Oil-gas-hydrogen-electricity comprehensive energy service station development and evolution simulation system and method

Abstract

The invention discloses a development and evolution simulation system and method for an oil-gas-hydrogen-electricity integrated energy service station, and belongs to the technical field of energy infrastructure planning, and the simulation system can achieve the change simulation of a causal relationship among various complex factors of the integrated energy service station, can achieve the development and evolution research of the integrated energy service station quickly and reliably, and improves the development and evolution efficiency of the integrated energy service station. And a more real and reliable data basis is provided for energy enterprises, power grid companies, government supervision departments, third-party investors and the like to make decisions such as scientific site selection, investment decision, scale determination, development stage pre-judgment, power distribution network collaborative planning and the like of the user-side comprehensive energy service station.

Description

Technical Field

[0001] This application belongs to the field of energy infrastructure planning technology, specifically involving a simulation system and method for the development and evolution of integrated oil, gas, hydrogen and electricity energy service stations. It provides data and technical support for energy companies, power grid companies, government regulatory departments and third-party investors to conduct scientific site selection, investment decisions, scale determination, development stage prediction and distribution network collaborative planning for user-side integrated energy service stations. Background Technology

[0002] With the acceleration of energy transition and the advancement of the "dual carbon" goal, traditional gas stations on the user side are gradually evolving into comprehensive energy service stations that provide complementary services such as oil, gas, hydrogen, and electricity. They have great potential, especially in areas with abundant renewable energy, strong transportation demand, and strong policy support.

[0003] User-side integrated energy service stations for oil, gas, hydrogen, and electricity are affected by complex factors such as investment, energy demand, policies, and technology. However, existing technologies lack quantitative analysis of the causal relationships between complex influencing factors (such as the distribution of gas stations, the intentions of third-party entities, and the constraints of the power distribution network), as well as the ability to build dynamic models based on this to predict their number growth, spatial distribution, and energy structure evolution in a specific region. In particular, they neglect the impact of the deep coupling between regional characteristics and the power distribution network. Summary of the Invention

[0004] To address the problems existing in the prior art, this application proposes a simulation system and method for the development and evolution of integrated oil, gas, hydrogen and electricity energy service stations.

[0005] This application is achieved through the following technical solution:

[0006] A simulation system for the development and evolution of integrated oil, gas, hydrogen, and electricity energy service stations includes:

[0007] The data acquisition module interacts with an external platform through a multi-source data acquisition engine to obtain multi-source data;

[0008] The key factor screening module, in combination with the system dynamics modeling requirements, screens key factors from the initial factor set.

[0009] The model building module uses causal loop analysis to identify the feedback relationships between the key factors and establish a system dynamics model.

[0010] The development and evolution module calls the system dynamics model to perform real-time calls and iterative calculations on key factor data in the database, thereby realizing the simulation of the development and evolution of the integrated energy service station;

[0011] A database is used to store the data acquired by the data acquisition module and the simulation results of the development and evolution of the integrated energy service station by the development and evolution module;

[0012] And an output module, which outputs the simulation results of the development and evolution of the integrated energy service station of the development and evolution module to an external platform for auxiliary decision-making through a communication interface.

[0013] In some implementations, the data acquisition module obtains historical and forecast data on oil and electricity prices in real time through data interfaces authorized by energy regulatory authorities, obtains data on the geographical distribution and operational status of gas stations and CNG stations through traffic management platform data exchange protocols, obtains metadata on regional macroeconomic indicators, technical standards, and policy documents through government data interface APIs, and obtains data on the technological maturity, price, and energy consumption of electric vehicles and hydrogen fuel cell vehicles through third-party energy market data service providers' interfaces.

[0014] In some implementations, the key factor screening module combines the requirements of system dynamics modeling, conducts multiple rounds of evaluation on the initial factor set through the expert Delphi method, uses principal component analysis to reduce dimensionality and eliminate redundant variables, and combines sensitivity analysis to quantify the influence intensity of each factor on the development and evolution of the integrated energy service station, and selects the factors whose influence intensity exceeds the threshold as key factors.

[0015] In some implementations, the key factors selected by the key factor screening module include: regional GDP, population, vehicle scale, policy subsidies, vehicle prices, gas station distribution, technology maturity, and infrastructure construction.

[0016] In some implementations, the system dynamics model established by the model building module includes:

[0017] The development simulation unit simulates the changes in the number of integrated energy service stations by studying the number of newly built, renovated, and decommissioned stations.

[0018] The demand simulation unit simulates changes in the demand for oil, gas, hydrogen, and electricity by studying the number of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles.

[0019] A technology simulation unit is used to simulate the changing trends of investment amount and technology maturity as integrated energy service stations develop.

[0020] In addition, a policy simulation unit is provided, which is used to simulate the impact of various policies on the development of integrated energy service stations.

[0021] In some implementations, the simulation process of the development simulation unit includes:

[0022] The total number of integrated energy service stations is calculated by summing the number of newly built stations, the number of renovated stations, and the number of stations eliminated each year.

[0023] The number of new stations to be built each year is calculated based on approval efficiency, land resources, power grid capacity, and power grid demand. The land resources are constrained by the total number of integrated energy service stations and the maximum number of stations that a region can accommodate. The power grid capacity is constrained by policy intensity, charging demand, and peak power grid capacity. The power grid demand is constrained by charging demand and the total number of integrated energy service stations.

[0024] The number of gas stations to be renovated each year is calculated based on the base number of gas stations to be renovated, hydrogen refueling demand, and maximum renovation ratio.

[0025] The number of integrated energy service stations to be phased out each year is calculated based on the total number of stations, their average lifespan, and technological maturity.

[0026] In some implementations, the simulation process of the demand simulation unit includes:

[0027] Calculate the scale of each vehicle type based on the purchase volume and scrap volume of each vehicle type;

[0028] The change in GDP is calculated based on the GDP growth rate, and the total GDP is calculated based on the cumulative change in GDP and the initial total GDP.

[0029] The population change is calculated based on the population growth rate, and the total population is calculated based on the cumulative population change and the initial GDP.

[0030] The target value for vehicle ownership per thousand people is calculated based on GDP growth rate, population growth rate, and the contribution rate of GDP and population to vehicles.

[0031] Calculate the number of vehicles per thousand people based on the size of each vehicle type and the total population.

[0032] The new vehicle quantity is calculated based on the target value of vehicle ownership per thousand people, the vehicle ownership per thousand people, and the demand factor.

[0033] The total increase in vehicles is calculated based on the size of each vehicle type, the average service life of the vehicles, the delay time, and the number of new vehicles added.

[0034] Calculate the total increase in vehicles for each vehicle type based on the total increase in vehicle volume and the purchase share of each vehicle type.

[0035] The attractiveness of each vehicle model is calculated based on its inherent attractiveness constant, price, purchase subsidy, energy consumption per 100 kilometers, maintenance cost per kilometer, average annual mileage, and charging convenience.

[0036] The energy requirements for each vehicle type are calculated based on its size, energy consumption per 100 kilometers, and average annual mileage.

[0037] In some embodiments, the simulation process of the technology simulation unit includes:

[0038] Calculate the cumulative investment amount based on the annual increase in investment;

[0039] Calculate the technology maturity level based on the annual growth rate of the technology maturity level.

[0040] Calculate the annual growth rate of technology maturity based on cumulative investment, technology maturity, and technology learning rate constant;

[0041] The amount of new investment is calculated based on annual net profit, government subsidies, and reinvestment rate.

[0042] Calculate the annual net profit based on energy sales revenue, operating costs of integrated energy service stations, and government subsidies;

[0043] Calculate energy sales revenue based on different energy demands and their corresponding prices;

[0044] Calculate the unit construction cost based on the cumulative investment amount and the level of technological maturity;

[0045] Calculate the operating cost of integrated energy service stations based on the total number and technological maturity of the stations.

[0046] The return on investment is calculated based on the unit construction cost, the total number of integrated energy service stations, and the annual net profit.

[0047] Adjust the reinvestment rate based on the rate of return on investment.

[0048] In some implementations, the simulation process of the policy simulation unit includes:

[0049] Calculate the policy intensity based on the rate of policy adjustment;

[0050] Calculate the policy adjustment rate based on the intensity of policy objectives and policy intensity;

[0051] Calculate approval efficiency based on policy intensity and government implementation efficiency;

[0052] Government subsidies are calculated based on policy intensity, cumulative investment amount, and maximum investment target.

[0053] On the other hand, this application proposes a simulation method for the development and evolution of integrated oil, gas, hydrogen, and electricity energy service stations. This method is implemented based on any of the embodiments described in the above simulation system, and includes:

[0054] Real-time acquisition of data on key factors and input into a pre-established system dynamics model;

[0055] The development and evolution of integrated energy service stations are simulated through iterative calculations using the system dynamics model.

[0056] The simulation results of the development and evolution of the integrated energy service station are output to an external platform for decision support.

[0057] This application proposes a simulation system and method for the development and evolution of integrated energy service stations based on oil, gas, hydrogen, and electricity. This simulation system can simulate the causal relationship changes among various complex factors in integrated energy service stations, and can quickly and reliably conduct research on the development and evolution of integrated energy service stations. It provides more realistic and reliable data for energy companies, power grid companies, government regulatory departments, and third-party investors to make decisions on the scientific site selection, investment decisions, scale determination, development stage prediction, and distribution network collaborative planning of user-side integrated energy service stations. Attached Figure Description

[0058] The accompanying drawings, which are included to provide a further understanding of the embodiments of this application and form part of this application, do not constitute a limitation on the embodiments of this application. In the drawings:

[0059] Figure 1 This is a schematic diagram of the simulation system architecture proposed in the embodiments of this application;

[0060] Figure 2 This is a schematic diagram of the system dynamics model structure proposed in the embodiments of this application;

[0061] Figure 3 This is a flowchart of the simulation method proposed in the embodiments of this application. Detailed Implementation

[0062] In the following, the terms “comprising” or “may include” as used in the various embodiments of this application indicate the presence of a function, operation, or element of the invention and do not limit the addition of one or more functions, operations, or elements. Furthermore, as used in the various embodiments of this application, the terms “comprising,” “having,” and their cognates are intended only to indicate a specific feature, number, step, operation, element, component, or combination of the foregoing and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing, or adding one or more combinations of the foregoing.

[0063] In various embodiments of this application, the expression "or" or "at least one of A and / or B" includes any combination or all combinations of the words listed simultaneously. For example, the expression "A or B" or "at least one of A and / or B" may include A, may include B, or may include both A and B.

[0064] The terms used in the various embodiments of this application (such as "first," "second," etc.) may modify various constituent elements in the various embodiments, but do not limit the corresponding constituent elements. For example, the above terms do not limit the order and / or importance of the elements. The above terms are only used for the purpose of distinguishing one element from other elements. For example, a first user device and a second user device refer to different user devices, although both are user devices. For example, without departing from the scope of the various embodiments of this application, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

[0065] It should be noted that if a description is made of "connecting" one component to another, then the first component can be directly connected to the second component, and a third component can be "connected" between the first and second components. Conversely, when a component is "directly connected" to another component, it can be understood that there is no third component between the first and second components.

[0066] The terminology used in the various embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the various embodiments of this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. The terms (such as those defined in a generally used dictionary) are to be interpreted as having the same meaning as in the context of the relevant technical field and are not to be interpreted as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0067] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the embodiments and accompanying drawings. The illustrative embodiments and descriptions of this application are only for explaining this application and are not intended to limit this application.

[0068] To address the difficulty of establishing causal relationships and interrelationships among complex factors using existing technologies, and the challenge of rapidly and reliably conducting research on the development and evolution of integrated energy service stations, this application proposes a simulation system and method for the development and evolution of integrated oil, gas, hydrogen, and electricity energy service stations.

[0069] like Figure 1 As shown, the simulation system proposed in this application includes:

[0070] The data acquisition module interacts with external platforms through the system's built-in multi-source data acquisition engine to acquire multi-source data. This includes real-time acquisition of historical and forecast data on oil and electricity prices via data interfaces authorized by energy regulatory authorities; acquisition of data on the geographical distribution and operational status of gas stations and CNG stations via traffic management platform data exchange protocols; acquisition of macroeconomic indicators, technical standards, and policy document metadata for a specific region via government data interface APIs; and subscription to data on the technological maturity, pricing, and energy consumption indicators of electric and hydrogen fuel cell vehicles via third-party energy market data service provider interfaces. The system's built-in multi-protocol communication interface ensures secure data transmission and writes data to a database or edge storage device for real-time access and iterative calculations by the system's dynamics model.

[0071] The key factor screening module, combined with the requirements of system dynamics modeling, conducts multiple rounds of evaluation of the initial factor set using the expert Delphi method, eliminates redundant variables using principal component analysis, and quantifies the influence intensity of each factor on the development and evolution of integrated energy service stations using sensitivity analysis. Factors with influence intensity exceeding a threshold are selected as key factors. In this embodiment, the key factor screening module analyzes and determines factors such as regional GDP, population, vehicle scale, policy subsidies, vehicle prices, gas station distribution, technological maturity, and infrastructure construction as key factors.

[0072] The model building module uses causal loop analysis to identify feedback relationships between key factors selected and establish a system dynamics model.

[0073] The development and evolution module calls the system dynamics model to perform real-time calls and iterative calculations on key factor data in the database, thereby realizing the simulation of the development and evolution of integrated energy service stations.

[0074] The database is used to store the data acquired by the data acquisition module and the simulation results of the development and evolution of the integrated energy service station by the development and evolution module.

[0075] In addition, there is an output module, which outputs the simulation results of the development and evolution of the integrated energy service station from the development and evolution module to an external platform through the system's built-in communication interface, providing data support for energy companies, power grid companies, government regulatory departments, and third-party investors.

[0076] Furthermore, such as Figure 2 As shown, the system dynamics model established by the model building module in this application embodiment includes:

[0077] The development simulation unit studies the number of newly built, renovated, and decommissioned integrated energy service stations to simulate changes in the number of such stations. Its core focus is the interaction between station scale and external constraints. The number of new stations is subject to multiple constraints, including investment capacity, land resources, and grid capacity. Investment capacity depends on reinvestment of net revenue and government subsidies; land resources and grid capacity become increasingly scarce as the number of stations increases. The number of renovated stations is determined by both the existing number of gas stations to be renovated and the intensity of hydrogen refueling demand; higher demand leads to a greater number of renovations.

[0078] The demand simulation unit studies the changes in demand for oil, gas, hydrogen, and electricity by examining the number of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles. Its key lies in the two-way driving force of energy supply and vehicle growth. Vehicle ownership is interconnected with government subsidies, infrastructure construction needs, and energy demand. Government subsidies directly reduce consumers' vehicle purchase costs, increasing the attractiveness of specific models and thus promoting their market share growth (i.e., increased ownership). As the ownership of a certain type of vehicle increases, the demand for related infrastructure construction increases accordingly. Improved infrastructure coverage significantly enhances user convenience, creating a positive cycle. Simultaneously, the growth in vehicle ownership pushes up energy demand, leading to fluctuations in the prices of electricity, hydrogen, or natural gas. These changes in energy costs, in turn, affect the economic viability of different vehicle models.

[0079] The technology simulation unit simulates the changing trends of investment and technology maturity as integrated energy service stations develop. Its core is a positive feedback loop between investment and technology maturity. Increased cumulative investment directly drives improvements in technology maturity, which in turn significantly reduces unit construction and operating costs, thereby increasing net revenue. Increased net revenue further stimulates increased annual investment, creating a self-reinforcing cycle. Government subsidies, as external incentives, supplement investment sources and, together with cost reduction through technology, support the sustainability of net revenue. The rate of return on investment indirectly regulates investment scale by influencing the reinvestment rate, ensuring the stability of the investment and technology cycle.

[0080] In addition, there is a policy simulation unit, which influences the development of integrated energy service stations through various policies. Its core is the dynamic balance between policy objectives and implementation effects. The intensity of policy objectives fluctuates on a five-year cycle, driving changes in the rate of policy adjustment, which in turn affects the rise and fall of the actual policy intensity index. Increased policy intensity directly improves approval efficiency and government subsidies, accelerating new construction and renovation activities. Simultaneously, government subsidies decrease as cumulative investment approaches its upper limit, forming a self-regulating mechanism.

[0081] Furthermore, the development simulation unit in this application embodiment is represented as follows:

[0082] ;

[0083] ;

[0084] ;

[0085] ;

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] in, This refers to the total number of integrated energy service stations; This refers to the number of new sites built each year. The number of stations converted from traditional gas stations each year; This represents the number of sites eliminated each year. This is the initial time; The simulation lifespan; Indicates approval efficiency; Land constraints indicate the maximum number of new sites that can be built each year; The total capacity that the power grid can provide; This represents the average grid demand per station. This is the land occupancy coefficient, representing the percentage reduction in remaining land for each additional station. This represents the maximum number of stations that the area can accommodate. As for policy intensity; For charging needs; This represents the peak capacity of the power grid. This is the overcapacity penalty coefficient; This is the charging demand allocation coefficient; This refers to the annual increase in investment. Unit construction cost; Initial land constraints; The total initial capacity that the power grid can provide; This represents the initial average grid demand per station. This represents the maximum possible modification ratio; The number of traditional gas stations awaiting renovation; For hydrogen demand; This represents the inhibition function of hydrogen demand on modification intentions; The preferred value for homeowners' willingness to renovate is 0.7 in this application embodiment; Average lifespan of the site; This indicates that only when the technology maturity level exceeds 0.7 will the excess portion accelerate the obsolescence rate. An additional acceleration factor when the technology maturity exceeds 0.7; For technology maturity.

[0091] Furthermore, the requirement simulation unit in this application embodiment is represented as follows:

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[0113] in, For electric vehicles, the scale is determined by their purchase volume. and scrap volume The combined effect determines; For traditional vehicle scale, based on its purchase volume and scrap volume The combined effect determines; The scale of hydrogen fuel cell vehicles is determined by their purchase volume. and scrap volume The combined effect determines; The scale of natural gas vehicles is determined by their purchase volume. and scrap volume The combined effect determines; The average lifespan of a vehicle; Total GDP; GDP growth rate; For population size; Population growth rate; The target value for the number of vehicles per thousand people; It is a constant, reflecting the contribution rate of GDP and population to vehicles; Vehicle ownership per thousand people; For the increase in vehicle volume; Demand factor; For delay time; The total increase in vehicles is determined by both the number of new vehicles added and the number of vehicles scrapped. , , and The purchase share of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively; , , , The attractiveness of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively; The sum of the attractiveness of electric vehicles, conventional vehicles, hydrogen vehicles, and natural gas vehicles; , , , These are the inherent attraction constants for electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively. ~ The sensitivity coefficients for each factor; , , , These are the prices for electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively. , , The subsidies are for the purchase of electric vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively. , , , Energy consumption per 100 kilometers for electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively; , , , The maintenance cost per kilometer for electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively; , , , These are the average annual mileages of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively. , , , The charging convenience for electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively; , , and These are the demands for electricity, hydrogen, oil, and gas, respectively. , , , For the initial scale of electric vehicles, conventional vehicles, hydrogen vehicles and natural gas vehicles; This represents the initial total GDP. This represents the initial population size. The initial target value for vehicle ownership per thousand people; , , , These figures represent the scrapping volumes of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles, respectively.

[0114] Furthermore, the technical simulation unit in this application embodiment is represented as follows:

[0115] ;

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[0119] ;

[0120] ;

[0121] ;

[0122] ;

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[0125] in, This refers to the cumulative investment amount; This refers to the annual increase in investment. Represents technological maturity; This represents the annual growth rate of technology maturity. This is the constant for the technology learning rate; technology growth is positively correlated with investment scale, but slows down as the technology matures. The smaller the technology gap, the slower the growth. The reinvestment rate is the proportion of net income that is reinvested. Net profit for the year; Government subsidies; Revenue from energy sales; Operating costs for integrated energy service stations; For charging price, For the price of hydrogen, For gas prices, The price of gas; Unit construction cost; For learning curve coefficients; and These represent the extent to which technology-driven cost reductions reduce unit construction and operating costs. For return on investment.

[0126] Furthermore, the policy simulation unit in this application embodiment is represented as follows:

[0127] ;

[0128] ;

[0129] ;

[0130] ;

[0131] ;

[0132] in, As for policy intensity; To adjust the rate of policy changes; The speed coefficient indicates the rate of policy adjustment. The intensity of policy objectives; The factor decays over time, representing the natural decay of the policy effect over time (approximately 2% decay per year). To improve government efficiency, the preferred embodiment of this application is 0.8; It is an exponentially decaying function; The reduction factor represents the degree of subsidy reduction as a percentage of cumulative investment to the maximum investment. The maximum investment target means that when the cumulative investment reaches this value, the subsidy will be significantly reduced. To determine the fluctuation range, the policy target strength is initially set at 0.8, with a 5-year cycle of ± Fluctuating within a range; Initial government subsidies; The strength of the initial policy objectives.

[0133] The simulation system proposed in this application can simulate the causal relationship changes among various complex factors in integrated energy service stations, and can quickly and reliably realize the development and evolution research of integrated energy service stations. It provides data and technical support for energy companies, power grid companies, government regulatory departments and third-party investors to conduct scientific site selection, investment decisions, scale determination, development stage prediction and distribution network collaborative planning of user-side integrated energy service stations.

[0134] Based on the above simulation system, this application also proposes a simulation method for the development and evolution of integrated oil, gas, hydrogen, and electricity energy service stations, such as... Figure 3 As shown, the method proposed in this application includes the following steps:

[0135] Real-time acquisition of data on key factors and input into a pre-established system dynamics model;

[0136] The evolution of integrated energy service stations is simulated through iterative calculations using a system dynamics model.

[0137] The simulation results of the development and evolution of integrated energy service stations will be output to an external platform for decision support.

[0138] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application 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.

[0139] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. 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... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0140] 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.

[0141] 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.

[0142] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above description is only a specific embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station, characterized in that, include: The data acquisition module interacts with an external platform through a multi-source data acquisition engine to obtain multi-source data; The key factor screening module, in combination with the system dynamics modeling requirements, screens key factors from the initial factor set. The model building module uses causal loop analysis to identify the feedback relationships between the key factors and establish a system dynamics model. The development and evolution module calls the system dynamics model to perform real-time calls and iterative calculations on key factor data in the database, thereby realizing the simulation of the development and evolution of the integrated energy service station; A database is used to store the data acquired by the data acquisition module and the simulation results of the development and evolution of the integrated energy service station by the development and evolution module; And an output module, which outputs the simulation results of the development and evolution of the integrated energy service station of the development and evolution module to an external platform for auxiliary decision-making through a communication interface.

2. The simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 1, characterized in that, The data acquisition module obtains historical and forecast data on oil and electricity prices in real time through data interfaces authorized by energy regulatory authorities, obtains data on the geographical distribution and operational status of gas stations and CNG stations through the data exchange protocol of the traffic management platform, obtains metadata on regional macroeconomic indicators, technical standards and policy documents through government data interface APIs, and obtains data on the technological maturity, price and energy consumption of electric vehicles and hydrogen fuel cell vehicles through third-party energy market data service providers' interfaces.

3. The simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 1, characterized in that, The key factor screening module, in conjunction with the system dynamics modeling requirements, conducts multiple rounds of evaluation of the initial factor set using the expert Delphi method, uses principal component analysis to reduce dimensionality and eliminate redundant variables, and combines sensitivity analysis to quantify the influence intensity of each factor on the development and evolution of the integrated energy service station, selecting factors whose influence intensity exceeds the threshold as key factors.

4. The simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 3, characterized in that, The key factors selected by the key factor screening module include: regional GDP, population, vehicle scale, policy subsidies, vehicle price, distribution of gas stations, technology maturity, and infrastructure construction.

5. A simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to any one of claims 1-4, characterized in that, The system dynamics model established by the model building module includes: The development simulation unit simulates the changes in the number of integrated energy service stations by studying the number of newly built, renovated, and decommissioned stations. The demand simulation unit simulates changes in the demand for oil, gas, hydrogen, and electricity by studying the number of electric vehicles, conventional vehicles, hydrogen-powered vehicles, and natural gas vehicles in use. A technology simulation unit is used to simulate the changing trends of investment amount and technology maturity as integrated energy service stations develop. In addition, a policy simulation unit is provided, which is used to simulate the impact of various policies on the development of integrated energy service stations.

6. The simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 5, characterized in that, The simulation process of the development simulation unit includes: The total number of integrated energy service stations is calculated by summing the number of newly built stations, the number of renovated stations, and the number of stations eliminated each year. The number of new stations to be built each year is calculated based on approval efficiency, land resources, power grid capacity, and power grid demand. The land resources are constrained by the total number of integrated energy service stations and the maximum number of stations that a region can accommodate. The power grid capacity is constrained by policy intensity, charging demand, and peak power grid capacity. The power grid demand is constrained by charging demand and the total number of integrated energy service stations. The number of gas stations to be renovated each year is calculated based on the base number of gas stations to be renovated, hydrogen refueling demand, and maximum renovation ratio. The number of integrated energy service stations to be phased out each year is calculated based on the total number of stations, their average lifespan, and technological maturity.

7. The simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 6, characterized in that, The simulation process of the demand simulation unit includes: Calculate the scale of each vehicle type based on the purchase volume and scrap volume of each vehicle type; The change in GDP is calculated based on the GDP growth rate, and the total GDP is calculated based on the cumulative change in GDP and the initial total GDP. The population change is calculated based on the population growth rate, and the total population is calculated based on the cumulative population change and the initial GDP. The target value for vehicle ownership per thousand people is calculated based on GDP growth rate, population growth rate, and the contribution rate of GDP and population to vehicles. Calculate the number of vehicles per thousand people based on the size of each vehicle type and the total population. The new vehicle quantity is calculated based on the target value of vehicle ownership per thousand people, the vehicle ownership per thousand people, and the demand factor. The total increase in vehicles is calculated based on the size of each vehicle type, the average service life of the vehicles, the delay time, and the number of new vehicles added. Calculate the total increase in vehicles for each vehicle type based on the total increase in vehicle volume and the purchase share of each vehicle type. The attractiveness of each vehicle model is calculated based on its inherent attractiveness constant, price, purchase subsidy, energy consumption per 100 kilometers, maintenance cost per kilometer, average annual mileage, and charging convenience. The energy requirements for each vehicle type are calculated based on its size, energy consumption per 100 kilometers, and average annual mileage.

8. The simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 7, characterized in that, The simulation process of the technology simulation unit includes: Calculate the cumulative investment amount based on the annual increase in investment; Calculate the technology maturity level based on the annual growth rate of the technology maturity level. Calculate the annual growth rate of technology maturity based on cumulative investment, technology maturity, and technology learning rate constant; The amount of new investment is calculated based on annual net profit, government subsidies, and reinvestment rate. Calculate the annual net profit based on energy sales revenue, operating costs of integrated energy service stations, and government subsidies; Calculate energy sales revenue based on different energy demands and their corresponding prices; Calculate the unit construction cost based on the cumulative investment amount and the level of technological maturity; Calculate the operating cost of integrated energy service stations based on the total number and technological maturity of the stations. The return on investment is calculated based on the unit construction cost, the total number of integrated energy service stations, and the annual net profit. Adjust the reinvestment rate based on the rate of return on investment.

9. A simulation system for the development and evolution of an integrated oil, gas, hydrogen, and electricity energy service station according to claim 8, characterized in that, The simulation process of the policy simulation unit includes: Calculate the policy intensity based on the rate of policy adjustment; Calculate the policy adjustment rate based on the intensity of policy objectives and policy intensity; Calculate approval efficiency based on policy intensity and government implementation efficiency; Government subsidies are calculated based on policy intensity, cumulative investment amount, and maximum investment target.

10. A simulation method for the development and evolution of integrated oil, gas, hydrogen, and electricity energy service stations, characterized in that, The method is implemented based on the simulation system described in any one of claims 1-9, and includes: Real-time acquisition of data on key factors and input into a pre-established system dynamics model; The development and evolution of integrated energy service stations are simulated through iterative calculations using the system dynamics model. The simulation results of the development and evolution of the integrated energy service station are output to an external platform for decision support.

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