Oil-gas-hydrogen-electricity integrated energy service station coupling modeling method and related equipment

Abstract

The invention discloses an oil-gas-hydrogen-electricity comprehensive energy service station coupling modeling method and related equipment, and relates to the field of energy internet, and the method comprises the steps: taking operation and price parameters of an electrolytic cell, a compressor, a storage tank, terminal supply, electric energy storage, a gas turbine, a photovoltaic power grid, a superior power grid and the like; based on time-sharing demands of vehicles (fuel oil, natural gas, hydrogen fuel cells and electric vehicles) and single-machine capacity and number of terminal supply equipment, time-sharing electric power balance of a supply end and a power utilization end, hydrogen / gas storage cross-period inventory continuity, electric energy storage charging and discharging and SOC constraint are established, and scale matching and the maximum installation number are set. An optimization model is constructed and solved by taking energy sales income operation and maintenance reduction cost, light abandoning cost and energy purchasing cost as objective functions, time-sharing equipment output, electricity purchasing quantity, oil / gas / hydrogen flow and electric energy storage state are output, and a basis is provided for station-level scheduling and planning.

Description

Technical Field

[0001] This work relates to the field of energy internet, specifically to a coupled modeling method and related equipment for integrated oil, gas, hydrogen, and electricity energy service stations. Background Technology

[0002] Driven by the current global energy structure transformation and the "dual carbon" goal, traditional single-energy supply models are no longer sufficient to meet the energy demands of green, low-carbon, and multi-energy complementarity. Integrated energy service stations, which combine multiple energy sources such as oil, gas, hydrogen, and electricity, have become an important development direction for transportation energy supply infrastructure. These service stations achieve coordinated energy supply and optimized scheduling by integrating equipment across multiple links, including sources, grids, loads, and storage. However, the complexity of their multi-energy coupling also brings challenges in planning, design, operation, and control.

[0003] In recent years, demonstration projects for integrated energy service stations have been gradually launched both domestically and internationally. The Wanquan integrated energy station, put into operation by the State Energy Group during the Winter Olympics, provides integrated services for refueling, hydrogen refueling, and charging. The Jinlong integrated energy service station built by China National Petroleum Corporation in Yanqing, Beijing, possesses the capability to coordinate oil, gas, hydrogen, electricity, and non-oil businesses. Sinopec has pioneered the construction of a five-in-one integrated energy station in Northeast China, encompassing oil, gas, hydrogen, electricity, and non-oil services. These projects demonstrate the trend of multi-energy coupling, but currently, a systematic modeling method is still lacking to support the coordinated optimization of all aspects of these projects.

[0004] Integrated energy service stations encompass various facilities, including photovoltaic power generation, water electrolysis for hydrogen production, energy storage systems, charging piles, fuel dispensers, and hydrogen refueling equipment. These energy subsystems are strongly coupled. However, existing research often focuses on modeling single energy sources or localized processes, failing to adequately consider the coupling mechanisms of multiple energy flows. This leads to limitations in overall system energy efficiency and insufficient economic optimization. Therefore, a modeling method that accurately characterizes the multi-energy coupling relationships within integrated energy service stations is urgently needed to reveal the coupling mechanisms across the entire oil-gas-hydrogen-electricity chain and provide theoretical support for system planning, design, operation scheduling, and benefit assessment. This research aims to address these issues through coupling modeling, promoting the development of integrated energy service stations towards high efficiency and low carbon emissions. Summary of the Invention

[0005] The technical problem to be solved by this invention is the lack of integrated planning for cost-benefit measurement in existing integrated oil, gas, hydrogen and electricity energy service stations. The purpose is to provide a coupled modeling method for integrated oil, gas, hydrogen and electricity energy service stations, which solves the problems of incomplete multi-energy coupling and lack of constraints that lead to scheduling infeasibility and economic deviation.

[0006] This invention is achieved through the following technical solution:

[0007] A coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations, including

[0008] The system acquires operating parameters of in-station equipment, parameters of external energy supply units, and price parameters. The operating parameters of in-station equipment include those of electrolyzers, hydrogen compressors, hydrogen storage tanks, hydrogen dispensers, electric energy storage systems, charging piles, gas turbines, natural gas compressors, gas storage tanks, gas dispensers, oil pumps, and fuel dispensers. External energy supply units include photovoltaic systems and the upstream power grid. The price parameters include electricity purchase and sale prices, natural gas purchase and sale prices, fuel oil purchase and sale prices, and hydrogen prices.

[0009] The system obtains the time-of-use energy demand of gasoline vehicles, natural gas vehicles, hydrogen fuel cell vehicles, and electric vehicles, and obtains the scale matching of the corresponding terminal supply equipment to establish a measurement relationship for energy sales revenue. The terminal supply equipment includes fuel dispensers, gas dispensers, hydrogen dispensers, and charging piles.

[0010] Establish a time-sharing power balance between the supply side and the consumption side. Take the output of photovoltaic power, gas turbine power, discharge power of electric energy storage system and power purchased by the upper-level grid as the supply side, and take the input power of electrolyzer, hydrogen compressor input power, natural gas compressor input power, oil pump input power, charging power of electric energy storage system and power demand of electric vehicle as the consumption side.

[0011] Establish a measurement relationship between photovoltaic power output and curtailment penalty coefficient to measure curtailment cost;

[0012] Establish operational constraints, including at least: cross-period inventory-flow balance and inventory upper and lower limits constraints for hydrogen storage tanks and gas storage tanks, charge and discharge energy balance, capacity upper and lower limits and charge and discharge power upper limits constraints for electric energy storage systems, and minimum safe operating power constraints for electrolyzers.

[0013] The objective function for total revenue is calculated by subtracting operation and maintenance costs, curtailment costs, and energy purchase costs from energy sales revenue. Operation and maintenance costs include, at a minimum, fixed operation and maintenance costs for terminal supply equipment charged by quantity, and variable operation and maintenance costs for equipment within the station charged by operating power. Energy sales revenue is measured based on electricity prices, natural gas prices, fuel oil prices, and hydrogen prices. Energy purchase costs include, at a minimum, the cost of electricity purchased from the upstream power grid, the cost of natural gas purchased from external sources, and the cost of fuel oil purchased from external sources.

[0014] Under the conditions of satisfying time-of-use power balance and operation constraints, an optimization model is constructed and solved with the goal of maximizing total revenue. The optimization results are output for time-of-use supply-side equipment output, oil / gas / electricity purchase volume, oil / gas / hydrogen flow rate, and the state of the energy storage system.

[0015] Furthermore, the time-of-use energy requirements of the aforementioned gasoline-powered vehicles, natural gas vehicles, hydrogen fuel cell vehicles, and electric vehicles are determined according to the following rules:

[0016] Collect or analyze the distribution of vehicle arrival times and daily mileage.

[0017] By combining the vehicle's initial energy state or remaining range parameters, the mileage requirement is converted into time-of-use energy requirement according to the vehicle model's energy consumption / gas consumption / fuel consumption / hydrogen consumption coefficient per unit mileage;

[0018] The time-of-use fuel demand, time-of-use natural gas demand, time-of-use hydrogen demand, and time-of-use electricity demand are aggregated according to vehicle type in discrete time periods, and used as inputs for matching the scale of terminal supply equipment and power balance.

[0019] Furthermore, the scale matching of the terminal supply equipment includes:

[0020] The total demand for gasoline vehicles, natural gas vehicles, hydrogen fuel cell vehicles and electric vehicles during the statistical period is matched with the average daily supply of corresponding terminal supply equipment. The required terminal supply equipment is not less than "total demand / average daily supply per unit" and does not exceed the maximum number of installed units.

[0021] The average daily supply per unit can be adjusted according to the availability and maintenance ratio of the terminal supply equipment, and measured within the business hours window.

[0022] Furthermore, the operation includes at least:

[0023] The inventory of hydrogen storage tanks in discrete time periods is determined by the previous period's inventory, the current period's inflow and outflow, and takes into account losses or self-consumption during the compression storage process; the inventory is constrained by upper and lower limits and a safety stock buffer, and both the inventory level and the inflow / outflow satisfy non-negative constraints.

[0024] The inventory of the gas storage tank in discrete time periods is determined by the previous period's inventory, the current period's inflow and the current period's outflow, and takes into account the loss or self-consumption during the compression and storage process; the inventory is constrained by upper and lower limits and a safety stock buffer, and both the inventory quantity and the inflow / outflow quantity satisfy non-negative constraints.

[0025] Inventory constraints use the initial inventory as the boundary condition and set the target inventory at the end of the period or the inventory carried over across periods.

[0026] Furthermore, the revenue from energy sales includes:

[0027] Electricity sales revenue measured by time period is measured in terms of time-of-use charging volume and electricity price.

[0028] Natural gas sales revenue measured by time period is calculated based on the amount of gas dispensed and the price of natural gas.

[0029] Fuel sales revenue measured by time period is based on the amount of fuel refueled and the fuel price per time period.

[0030] Revenue from hydrogen sales measured by time period is based on the amount of hydrogen refueling per time period and the price of hydrogen.

[0031] The electricity price mentioned above is a time-varying parameter, while the prices of natural gas, fuel oil, and hydrogen are fixed parameters, and are measured according to a unified pricing rule and monetary standard.

[0032] Furthermore, the operation and maintenance costs include fixed operation and maintenance costs of terminal supply equipment charged by quantity, and variable operation and maintenance costs of station equipment charged by operating power; the curtailment cost is measured by the amount of curtailed solar power and the curtailment penalty coefficient; the energy purchase cost includes at least the electricity purchase cost from the upper-level power grid, the gas purchase cost from external natural gas, and the oil purchase cost from external fuel oil, measured by time-of-use price × purchase quantity.

[0033] Furthermore, the modeling employs typical day-to-time discretization and sets the following for the energy storage system:

[0034] SOC upper and lower limits and initial / final SOC conditions;

[0035] Charging and discharging are mutually exclusive; simultaneous charging and discharging are prohibited within the same time period.

[0036] Charge and discharge efficiency or round-trip efficiency constraints are applied, and the charge and discharge quantities are directionally corrected accordingly.

[0037] The power and capacity limits are constrained, and the timing relationship of charge / discharge energy balance is satisfied.

[0038] This invention provides a coupled modeling system for integrated oil, gas, hydrogen, and electricity energy service stations, used to implement the coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations as described above, including:

[0039] Equipment operating parameter acquisition unit: used to acquire operating parameters of electrolyzer, hydrogen compressor, hydrogen storage tank, hydrogen dispenser, electric energy storage system, charging pile, gas turbine, natural gas compressor, gas storage tank, gas dispenser, oil pump, and fuel dispenser; external power supply unit includes photovoltaic and upstream power grid.

[0040] Price parameter acquisition unit: used to acquire time-of-use electricity purchase and sale price, natural gas purchase and sale price, fuel oil purchase and sale price and hydrogen price, and to call upon them for revenue and cost measurement;

[0041] Demand Acquisition and Conversion Unit: Used to acquire the time-of-use energy demand of fuel vehicles, natural gas vehicles, hydrogen fuel cell vehicles and electric vehicles, and to receive the single-unit supply capacity and quantity of fuel dispensers, gas dispensers, hydrogen dispensers and charging piles for scale matching and billing.

[0042] Time-of-use power balance modeling unit: used to establish the time-of-use power balance relationship between the supply side and the power consumption side in discrete time periods;

[0043] Operational constraint setting unit: used to set the minimum safe operating power constraint of the electrolyzer, and to establish operational constraints for the charging and discharging energy balance, capacity and power upper and lower limits, charging and discharging mutual exclusion and efficiency of the electric energy storage system; to establish cross-period inventory-flow balance, inventory upper and lower limits and non-negative constraints for hydrogen storage tanks and gas storage tanks, and to set initial and end-of-period inventory conditions;

[0044] Revenue and Cost Metering Unit: Used to measure energy sales revenue, curtailment costs, energy purchase costs, and operation and maintenance costs to obtain total revenue;

[0045] Optimization Solving Unit: Under the conditions of satisfying time-sharing power balance, medium inventory continuity and operation constraints, it constructs and solves an optimization model with the goal of maximizing total revenue, and outputs the optimization results of time-sharing supply-side equipment output, oil / gas / electricity purchase volume, oil / gas / hydrogen flow rate and energy storage system status.

[0046] Result output unit: used to provide the optimization solution results to the energy service station.

[0047] The present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the coupling modeling method for integrated oil, gas, hydrogen and electricity energy service stations as described above.

[0048] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the coupling modeling method for integrated oil, gas, hydrogen and electricity energy service stations as described above.

[0049] Compared with the prior art, the present invention has the following advantages and beneficial effects: by establishing time-sharing power balance between photovoltaic / gas turbine / electric energy storage / upstream power grid and electrolyzer / compressor / oil pump / terminal load, the common problems of "energy non-conservation and scheduling solution failure" in the prior art are avoided; unified constraints from the source side to the load side significantly improve the proportion of feasible solutions and the feasibility of scheduling.

[0050] By establishing cross-period inventory-flow balance and upper / lower limits / non-negative constraints for hydrogen and gas storage tanks, the risk of supply disruptions and inflated inventory caused by traditional models that only substitute instantaneous flow for inventory is avoided. Initial / ending inventory figures can be combined to consider both operational and cross-cycle load factors. Time-of-use energy demand for fuel / natural gas / hydrogen fuel cells / electric vehicles is obtained by vehicle type, and the individual supply capacity and quantity of fuel dispensers / gas dispensers / hydrogen dispensers / charging piles are incorporated into the optimization, bringing the actual capacity of the terminal side into the calculation. Combined with scale matching based on "total daily quantity of statistical period - average daily supply per unit - maximum number of installed units," over- or under-allocation and queuing congestion are reduced, improving terminal service quality and resource utilization.

[0051] By integrating energy sales revenue (electricity / gas / oil / hydrogen time-of-use pricing) with energy purchase costs (electricity / gas), curtailment costs (penalty items), and operation and maintenance costs (fixed items based on quantity + variable items based on power / energy) into the objective function, we can avoid inflated profits or missing cost items. This facilitates price sensitivity and refined cost attribution, supporting business decisions. By setting constraints on the energy storage system, such as charge / discharge energy balance, upper and lower limits for power and capacity, SOC boundaries, charge / discharge mutual exclusion, and efficiency, energy storage can play a role in peak-valley load shifting, peak shaving and valley filling, and following fluctuations, reducing peak-period electricity / gas purchase expenditures, minimizing curtailment penalties, and improving the absorption of new energy sources.

[0052] Setting minimum safe operating power and other operational boundaries for the electrolyzer reduces the risks of frequent start-ups and shutdowns and crosstalk, improving the safety and lifespan of the hydrogen production unit while balancing economic efficiency and safety. The system employs an object organization method of "oil / gas / hydrogen / electricity separate sets + total set" and a higher-level constraint framework of "power balance—continuous inventory—scale matching—cost-benefit—energy storage behavior," resulting in a clear structure. It facilitates the addition or removal of equipment, the integration of new pricing rules or scenario parameters, and possesses good scalability and portability. Using typical daily-time discrete methods, the data source is clear, and the computational complexity is moderate. The optimization results are directly output as operable quantities such as equipment time-of-use output, electricity purchase, oil / gas / hydrogen time-of-use flow, and energy storage status, facilitating docking with station-level control and planning evaluation. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0054] Figure 1 This is a schematic diagram of the equipment connection relationship within the energy service station in Example 1. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0056] Example 1

[0057] A coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations includes:

[0058] The system acquires operating parameters of in-station equipment, external energy supply unit parameters, and price parameters. The in-station equipment operating parameters include those of the electrolyzer, hydrogen compressor, hydrogen storage tank, hydrogen dispenser, electric energy storage system, charging pile, gas turbine, natural gas compressor, gas storage tank, gas dispenser, oil pump, and fuel dispenser. External energy supply units include photovoltaic power and the upstream power grid. The price parameters include electricity purchase and sale prices, natural gas purchase and sale prices, fuel oil purchase and sale prices, and hydrogen sales prices. In this embodiment, the purchase and sale prices include both the purchase price and the selling price.

[0059] The system obtains the time-of-use energy demand of gasoline vehicles, natural gas vehicles, hydrogen fuel cell vehicles, and electric vehicles, and obtains the scale matching of the corresponding terminal supply equipment to establish a measurement relationship for energy sales revenue. The terminal supply equipment includes fuel dispensers, gas dispensers, hydrogen dispensers, and charging piles.

[0060] Establish a time-sharing power balance between the supply side and the consumption side. Take the output of photovoltaic power, gas turbine power, discharge power of electric energy storage system and power purchased by the upper-level grid as the supply side, and take the input power of electrolyzer, hydrogen compressor input power, natural gas compressor input power, oil pump input power, charging power of electric energy storage system and power demand of electric vehicle as the consumption side.

[0061] Establish a measurement relationship between photovoltaic power output and curtailment penalty coefficient to measure curtailment cost;

[0062] Establish operational constraints, including at least: cross-period inventory-flow balance and inventory upper and lower limits constraints for hydrogen storage tanks and gas storage tanks, charge and discharge energy balance, capacity upper and lower limits and charge and discharge power upper limits constraints for electric energy storage systems, and minimum safe operating power constraints for electrolyzers.

[0063] The objective function for total revenue is calculated by subtracting operation and maintenance costs, curtailment costs, and energy purchase costs from energy sales revenue. Operation and maintenance costs include, at a minimum, fixed operation and maintenance costs for terminal supply equipment charged by quantity, and variable operation and maintenance costs for equipment within the station charged by operating power. Energy sales revenue is measured based on electricity prices, natural gas prices, fuel oil prices, and hydrogen prices. Energy purchase costs include, at a minimum, the cost of electricity purchased from the upstream power grid, the cost of natural gas purchased from external sources, and the cost of fuel oil purchased from external sources.

[0064] Under the conditions of satisfying time-of-use power balance and operation constraints, an optimization model is constructed and solved with the goal of maximizing total revenue. The optimization results are output for time-of-use supply-side equipment output, oil / gas / electricity purchase volume, oil / gas / hydrogen flow rate, and the state of the energy storage system.

[0065] The electrical relationships of the equipment within the energy service station are as follows: Figure 1 As shown.

[0066] In this embodiment, the time-of-use energy requirements of the gasoline-powered vehicle, natural gas vehicle, hydrogen fuel cell vehicle, and electric vehicle are determined according to the following rules:

[0067] Collect or analyze the distribution of vehicle arrival times and daily mileage.

[0068] By combining the vehicle's initial energy state or remaining range parameters, the mileage requirement is converted into time-of-use energy requirement according to the vehicle model's energy consumption / gas consumption / fuel consumption / hydrogen consumption coefficient per unit mileage;

[0069] The time-of-use fuel demand, time-of-use natural gas demand, time-of-use hydrogen demand, and time-of-use electricity demand are aggregated according to vehicle type in discrete time periods, and used as inputs for matching the scale of terminal supply equipment and power balance.

[0070] The demand for automobiles is mainly affected by factors such as mileage, return time, and the supply and demand of charging equipment. In this embodiment, traditional fuel vehicles, natural gas vehicles, electric vehicles, and hydrogen fuel cell vehicles are charged through integrated energy service stations. For ease of calculation, this embodiment approximately assumes that the vehicles charged through integrated energy service stations have the same specifications and models, and the same characteristics of refueling, gas charging, and hydrogen charging. The probability density of the vehicle charging time is shown in the following formula.

[0071]

[0072] In the formula, , These are the mean and standard deviation of a normal distribution, respectively. The moment when the car begins to charge.

[0073] The probability density function of a car user's driving mileage is shown in the following formula.

[0074]

[0075] In the formula, This refers to the daily mileage of a car. This is the expected value; The standard deviation is denoted as .

[0076] Assuming that the refueling and hydrogen refueling behaviors of traditional gasoline vehicles, natural gas vehicles, electric vehicles, and hydrogen fuel cell vehicles are independent, a fuel, gas, hydrogen, and electricity demand model can be established for each vehicle. Using Monte Carlo simulation sampling, random samples are taken from vehicle capacity, mileage, and state of energy to calculate the refueling, gas, charging, and hydrogen refueling demands of a single vehicle. These are then summed to obtain the large-scale fuel, gas, hydrogen, and electricity demands for traditional gasoline vehicles, natural gas vehicles, electric vehicles, and hydrogen fuel cell vehicles. , , and .

[0077] In this embodiment, the scale matching of the terminal supply equipment includes:

[0078] The total demand for gasoline vehicles, natural gas vehicles, hydrogen fuel cell vehicles and electric vehicles during the statistical period is matched with the average daily supply of corresponding terminal supply equipment. The required terminal supply equipment is not less than "total demand / average daily supply per unit" and does not exceed the maximum number of installed units.

[0079] The average daily supply per unit can be adjusted according to the availability and maintenance ratio of the terminal supply equipment, and measured within the business hours window.

[0080] in,

[0081] The demand matching for gasoline-powered vehicles is as follows:

[0082]

[0083]

[0084] In the formula, The number of fuel dispensers installed at the energy station; Let be the fuel demand at time t; The average amount of fuel dispensed per fuel pump per day; The maximum number of refueling machines to be installed at an energy station.

[0085] The demand matching for natural gas vehicles is as follows:

[0086]

[0087]

[0088] In the formula, The number of gas dispensers installed at the energy station; This represents the average daily gas dispensing volume of a single gas dispenser. The maximum number of gas dispensers to be installed at an energy station.

[0089] The demand matching for hydrogen fuel cell vehicles is as follows:

[0090]

[0091]

[0092] In the formula, The number of hydrogen refueling machines installed at energy stations; This represents the average amount of hydrogen dispensed per day by a single hydrogen dispenser. The maximum number of hydrogen refueling machines to be installed at an energy station.

[0093] The demand matching for electric vehicles is as follows:

[0094]

[0095]

[0096] In the formula, The number of charging piles installed at the energy station; Let t be the charging demand at time t; The average daily charging volume of a single charging station. The maximum number of charging piles to be installed at the energy station.

[0097] The demand matching for natural gas vehicles is as follows:

[0098]

[0099]

[0100] In the formula, The number of gas dispensers installed at the energy station; This represents the average daily gas dispensing volume of a single gas dispenser. The maximum number of gas dispensers to be installed at an energy station.

[0101] By establishing time-sharing power balance between photovoltaic / gas turbine / electric energy storage / upstream grid and electrolyzer / compressor / oil pump / terminal load, the common problems of "energy non-conservation and scheduling solution failure" in existing technologies are avoided; unified constraints from the source side to the load side significantly improve the proportion of feasible solutions and the feasibility of scheduling.

[0102] The operational constraints include at least:

[0103] The inventory of hydrogen storage tanks in discrete time periods is determined by the previous period's inventory, the current period's inflow and outflow, and takes into account losses or self-consumption during the compression storage process; the inventory is constrained by upper and lower limits and a safety stock buffer, and both the inventory level and the inflow / outflow satisfy non-negative constraints.

[0104] The inventory of the gas storage tank in discrete time periods is determined by the previous period's inventory, the current period's inflow and the current period's outflow, and takes into account the loss or self-consumption during the compression and storage process; the inventory is constrained by upper and lower limits and a safety stock buffer, and both the inventory quantity and the inflow / outflow quantity satisfy non-negative constraints.

[0105] Inventory constraints use the initial inventory as the boundary condition and set the target inventory at the end of the period or the inventory carried over across periods.

[0106] The amount of hydrogen stored in the hydrogen storage tank at different times satisfies the following formula:

[0107]

[0108]

[0109]

[0110] In the formula, and The hydrogen storage capacity of the hydrogen storage tanks at time t and t+1 are respectively. Let be the hydrogen demand at time t; Let t be the amount of hydrogen flowing into the hydrogen storage tank at time t; The hydrogen dissipation rate from the compressor to the hydrogen storage tank; , These represent the lower and upper limits of hydrogen storage capacity in the hydrogen storage tank, respectively.

[0111] The amount of natural gas stored in the gas storage tank at different times satisfies the following formula:

[0112]

[0113]

[0114]

[0115] In the formula, and These represent the natural gas storage capacity of the gas storage tank at time t and time t+1, respectively. Let be the natural gas demand at time t; Let t be the amount of natural gas flowing into the storage tank at time t; The natural gas loss rate from the compressor to the hydrogen storage tank; , These are the lower and upper limits for the natural gas storage capacity of the gas storage tank, respectively.

[0116] This invention establishes a cross-period inventory-flow balance and upper and lower limits / non-negative constraints for hydrogen storage tanks and gas storage tanks, avoiding the risk of supply disruption and inflated inventory caused by the traditional model that only uses instantaneous flow to replace inventory; it can combine initial / ending inventory calibers to take into account both operation and cross-cycle continuity.

[0117] In this embodiment, the input power of the electrolyzer, the input power of the hydrogen compressor, the input power of the natural gas compressor, the input power of the oil pump, the charging power of the electric energy storage system, and the power demand of the electric vehicle are used as the power consumption terminals.

[0118] The input power of the electrolytic cell is shown in the following formula:

[0119]

[0120] In the formula, The electrical power consumed in producing hydrogen in an electrolyzer; The high calorific value of hydrogen; Let t be the hydrogen production rate of the electrolyzer at time t; This refers to the energy efficiency of the electrolyzer.

[0121] During operation, the power of an electrolytic cell can briefly exceed its rated power, reaching 110% to 130% of the rated power. However, high-power operation will cause heat loss in the electrolytic cell, leading to a decrease in its operating efficiency. When operating at low power, the electrolytic cell's operating power must not be lower than 20% of its rated power; otherwise, hydrogen-oxygen cross-contamination and an explosion may occur. Therefore, the minimum safe operating power for an electrolytic cell is 20%. .

[0122]

[0123]

[0124] In the formula, This refers to the rated power of the electrolytic cell; This represents the upper limit of the electrolytic cell ramp rate.

[0125] The input power of the hydrogen compressor is shown below:

[0126]

[0127]

[0128] In the formula, The electrical power consumed by the compressor to compress hydrogen; Let t be the amount of hydrogen flowing into the compressor; This represents the active power consumption rate of the compressor at the reference operating pressure. This is the normal operating pressure of the compressor; Standard atmospheric pressure; This is the reference operating pressure for the compressor; Hydrogen dissipation rate from the electrolyzer to the compressor

[0129] The input power of the natural gas compressor is shown below:

[0130]

[0131]

[0132] In the formula, This refers to the electrical power of the compressor. Natural gas flow rate (kg / h); The gas average compressibility factor; It is the gas constant; This refers to the temperature of the gas entering the compressor. , These are the compressor inlet and outlet pressures, respectively. The adiabatic index of the gas can be taken as 1.27~1.31 for natural gas, which is mainly composed of methane. The standard state density; The amount of natural gas entering the compressor

[0133] The input power of the oil transfer pump is as follows:

[0134]

[0135]

[0136] In the formula, This refers to the electrical power of the oil pump. The amount of oil entering the oil pump, in m³ / h; ρ is the density of the oil; ρ is the acceleration due to gravity; This refers to the head of the oil pump. For the efficiency of the oil pump; The height difference between the inlet and outlet liquid levels; The pressure difference between inlet and outlet; The pipeline friction loss is calculated using Darcy's formula.

[0137] Photovoltaic output, gas turbine output, energy storage system discharge power, and power purchased from the upstream grid serve as the supply side. In this embodiment, power generation is achieved through the gas turbine in the CHP unit, as shown below:

[0138]

[0139] In the formula, Let t be the electrical and thermal power output by CHP. Input natural gas power to the CHP unit; For CHP gas-to-electricity conversion efficiency; The upper limit for natural gas power input to CHP; This represents the maximum ramp limit for input natural gas power.

[0140] In this embodiment, the modeling adopts typical day-time discretization, and the following settings are applied to the energy storage system:

[0141] SOC upper and lower limits and initial / final SOC conditions;

[0142] Charging and discharging are mutually exclusive; simultaneous charging and discharging are prohibited within the same time period.

[0143] Charge and discharge efficiency or round-trip efficiency constraints are applied, and the charge and discharge quantities are directionally corrected accordingly.

[0144] The power and capacity limits are constrained, and the timing relationship of charge / discharge energy balance is satisfied.

[0145] Represented as:

[0146]

[0147] In the formula, , , These represent the charging and discharging power and capacity of the ESS during a typical day t period, respectively. , These are the charging and discharging efficiencies of the ESS, respectively. , These are the lower and upper limits of the ESS capacity, respectively. , These are the upper limits of the charging and discharging power of the ESS, respectively.

[0148] Constraints such as charge / discharge energy balance, upper and lower limits of power and capacity, SOC boundary, charge / discharge mutual exclusion and efficiency are set for energy storage systems, so that energy storage can play a role in peak-valley load shifting, peak shaving and valley filling and following fluctuations, reduce peak electricity / gas purchase expenditures, reduce curtailment penalties for solar power, and improve the consumption of new energy.

[0149] In this embodiment, the power balance between the supply end and the consumption end is expressed as follows:

[0150]

[0151] The revenue from energy sales includes:

[0152] Electricity sales revenue measured by time period is measured in terms of time-of-use charging volume and electricity price.

[0153] Natural gas sales revenue measured by time period is calculated based on the amount of gas dispensed and the price of natural gas.

[0154] Fuel sales revenue measured by time period is based on the amount of fuel refueled and the fuel price per time period.

[0155] Revenue from hydrogen sales measured by time period is based on the amount of hydrogen refueling per time period and the price of hydrogen.

[0156] The electricity price mentioned above is a time-varying parameter, while the prices of natural gas, fuel oil, and hydrogen are fixed parameters, and are measured according to a unified pricing rule and monetary standard.

[0157] Represented as:

[0158]

[0159] In the formula: , , and These are time-of-use electricity prices, natural gas prices, fuel oil prices, and hydrogen prices;

[0160] By obtaining time-of-use energy demand for fuel / natural gas / hydrogen fuel cells / electric vehicles based on vehicle type, and incorporating the single-unit supply capacity and quantity of fuel dispensers / gas dispensers / hydrogen dispensers / charging piles, the actual capacity on the terminal side is included in the optimization; in conjunction with the scale matching of "total amount of statistical period (day) - average daily supply of single unit - maximum number of installed units", over- or under-allocation and queuing congestion are reduced, and the quality of terminal services and resource utilization are improved.

[0161] By incorporating energy sales revenue (electricity / gas / oil / hydrogen time-of-use pricing) along with energy purchase costs (electricity / gas purchase), curtailment costs (penalty item), and operation and maintenance costs (fixed items based on quantity + variable items based on power / energy) into the objective function, we can avoid inflated profits or missing cost items. This approach facilitates price sensitivity and refined cost attribution, supporting business decision-making.

[0162] In this embodiment, the operation and maintenance cost includes the fixed operation and maintenance cost of terminal supply equipment billed by quantity, and the variable operation and maintenance cost of station equipment billed by operating power; the curtailment cost is measured by the amount of curtailed solar power and the curtailment penalty coefficient; the energy purchase cost includes at least the electricity purchase cost from the upstream power grid, the gas purchase cost from external sources, and the fuel purchase cost from external sources, measured by time-of-use price × purchase quantity. The operation and maintenance cost is expressed as:

[0163]

[0164] In the formula: The unit cost of operation and maintenance for fuel dispensers, gas dispensers, hydrogen dispensers, and charging stations; For equipment Operating power; The number of devices within the integrated energy service station; For equipment The unit operation and maintenance cost;

[0165] The cost of curtailment is expressed as:

[0166]

[0167] In the formula: This is the penalty coefficient for discarded light; This represents the predicted photovoltaic output for time period t.

[0168] Energy purchase cost is expressed as:

[0169]

[0170] In the formula: To contribute to actual photovoltaic power; This is for purchasing electricity from the higher-level power grid.

[0171] Therefore, the objective function, which aims to maximize the total revenue of the integrated oil, gas, hydrogen, and electricity energy service station, is expressed as:

[0172]

[0173] In the formula: , , and These are the energy sales revenue, operation and maintenance costs, curtailment costs, and energy purchase costs of the integrated energy service station.

[0174] For the above optimization model, a typical day-to-time discretization model is preferred. For nonlinear terms containing logarithmic / productive terms (such as the power characteristics of compressors and oil pumps), piecewise linear approximation or convex / second-order conical processing can be performed. The number of equipment is defined as an integer variable, and power / flow / SOC are defined as continuous variables, forming a mixed integer (linear / second-order conical) programming model. Under the constraints of time-to-time power balance, medium inventory continuity, energy storage balance and capacity / power upper limit, and terminal scale matching and maximum installed capacity, the solution is performed with the goal of maximizing total revenue. The solver can be a general mathematical programming solver with large-scale optimization capabilities. The solution terminates when the objective converges or the time upper limit / relative gap threshold is used. The output results, such as equipment time-to-time output, purchased electricity, oil / gas / hydrogen time-to-time flow, and energy storage status, are used for scheduling and evaluation. The above discretization, balance, and constraint elements have been given item by item in the embodiments (power balance, inventory and energy storage, revenue / cost measurement, objective function).

[0175] Example 2

[0176] This invention provides a coupled modeling system for integrated oil, gas, hydrogen, and electricity energy service stations, used to implement the coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations as described in Example 1, comprising:

[0177] Equipment operating parameter acquisition unit: used to acquire operating parameters of electrolyzer, hydrogen compressor, hydrogen storage tank, hydrogen dispenser, electric energy storage system, charging pile, gas turbine, natural gas compressor, gas storage tank, gas dispenser, oil pump, and fuel dispenser; external power supply unit includes photovoltaic and upstream power grid.

[0178] Price parameter acquisition unit: used to acquire time-of-use electricity purchase and sale price, natural gas purchase and sale price, fuel oil purchase and sale price and hydrogen price, and to call upon them for revenue and cost measurement;

[0179] Demand Acquisition and Conversion Unit: Used to acquire the time-of-use energy demand of fuel vehicles, natural gas vehicles, hydrogen fuel cell vehicles and electric vehicles, and to receive the single-unit supply capacity and quantity of fuel dispensers, gas dispensers, hydrogen dispensers and charging piles for scale matching and billing.

[0180] Time-of-use power balance modeling unit: used to establish the time-of-use power balance relationship between the supply side and the power consumption side in discrete time periods;

[0181] Operational constraint setting unit: used to set the minimum safe operating power constraint of the electrolyzer, and to establish operational constraints for the charging and discharging energy balance, capacity and power upper and lower limits, charging and discharging mutual exclusion and efficiency of the electric energy storage system; to establish cross-period inventory-flow balance, inventory upper and lower limits and non-negative constraints for hydrogen storage tanks and gas storage tanks, and to set initial and end-of-period inventory conditions;

[0182] Revenue and Cost Metering Unit: Used to measure energy sales revenue, curtailment costs, energy purchase costs, and operation and maintenance costs to obtain total revenue;

[0183] Optimization Solving Unit: Under the conditions of satisfying time-sharing power balance, medium inventory continuity and operation constraints, it constructs and solves an optimization model with the goal of maximizing total revenue, and outputs the optimization results of time-sharing supply-side equipment output, oil / gas / electricity purchase volume, oil / gas / hydrogen flow rate and energy storage system status.

[0184] Result output unit: used to provide the optimization solution results to the energy service station.

[0185] Example 3

[0186] The present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the coupling modeling method for integrated oil, gas, hydrogen and electricity energy service stations as described above.

[0187] Example 4

[0188] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the coupling modeling method for integrated oil, gas, hydrogen and electricity energy service stations as described above.

[0189] 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.

[0190] 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, as well as 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.

[0191] 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.

[0192] 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.

[0193] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations, characterized in that, include: The system acquires operating parameters of in-station equipment, parameters of external energy supply units, and price parameters. The operating parameters of in-station equipment include those of electrolyzers, hydrogen compressors, hydrogen storage tanks, hydrogen dispensers, electric energy storage systems, charging piles, gas turbines, natural gas compressors, gas storage tanks, gas dispensers, oil pumps, and fuel dispensers. External energy supply units include photovoltaic systems and the upstream power grid. The price parameters include electricity purchase and sale prices, natural gas purchase and sale prices, fuel oil purchase and sale prices, and hydrogen prices. The system obtains the time-of-use energy demand of gasoline vehicles, natural gas vehicles, hydrogen fuel cell vehicles, and electric vehicles, and obtains the scale matching of the corresponding terminal supply equipment to establish a measurement relationship for energy sales revenue. The terminal supply equipment includes fuel dispensers, gas dispensers, hydrogen dispensers, and charging piles. Establish a time-sharing power balance between the supply side and the consumption side. Take the output of photovoltaic power, gas turbine power, discharge power of electric energy storage system and power purchased by the upper-level grid as the supply side, and take the input power of electrolyzer, hydrogen compressor input power, natural gas compressor input power, oil pump input power, charging power of electric energy storage system and power demand of electric vehicle as the consumption side. Establish a measurement relationship between photovoltaic power output and curtailment penalty coefficient to measure curtailment cost; Establish operational constraints, including at least: cross-period inventory-flow balance and inventory upper and lower limits constraints for hydrogen storage tanks and gas storage tanks, charge and discharge energy balance, capacity upper and lower limits and charge and discharge power upper limits constraints for electric energy storage systems, and minimum safe operating power constraints for electrolyzers. The objective function for total revenue is the energy sales revenue minus operation and maintenance costs, curtailment costs, and energy purchase costs. Among these, operation and maintenance costs include at least: fixed operation and maintenance costs of terminal supply equipment charged by quantity, and variable operation and maintenance costs of equipment within the station charged by operating power. Energy sales revenue is measured by the electricity price, natural gas price, fuel oil price, and hydrogen price. Under the conditions of satisfying time-of-use power balance and operation constraints, an optimization model is constructed and solved with the goal of maximizing total revenue. The optimization results are output for time-of-use supply-side equipment output, oil / gas / electricity purchase volume, oil / gas / hydrogen flow rate, and the state of the energy storage system.

2. The coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations according to claim 1, characterized in that, The time-of-use energy requirements of gasoline-powered vehicles, natural gas vehicles, hydrogen fuel cell vehicles, and electric vehicles are determined according to the following rules: Collect or analyze the distribution of vehicle arrival times and daily mileage. By combining the vehicle's initial energy state or remaining range parameters, the mileage requirement is converted into time-of-use energy requirement according to the vehicle model's energy consumption / gas consumption / fuel consumption / hydrogen consumption coefficient per unit mileage; The time-of-use fuel demand, time-of-use natural gas demand, time-of-use hydrogen demand, and time-of-use electricity demand are aggregated according to vehicle type in discrete time periods, and used as inputs for matching the scale of terminal supply equipment and power balance.

3. The coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations according to claim 2, characterized in that, The scale matching of the terminal supply equipment includes: The total demand for gasoline vehicles, natural gas vehicles, hydrogen fuel cell vehicles and electric vehicles during the statistical period is matched with the average daily supply of the corresponding terminal supply equipment. The required terminal supply equipment is not less than "total demand / average daily supply per unit" and does not exceed the maximum number of installed units. The average daily supply per unit can be adjusted according to the availability and maintenance ratio of the terminal supply equipment, and measured within the business hours window.

4. The coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations according to claim 1, characterized in that, The operation includes at least: The inventory of hydrogen storage tanks in discrete time periods is determined by the previous period's inventory, the current period's inflow and outflow, and takes into account losses or self-consumption during the compression storage process; the inventory is constrained by upper and lower limits and a safety stock buffer, and both the inventory level and the inflow / outflow satisfy non-negative constraints. The inventory of the gas storage tank in discrete time periods is determined by the previous period's inventory, the current period's inflow and the current period's outflow, and takes into account the loss or self-consumption during the compression and storage process; the inventory is constrained by upper and lower limits and a safety stock buffer, and both the inventory quantity and the inflow / outflow quantity satisfy non-negative constraints. Inventory constraints use the initial inventory as the boundary condition and set the target inventory at the end of the period or the inventory carried over across periods.

5. The coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations according to claim 1, characterized in that, The revenue from energy sales includes: Electricity sales revenue measured by time period is measured in terms of time-of-use charging volume and electricity price. Natural gas sales revenue measured by time period is calculated based on the amount of gas dispensed and the price of natural gas. Fuel sales revenue measured by time period is based on the amount of fuel refueled and the fuel price per time period. Hydrogen sales revenue measured by time period is based on the amount of hydrogen refueling per time period and the price of hydrogen. The above electricity prices are time-varying parameters, while the prices of natural gas, fuel oil, and hydrogen are fixed parameters, and are measured according to unified pricing rules and monetary standards.

6. The coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations according to claim 1, characterized in that, The operation and maintenance costs include fixed operation and maintenance costs of terminal supply equipment charged by quantity, and variable operation and maintenance costs of station equipment charged by operating power; the curtailment cost is measured by the amount of curtailed solar power and the curtailment penalty coefficient; the energy purchase cost includes at least the electricity purchase cost from the upper-level power grid, the gas purchase cost from external natural gas, and the oil purchase cost from external fuel oil, measured by time-of-use price × purchase quantity.

7. The coupled modeling method for integrated oil, gas, hydrogen, and electricity energy service stations according to claim 1, characterized in that, The modeling employs typical day-to-time discretization and sets the following for the energy storage system: SOC upper and lower limits and initial / final SOC conditions; Charging and discharging are mutually exclusive; simultaneous charging and discharging are prohibited within the same time period. Charge and discharge efficiency or round-trip efficiency constraints are applied, and the charge and discharge quantities are directionally corrected accordingly. The power and capacity limits are constrained, and the timing relationship of charge / discharge energy balance is satisfied.

8. A coupled modeling system for an integrated oil, gas, hydrogen, and electricity energy service station, characterized in that, The method for coupled modeling of oil, gas, hydrogen, and electricity integrated energy service stations according to any one of claims 1 to 7 includes: Equipment operating parameter acquisition unit: used to acquire operating parameters of electrolyzer, hydrogen compressor, hydrogen storage tank, hydrogen dispenser, electric energy storage system, charging pile, gas turbine, natural gas compressor, gas storage tank, gas dispenser, oil pump, and fuel dispenser; external power supply unit includes photovoltaic and upstream power grid. Price parameter acquisition unit: used to acquire time-of-use electricity purchase and sale price, natural gas purchase and sale price, fuel oil purchase and sale price and hydrogen price, and to call for revenue and cost measurement; Demand Acquisition and Conversion Unit: Used to acquire the time-of-use energy demand of fuel vehicles, natural gas vehicles, hydrogen fuel cell vehicles and electric vehicles, and to receive the single-unit supply capacity and quantity of fuel dispensers, gas dispensers, hydrogen dispensers and charging piles for scale matching and billing. Time-of-use power balance modeling unit: used to establish the time-of-use power balance relationship between the supply side and the power consumption side in discrete time periods; Operational constraint setting unit: used to set the minimum safe operating power constraint of the electrolyzer, and to establish operational constraints for the charging and discharging energy balance, capacity and power upper and lower limits, charging and discharging mutual exclusion and efficiency of the electric energy storage system; to establish cross-period inventory-flow balance, inventory upper and lower limits and non-negative constraints for hydrogen storage tanks and gas storage tanks, and to set initial and end-of-period inventory conditions; Revenue and Cost Metering Unit: Used to measure energy sales revenue, curtailment costs, energy purchase costs, and operation and maintenance costs to obtain total revenue; Optimization Solving Unit: Under the conditions of satisfying time-sharing power balance, medium inventory continuity and operation constraints, it constructs and solves an optimization model with the goal of maximizing total revenue, and outputs the optimization results of time-sharing supply-side equipment output, oil / gas / electricity purchase volume, oil / gas / hydrogen flow rate and energy storage system status. Result output unit: used to provide the optimization solution results to the energy service station.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the oil, gas, hydrogen and electricity integrated energy service station coupling modeling method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the oil, gas, hydrogen and electricity integrated energy service station coupling modeling method as described in any one of claims 1 to 7.

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