An integrated energy system extension energy hub simulation method and device

Abstract

The application relates to the technical field of comprehensive energy system analysis, and particularly provides an extended energy hub simulation method and device for a comprehensive energy system, which comprises the following steps: obtaining equipment parameters in a comprehensive energy system to be analyzed; substituting the equipment parameters into a pre-constructed extended energy hub simulation model of the comprehensive energy system; and performing simulation analysis on the comprehensive energy system to be analyzed based on the extended energy hub simulation model of the comprehensive energy system, so as to obtain a simulation result. The technical scheme provided by the application improves the accuracy of the model and enriches the application scenarios of the simulation method.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system analysis technology, specifically to a simulation method and apparatus for an extended energy hub in an integrated energy system. Background Technology

[0002] To achieve low-carbon development, integrated energy systems, with advantages such as multi-energy complementarity and cascaded energy utilization, are an important solution for the low-carbon transformation of the energy industry. An integrated energy system consists of energy networks including heating, cooling, natural gas, and power distribution networks, and has functions such as energy transmission, distribution, conversion, and balancing. Constructing a high-precision model of multi-energy flow coupling is both a key focus and a challenge in the study of integrated energy systems.

[0003] Currently, the energy hub model is the mainstream multi-energy flow coupling model, which abstracts energy supply and load demand into a multi-input multi-output port network model, reducing the complexity of computation and analysis. However, current energy hub models do not consider the impact of seasonal differences on load characteristics and all adopt the same operation control strategy, resulting in unreasonable energy allocation and high energy costs. On the other hand, energy storage grid connection, electric vehicle V2G, and demand-side response are rapidly developing and highly coupled in system operation, making it particularly important to consider their impact on the operating characteristics of the integrated energy system. Therefore, it is of great significance to establish an extended energy hub model for the integrated energy system that considers controllable loads and to conduct simulation analysis considering the impact of seasonal load differences on the model. Summary of the Invention

[0004] To overcome the above-mentioned shortcomings, this invention proposes a simulation method and device for an extended energy hub in an integrated energy system.

[0005] Firstly, a simulation method for an extended energy hub in an integrated energy system is provided, the simulation method for an extended energy hub in an integrated energy system comprising:

[0006] Obtain the equipment parameters of the integrated energy system to be analyzed;

[0007] The equipment parameters are substituted into the pre-constructed extended energy hub simulation model of the integrated energy system, and the integrated energy system to be analyzed is simulated and analyzed based on the extended energy hub simulation model of the integrated energy system to obtain the simulation results.

[0008] Preferably, the equipment parameters include at least one of the following: energy supply-load coupling matrix, energy storage-load coupling matrix, influence coefficient matrix of energy output when energy participates in demand response, energy input matrix of integrated energy system, energy input of new energy source, energy storage capacity, user electricity consumption response behavior matrix, auxiliary state variable matrix, energy supply coupling matrix of electric vehicle, energy storage coupling matrix of electric vehicle, energy input of electric vehicle, and energy storage capacity of electric vehicle.

[0009] Preferably, in the process of performing simulation analysis on the integrated energy system to be analyzed and obtaining simulation results, the simulation results include at least one of the following: power purchase change curve, power sales change curve, and energy cost change curve.

[0010] Preferably, the mathematical model of the pre-constructed integrated energy system energy hub simulation model is as follows:

[0011]

[0012] In the above formula, L is the output load matrix of the integrated energy system, L T Energy output from renewable energy sources connected to the grid, ΔL represents the load change caused by demand-side response, L EV Let C be the energy output of the electric vehicle, S be the energy supply-load coupling matrix, D be the energy storage load coupling matrix, D be the energy output impact coefficient matrix when energy participates in demand response, and P be the energy input matrix of the integrated energy system. R Let E be the energy input from new energy sources, H be the storage vector in the form of energy storage, ε be the user's electricity consumption response matrix, and C be the auxiliary state variable matrix. EV S is the power supply coupling matrix for electric vehicles. EV Let P be the energy storage coupling matrix of the electric vehicle. EV E represents the energy input of an electric vehicle. EV This refers to the energy storage capacity of electric vehicles.

[0013] Furthermore, if the current season is winter, then the mathematical model of the energy supply-load coupling matrix is: Otherwise, the mathematical model of the energy supply-load coupling matrix is: Where, η T , These are the conversion efficiencies of the transformer and the gas-fired boiler, respectively. The conversion efficiency of natural gas into heat energy. For air conditioning cooling efficiency, Let be the conversion efficiency of natural gas to electricity, and λ, β, and v be the distribution ratios of electricity, refrigeration, and natural gas. For air conditioning heating efficiency, η ARThis refers to the conversion efficiency of the refrigeration unit.

[0014] Furthermore, the mathematical model of the energy input matrix of the integrated energy system is as follows:

[0015] P = [P] e,EH P g,EH ] T

[0016] In the above formula, P e,EH P is the input electrical power. g,EH This refers to the imported natural gas.

[0017] Furthermore, when the electric vehicle is in a driving state, the auxiliary state variable matrices are as follows: (1 0 0 0) T When the electric vehicle is in refueling mode, the auxiliary state variable matrices are as follows: (0 1 00) T When the electric vehicle is in a charging load state, the auxiliary state variable matrices are as follows: (0 0 10) T When the electric vehicle is operating in grid-connected service mode, the auxiliary state variable matrices are as follows: (0 0 01) T .

[0018] Furthermore, the mathematical model for the load change caused by the demand-side response is as follows:

[0019]

[0020] In the above formula, d nn Let be the coefficient of influence of energy n on the output of energy n when energy n participates in demand response.

[0021] Secondly, a simulation device for an extended energy hub of an integrated energy system is provided, the simulation device comprising:

[0022] The acquisition module is used to acquire equipment parameters in the integrated energy system to be analyzed.

[0023] The analysis module is used to input the equipment parameters into a pre-built extended energy hub simulation model of the integrated energy system, and to perform simulation analysis on the integrated energy system to be analyzed based on the extended energy hub simulation model of the integrated energy system to obtain simulation results.

[0024] Preferably, the equipment parameters include at least one of the following: energy supply-load coupling matrix, energy storage-load coupling matrix, influence coefficient matrix of energy output when energy participates in demand response, energy input matrix of integrated energy system, energy input of new energy source, energy storage capacity, user electricity consumption response behavior matrix, auxiliary state variable matrix, energy supply coupling matrix of electric vehicle, energy storage coupling matrix of electric vehicle, energy input of electric vehicle, and energy storage capacity of electric vehicle.

[0025] Preferably, in the process of performing simulation analysis on the integrated energy system to be analyzed and obtaining simulation results, the simulation results include at least one of the following: power purchase change curve, power sales change curve, and energy cost change curve.

[0026] Preferably, the mathematical model of the pre-constructed integrated energy system energy hub simulation model is as follows:

[0027]

[0028] In the above formula, L is the output load matrix of the integrated energy system, L T Energy output from renewable energy sources connected to the grid, ΔL represents the load change caused by demand-side response, L EV Let C be the energy output of the electric vehicle, S be the energy supply-load coupling matrix, D be the energy storage load coupling matrix, D be the energy output impact coefficient matrix when energy participates in demand response, and P be the energy input matrix of the integrated energy system. R Let E be the energy input from new energy sources, H be the storage vector in the form of energy storage, ε be the user's electricity consumption response matrix, and C be the auxiliary state variable matrix. EV S is the power supply coupling matrix for electric vehicles. EV Let P be the energy storage coupling matrix of the electric vehicle. EV E represents the energy input of an electric vehicle. EV This refers to the energy storage capacity of electric vehicles.

[0029] Furthermore, if the current season is winter, then the mathematical model of the energy supply-load coupling matrix is: Otherwise, the mathematical model of the energy supply-load coupling matrix is: Where, η T , These are the conversion efficiencies of the transformer and the gas-fired boiler, respectively. The conversion efficiency of natural gas into heat energy. For air conditioning cooling efficiency, Let be the conversion efficiency of natural gas to electricity, and λ, β, and v be the distribution ratios of electricity, refrigeration, and natural gas. For air conditioning heating efficiency, η ARThis refers to the conversion efficiency of the refrigeration unit.

[0030] Furthermore, the mathematical model of the energy input matrix of the integrated energy system is as follows:

[0031] P = [P] e,EH P g,EH ] T

[0032] In the above formula, P e,EH P is the input electrical power. g,EH This refers to the imported natural gas.

[0033] Furthermore, when the electric vehicle is in a driving state, the auxiliary state variable matrices are as follows: (1 0 0 0) T When the electric vehicle is in refueling mode, the auxiliary state variable matrices are as follows: (0 10 0) T When the electric vehicle is in a charging load state, the auxiliary state variable matrices are as follows: (0 0 10) T When the electric vehicle is operating in grid-connected service mode, the auxiliary state variable matrices are as follows: (0 0 01) T .

[0034] Furthermore, the mathematical model for the load change caused by the demand-side response is as follows:

[0035]

[0036] In the above formula, d nn Let be the coefficient of influence of energy n on the output of energy n when energy n participates in demand response.

[0037] Thirdly, a computer device is provided, comprising: one or more processors;

[0038] The processor is used to store one or more programs;

[0039] When the one or more programs are executed by the one or more processors, the extended energy hub simulation method of the integrated energy system is implemented.

[0040] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the computer program is executed, the extended energy hub simulation method of the integrated energy system is implemented.

[0041] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects:

[0042] This invention provides a simulation method and apparatus for an extended energy hub in an integrated energy system, comprising: acquiring equipment parameters in the integrated energy system to be analyzed; substituting the equipment parameters into a pre-constructed extended energy hub simulation model of the integrated energy system; and performing simulation analysis on the integrated energy system to be analyzed based on the extended energy hub simulation model to obtain simulation results. The technical solution provided by this invention improves the accuracy of the model and enriches the application scenarios of the simulation method. Specifically:

[0043] The technical solution of this invention analyzes the differences in load characteristics in different seasons, proposes an extended energy hub simulation model for a comprehensive energy system that considers seasonal differences, provides a new solution for the rational allocation of energy in a comprehensive energy system, and achieves optimized reduction of energy costs.

[0044] The technical solution of this invention, based on the research of an extended energy hub simulation model of an integrated energy system considering seasonal differences, analyzes the impact of electric vehicles, energy storage, new energy grid connection and demand response on the operation of the integrated energy system, and proposes an extended mathematical model of the energy hub, which improves the applicability of the model and enriches the application scenarios of the model. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the main steps of the simulation method for the extended energy hub of the integrated energy system according to an embodiment of the present invention;

[0046] Figure 2 This is a diagram of an energy hub structure considering seasonal differences according to an embodiment of the present invention;

[0047] Figure 3 This is a typical energy consumption architecture diagram of a factory according to an embodiment of the present invention;

[0048] Figure 4 This is a typical energy consumption architecture diagram for summer according to an embodiment of the present invention;

[0049] Figure 5 This is a typical energy consumption architecture diagram for winter according to an embodiment of the present invention;

[0050] Figure 6 This is a summer factory energy cost curve according to an embodiment of the present invention;

[0051] Figure 7 This is a winter energy cost curve for factories according to an embodiment of the present invention;

[0052] Figure 8 This is a main structural block diagram of the extended energy hub simulation device of the integrated energy system according to an embodiment of the present invention. Detailed Implementation

[0053] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] As disclosed in the background section, integrated energy systems, which possess advantages such as multi-energy complementarity and cascaded energy utilization, are an important solution for the low-carbon transformation of the energy industry in order to achieve low-carbon development. Integrated energy systems consist of energy networks such as heating systems, cooling systems, natural gas systems, and power distribution networks, and have functions such as energy transmission, distribution, conversion, and balancing. Constructing a high-precision model of multi-energy flow coupling is both a key focus and a challenge in the study of integrated energy systems.

[0056] Currently, the energy hub model is the mainstream multi-energy flow coupling model, which abstracts energy supply and load demand into a multi-input multi-output port network model, reducing the complexity of computation and analysis. However, current energy hub models do not consider the impact of seasonal differences on load characteristics and all adopt the same operation control strategy, resulting in unreasonable energy allocation and high energy costs. On the other hand, energy storage grid connection, electric vehicle V2G, and demand-side response are rapidly developing and highly coupled in system operation, making it particularly important to consider their impact on the operating characteristics of the integrated energy system. Therefore, it is of great significance to establish an extended energy hub model for the integrated energy system that considers controllable loads and to conduct simulation analysis considering the impact of seasonal load differences on the model.

[0057] To address the aforementioned problems, this invention provides a simulation method and apparatus for an extended energy hub in an integrated energy system. The method includes: acquiring equipment parameters from the integrated energy system to be analyzed; substituting the equipment parameters into a pre-constructed extended energy hub simulation model of the integrated energy system; and performing simulation analysis on the integrated energy system based on the extended energy hub simulation model to obtain simulation results. The technical solution provided by this invention improves the accuracy of the model and enriches the application scenarios of the simulation method. Specifically:

[0058] The technical solution of this invention analyzes the differences in load characteristics in different seasons, proposes an extended energy hub simulation model for a comprehensive energy system that considers seasonal differences, provides a new solution for the rational allocation of energy in a comprehensive energy system, and achieves optimized reduction of energy costs.

[0059] The technical solution of this invention, based on the research of an extended energy hub simulation model of an integrated energy system considering seasonal differences, analyzes the impact of electric vehicles, energy storage, new energy grid connection, and demand response on the operation of the integrated energy system, and proposes an extended mathematical model for the energy hub, thereby improving the model's applicability and enriching its application scenarios. The above solution is described in detail below.

[0060] Example 1

[0061] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of an extended energy hub simulation method for an integrated energy system according to an embodiment of the present invention. Figure 1 As shown, the simulation method for the extended energy hub of the integrated energy system in this embodiment of the invention mainly includes the following steps:

[0062] Step S101: Obtain the equipment parameters of the integrated energy system to be analyzed;

[0063] Step S102: Substitute the equipment parameters into the pre-constructed extended energy hub simulation model of the integrated energy system, and perform simulation analysis on the integrated energy system to be analyzed based on the extended energy hub simulation model of the integrated energy system to obtain simulation results.

[0064] In this embodiment, the characteristics of load differ across seasons, and the operational status of the integrated energy system equipment in different seasons is analyzed. Based on the input equipment parameters, including: the energy supply-load coupling matrix, the energy storage-load coupling matrix, the influence coefficient matrix of energy output when participating in demand response, the energy input matrix of the integrated energy system, the energy input of new energy sources, the energy storage capacity, the user's electricity consumption response behavior matrix, the auxiliary state variable matrix, the energy supply coupling matrix of electric vehicles, the energy storage coupling matrix of electric vehicles, the energy input of electric vehicles, and the energy storage capacity of electric vehicles, a simulation of the extended energy hub model of the integrated energy system considering multiple loads is achieved. The simulation analysis mainly includes steady-state characteristic analysis, dynamic characteristic analysis, and energy flow calculation, obtaining parameters such as purchased power, sold power, and energy cost and their changing characteristics. The spatiotemporal distribution of energy flows such as electricity, cooling, heating, and gas is calculated. Based on the changes in energy cost according to the simulation results, theoretical support is provided for the energy allocation scheme of the integrated energy system, effectively improving the comprehensive energy utilization rate and achieving optimized operation of the integrated energy system.

[0065] In this embodiment, the mathematical model of the energy hub simulation model of the pre-built integrated energy system, which includes electric vehicles, energy storage devices, new energy grid connection, and demand response extension units, is as follows:

[0066]

[0067] In the above formula, L is the output load matrix of the integrated energy system, L T Energy output from renewable energy sources connected to the grid, ΔL represents the load change caused by demand-side response, L EV Let C be the energy output of the electric vehicle, S be the energy supply-load coupling matrix, D be the energy storage load coupling matrix, D be the energy output impact coefficient matrix when energy participates in demand response, and P be the energy input matrix of the integrated energy system. R Let E be the energy input from new energy sources, H be the storage vector in the form of energy storage, ε be the user's electricity consumption response matrix, and C be the auxiliary state variable matrix. EV S is the power supply coupling matrix for electric vehicles. EV Let P be the energy storage coupling matrix of the electric vehicle. EV E represents the energy input of an electric vehicle. EV This refers to the energy storage capacity of electric vehicles.

[0068] In one embodiment, the present invention considers the impact of seasonal differences on load characteristics, introduces electricity, cooling, and natural gas distribution coefficients, and proposes an energy hub model as shown in the appendix. Figure 2 As shown, if the current season is winter, then the mathematical model of the energy supply-load coupling matrix is: Otherwise, the mathematical model of the energy supply-load coupling matrix is: Where, η T , These are the conversion efficiencies of the transformer and the gas-fired boiler, respectively. The conversion efficiency of natural gas into heat energy. For air conditioning cooling efficiency, Let be the conversion efficiency of natural gas to electricity, and λ, β, and v be the distribution ratios of electricity, refrigeration, and natural gas. For air conditioning heating efficiency, η AR This refers to the conversion efficiency of the refrigeration unit.

[0069] The mathematical model for the energy input matrix of the integrated energy system is as follows:

[0070] P = [P] e,EH P g,EH ] T

[0071] In the above formula, P e,EH P is the input electrical power. g,EH This refers to the imported natural gas.

[0072] In one implementation, when the electric vehicle is in a driving state, the auxiliary state variable matrices are as follows: (1 0 0 0) TWhen the electric vehicle is in refueling mode, the auxiliary state variable matrices are as follows: (0 1 0 0) T When the electric vehicle is in a charging load state, the auxiliary state variable matrices are as follows: (0 0 1 0) T When the electric vehicle is operating in grid-connected service mode, the auxiliary state variable matrices are as follows: (0 0 0 1) T .

[0073] In one implementation, the mathematical model for the load change caused by the demand-side response is as follows:

[0074]

[0075] In the above formula, d nn Let be the coefficient of influence of energy n on the output of energy n when energy n participates in demand response.

[0076] This invention takes a real factory's integrated energy system as an example. The main energy conversion equipment in the factory includes: gas turbines, waste heat boilers, absorption chillers, electric refrigeration air conditioners, gas boilers, ice storage devices, and various steam-driven equipment, and also incorporates battery energy storage and new energy (taking photovoltaics as an example) equipment. The factory's production process involves the coupling and conversion of four energy forms: cold, heat, electricity, and gas. Its energy supply architecture is as follows: Figure 3 As shown.

[0077] This example only considers the load conditions on typical days in summer and winter. Summer cooling load demand is higher than heating load demand. The electric refrigeration air conditioner only provides cooling load, not heating load. The absorption chiller also converts excess heat energy in the system into cooling energy. The rest of the architecture remains unchanged. The typical summer energy supply architecture is as follows: Figure 4 As shown. In winter, the demand for heat load is large, while the demand for cooling load is small. Air conditioners, micro gas turbines, gas boilers, and absorption chillers all provide heat load, while a small amount of cooling load is provided only by cold storage devices. A typical energy consumption structure in winter is as follows: Figure 5 As shown.

[0078] Factory energy costs mainly include equipment operation and maintenance costs, electricity purchase costs, energy storage depreciation costs, fuel costs, heat purchase costs, and start-up and shutdown costs. Their calculation formulas are as follows:

[0079] C ATC =C om +C ES +C HS +C bw +C f +C SS

[0080] In the formula: C omIndicates operating and maintenance costs; C ES Indicates the cost of electricity purchase; C HS Indicates the cost of purchasing heat; C bw Indicates the depreciation cost of energy storage; C f Indicates fuel cost; C SS This indicates start-up and shutdown costs.

[0081] The energy consumption process of the factory was simulated and analyzed based on the extended energy hub model. The comprehensive energy cost of the factory user obtained by the simulation was compared with the energy cost of the factory obtained by traditional simulation methods. The summer and winter energy cost curves of the factory are as follows. Figure 6 and Figure 7 As shown in the figure, the typical daily cost reduction is 3600 yuan in summer and 14800 yuan in winter. Therefore, the simulation method described in this invention reduces factory energy costs by improving simulation accuracy compared to traditional simulation methods. Furthermore, considering the impact of seasonal differences on the integrated energy system provides a better solution for energy allocation, achieving a reduction in energy costs. Moreover, it considers the participation of new energy sources, such as photovoltaics, and energy storage batteries in system operation, broadening the applicability of the model.

[0082] Example 2

[0083] Based on the same inventive concept, this invention also provides an extended energy hub simulation device for an integrated energy system, such as... Figure 8 As shown, the extended energy hub simulation device of the integrated energy system includes:

[0084] The acquisition module is used to acquire equipment parameters in the integrated energy system to be analyzed.

[0085] The analysis module is used to input the equipment parameters into a pre-built extended energy hub simulation model of the integrated energy system, and to perform simulation analysis on the integrated energy system to be analyzed based on the extended energy hub simulation model of the integrated energy system to obtain simulation results.

[0086] Preferably, the equipment parameters include at least one of the following: energy supply-load coupling matrix, energy storage-load coupling matrix, influence coefficient matrix of energy output when energy participates in demand response, energy input matrix of integrated energy system, energy input of new energy source, energy storage capacity, user electricity consumption response behavior matrix, auxiliary state variable matrix, energy supply coupling matrix of electric vehicle, energy storage coupling matrix of electric vehicle, energy input of electric vehicle, and energy storage capacity of electric vehicle.

[0087] Preferably, in the process of performing simulation analysis on the integrated energy system to be analyzed and obtaining simulation results, the simulation results include at least one of the following: power purchase change curve, power sales change curve, and energy cost change curve.

[0088] Preferably, the mathematical model of the pre-constructed integrated energy system energy hub simulation model is as follows:

[0089]

[0090] In the above formula, L is the output load matrix of the integrated energy system, L T Energy output from renewable energy sources connected to the grid, ΔL represents the load change caused by demand-side response, L EV Let C be the energy output of the electric vehicle, S be the energy supply-load coupling matrix, D be the energy storage load coupling matrix, D be the energy output impact coefficient matrix when energy participates in demand response, and P be the energy input matrix of the integrated energy system. R Let E be the energy input from new energy sources, H be the storage vector in the form of energy storage, ε be the user's electricity consumption response matrix, and C be the auxiliary state variable matrix. EV S is the power supply coupling matrix for electric vehicles. EV Let P be the energy storage coupling matrix of the electric vehicle. EV E represents the energy input of an electric vehicle. EV This refers to the energy storage capacity of electric vehicles.

[0091] Furthermore, if the current season is winter, then the mathematical model of the energy supply-load coupling matrix is: Otherwise, the mathematical model of the energy supply-load coupling matrix is: Where, η T , These are the conversion efficiencies of the transformer and the gas-fired boiler, respectively. The conversion efficiency of natural gas into heat energy. For air conditioning cooling efficiency, Let be the conversion efficiency of natural gas to electricity, and λ, β, and v be the distribution ratios of electricity, refrigeration, and natural gas. For air conditioning heating efficiency, η AR This refers to the conversion efficiency of the refrigeration unit.

[0092] Furthermore, the mathematical model of the energy input matrix of the integrated energy system is as follows:

[0093] P = [P] e,EH P g,EH ] T

[0094] In the above formula, P e,EH P is the input electrical power.g,EH This refers to the imported natural gas.

[0095] Furthermore, when the electric vehicle is in a driving state, the auxiliary state variable matrices are as follows: (1 0 0 0) T When the electric vehicle is in refueling mode, the auxiliary state variable matrices are as follows: (0 10 0) T When the electric vehicle is in a charging load state, the auxiliary state variable matrices are as follows: (0 0 10) T When the electric vehicle is operating in grid-connected service mode, the auxiliary state variable matrices are as follows: (0 0 01) T .

[0096] Furthermore, the mathematical model for the load change caused by the demand-side response is as follows:

[0097]

[0098] In the above formula, d nn Let be the coefficient of influence of energy n on the output of energy n when energy n participates in demand response.

[0099] Example 3

[0100] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby realizing the steps of the extended energy hub simulation method for an integrated energy system in the above embodiments.

[0101] Example 4

[0102] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the extended energy hub simulation method for an integrated energy system in the above embodiments.

[0103] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0104] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0105] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0106] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An integrated energy system extended energy hub simulation method, characterized in that, The method comprises: obtaining device parameters in a comprehensive energy system to be analyzed; substituting the device parameters into a pre-constructed extended energy hub simulation model of the comprehensive energy system, and performing simulation analysis on the comprehensive energy system to be analyzed based on the extended energy hub simulation model of the comprehensive energy system, to obtain simulation results; the device parameters include at least one of the following: a supply-load coupling matrix, a storage-load coupling matrix, an influence coefficient matrix of energy output when energy participates in demand response, an energy input matrix of the comprehensive energy system, a new energy energy input amount, a storage capacity, a user electricity response behavior matrix, an auxiliary state variable matrix, an electric vehicle supply coupling matrix, an electric vehicle storage coupling matrix, an electric vehicle energy input amount, and an electric vehicle energy storage amount; a mathematical model of the pre-constructed energy hub simulation model of the comprehensive energy system is as follows: In the above formula, L is the output load matrix of the integrated energy system, L T is the new energy grid-connected output energy, ΔL is the load change caused by demand side response, L EV is the energy output of the electric vehicle, C is the energy supply-load coupling matrix, S is the energy storage load coupling matrix, D is the influence coefficient matrix of energy output when energy participates in demand response, P is the energy input matrix of the integrated energy system, P R is the new energy input, E is the storage amount vector of energy storage, H is the user's electricity response behavior matrix, ε is the auxiliary state variable matrix, C EV is the energy supply coupling matrix of the electric vehicle, S EV is the energy storage coupling matrix of the electric vehicle, P EV is the energy input of the electric vehicle, E EV is the energy storage amount of the electric vehicle.

2. The method of claim 1, wherein, in the process of performing simulation analysis on the comprehensive energy system to be analyzed to obtain simulation results, the simulation results include at least one of the following: a change curve of purchased power, a change curve of sold power, and a change curve of energy use cost.

3. The method of claim 1, wherein, If the current season is winter, the mathematical model of the energy supply-load coupling matrix is: Otherwise, the mathematical model of the energy supply-load coupling matrix is: Wherein, η T , is the conversion efficiency of the transformer gas boiler respectively, is the conversion efficiency of natural gas into heat energy, is the air conditioning refrigeration efficiency, is the conversion efficiency of natural gas into electric energy, λ, β, v are the distribution proportions of electric energy, refrigeration and natural gas, is the air conditioning heating efficiency, η AR is the conversion efficiency of the refrigeration machine.

4. The method of claim 1, wherein, a mathematical model of the energy input matrix of the comprehensive energy system is as follows: P = [P e,EH P g,EH ] T In the above formula, P e,EH is the input electric power, P g,EH is the input natural gas.

5. The method of claim 1, wherein, When the running state of the electric vehicle is the driving state, the auxiliary state variable matrixes are respectively: (1 0 0 0) T ; when the running state of the electric vehicle is the refueling state, the auxiliary state variable matrixes are respectively: (0 1 0 0) T ; when the running state of the electric vehicle is the charging load state, the auxiliary state variable matrixes are respectively: (0 0 1 0) T ; when the running state of the electric vehicle is the grid-connected service state, the auxiliary state variable matrixes are respectively: (0 0 0 1) T .

6. The method of claim 1, wherein, a mathematical model of the load change amount caused by the demand side response is as follows: In the above formula, d nn is the influence coefficient of energy n output when energy n participates in demand response.

7. An extended energy hub simulation device for an integrated energy system, characterized in that, The device comprises: an obtaining module configured to obtain device parameters in a comprehensive energy system to be analyzed; an analysis module configured to substitute the device parameters into a pre-constructed extended energy hub simulation model of the comprehensive energy system, and perform simulation analysis on the comprehensive energy system to be analyzed based on the extended energy hub simulation model of the comprehensive energy system, to obtain simulation results; the device parameters include at least one of the following: a supply-load coupling matrix, a storage-load coupling matrix, an influence coefficient matrix of energy output when energy participates in demand response, an energy input matrix of the comprehensive energy system, a new energy energy input amount, a storage capacity, a user electricity response behavior matrix, an auxiliary state variable matrix, an electric vehicle supply coupling matrix, an electric vehicle storage coupling matrix, an electric vehicle energy input amount, and an electric vehicle energy storage amount; a mathematical model of the pre-constructed energy hub simulation model of the comprehensive energy system is as follows: In the above formula, L is the output load matrix of the integrated energy system, L T is the new energy grid-connected output energy, ΔL is the load change caused by demand side response, L EV is the energy output of the electric vehicle, C is the energy supply-load coupling matrix, S is the energy storage load coupling matrix, D is the influence coefficient matrix of energy output when energy participates in demand response, P is the energy input matrix of the integrated energy system, P R is the new energy input, E is the storage amount vector of energy storage, H is the user's electricity response behavior matrix, ε is the auxiliary state variable matrix, C EV is the energy supply coupling matrix of the electric vehicle, S EV is the energy storage coupling matrix of the electric vehicle, P EV is the energy input of the electric vehicle, E EV is the energy storage amount of the electric vehicle.

8. The apparatus of claim 7, wherein, in the process of performing simulation analysis on the comprehensive energy system to be analyzed to obtain simulation results, the simulation results include at least one of the following: a change curve of purchased power, a change curve of sold power, and a change curve of energy use cost.

9. The apparatus of claim 7, wherein, If the current season is winter, the mathematical model of the energy supply-load coupling matrix is: Otherwise, the mathematical model of the energy supply-load coupling matrix is: Wherein, η T , is the conversion efficiency of the transformer gas boiler, is the conversion efficiency of natural gas into heat energy, is the air conditioning refrigeration efficiency, is the conversion efficiency of natural gas into electric energy, λ, β, v are the distribution proportions of electric energy, refrigeration and natural gas, is the air conditioning heating efficiency, η AR is the conversion efficiency of the refrigeration machine.

10. The apparatus of claim 7, wherein, a mathematical model of the energy input matrix of the comprehensive energy system is as follows: P = [P e,EH P g,EH ] T In the above formula, P e,EH is the input electric power, P g,EH is the input natural gas.

11. The apparatus of claim 7, wherein, When the running state of the electric vehicle is the driving state, the auxiliary state variable matrixes are respectively: (1 0 0 0) T ; when the running state of the electric vehicle is the refueling state, the auxiliary state variable matrixes are respectively: (0 1 0 0) T ; when the running state of the electric vehicle is the charging load state, the auxiliary state variable matrixes are respectively: (0 0 1 0) T ; when the running state of the electric vehicle is the grid-connected service state, the auxiliary state variable matrixes are respectively: (0 0 0 1) T .

12. The apparatus of claim 7, wherein, a mathematical model of the load change amount caused by the demand side response is as follows: In the above formula, d nn is the influence coefficient of energy n output when energy n participates in demand response.

13. A computer device, comprising: comprises: one or more processors; the processor is configured to store one or more programs; when the one or more programs are executed by the one or more processors, the one or more programs realize the extended energy hub simulation method of the comprehensive energy system according to any one of claims 1 to 6.

14. A computer-readable storage medium, characterized in that, a computer program is stored thereon, and the computer program is executed to realize the extended energy hub simulation method of the comprehensive energy system according to any one of claims 1 to 6.

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