multigraph are labeled with the device information and energy information involved in the graph nodes at both ends of the directed edges.

[0072] The energy information includes energy conversion relationships, thus allowing directed edges to be generated between graph nodes, resulting in a first directed multigraph. The direction of the directed edges indicates the energy flow. Each directed edge is labeled with information about the equipment and energy involved, such as equipment name and energy conversion efficiency, on both ends of the graph node.

[0073] In some optional embodiments, if the energy output direction of a target graph node is connected to multiple directed edges, then a number of sub-loops equal to the number of directed edges are added to the target graph node, and the energy allocation parameters corresponding to the directed edges of each sub-loop are labeled. That is, when the energy of a target graph node will be allocated to directed edges of different branches, a number of sub-loops equal to the number of branches can be added to the target graph node, and the energy allocation parameters corresponding to their respective branches can be labeled for the sub-loops.

[0074] As an example, Figure 4 It shows Figure 3 The system corresponds to the first directed multigraph, where I is a virtual input node, O is a virtual output node, and Ng I For natural gas nodes, Ee CHP As an energy node, He CHP For thermal nodes, Ce CERGFor cold energy nodes, directed edges are added between graph nodes to indicate the direction of energy flow. These directed edges also indicate the equipment and energy information involved in the graph nodes at both ends of the edge. For example, for Ng... I Nodes and Ee CHP The directed edges between nodes are reinforced with device information (CHP) and energy information (η). Ee (Energy conversion efficiency), Ee CHP Nodes and Ce CERG Add device information CERG and energy information COP to the directed edges between nodes. CERG (Coefficient of performance). In addition, due to Ee CHP If a node's energy output direction is connected to two directed edges, then for that node's energy output direction... CHP Add two sub-rings to the node and label the energy allocation parameters (such as ρ1 and ρ2) of the directed edges corresponding to each sub-ring.

[0075] It should be understood that virtual input nodes and virtual output nodes do not involve energy conversion between devices, so no device information or energy information is added to the directed edges connecting these two nodes.

[0076] Step S230: Simplify the first directed multigraph based on the energy information to obtain the second directed multigraph.

[0077] Considering that in an integrated energy system, each form of energy can flow along a specific path, and that energy flow includes energy conversion, efficiency changes, and energy losses, the parameters on each path can be represented as the product of the parameters of each directed edge in that path. This means that the parameters on the directed edges can flow along the direction of energy flow, while the product of the parameters along the entire path remains unchanged. Based on this, an exemplary embodiment of this disclosure simplifies the first directed multigraph by utilizing the parameter flow of a directed multigraph. Specifically, the process includes: First, starting from the virtual input node, the energy information marked on the directed edges of the first directed multigraph is moved along the direction of the directed edge until it is impossible to move to a new directed edge.

[0078] Specifically, if a tail graph node of a target directed edge has a sub-cycle, the energy information marked on the target directed edge will no longer be moved. Furthermore, if a target directed edge exists, the energy allocation parameters corresponding to the sub-cycle of the target directed edge will be added to the directed edge in the energy output direction of the tail graph node, and the sub-cycle will be deleted.

[0079] This can be understood as meaning that "until it can no longer move to a new directed edge" refers to the energy information moving to a directed edge connected to the virtual output node, or the tail graph node of the energy information having a sub-cycle. For a target directed edge, the sub-cycle on the corresponding tail graph node is deleted, and the energy allocation parameter corresponding to the sub-cycle is added to the directed edge in the energy output direction of the tail graph node.

[0080] Secondly, device information is added to each directed edge to represent the energy conversion medium between the graph nodes connected by the directed edge.

[0081] As an example, Figure 5 A schematic diagram of obtaining a second directed multigraph is shown, and the simplified process is explained in conjunction with the first directed multigraph described above.

[0082] Starting with the virtual input node, the parameters (energy information) on each directed edge flow along the outflow direction of the node at the tail of the edge. If the tail node of a directed edge has a child cycle, the parameters do not flow. For example, edge (Ng) I -He CHP) The parameters (CHP, ηHe) are derived from the tail graph node (He) of this edge. CHP The outflow direction is towards the edge (He) CHP -O). But there are directed edges (Ng) I -Ee CHP The parameters of ) cannot flow because of the tail graph node (Ee) CHP It has sub-rings.

[0083] Since the number of sub-loops is the same as the number of directed edges in the branches of the tail graph nodes, the energy allocation parameters on the sub-loops of the tail graph nodes are assigned to the directed edges in the output direction of the tail graph nodes, for example, node (Ee). CHP It has two sub-rings with energy allocation parameters (ρ1) and (ρ2) respectively, which are allocated to the edge (Ee). CHP -Ce CERG ) and (Ee CHP After -O), these sub-rings can be deleted.

[0084] Furthermore, after completing the parameter flow, device information can be added to each directed edge to indicate which devices (i.e., energy conversion media) are involved in the energy conversion. For example, (CHP-CERG) can be added to the edge connecting Ee and Ce, and (CHP-O) can be added to the edge connecting Ee and O to obtain a second directed multigraph.

[0085] By using parameter flow, sub-cycles in the first directed multigraph can be removed, simplifying the modeling process and making it clearer.

[0086] Step S240: Merge the graph nodes in the second directed multigraph according to the energy category to obtain a directed multigraph.

[0087] Considering that integrated energy systems may obtain the same type of energy from different devices—for example, thermal energy may be output from both a combined heat and power (CHP) unit and an auxiliary boiler unit—there may be duplicate energy nodes in the directed multigraph. Therefore, such nodes need to be merged.

[0088] In this process, graph nodes with the same energy category in the second directed multigraph can be merged to obtain a merged node. Then, all directed edges connected to the graph nodes with the same energy category can be switched to the merged node to obtain a directed multigraph.

[0089] It should be noted that the above examples are for illustrative purposes only. The number and types of graph nodes in the directed multigraph of the exemplary embodiments of this disclosure may be more complex and are determined according to the actual scenario.

[0090] The exemplary embodiments of this disclosure clarify the system input / output boundaries by defining virtual input nodes and virtual output nodes. This means that external energy supply and internal demand are incorporated into a unified topology through virtual nodes, avoiding the problem of ambiguous boundary conditions in modeling and facilitating global energy flow analysis. Furthermore, each directed edge precisely corresponds to a physical device or transmission path, preserving the original data granularity. Multiple devices with the same energy conversion direction are independently expressed through multiple edges (sub-loops), avoiding information loss and further refining device-level modeling. Simplifying the process reduces the number of sub-loops, improving computational speed. Merging graph nodes according to energy categories avoids graph size explosion caused by energy subdivision while preserving multi-energy coupling relationships. Simultaneously, the merged nodes directly correspond to the "energy layer" in the hierarchical model (i.e., adapting to the hierarchical network structure), facilitating subsequent generation of inter-layer matrices.

[0091] As can be seen, the exemplary embodiments of this disclosure achieve a high-precision, low-redundancy, and highly computable multi-energy coupling representation in the modeling of integrated energy systems through a phased directed multigraph construction method of virtual node introduction → preliminary graph construction → simplification → node merging.

[0092] In step S120, an adjacency matrix of the integrated energy system is constructed based on the directed multigraph. The adjacency matrix is ​​a matrix structure that represents the energy conversion relationship in the integrated energy system. The non-empty element information of the row and column intersections reflects the directed conversion path and equipment information between energy.

[0093] In the exemplary embodiments of this disclosure, the adjacency matrix is ​​used to describe the conversion relationships and device connections between different energy nodes (such as electricity, heat, natural gas, etc.) in the system. Its core function is to convert complex directed multigraphs (containing multiple edges and different energy types) into a matrix form that can be efficiently processed by a computer, facilitating subsequent path analysis, optimization calculations, and system simulation. Figure 6 A flowchart for constructing an adjacency matrix is ​​shown, which includes the following steps: Step S610: Determine the number of rows and columns of the matrix based on the preset virtual inputs and virtual outputs and the number of energy categories involved in the integrated energy system. The first row and first column of the matrix represent virtual inputs, and the last row and last column represent virtual outputs. The rows and columns of the matrix adopt the same energy category sorting method.

[0094] A virtual input and a virtual output are pre-set. The virtual input and virtual output can be determined based on the virtual energy. The virtual input represents the source side of the external energy input to the system, and the virtual output represents the load side of the energy supplied by the system. The data of the virtual input and virtual output are collected by the data collection device of the control node and transmitted to the system controller through the data bus.

[0095] The adjacency matrix can be a square matrix. If the integrated energy system includes n types of energy, one virtual input, and one virtual output, a matrix of size (n+2)×(n+2) can be obtained. This can be understood as determining the number of rows and columns of the matrix based on the preset number of virtual inputs, the number of virtual outputs, and the total number of energy categories involved in the integrated energy system.

[0096] In a given matrix, the first row and first column represent virtual inputs, and the last row and last column represent virtual outputs. The rows and columns of the matrix in the middle rows are ordered by the same energy category; that is, the middle n rows and n columns arrange n types of energy in the same order. Figure 5 Taking the directed multigraph shown as an example, the integrated energy system involves four types of energy (electricity Ee, natural gas Ng, heat He, and cold energy Ce, respectively). The corresponding adjacency matrix is ​​a 6-row, 6-column matrix, where the rows and columns of the matrix are sorted by energy category as I (virtual input node), Ee, Ng, He, Ce, and O (virtual output node).

[0097] Step S620: For directed edges in a directed multigraph, determine the target position in the matrix according to the energy categories at both ends of the directed edge, and use the corresponding device information and energy information as the element information of the target position to obtain the adjacency matrix.

[0098] This can be understood as using the device and energy information on the directed edges of a directed multigraph as the element information of the corresponding position in the adjacency matrix. In other words, the corresponding position in the adjacency matrix is ​​marked as the device and energy information corresponding to each directed edge.

[0099] As an example, still using Figure 5 Taking the directed multigraph shown as an example, for the device information and energy information corresponding to edge (I-Ng) as ((II)1), the first row is determined according to "I", and the third column is determined according to "Ng". Then, '(II)1' is marked in the first row and third column of the adjacency matrix (target position), i.e., C I-O (I, Ng), C I-O Used to represent the adjacency matrix. Similarly, C I-O (He, O) indicates that the target position in the adjacency matrix is ​​the position in the 4th row and 6th column. Then, the corresponding device information and energy information "((CHP-O)η" will be entered. He ()” serves as the element information for the target location.

[0100] Of course, if there are target energy nodes in a directed multigraph that are not connected by directed edges, then the position corresponding to the target energy node in the adjacency matrix is ​​set to zero. This can be understood as the element information being (0) when there are no directed edges between energy nodes.

[0101] According to the above method, the following can be obtained: Figure 5 The adjacency matrix constructed from the directed multigraph shown is as follows: Figure 7 As shown.

[0102] The exemplary embodiments of this disclosure use the first row and first column of the adjacency matrix to represent virtual inputs, representing external energy inputs, enabling the model to uniformly handle boundary conditions. The last row and last column represent virtual outputs, representing the final energy demand, preventing energy flow from terminating at arbitrary internal nodes. In other words, it clearly distinguishes between internal system transformations and external interactions, facilitating the calculation of energy input-output balance and supporting multi-energy collaborative optimization. Self-connection of nodes (e.g., "electricity → electricity") is prohibited in the directed multigraph to avoid logical redundancy. Each energy type corresponds to only a single node, ensuring matrix compactness, thereby reducing invalid computations, improving matrix operation efficiency, and preventing energy loops from interfering with optimization results. Furthermore, the matrix rows and columns are sorted by the same energy category, ensuring consistency in transformation path directions. Each directed edge is mapped to the target position in the matrix according to the energy types at its two ends. This not only transforms the complex graph structure into a sparse matrix storage, saving memory space, but also supports dynamic updates to adapt to real-time scheduling requirements.

[0103] In step S130, the adjacency matrix is ​​traversed to determine multiple energy conversion paths of the integrated energy system, and the target coupling matrix model of the integrated energy system is constructed based on the element information of each energy conversion path.

[0104] In an exemplary embodiment of this disclosure, after obtaining the adjacency matrix, the energy conversion path can be obtained by iteratively searching the adjacency matrix, and then the element information on the energy conversion path can be used to construct the target coupling matrix.

[0105] Figure 8 A flowchart for determining an energy conversion path is shown, the process including: Step S810: Starting from the element at the top left corner of the adjacency matrix, search for the first non-zero element in a preset order, and determine the position of the first non-zero element as the current position.

[0106] The preset order can be to start from the row containing the starting point in the adjacency matrix and search row by row from left to right. When the first non-zero element is found, the position of the first non-zero element is marked as the current position. In addition, the current position and the element information of the current position (such as device information and energy information) can also be recorded.

[0107] As an example, with Figure 7 Taking the adjacency matrix shown as an example, if its first non-zero element is located in the 1st row and 3rd column, then the current position is determined to be C. I-O (I, Ng), whose device information includes input device "I", output device "I", and energy information "1", its energy conversion process can be represented as: Formula 1 Step S820: Based on the current position, search the adjacency matrix for reference non-zero elements that are the same as the input device and the output device at the current position in a preset order, update the position of the reference non-zero element to the current position, and return to the step of determining the first non-zero element, until the output device corresponding to the current position is a virtual output.

[0108] The starting row can be determined based on the column number of the current position. Starting from the first element of the starting row, the adjacency matrix is ​​searched in a preset order to obtain the reference non-zero element. Then, the position of the reference non-zero element is updated to the current position, and the process returns to the step of determining the first non-zero element, continuing the search in the adjacency matrix until the output device corresponding to the current position is a virtual output.

[0109] As an example, the current position C is obtained above. I-OAfter (I, Ng), the column number "Ng" is used to determine the starting row as the row number for the new iteration. Then, starting from the first element of row "Ng", the search for the first non-zero element in the adjacency matrix begins. Therefore, starting from row "Ng" (i.e., row 3), the first non-zero element found from left to right is in row 2, column 2, i.e., position C. I-O (Ng, Ee), its device information includes input device "I", output device "CHP", and energy information "η". Ee "This input device is the same as the C in the previous search." I-O The output "I" of (I, Ng) is the same, which meets the search requirements. Its energy conversion process can be represented as: Formula 2 Then, update the current position to C. I-O (Ng, Ee), and continue searching in the adjacency matrix for reference non-zero elements that are the same as the input device and the output device at the current position in a preset order.

[0110] Repeat the search process described above until the output device at the current location is a virtual output "O".

[0111] Step S830: Determine the energy conversion path based on the position, equipment information, and energy information of the first non-zero element and each reference non-zero element.

[0112] After the iteration stops because the output device at the current location is a virtual output, the energy conversion processes are connected based on the first non-zero element, the position, device information, and energy information corresponding to each reference non-zero element, to obtain a complete energy conversion path. As in the example above, the first complete energy conversion path is: Formula 3 Step S840: Iteratively update the adjacency matrix according to the energy conversion path, and return the updated adjacency matrix to the step of searching for the first non-zero element to determine the energy conversion path, until all elements of the obtained adjacency matrix are zero.

[0113] This can be understood as follows: after obtaining a complete energy conversion path, the adjacency matrix needs to be updated, and based on the updated adjacency matrix, the process returns to the step of searching for the first non-zero element. This process is repeated, traversing the updated adjacency matrix to search for the next energy conversion path. The stopping condition for this iterative loop is that all elements of the adjacency matrix obtained during the process are zero.

[0114] Specifically, based on the input devices and / or output devices corresponding to the non-zero elements on the energy conversion path, and the output devices and / or input devices corresponding to the other elements in the adjacency matrix besides the non-zero elements on the energy conversion path, the non-zero elements in the adjacency matrix are deleted or retained to obtain the updated adjacency matrix.

[0115] Specifically, this step processes the non-zero elements on each obtained energy conversion path and correspondingly processes the non-zero elements in the adjacency matrix to obtain an updated adjacency matrix. Specifically, for any non-zero element in the energy conversion path, if the column number of the input device corresponding to another element in the adjacency matrix is ​​the same as the row number of the output device corresponding to the non-zero element in the adjacency matrix, the non-zero element is retained; otherwise, the non-zero element is deleted.

[0116] Alternatively, if the column number of the output device corresponding to another element in the adjacency matrix is ​​the same as the row number of the input device corresponding to the non-zero element in the adjacency matrix, then the non-zero element is retained; otherwise, the non-zero element is deleted.

[0117] As an example, for path 1, C in the adjacency matrix I-O The element of (I, Ng) is ((II)1). Check if the non-zero elements outside path 1 contain either an output device of 'I' in column 'I' or an input device of 'I' in row 'Ng'. Element C was found. I-O The input to (Ng, Ee) is 'I', so the position C in the adjacency matrix is... I-O The element ((II)1) of (I, Ng) is retained in the new adjacency matrix. Correspondingly, for C... I-O (Ee, Ce), whose corresponding element is ((CHP-CERG)ρ1). Outside of path 1, the output device in column 'Ce' does not contain 'CHP', and the input device in row 'Ce' does not contain 'CERG'. Therefore, the element at position CI-O(Ee, Ce) in the new adjacency matrix is ​​(0). Using this method, Figure 7 The corresponding adjacency matrix is ​​updated to obtain the updated adjacency matrix, and based on this, the process returns to the step of obtaining the first non-zero element to search for the second energy conversion path. For example... Figure 9 The diagram shows the trajectory of the path search based on the adjacency matrix in the above example. By repeating the search process described above, in addition to path 1 shown in Equation 3, the following two paths are also obtained: Formula 4 Formula 5 Step S850: Based on the obtained energy conversion paths, determine multiple energy conversion paths of the integrated energy system.

[0118] Through the iterative search process described above, the obtained energy conversion paths are identified as multiple energy conversion paths of the integrated energy system.

[0119] The exemplary embodiments disclosed herein ensure that all possible paths are covered by a fixed starting point (top left corner) and a preset search order, avoiding omissions. Furthermore, the paths always start from a virtual input and end at a virtual output, guaranteeing the integrity and rationality of the energy flow and significantly improving the reliability of path searching. Iterative updates of the "current position," i.e., matching the "current output device" with the "next input device" (i.e., the association between column and row numbers in the matrix), enable automatic path concatenation. Irrelevant elements are deleted after each iteration, accelerating subsequent searches and improving accuracy, preventing redundant calculations. The search terminates when all elements are deleted, ensuring that all feasible paths are enumerated and avoiding infinite loops, making it suitable for large-scale integrated energy systems. In addition, by fully recording the parameters of each path (location, device information, energy information), a traceable data foundation is provided for energy efficiency analysis.

[0120] After obtaining multiple energy conversion paths of the integrated energy system, a target coupling matrix can be constructed based on the element information of the energy conversion paths, such as... Figure 10 The diagram shows a flowchart for constructing a target coupling matrix model, which includes: Step S1010: For each energy conversion path, construct a coupling matrix based on the element information of the energy conversion path.

[0121] The positions of the elements in the coupling matrix reflect the equipment and energy information included in the energy conversion path. Specifically, constructing the coupling matrix for each energy conversion path includes: First, an empty matrix is ​​constructed based on the energy nodes of the directed multigraph. The rows and columns of the empty matrix are sorted in the same way according to the energy category.

[0122] In this example, the rows and columns of the empty matrix are sorted using the same energy category as the rows and columns of the adjacency matrix. For instance, if the example above includes four types of energy nodes, a 4×4 matrix is ​​constructed, and the rows and columns are sorted using the order Ee, Ng, He, Ce.

[0123] Secondly, for each energy conversion path, the target position in the empty matrix is ​​determined based on the element information on the energy conversion path, and the elements of the target position are determined based on the energy information on the energy conversion path to obtain the coupling matrix of the energy conversion path.

[0124] For any energy conversion path, except for the input node I and the output node O, the category of the energy node at the end of the path is used as the row number, and the category of the energy node at the starting point is used as the column number, so as to determine the target position corresponding to the path in the empty matrix.

[0125] Taking path 1 above as an example, its corresponding energy conversion process is from "Ng" to "Ce". Therefore, the position with column number "Ng" and row number "Ce" in the empty matrix is ​​determined as the target position. The product of the element information (energy information) along this path is taken as the element of the target position, as shown in Equation 6: Formula 6 Among them, H path1 This is the coupling matrix for path 1. Similarly, the coupling matrices for paths 2 and 3 can be obtained respectively.

[0126] Step S1020: Merge the coupling matrices corresponding to each energy conversion path to obtain the target coupling matrix model of the integrated energy system.

[0127] After obtaining the coupling matrix of each energy conversion path, the coupling matrices corresponding to each energy conversion path can be added together according to the corresponding element positions to obtain the target coupling matrix model.

[0128] As an example, continuing with the example above, we add the corresponding elements of the coupling matrices of each path to obtain the target coupling matrix model. For example... Figure 11 The diagram shows the coupling process for obtaining the target coupling matrix model, where H is the target coupling matrix model.

[0129] An exemplary embodiment of this disclosure transforms a linear path into a local coupling matrix, preserving path details and reflecting cross-energy dependencies. Furthermore, it merges the corresponding elements of each path coupling matrix according to weights (such as path utilization) to form a target coupling matrix model, thereby achieving visualization and quantification of global coupling relationships and providing a more intuitive basis for system planning.

[0130] The following uses the integrated energy system as an example of the energy supply system for a university experimental hall (a building-type integrated energy system) to illustrate the modeling method of the integrated energy system based on directed multigraphs in the exemplary embodiments of this disclosure.

[0131] like Figure 12 The diagram shows the structure of the energy supply system for the university's experimental hall. The system's external connections include an input side (source side) and an output side (load). The input side connects to the energy network, receiving electricity and natural gas from the power grid and natural gas network. Additionally, the input side includes photovoltaic equipment to supply electricity. The output side connects to the experimental hall, which covers approximately 1062 square meters and consists of three sub-laboratories and a control room. The main energy-consuming units within the experimental hall include: ① three sets of water pump experimental platforms; ② one set of water quality monitoring experimental platforms; ③ one set of circulating water experimental platforms; ④ power distribution and control equipment; and ⑤ the lighting and staff power consumption of the experimental hall.

[0132] The system's internal components include various energy conversion devices, specifically: ① a combined heat and power (CHP) unit, which uses a micro gas turbine to generate electricity and a heat recovery device to produce heat, enabling the conversion of natural gas into electricity and heat; ② a gas boiler (GB), which uses gas combustion to heat water, enabling the conversion of natural gas into heat; ③ an electric refrigerator (EC), which uses electricity to start a compressor for refrigeration, enabling the conversion of electricity into cold energy, with air as the primary carrier; and ④ an absorption refrigerator (AC), which uses refrigerant to absorb heat and generate cold energy, enabling the conversion of heat into cold energy. The parameters for these devices are obtained based on equipment selection and dynamic fitting in the actual scenario.

[0133] The system can achieve cascaded energy utilization during operation. Its operation process includes: ① Natural gas combustion drives a micro gas turbine to generate electricity, which is directly supplied to the output side and electric chiller for cooling; ② The waste heat of the micro gas turbine is absorbed to heat water, and the hot water is supplied to the output side and absorption refrigeration unit for cooling; ③ The gas boiler serves as an auxiliary heating device to supplement heat energy.

[0134] For ease of understanding, use Figure 13 The diagram shown represents a direct-connection system. In actual modeling, some information is needed for each directed connection, including: ① the number of lines; ② input and output devices; ③ the form (type) of energy before and after conversion on the line; ④ the energy transmission efficiency of the lines (included in energy information); and ⑤ the allocation coefficients set at control nodes to control energy distribution (included in energy information). This information is specifically as follows: Figure 14 As shown, where L i This indicates the energy flow path, including specific information such as... Figure 15 As shown, L101 and L102 represent lines from the power grid and the natural gas grid, respectively; L41 and L42 are two branch lines generated in the combined heat and power (CHP) process; 'In' represents equipment connected to the front end of the production line; 'Out' represents equipment connected to the end of the line; 'ETB' represents the energy form before conversion on this line; 'ETA' represents the energy form after conversion on this line.

[0135] After acquiring the device information and energy information in the energy process of the system, a directed multigraph is constructed according to the method of the exemplary embodiment described above. For example, Figure 16This is a schematic diagram of a directed multigraph, in which each energy node represents a type of energy, each directed edge represents the transfer of energy, the parameters on the directed edges represent the energy conversion relationship, and the output degree of the node represents the distribution of energy. That is, on each output edge, the output energy needs to be multiplied by the distribution coefficient (i.e., the energy distribution parameter).

[0136] See also Figure 16 The system contains four types of energy: electricity, natural gas, heat, and cold energy, in addition to two virtual energy sources (virtual input and virtual output). Therefore, the energy adjacency matrix (C) I-O The size of the matrix is ​​6×6. According to the aforementioned construction method, the elements of the coupling matrix are positioned based on the 'front-end (input) energy form' and 'back-end (output) energy form' of each path, and are filled with the device information and energy information of each path, i.e., input devices, output devices, and conversion efficiency, etc. Empty positions are filled with '0', thus obtaining the adjacency matrix of the system. For example... Figure 17 The diagram shown illustrates how the system obtains the adjacency matrix.

[0137] Furthermore, regarding Figure 17 The adjacency matrix shown is traversed to determine multiple energy conversion paths of the system, and a target coupling matrix model of the integrated energy system is constructed based on the element information of each energy conversion path. The process for searching the first path can be found in [reference needed]. Figure 18 As shown. After the search, the energy traversed by path 1 is as follows: Figure 18 As shown by the dashed line, the parameters (equipment information and energy information) of this path can be represented by the product of all parameters on the path. Figure 18 The circuit in the diagram can be represented as follows: the energy flow is “Source--Ee--Ce--Load”, the parameter (energy information) is “θ2θ3”, and the parameter details are “α2α3(1-ρ1) COP”. EC ".

[0138] Similarly, the path search can be performed using the method described in the example above. Figure 19 This demonstrates the complete process of path search based on adjacency matrix for the power supply system of the university's experimental hall. Correspondingly, the path parameters for all paths are as follows: Figure 20 As shown.

[0139] Finally, for each energy conversion path, a coupling matrix is ​​constructed based on the element information of the energy conversion path, and the coupling matrices corresponding to each energy conversion path are fused to obtain the target coupling matrix model of the system, as shown in Equation 7: Formula 7 As mentioned above, since the system includes four energy categories (Ee, Ng, He, Ce), the coupling matrix model shown in Equation 7 is a 4×4 coupling matrix, where the matrix Source is a matrix composed of source inputs (virtual input nodes).

[0140] Since the specific details of constructing the directed multigraph, constructing the adjacency matrix, path search, and constructing the coupling matrix have been described in the exemplary embodiments above, they will not be repeated here.

[0141] The following section uses the energy supply system of the aforementioned university experimental hall as an example to illustrate the dynamic optimization control of the energy of the integrated energy system based on the target coupling matrix model. The control variables for energy management of the integrated energy system using the target coupling matrix model include: ① and These two parameters are power distribution parameters, which are used by power electronic devices to distribute electrical energy through current control; ② This parameter is regulated by the natural gas valve; ③ and These two parameters are controlled by the valves in the hot water pipes, which manage the distribution of hot water.

[0142] Specifically, in energy management, the optimizer aims to minimize the system's input energy cost. It establishes equality constraints using the objective coupling matrix model and inequality constraints using the energy input range of the equipment, as shown in Equation 8. This is a nonlinear constrained optimization problem, and the interior point method is used as the solution algorithm. Formula 8 Furthermore, based on the system's load data, to reflect the impact of ambient temperature, simulation experiments were conducted using data from a summer and a winter day. The load conditions are as follows: Figure 21 As shown, (a) represents the simulation result on a summer day, and (b) represents the simulation result on a winter day.

[0143] like Figure 22 The diagram shows the control parameter variation curves for the dynamic energy management of this disclosure. (a) represents the control parameter variation curves of the system in summer, and (b) represents the control parameter variation curves of the system in winter. It can be seen that multiple control parameters remain constant, while only one control parameter shows a significant change. This is because the energy management does not consider the dynamic performance of the equipment and lacks constraints on the equipment; therefore, optimization results can often be achieved by controlling only a few parameters. Figure 23 The diagram shows the energy consumption of the system under dynamic energy management based on this disclosure. (a) is the energy consumption distribution of the system under dynamic optimization control on a summer day, and (b) is the energy consumption distribution of the system under dynamic optimization control on a winter day. Figure 24The figures shown are cost diagrams for dynamic energy management based on this disclosure. (a) shows the cost of the system under dynamic optimization control on a summer day, and (b) shows the cost of the system under dynamic optimization control on a winter day. Figure 23 and Figure 24 It can be seen that the experimental hall, which originally consumed only electricity, achieved the complementarity of electricity, natural gas, and solar energy when powered by the integrated energy system, realizing the utilization of clean energy. This integrated energy supply system, through the adjustment of control parameters, can achieve optimized allocation of electricity and natural gas. Compared to before the application of the integrated energy supply system, when using only electricity, with grid electricity prices of 1 yuan / kWh and natural gas prices of 2.67 yuan / cubic meter, the average daily energy savings in summer and winter can reach approximately 37% and 49%, respectively.

[0144] Through energy management, the energy flow of electrical, thermal, and cold energy in the energy supply system is as follows: Figures 25 to 27 As shown, in each figure, (a) represents the result of the system on a summer day, and (b) represents the result of the system on a winter day. Combined with... Figures 25-27 It can be seen that the electricity is mainly provided by CHP, which can effectively reduce the power consumption of the grid and reduce energy costs. When the power supply capacity of CHP is insufficient, such as at 9:00 and 14:00, the photovoltaic and grid provide supplementary electricity. The heat energy is mainly provided by CHP, while the GB provides supplementary heat energy. The cooling energy is supplied by EC and AC in a complementary manner, which reflects the cooling capacity of electricity and natural gas respectively.

[0145] In addition, when calculating the benefits of optimized control methods, the following economic factors can also be considered: ① The project cycle is 10 years; therefore, the cost of equipment, systems, and other one-time investments is divided by 10 to obtain the annual cost; ② In 2019, the grid electricity price and natural gas price were RMB 1 / kWh and RMB 2.67 / cubic meter, respectively; ③ The government provides support for new energy projects. For example, the provincial government provides a power generation subsidy of RMB 0.42 / kWh for distributed photovoltaic power generation projects. At the same time, the provincial government and the municipal government each provide an installation subsidy of RMB 1 / watt.

[0146] Therefore, in energy management using the target coupling matrix model, the cost of the system after optimized control is as follows: Figure 28 As shown. By Figure 28 It can be seen that, in energy management using the target coupling matrix model, the annual cost of the system after optimized control is approximately 202,453.50 yuan. Before using this integrated energy system, the only energy source used in the experimental hall was electricity, with an annual electricity consumption of approximately 464,928.41 kWh and an electricity cost of 464,928.41 yuan. Calculations show that after constructing and using the integrated energy system for energy supply and implementing energy management, energy costs are reduced by approximately 56.45%.

[0147] The exemplary embodiment of this disclosure, which uses a directed multigraph-based integrated energy system modeling method, firstly, constructs a directed multigraph to intuitively represent various energy types and energy flow paths in graph theory form, clearly expressing complex coupling relationships across energy types. Secondly, the introduction of an adjacency matrix transforms the graph structure into a matrix form that can be efficiently processed by a computer. The non-empty elements at row and column intersections accurately record the direction and parameters of the conversion paths, and matrix traversal allows for automated iterative searching of all energy conversion paths, significantly improving the completeness of complex system analysis. Furthermore, the target coupling matrix model integrates path element information, forming a computable model framework. This facilitates obtaining optimal energy flow allocation through matrix operations, and when new equipment is added, only the matrix dimension needs to be expanded without reconstructing the model architecture, making it adaptable to integrated energy systems of different scales. Therefore, the exemplary embodiment of this disclosure utilizes a directed multigraph structure to express the energy conversion paths of the system, and iteratively searches for energy paths using an adjacency matrix, thereby constructing a coupling matrix model with clear physical meaning and easy programming implementation. This significantly improves the accuracy, versatility, and efficiency of integrated energy system modeling, providing model support for the planning, real-time scheduling, and benefit evaluation of integrated energy systems.

[0148] In an exemplary embodiment of this disclosure, a comprehensive energy system modeling apparatus based on directed multigraphs is also provided. (See reference...) Figure 29 As shown, the device 2900 may include a graph construction module 2910, a matrix construction module 2920, and a model construction module 2930. Specifically: The graph construction module 2910 is used to construct a directed multigraph based on the equipment information and energy information in the energy process of the integrated energy system. The directed multigraph is used to reflect the coupling relationship between different energies in the integrated energy system. The matrix construction module 2920 is used to construct the adjacency matrix of the integrated energy system based on the directed multigraph. The adjacency matrix is ​​a matrix structure representing the energy conversion relationship in the integrated energy system. The non-empty element information of the row and column intersections reflects the directed conversion path between energies and the equipment information. The model construction module 2930 is used to traverse the adjacency matrix to determine multiple energy conversion paths of the integrated energy system, and construct the target coupling matrix model of the integrated energy system based on the element information on each energy conversion path.

[0149] Since the details of each functional module of the integrated energy system modeling apparatus based on directed multigraphs in the exemplary embodiments of this disclosure have been described in the exemplary embodiments of the integrated energy system modeling method based on directed multigraphs described above, they will not be repeated here.

[0150] It should be noted that although several modules or units of the integrated energy system modeling device based on directed multigraphs have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0151] Exemplary embodiments of this disclosure also provide a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the aforementioned method for modeling an integrated energy system based on directed multigraphs.

[0152] In one implementation, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing a computer program, such as read-only memory, NAND flash memory, etc.

[0153] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0154] Computer program code can be written in one or more programming languages. The program code can execute entirely on the user's computing device, or partially on the user's computing device, or as a standalone software package, or partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device through any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or it can be connected to an external computing device (e.g., through an internet connection provided by a mobile network operator).

[0155] Computer programs can be carried or transmitted via signals such as electricity, magnetism, light, electromagnetic radiation, and infrared radiation. Electronic devices can convert the signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, to execute) the method steps of various exemplary embodiments of this disclosure, such as the steps of the above-described integrated energy system modeling method based on directed multigraphs.

[0156] Furthermore, in exemplary embodiments of this disclosure, an electronic device capable of implementing the above-described methods is also provided. Those skilled in the art will understand that various aspects of this disclosure can be implemented as systems, methods, or program products. Therefore, various aspects of this disclosure can be specifically implemented as: entirely hardware embodiments, entirely software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, collectively referred to herein as "circuit," "module," or "system."

[0157] The following reference Figure 30 To describe an electronic device 3000 according to such an embodiment of the present disclosure. Figure 30 The electronic device 3000 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0158] like Figure 30 As shown, the electronic device 3000 is manifested in the form of a general-purpose computing device. The components of the electronic device 3000 may include, but are not limited to: at least one processing unit 3010, at least one storage unit 3020, a bus 3030 connecting different system components (including storage unit 3020 and processing unit 3010), and a display unit 3040.

[0159] The storage unit stores program code that can be executed by the processing unit 3010, causing the processing unit 3010 to perform the steps described in the "Exemplary Methods" section above according to various exemplary embodiments of this disclosure.

[0160] Storage unit 3020 may include readable media in the form of volatile storage units, such as random access memory (RAM) 3030 and / or cache memory 3022, and may further include read-only memory (ROM) 3023.

[0161] Storage unit 3020 may also include a program / utility 3024 having a set (at least one) program module 3025, such program module 3025 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0162] Bus 3030 can represent one or more of several types of bus structures, including memory cell bus or memory cell controller, peripheral bus, graphics acceleration port, processing unit, or local bus using any of the multiple bus structures.

[0163] Electronic device 3000 can also communicate with one or more external devices 3100 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 3000, and / or with any device that enables electronic device 3000 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 3050. Furthermore, electronic device 3000 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 3060. As shown, network adapter 3060 communicates with other modules of electronic device 3000 via bus 3030. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 3000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0164] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0165] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0166] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A comprehensive energy system modeling method based on directed multigraphs, characterized in that, include: A directed multigraph is constructed based on the equipment information and energy information in the energy process of the integrated energy system. The directed multigraph is used to reflect the coupling relationship between different energies in the integrated energy system. The adjacency matrix of the integrated energy system is constructed based on the directed multigraph. The adjacency matrix is ​​a matrix structure representing the energy conversion relationship in the integrated energy system. The non-empty element information of the row and column intersections reflects the directed conversion path and equipment information between energy. The adjacency matrix is ​​traversed to determine multiple energy conversion paths of the integrated energy system, and a target coupling matrix model of the integrated energy system is constructed based on the element information of each energy conversion path.

2. The method according to claim 1, characterized in that, The directed multigraph uses the energy involved in the integrated energy system as energy nodes, and the directed edges between energy nodes are labeled with the equipment information and energy information corresponding to the energy nodes. The directed multigraph is a directed multigraph without self-loops and without repeating energy nodes. The construction of the adjacency matrix of the integrated energy system based on the directed multigraph includes: The number of rows and columns of the matrix is ​​determined based on the preset virtual inputs and virtual outputs and the number of energy categories involved in the integrated energy system. The first row and first column of the matrix represent virtual inputs, and the last row and last column represent virtual outputs. The rows and columns of the matrix adopt the same energy category sorting method. For the directed edges in the directed multigraph, the target position is determined in the matrix according to the energy categories at both ends of the directed edge, and the corresponding device information and energy information are used as the element information of the target position to obtain the adjacency matrix.

3. The method according to claim 2, characterized in that, If there are target energy nodes in the directed multigraph that are not connected by directed edges, then the position corresponding to the target energy node in the adjacency matrix is ​​set to zero.

4. The method according to claim 2, characterized in that, The step of traversing the adjacency matrix to determine multiple energy conversion paths of the integrated energy system includes: Starting from the element at the top left corner of the adjacency matrix, search for the first non-zero element in a preset order, and determine the position of the first non-zero element as the current position; Based on the current position, search the adjacency matrix for reference non-zero elements that are the same as the output device of the current position in the preset order, update the position of the reference non-zero element to the current position, and return to the step of determining the first non-zero element, until the output device corresponding to the current position is the virtual output; The energy conversion path is determined based on the position, device information, and energy information corresponding to the first non-zero element and each of the reference non-zero elements; The adjacency matrix is ​​iteratively updated according to the energy conversion path, and the updated adjacency matrix is ​​returned to the step of searching for the first non-zero element to determine the energy conversion path, until all elements of the obtained adjacency matrix are zero; Based on the obtained energy conversion paths, multiple energy conversion paths of the integrated energy system are determined.

5. The method according to claim 4, characterized in that, The step of searching the adjacency matrix for reference non-zero elements that are the same as the output device at the current position, based on the current position and in the preset order, includes: Determine the starting row based on the column number of the current position; Starting from the first element of the starting row, the adjacency matrix is ​​searched in the preset order to obtain the reference non-zero element.

6. The method according to claim 4, characterized in that, The iterative update of the adjacency matrix based on the energy conversion path includes: Based on the input devices and / or output devices corresponding to the non-zero elements on the energy conversion path, and the output devices and / or input devices corresponding to the other elements in the adjacency matrix besides the non-zero elements on the energy conversion path, the non-zero elements in the adjacency matrix are deleted or retained to obtain an updated adjacency matrix.

7. The method according to claim 6, characterized in that, The iterative update of the adjacency matrix based on the energy conversion path includes: For any non-zero element in the energy conversion path, if the column number of the input device corresponding to the other element in the adjacency matrix is ​​the same as the row number of the output device corresponding to the non-zero element in the adjacency matrix, then the non-zero element is retained; otherwise, the non-zero element is deleted. Alternatively, if the column number of the output device corresponding to the other element in the adjacency matrix is ​​the same as the row number of the input device corresponding to the non-zero element in the adjacency matrix, then the non-zero element is retained; otherwise, the non-zero element is deleted.

8. The method according to claim 1, characterized in that, The construction of the target coupling matrix model of the integrated energy system based on the element information of each energy conversion path includes: For each energy conversion path, a coupling matrix is ​​constructed based on the element information of the energy conversion path. The positions of the elements in the coupling matrix are used to reflect the device information and energy information included in the energy conversion path. By fusing the coupling matrices corresponding to each energy conversion path, the target coupling matrix model of the integrated energy system is obtained.

9. The method according to claim 8, characterized in that, The step of fusing the coupling matrices corresponding to each of the energy conversion paths to obtain the target coupling matrix model of the integrated energy system includes: The coupling matrices corresponding to each energy conversion path are added together according to their element positions to obtain the target coupling matrix model.

10. The method according to claim 8, characterized in that, The step of constructing a coupling matrix for each energy conversion path based on the element information of the energy conversion path includes: An empty matrix is ​​constructed based on the energy nodes of the directed multigraph, wherein the rows and columns of the empty matrix are sorted in the same way according to the energy category. For each energy conversion path, the target position in the empty matrix is ​​determined based on the element information on the energy conversion path, and the elements of the target position are determined based on the energy information on the energy conversion path to obtain the coupling matrix of the energy conversion path.

11. The method according to claim 1, characterized in that, The construction of a directed multigraph based on equipment information and energy information in the energy process of the integrated energy system includes: Virtual input nodes and virtual output nodes are determined, and the energy involved in the integrated energy system is represented as energy nodes, so as to determine graph nodes based on the virtual input nodes, the virtual output nodes, and the energy nodes; Based on the energy information, directed edges between graph nodes are determined to obtain a first directed multigraph, wherein the directed edges of the first directed multigraph are labeled with device information and energy information related to the graph nodes at both ends of the directed edges; The first directed multigraph is simplified based on the energy information to obtain the second directed multigraph; The graph nodes in the second directed multigraph are merged according to the energy category to obtain the directed multigraph.

12. A comprehensive energy system modeling device based on directed multigraphs, characterized in that, include: The graph construction module is used to construct a directed multigraph based on the equipment information and energy information in the energy process of the integrated energy system. The directed multigraph is used to reflect the coupling relationship between different energies in the integrated energy system. The matrix construction module is used to construct the adjacency matrix of the integrated energy system based on the directed multigraph. The adjacency matrix is ​​a matrix structure representing the energy conversion relationship in the integrated energy system. The non-empty element information of the row and column intersections reflects the directed conversion path and equipment information between energy. The model building module is used to traverse the adjacency matrix to determine multiple energy conversion paths of the integrated energy system, and to construct the target coupling matrix model of the integrated energy system based on the element information of each energy conversion path.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 11.

14. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 11 by executing the executable instructions.

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