Modeling method and system of urban area electric-hydrogen coupled energy network

Abstract

A modeling method and system for an urban area electric-hydrogen coupled energy network takes the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility as the electric-hydrogen energy flow constraint condition, and takes the minimum total operation and maintenance cost as the electric-hydrogen energy flow target, to establish a collaborative optimization model of the electric-hydrogen coupled network; obtains the predicted value of electric energy production and the predicted value of electric energy demand, the predicted value of hydrogen production and the predicted value of hydrogen demand, the predicted value of gas production and the predicted value of gas demand, and uses the collaborative optimization model to output the operating parameters of the power network model, the gas network model and the hydrogen energy network model; uses the power network model, the gas network model, the hydrogen energy network model and their operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility to construct an electric-hydrogen coupled energy network model.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban area integrated energy systems, and in particular relates to a modeling method and a modeling system for an electric hydrogen coupled energy network suitable for urban areas. Background Art

[0002] With the rapid development and widespread application of renewable energy, the power system has an increasing demand for flexibility to cope with its own intermittent and volatile problems. In this context, the importance of hydrogen energy is becoming increasingly prominent. With the help of Power-to-Hydrogen (P2H) technology, the excess renewable energy can be converted into hydrogen and stored; then the hydrogen can be converted back into electricity using Hydrogen-to-Power (H2P) technology. In addition, hydrogen can be mixed with natural gas to enhance the flexibility and efficiency of the natural gas network. The coupled energy network of electricity, gas and hydrogen has been initially verified in some park applications. However, these applications are mostly limited to the optimal scheduling of a single energy form (electricity, gas or hydrogen).

[0003] In the existing technology, urban areas are areas with highly concentrated energy demand, and their load demand presents complex and changeable characteristics. In the design of urban energy systems, there is a lack of a coordinated operation mechanism for electricity, gas and hydrogen in urban areas. This lack makes it impossible to achieve dynamic joint scheduling of electricity and hydrogen energy, which in turn causes a series of serious problems. On the one hand, the utilization rate of renewable energy is low, and a large amount of renewable energy is wasted due to the inability to effectively store and flexibly convert it. On the other hand, the volatility of the energy system increases, and the stability of power supply is seriously affected, which not only has an impact on large energy users such as industrial production, but also brings inconvenience to residents' lives. At the same time, the problem of poor supply reliability also follows, and it is impossible to guarantee the stable supply of energy under different demand scenarios, which increases the risk of energy supply interruption.

[0004] At the same time, with the widespread application of hydrogen in many fields such as transportation, industry, and construction, energy use scenarios are also highly diversified, and the application modes and demand characteristics of hydrogen energy are different. In the field of transportation, hydrogen energy is mainly used as a power source for vehicles such as fuel cell vehicles, which has special requirements for the continuity of hydrogen energy supply and the layout of hydrogen refueling facilities; in the industrial field, hydrogen energy may participate in the production process as a raw material or energy, and needs to meet specific process parameters and energy supply stability; in the field of construction, hydrogen energy can be used for distributed energy supply and energy storage, etc., and has high requirements for coordinated operation with other energy sources such as electricity and gas.

[0005] Therefore, the electric hydrogen coupled energy system in urban areas needs to meet the needs of different types of users at different times and scenarios. How to effectively couple hydrogen energy with electricity and gas networks and establish an efficient timing scheduling mechanism in the process of energy flow has become a technical problem that needs to be overcome in the current energy field. This requires not only in-depth research on the physical and chemical properties of different energy forms, but also comprehensive consideration of multiple factors such as the characteristics of energy demand in complex urban environments, the layout of energy infrastructure, and the operation mechanism of the energy market, so as to achieve efficient, stable and sustainable operation of urban regional energy systems. Summary of the invention

[0006] In order to address the deficiencies in the prior art, the present invention provides a method and system for modeling an urban area electric-hydrogen coupled energy network, constructs a coupling model of electricity, gas, and hydrogen energy networks, and characterizes the degree to which the electric-hydrogen coupled energy system in the urban area satisfies the needs of different types of users at different times and scenarios, thereby achieving joint optimization and coordinated operation of multiple energy systems and improving the overall efficiency and stability of the urban energy system.

[0007] The present invention adopts the following technical solution.

[0008] The present invention proposes a method for modeling an urban area electric hydrogen coupling energy network, comprising:

[0009] Obtain the topological structures of the power network, gas network, and hydrogen energy network in the urban area, and construct the power network model, gas network model, and hydrogen energy network model respectively; wherein each network model includes each uncoupled node within the network and the connection path between each uncoupled node; the energy transmission efficiency on the connection path is used as the characteristic length of the connection path, the power storage facility in the power network model uses the charge state of the battery as the characteristic value, and the hydrogen storage facility in the hydrogen energy network model uses the hydrogen storage level of the hydrogen storage equipment as the characteristic value;

[0010] Obtain the topological structure of the coupling between the power network and the hydrogen energy network to determine the coupling paths between the electric-hydrogen coupling nodes and the electric-hydrogen coupling nodes of the power network model and the hydrogen energy network model; obtain the topological structure of the coupling between the gas network and the hydrogen energy network to determine the coupling paths between the gas network model and the gas-hydrogen coupling nodes and the gas-hydrogen coupling nodes of the hydrogen energy network model; obtain the topological structure of the coupling between the gas network and the power network to determine the coupling paths between the gas network model and the gas-electricity coupling nodes and the gas-electricity coupling nodes of the power network model; use the energy transmission efficiency on the coupling path as the characteristic length of the coupling path;

[0011] Taking the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility as the constraints of the electric hydrogen energy flow, and taking the minimum total operation and maintenance cost as the electric hydrogen energy flow target, a collaborative optimization model of the electric hydrogen coupling network is established; the predicted values ​​of electric energy production and electric energy demand, the predicted values ​​of hydrogen production and hydrogen demand, and the predicted values ​​of gas production and gas demand are obtained, and the collaborative optimization model of the electric hydrogen coupling network is used to output the operating parameters of the electric power network model, the operating parameters of the gas network model and the operating parameters of the hydrogen energy network model;

[0012] An electric-hydrogen coupled energy network model is constructed using the power network model and its operating parameters, the gas network model and its operating parameters, the hydrogen energy network model and its operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility.

[0013] Preferably, in the power network model, the characteristic length of the connection path is the power transmission efficiency of the transmission line, which satisfies the following relationship:

[0014] ,

[0015] In the formula, is the power transmission efficiency of the transmission line, is the power at the power flow input end of the transmission line, is the power at the power flow output end of the transmission line.

[0016] Preferably, in the gas network model, the characteristic length of the connection path is the gas transmission efficiency of the gas pipeline, which satisfies the following relationship:

[0017] ,

[0018] In the formula, is the gas transmission efficiency of the gas pipeline, is the gas mass flow rate at the pipeline inlet, is the gas mass flow rate at the pipeline outlet.

[0019] Preferably, in the hydrogen network model, the characteristic length of the connection path is the hydrogen transmission efficiency of the hydrogen pipeline, which satisfies the following relationship:

[0020] ,

[0021] In the formula, The hydrogen transmission efficiency of the hydrogen pipeline, is the hydrogen mass flow rate at the pipeline inlet, is the hydrogen mass flow rate at the pipeline outlet.

[0022] Preferably, the power storage facility in the power network model uses the state of charge of the battery as a characteristic value, satisfying the following relationship:

[0023] ,

[0024] In the formula, for The battery's state of charge at all times, for The remaining battery power at all times, is the rated capacity of the battery.

[0025] Preferably, the hydrogen storage facilities in the hydrogen energy network model use the hydrogen storage level of the hydrogen storage equipment as the characteristic value, satisfying the following relationship:

[0026] ,

[0027] In the formula, is the hydrogen storage level of the hydrogen storage device, for The quality of hydrogen in the hydrogen storage facility at all times, is the rated hydrogen storage capacity of the hydrogen storage facility.

[0028] Preferably, the characteristic length of the coupling path between the electric-hydrogen coupling nodes is the power transmission efficiency of the transmission line.

[0029] Preferably, the characteristic length of the coupling path between the gas-hydrogen coupling nodes is the hydrogen-blended natural gas mixing transmission efficiency of the gas pipeline, which satisfies the following relationship:

[0030] ,

[0031] In the formula, The transmission efficiency of hydrogen-blended natural gas in gas pipelines. is the total mass of hydrogen after mixing, is the mass of hydrogen injected into the pipeline, The quality of the gas injected into the pipeline.

[0032] Preferably, the characteristic length of the coupling path between the gas-electricity coupling nodes is the gas transmission efficiency of the gas pipeline.

[0033] The present invention also proposes a city area electrical hydrogen coupling energy network modeling system, comprising:

[0034] The characteristic parameter determination module is used to obtain the topological structure of the power network, gas network and hydrogen energy network in the urban area, and construct the power network model, gas network model and hydrogen energy network model respectively; wherein each network model includes each uncoupled node within the network and the connection path between each uncoupled node; the energy transmission efficiency on the connection path is used as the characteristic length of the connection path, the power storage facility in the power network model uses the charge state of the battery as the characteristic value, and the hydrogen storage facility in the hydrogen energy network model uses the hydrogen storage level of the hydrogen storage equipment as the characteristic value; the topological structure of the coupling between the power network and the hydrogen energy network is obtained to determine each electric-hydrogen coupling node of the power network model and the hydrogen energy network model, and the coupling path between each electric-hydrogen coupling node; the topological structure of the coupling between the gas network and the hydrogen energy network is obtained to determine each gas-hydrogen coupling node of the gas network model and the hydrogen energy network model, and the coupling path between each gas-hydrogen coupling node; the topological structure of the coupling between the gas network and the power network is obtained to determine each gas-electricity coupling node of the gas network model and the power network model, and the coupling path between each gas-electricity coupling node; the energy transmission efficiency on the coupling path is used as the characteristic length of the coupling path;

[0035] An operating parameter determination module is used to establish a collaborative optimization model of an electric-hydrogen coupling network with characteristic lengths of each connection path, characteristic lengths of each coupling path, characteristic values ​​of power storage facilities, and characteristic values ​​of hydrogen storage facilities as constraints for electric-hydrogen energy flow, and with minimum total operation and maintenance cost as the electric-hydrogen energy flow target; obtain predicted values ​​of electric energy production and electric energy demand, predicted values ​​of hydrogen production and hydrogen demand, predicted values ​​of gas production and gas demand, and use the collaborative optimization model of the electric-hydrogen coupling network to output operating parameters of the electric network model, operating parameters of the gas network model, and operating parameters of the hydrogen energy network model;

[0036] The model building module is used to construct an electric-hydrogen coupled energy network model using the electric power network model and its operating parameters, the gas network model and its operating parameters, the hydrogen energy network model and its operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility.

[0037] The present invention is also a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0038] The present invention is also a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0039] The beneficial effects of the present invention are that, compared with the prior art, at least the collaborative optimization model of the electric-hydrogen coupling network proposed in the present invention is based on a collaborative optimization method, with the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility as the electric-hydrogen energy flow constraint conditions, and targeting the energy supply and demand imbalance under variable operating conditions, with the minimization of the total operation and maintenance cost as the optimization goal, the operating parameters of the electric-hydrogen coupling network are optimized through iterative operation to determine the optimal operating point that meets the energy demand of the entire urban area.

[0040] The operating parameters of the electric hydrogen coupling network used in the modeling of the present invention are not affected by human factors, and the established model is close to the optimal working state of the electric hydrogen coupling network. Based on the energy supply and demand forecast, the present invention designs a collaborative optimization scheduling strategy for the electric hydrogen coupling network, optimizes hydrogen production and storage, and meets the power balance requirements of electricity and gas. This method realizes the effective coordination of electricity and hydrogen energy through collaborative optimization scheduling, improves the efficiency and economy of the entire energy system, enhances the reliability of the urban energy network, and supports sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of a method for modeling an urban area electric hydrogen coupling energy network proposed by the present invention;

[0042] Figure 2 It is a schematic diagram of the topological structure of the electric-hydrogen coupled energy network modeling system in an embodiment of the present invention. The figure numbers in the figure are explained as follows: 1-power station, 2-substation, 3-load center, 4-hydrogen production device, 5-hydrogen storage facility, 6-fuel cell, 7-gas user, 8-gas supply station, 9-energy supply and demand prediction module, 10-cooperative optimization model of the electric-hydrogen coupled network. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0044] The present invention proposes a method for modeling an urban area electric hydrogen coupling energy network. Figure 1 As shown, including:

[0045] Step 1, obtain the topological structures of the power network, gas network and hydrogen energy network in the urban area, and construct the power network model, gas network model and hydrogen energy network model respectively; wherein each network model includes each uncoupled node within the network and the connection path between each uncoupled node; the energy transmission efficiency on the connection path is used as the characteristic length of the connection path, the power storage facility in the power network model uses the charge state of the battery as the characteristic value, and the hydrogen storage facility in the hydrogen energy network model uses the hydrogen storage level of the hydrogen storage equipment as the characteristic value.

[0046] The connection path represents the energy transmission process between each uncoupled node. The energy transmission efficiency on the connection path is used as the characteristic length of the connection path. The characteristic length of the connection path is used to achieve quantitative measurement of supply and demand between each uncoupled node.

[0047] In the embodiment, Figure 2 As shown, the power network model includes but is not limited to power station 1, substation 2, load center 3, and power storage facilities; the gas network model includes but is not limited to gas users 7 and gas supply stations 8; the hydrogen energy network model includes but is not limited to hydrogen production equipment 4, hydrogen storage facilities 5, and fuel cells 6.

[0048] In the embodiment, the uncoupled nodes of the power network include electrical nodes, the uncoupled nodes of the gas network include gas nodes, and the uncoupled nodes of the hydrogen energy network include hydrogen energy nodes; the uncoupled nodes within each network are only connected to the uncoupled nodes within the network, that is, the electrical nodes are only connected to the electrical nodes, and will not be connected to the gas nodes and hydrogen energy nodes, and the gas nodes and hydrogen energy nodes also conform to the same connection relationship;

[0049] Specifically, in the power network model, power stations, substations, primary loads, secondary loads and power storage facilities are used as non-coupled key nodes, tertiary loads and other nodes are used as non-coupled secondary nodes, 220kV and above transmission lines are used as key connection paths, and transmission lines and distribution lines of other voltage levels are used as secondary connection paths; in the gas network model, gas supply stations are used as non-coupled key nodes, gas users are used as non-coupled secondary nodes, and gas pipelines are used as key connection paths; in the hydrogen energy network model, hydrogen production devices, hydrogen storage facilities, and fuel cells are used as non-coupled key nodes, and other nodes are used as non-coupled secondary nodes, and hydrogen pipelines are used as key connection paths;

[0050] Specifically, in the power network model, the characteristic length of the connection path is the power transmission efficiency of the transmission line, which satisfies the following relationship:

[0051] ,

[0052] In the formula, is the power transmission efficiency of the transmission line, is the power at the power flow input end of the transmission line, is the power at the power flow output end of the transmission line.

[0053] Specifically, in the gas network model, the characteristic length of the connection path is the gas transmission efficiency of the gas pipeline, which satisfies the following relationship:

[0054] ,

[0055] In the formula, is the gas transmission efficiency of the gas pipeline, is the gas mass flow rate at the pipeline inlet, is the gas mass flow rate at the pipeline outlet.

[0056] Specifically, in the hydrogen network model, the characteristic length of the connection path is the hydrogen transmission efficiency of the hydrogen pipeline, which satisfies the following relationship:

[0057] ,

[0058] In the formula, The hydrogen transmission efficiency of the hydrogen pipeline, is the hydrogen mass flow rate at the pipeline inlet, is the hydrogen mass flow rate at the pipeline outlet.

[0059] The power storage facilities in the power network model use the state of charge of the battery as the characteristic value, satisfying the following relationship:

[0060] ,

[0061] In the formula, for The battery's state of charge at all times, for The remaining battery power at all times, is the rated capacity of the battery;

[0062] The hydrogen storage facilities in the hydrogen energy network model use the hydrogen storage level of the hydrogen storage equipment as the characteristic value, satisfying the following relationship:

[0063] ,

[0064] In the formula, is the hydrogen storage level of the hydrogen storage device, for The quality of hydrogen in the hydrogen storage facility at all times, is the rated hydrogen storage capacity of the hydrogen storage facility.

[0065] The electric power network model, gas network model and hydrogen energy network model established in the present invention can accurately reflect the physical characteristics and operating characteristics of each network.

[0066] In the embodiment, the working fluid and energy flow of each node in the hydrogen energy network in different time periods is simulated by dynamic analysis, and the conversion efficiency and energy loss of hydrogen in the links of electrolysis hydrogen production, hydrogen storage and fuel cell power generation are considered. The hydrogen energy network model includes: a hydrogen production sub-model, a hydrogen storage sub-model and a power generation sub-module.

[0067] Step 2, obtain the topological structure of the coupling between the power network and the hydrogen energy network to determine the coupling paths between the various electric-hydrogen coupling nodes and the various electric-hydrogen coupling nodes of the power network model and the hydrogen energy network model; obtain the topological structure of the coupling between the gas network and the hydrogen energy network to determine the coupling paths between the various gas-hydrogen coupling nodes and the various gas-hydrogen coupling nodes of the gas network model and the hydrogen energy network model; obtain the topological structure of the coupling between the gas network and the power network to determine the coupling paths between the various gas-electricity coupling nodes and the various gas-electricity coupling nodes of the gas network model and the power network model; and use the energy transmission efficiency on the coupling path as the characteristic length of the coupling path.

[0068] Figure 2 In the figure, the solid line represents the relationship between energy conversion and transmission. The gas transmitted from the gas network model to the power network model is converted into electricity by the gas generator set. The electricity transmitted from the power network model to the hydrogen energy network model is used to produce hydrogen. The hydrogen energy network model transmits electricity to the power network model and hydrogen to the gas network model.

[0069] In the embodiment, for the coupling of the power grid and the gas grid, the relationship between gas consumption and power output during gas turbine power generation, as well as the energy conversion relationship between power input and synthetic natural gas (methane) output during the operation of the power-to-gas (P2G) equipment are considered. For example, in the energy hub area of ​​a city, gas turbine power generation supplies power to surrounding loads, and its exhaust waste heat can be used to drive absorption chillers to meet regional cooling needs. This process involves the conversion and coordination of electricity, gas and cooling energy, and its energy flow path and conversion efficiency need to be detailed in the model.

[0070] In the embodiment, in terms of coupling between the power grid and the hydrogen energy grid, the focus is on analyzing the conversion efficiency of electricity to hydrogen during water electrolysis (P2H) and the conversion characteristics of hydrogen chemical energy to electricity during hydrogen fuel cell power generation (H2P). Taking the distributed energy station in the city as an example, when there is excess renewable energy generation, the excess electricity is stored as hydrogen through water electrolysis to produce hydrogen. When the demand for electricity increases, hydrogen fuel cells are used to generate electricity and feed back to the grid. The model needs to accurately simulate this dynamic electricity-hydrogen-electricity energy cycle process, including the working characteristics of the electrolyzer, the energy loss during hydrogen storage and transportation, and the output characteristics of the fuel cell.

[0071] In the embodiment, for the coupling of gas network and hydrogen energy network, the relevant characteristics and application scenarios of hydrogen-blended natural gas are studied. In the city's natural gas pipeline network, the combustion characteristics, transmission characteristics and influence on pipeline materials of hydrogen-blended natural gas at different hydrogen blending ratios are determined, and an energy flow model of hydrogen-blended natural gas in the gas network is established. At the same time, the energy conversion process such as cogeneration of heat and power using hydrogen-blended natural gas in distributed energy stations is considered, as well as the storage and distribution strategy of hydrogen in the gas network.

[0072] Specifically, the characteristic length of the coupling path between the electric-hydrogen coupling nodes is the power transmission efficiency of the transmission line.

[0073] Specifically, the characteristic length of the coupling path between the gas-hydrogen coupling nodes is the hydrogen-blended natural gas mixing transmission efficiency of the gas pipeline, which satisfies the following relationship:

[0074] ,

[0075] In the formula, The transmission efficiency of hydrogen-blended natural gas in gas pipelines. is the total mass of hydrogen after mixing, is the mass of hydrogen injected into the pipeline, The quality of the gas injected into the pipeline.

[0076] Specifically, the characteristic length of the coupling path between the gas-electricity coupling nodes is the gas transmission efficiency of the gas pipeline.

[0077] Step 3, taking the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility as the electric hydrogen energy flow constraint conditions, and taking the minimum total operation and maintenance cost as the electric hydrogen energy flow target, establish a collaborative optimization model of the electric hydrogen coupling network; obtain the predicted values ​​of electric energy production and electric energy demand, the predicted values ​​of hydrogen production and hydrogen demand, and the predicted values ​​of gas production and gas demand, and use the collaborative optimization model of the electric hydrogen coupling network to output the operating parameters of the power network model, the operating parameters of the gas network model, and the operating parameters of the hydrogen energy network model.

[0078] The collaborative optimization model of the electric-hydrogen coupling network proposed in the present invention is based on a collaborative optimization method. The characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility are used as constraints on the electric-hydrogen energy flow. Aiming at the imbalance of energy supply and demand under variable operating conditions, the minimization of the total operation and maintenance cost is taken as the optimization goal. The operating parameters of the electric-hydrogen coupling network are optimized through iterative operation to determine the optimal operating point that meets the energy demand of the entire urban area.

[0079] Therefore, the operating parameters of the electric hydrogen coupling network used in the modeling of the present invention are not affected by human factors, and the established model is close to the optimal working state of the electric hydrogen coupling network. Based on the energy supply and demand forecast, the present invention designs a collaborative optimization scheduling strategy for the electric hydrogen coupling network, optimizes hydrogen production and storage, and meets the power balance requirements of electricity and gas. This method realizes the effective coordination of electricity and hydrogen energy through collaborative optimization scheduling, improves the efficiency and economy of the entire energy system, enhances the reliability of the urban energy network, and supports sustainable development.

[0080] Step 4: construct an electric-hydrogen coupled energy network model using the power network model and its operating parameters, the gas network model and its operating parameters, the hydrogen energy network model and its operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility, and the characteristic value of the hydrogen storage facility.

[0081] like Figure 2 As shown, the energy supply and demand prediction module 9 obtains the predicted value of electricity production and electricity demand, the predicted value of hydrogen production and hydrogen demand, the predicted value of gas production and gas demand, and uses the collaborative optimization model 10 of the electric-hydrogen coupled network to output the operating parameters of the power network model, the operating parameters of the gas network model, and the operating parameters of the hydrogen network model.

[0082] In the embodiment, based on the electric-hydrogen coupled energy network model, the energy interaction mechanism between the power network, the gas network and the hydrogen energy network can be deeply studied, and fed back into the collaborative optimization model of the electric-hydrogen coupled network to build a more accurate electric-hydrogen coupled energy network model.

[0083] By integrating the coupling relationship and energy conversion process among the above-mentioned networks, a complete electric-hydrogen coupled energy flow model is established, which can accurately simulate the energy flow, conversion and storage of different energy forms in various links in urban areas, providing a solid theoretical basis for energy system analysis and optimization.

[0084] In the embodiment, the energy interaction mechanism between the power network, the gas network and the hydrogen energy network includes: when establishing the electric hydrogen coupling energy flow model, the demand characteristics and energy usage habits of different energy users in the urban area are fully considered. For industrial users, their demand for electricity and steam has continuity and stability requirements. The model needs to reflect the law of energy consumption in the industrial production process and the dynamic balance relationship with the energy supply system; for commercial users, such as large shopping malls and office buildings, their electricity load varies greatly with business hours, and the demand for air conditioning, refrigeration and heating is obvious. The model needs to consider the seasonal and daily variation characteristics of the energy demand of commercial buildings, as well as the interactive effects with the power, gas and hydrogen energy networks; for residential users, their energy demand is mainly electricity, heating and domestic hot water, and has obvious peak and valley characteristics. The model needs to accurately simulate the energy consumption patterns of residential users at different times, as well as the role of distributed energy equipment (such as household photovoltaic power generation, small fuel cell cogeneration system, etc.) in residential energy supply.

[0085] Introduce a feedback mechanism for real-time monitoring data and forecast data into the model to improve the accuracy and adaptability of the model. Install high-precision sensors at key nodes of the urban energy network to collect parameters such as the flow, pressure, and temperature of electricity, gas, and hydrogen in real time, input these data into the electric-hydrogen coupled energy flow model in real time, and dynamically correct and verify the model. At the same time, combined with forecast information such as meteorological data, economic data, and social activity data, the changing trend of urban energy demand is estimated in advance, so that the model can respond in advance, optimize the operation strategy of the energy system, and improve the reliability and flexibility of urban energy supply.

[0086] In the embodiment, historical operation data of power networks, gas networks and hydrogen energy networks in urban areas are widely collected, including power load curves for many years, gas consumption statistics, hydrogen production and consumption records, etc. These data are classified, sorted and analyzed in detail to extract the operation characteristics and laws of energy systems in different seasons, different date types (working days, holidays, etc.) and different stages of economic development. For example, the peak hours and peak values ​​of power load during high temperatures in summer, as well as the corresponding changes in gas and hydrogen demand, are analyzed; the growth trend of gas consumption during the winter heating period and its impact on power and hydrogen supply are studied. Advanced real-time monitoring equipment, such as smart meters, high-precision gas flow meters, hydrogen mass flow meters and pressure sensors, are installed at key nodes of the urban energy network to ensure that accurate energy operation data can be obtained in real time. These data are transmitted to the data processing center in real time through wireless communication technology, and used together with historical data as the basis for model verification and optimization.

[0087] Input historical data and real-time data into the electric-hydrogen coupled energy flow model, run the model for simulation calculation, and compare the model output results with the actual measured data. Focus on the differences in key parameters such as flow, power, and pressure of the energy flow. If it is found that the power load predicted by the model deviates from the actual measured value, carefully analyze the cause of the deviation. It may be that some emerging power loads (such as the growth of energy consumption in large-scale data centers) are not fully considered in the model, or the prediction of distributed energy generation is inaccurate (such as the simulation error of photovoltaic power generation affected by weather changes). The root mean square error (RMSE), mean absolute error (MAE) and Pearson correlation coefficient are introduced to evaluate the accuracy of the electric-hydrogen coupled energy network model. According to the comparison results, the model parameters are optimized and adjusted in a targeted manner. For the power network model, if it is found that the power grid loss rate in a certain area is higher than the model prediction value, check whether the line resistance parameters are accurate and whether they need to be corrected according to the actual line aging; for the gas network model, if the actual gas pressure at some nodes does not match the model calculation results, re-evaluate parameters such as the pipeline friction coefficient; for the hydrogen energy network model, if the simulated change of hydrogen storage capacity is different from the actual situation, adjust the leakage rate of the hydrogen storage facility and other parameters. Through continuous verification and optimization, the accuracy and reliability of the electrical-hydrogen coupled energy flow model are improved so that it can more realistically reflect the actual operation of the urban area energy system.

[0088] Use data mining and machine learning techniques to conduct in-depth analysis of historical data and real-time data, explore potential energy system operation modes and laws, and provide more information for model optimization. For example, use cluster analysis methods to classify energy consumption behaviors of different types of users, establish a user energy consumption pattern library, so as to more accurately simulate the energy needs of different user groups in the model; use neural network algorithms to learn and predict the dynamic characteristics of energy systems, discover possible energy supply and demand imbalances in advance, and provide early warning information for energy scheduling and optimization.

[0089] Establish an automated process and evaluation index system for model verification and optimization. By writing automated scripts, the model verification program is automatically run regularly (such as daily or weekly), the model output results are compared with the actual data, and the model performance is quantitatively evaluated based on preset evaluation indicators (such as root mean square error, mean absolute error, etc.). When the model performance is lower than the set threshold, the optimization program is automatically triggered to adjust the model parameters according to the data analysis results, improve the efficiency of model maintenance and optimization, and ensure that the model always maintains a high level of accuracy and reliability.

[0090] In the embodiment, based on the optimized electric hydrogen coupling energy flow model, the energy flow distribution of the urban regional energy system under the current operating state is comprehensively analyzed. The power flow direction, size and loss of each transmission line, substation and load node in the power network are calculated in detail to determine the transmission path and supply reliability of electricity in different areas of the city (such as commercial areas, industrial areas, residential areas, etc.). For example, through model analysis, it is found that some lines in the power grid of an old urban area are overloaded, which provides a basis for upgrading and transforming the power grid.

[0091] For the gas network, analyze the pressure distribution and flow distribution of gas in each pipeline and the supply between different users (residential users, industrial users, commercial users, etc.). Study the consumption patterns of gas in gas turbine power generation, heating boilers, industrial furnaces and other equipment, and evaluate the stability and safety of the gas supply system. For example, during the winter heating peak, the model predicts whether the gas supply can meet the needs of residents and industrial users, and whether emergency measures need to be taken (such as increasing the gas supply of gas storage or adjusting the gas supply priority).

[0092] For the hydrogen energy network, analyze the dynamic changes in the storage, production, consumption and delivery of hydrogen in hydrogen production devices, hydrogen storage facilities, fuel cell power generation units and hydrogen refueling stations. Evaluate the satisfaction of hydrogen fuel cell vehicle hydrogenation needs and the application effect of hydrogen as a storage and power generation medium in distributed energy systems. For example, according to the model, predict whether the hydrogen reserves at hydrogen refueling stations are sufficient during large-scale events in the city, and whether it is necessary to adjust the production plan of the hydrogen production device in advance.

[0093] In the process of operating status analysis and prediction, uncertainty analysis methods are introduced to consider the impact of factors such as the intermittent nature of renewable energy generation (such as the uncertainty of wind and solar energy), the randomness of energy demand (such as the uncertainty of residents' electricity consumption behavior), and the probability of energy equipment failure on the operation of the energy system. Through methods such as Monte Carlo simulation, a variety of possible operating scenarios are generated, and the operating status of the energy system in each scenario is analyzed and predicted, so as to obtain a more robust energy system optimization operation strategy and improve the ability of urban area energy systems to cope with uncertainty. For the reliability assessment of energy systems, the loss of load probability (LOLP) and the expected energy shortage (EENS) can be introduced to evaluate the reliability of energy systems from different angles, especially the ability to cope with load demand.

[0094] The beneficial effects of the present invention are that, compared with the prior art, at least include, by coupling electricity, gas and hydrogen energy networks, through reasonable model construction, it is possible to accurately plan the processes of electricity to hydrogen, hydrogen to electricity and electricity to gas according to the city's energy demand and renewable energy power generation, effectively store and convert excess renewable energy into other available energy forms, reduce wind and light abandonment, and increase the proportion and utilization efficiency of renewable energy in the urban energy system; based on real-time data collection and analysis, the model can dynamically optimize energy conversion and transmission strategies based on factors such as changes in urban power grid load and energy supply status. For example, when the power grid load is at a peak, quickly start hydrogen fuel cells or gas engines to supplement electricity; when the load is at a low point, store excess electricity or convert it into other energy forms. Effectively smooth out energy system fluctuations, ensure continuous and stable power supply, meet the city's diversified energy needs, improve industrial production efficiency, and ensure the quality of life of residents; fully consider the energy demand characteristics and infrastructure differences in different areas of the city, and optimize the energy network transmission model and energy station operation strategy. When local energy supply fails or is tight, it can quickly coordinate energy resources in other regions to achieve flexible allocation and mutual assistance of energy, ensure the stability and reliability of the city's energy supply under various working conditions, reduce the risk of energy interruptions, and enhance the resilience of the city's energy supply.

[0095] The present invention also proposes a city area electrical hydrogen coupling energy network modeling system, comprising:

[0096] The characteristic parameter determination module is used to obtain the topological structure of the power network, gas network and hydrogen energy network in the urban area, and construct the power network model, gas network model and hydrogen energy network model respectively; wherein each network model includes each uncoupled node within the network and the connection path between each uncoupled node; the energy transmission efficiency on the connection path is used as the characteristic length of the connection path, the power storage facility in the power network model uses the charge state of the battery as the characteristic value, and the hydrogen storage facility in the hydrogen energy network model uses the hydrogen storage level of the hydrogen storage equipment as the characteristic value; the topological structure of the coupling between the power network and the hydrogen energy network is obtained to determine each electric-hydrogen coupling node of the power network model and the hydrogen energy network model, and the coupling path between each electric-hydrogen coupling node; the topological structure of the coupling between the gas network and the hydrogen energy network is obtained to determine each gas-hydrogen coupling node of the gas network model and the hydrogen energy network model, and the coupling path between each gas-hydrogen coupling node; the topological structure of the coupling between the gas network and the power network is obtained to determine each gas-electricity coupling node of the gas network model and the power network model, and the coupling path between each gas-electricity coupling node; the energy transmission efficiency on the coupling path is used as the characteristic length of the coupling path;

[0097] An operating parameter determination module is used to establish a collaborative optimization model of an electric-hydrogen coupling network with characteristic lengths of each connection path, characteristic lengths of each coupling path, characteristic values ​​of power storage facilities, and characteristic values ​​of hydrogen storage facilities as constraints for electric-hydrogen energy flow, and with minimum total operation and maintenance cost as the electric-hydrogen energy flow target; obtain predicted values ​​of electric energy production and electric energy demand, predicted values ​​of hydrogen production and hydrogen demand, predicted values ​​of gas production and gas demand, and use the collaborative optimization model of the electric-hydrogen coupling network to output operating parameters of the electric network model, operating parameters of the gas network model, and operating parameters of the hydrogen energy network model;

[0098] The model building module is used to construct an electric-hydrogen coupled energy network model using the electric power network model and its operating parameters, the gas network model and its operating parameters, the hydrogen energy network model and its operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility.

[0099] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0100] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the above. The computer-readable storage medium used herein is not to be interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0101] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0102] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect through the Internet). In some embodiments, by using the state information of the computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit may execute the computer-readable program instructions, thereby implementing various aspects of the present disclosure.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements 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. A method for modeling an urban area electrical hydrogen coupling energy network, characterized in that: include: Obtain the topological structures of the power network, gas network, and hydrogen energy network in the urban area, and construct the power network model, gas network model, and hydrogen energy network model respectively; wherein each network model includes each uncoupled node within the network and the connection path between each uncoupled node; the energy transmission efficiency on the connection path is used as the characteristic length of the connection path, the power storage facility in the power network model uses the charge state of the battery as the characteristic value, and the hydrogen storage facility in the hydrogen energy network model uses the hydrogen storage level of the hydrogen storage equipment as the characteristic value; Obtain the topological structure of the coupling between the power network and the hydrogen energy network to determine the coupling paths between the electric-hydrogen coupling nodes and the electric-hydrogen coupling nodes of the power network model and the hydrogen energy network model; obtain the topological structure of the coupling between the gas network and the hydrogen energy network to determine the coupling paths between the gas network model and the gas-hydrogen coupling nodes and the gas-hydrogen coupling nodes of the hydrogen energy network model; obtain the topological structure of the coupling between the gas network and the power network to determine the coupling paths between the gas network model and the gas-electricity coupling nodes and the gas-electricity coupling nodes of the power network model; use the energy transmission efficiency on the coupling path as the characteristic length of the coupling path; Taking the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility as the constraints of the electric hydrogen energy flow, and taking the minimum total operation and maintenance cost as the electric hydrogen energy flow target, a collaborative optimization model of the electric hydrogen coupling network is established; the predicted values ​​of electric energy production and electric energy demand, the predicted values ​​of hydrogen production and hydrogen demand, and the predicted values ​​of gas production and gas demand are obtained, and the collaborative optimization model of the electric hydrogen coupling network is used to output the operating parameters of the electric power network model, the operating parameters of the gas network model and the operating parameters of the hydrogen energy network model; An electric-hydrogen coupled energy network model is constructed using the power network model and its operating parameters, the gas network model and its operating parameters, the hydrogen energy network model and its operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility.

2. The urban area electrical hydrogen coupling energy network modeling method according to claim 1 is characterized in that: In the power network model, the characteristic length of the connection path is the power transmission efficiency of the transmission line, which satisfies the following relationship: ， In the formula, is the power transmission efficiency of the transmission line, is the power at the power flow input end of the transmission line, is the power at the output end of the power flow on the transmission line.

3. The urban area electrical hydrogen coupling energy network modeling method according to claim 1 is characterized in that: In the gas network model, the characteristic length of the connection path is the gas transmission efficiency of the gas pipeline, which satisfies the following relationship: ， In the formula, is the gas transmission efficiency of the gas pipeline, is the gas mass flow rate at the pipeline inlet, is the gas mass flow rate at the pipeline outlet.

4. The urban area electrical hydrogen coupling energy network modeling method according to claim 1 is characterized in that: In the hydrogen network model, the characteristic length of the connection path is the hydrogen transmission efficiency of the hydrogen pipeline, which satisfies the following relationship: ， In the formula, The hydrogen transmission efficiency of the hydrogen pipeline, is the hydrogen mass flow rate at the pipeline inlet, is the hydrogen mass flow rate at the pipeline outlet.

5. The urban area electrical hydrogen coupling energy network modeling method according to claim 1 is characterized in that: The power storage facilities in the power network model use the state of charge of the battery as the characteristic value, satisfying the following relationship: ， In the formula, for The battery's state of charge at all times, for The remaining battery power at all times, is the rated capacity of the battery.

6. The urban area electrical hydrogen coupling energy network modeling method according to claim 1 is characterized in that: The hydrogen storage facilities in the hydrogen energy network model use the hydrogen storage level of the hydrogen storage equipment as the characteristic value, satisfying the following relationship: ， In the formula, is the hydrogen storage level of the hydrogen storage device, for The quality of hydrogen in the hydrogen storage facility at all times, is the rated hydrogen storage capacity of the hydrogen storage facility.

7. The urban area electrical hydrogen coupling energy network modeling method according to claim 2 is characterized in that: The characteristic length of the coupling path between the electric-hydrogen coupling nodes is the power transmission efficiency of the transmission line.

8. The urban area electrical hydrogen coupling energy network modeling method according to claim 1 is characterized in that: The characteristic length of the coupling path between the gas-hydrogen coupling nodes is the transmission efficiency of the hydrogen-blended natural gas in the gas pipeline, which satisfies the following relationship: ， In the formula, The transmission efficiency of hydrogen-blended natural gas in gas pipelines. is the total mass of hydrogen after mixing, is the mass of hydrogen injected into the pipeline, The quality of the gas injected into the pipeline.

9. The urban area electrical hydrogen coupling energy network modeling method according to claim 4 is characterized in that: The characteristic length of the coupling path between the gas-electricity coupling nodes is the gas transmission efficiency of the gas pipeline.

10. An urban area electrical hydrogen coupling energy network modeling system, characterized in that: include: The characteristic parameter determination module is used to obtain the topological structure of the power network, gas network and hydrogen energy network in the urban area, and construct the power network model, gas network model and hydrogen energy network model respectively; wherein each network model includes each uncoupled node within the network and the connection path between each uncoupled node; the energy transmission efficiency on the connection path is used as the characteristic length of the connection path, the power storage facility in the power network model uses the charge state of the battery as the characteristic value, and the hydrogen storage facility in the hydrogen energy network model uses the hydrogen storage level of the hydrogen storage equipment as the characteristic value; the topological structure of the coupling between the power network and the hydrogen energy network is obtained to determine each electric-hydrogen coupling node of the power network model and the hydrogen energy network model, and the coupling path between each electric-hydrogen coupling node; the topological structure of the coupling between the gas network and the hydrogen energy network is obtained to determine each gas-hydrogen coupling node of the gas network model and the hydrogen energy network model, and the coupling path between each gas-hydrogen coupling node; the topological structure of the coupling between the gas network and the power network is obtained to determine each gas-electricity coupling node of the gas network model and the power network model, and the coupling path between each gas-electricity coupling node; the energy transmission efficiency on the coupling path is used as the characteristic length of the coupling path; An operating parameter determination module is used to establish a collaborative optimization model of an electric-hydrogen coupling network with characteristic lengths of each connection path, characteristic lengths of each coupling path, characteristic values ​​of power storage facilities, and characteristic values ​​of hydrogen storage facilities as constraints for electric-hydrogen energy flow, and with minimum total operation and maintenance cost as the electric-hydrogen energy flow target; obtain predicted values ​​of electric energy production and electric energy demand, predicted values ​​of hydrogen production and hydrogen demand, predicted values ​​of gas production and gas demand, and use the collaborative optimization model of the electric-hydrogen coupling network to output operating parameters of the electric network model, operating parameters of the gas network model, and operating parameters of the hydrogen energy network model; The model building module is used to construct an electric-hydrogen coupled energy network model using the electric power network model and its operating parameters, the gas network model and its operating parameters, the hydrogen energy network model and its operating parameters, the characteristic length of each connection path, the characteristic length of each coupling path, the characteristic value of the power storage facility and the characteristic value of the hydrogen storage facility.

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