Energy optimization scheduling method based on hydrogen green certificate and new energy vehicle carbon quota

Abstract

The present invention discloses an energy optimization scheduling method based on hydrogen energy green certificates and new energy vehicle carbon quotas, including: constructing a park comprehensive energy system model based on the composition of hydrogen energy diversified terminal applications; constructing a green hydrogen energy certificate trading mechanism model and a new energy vehicle carbon quota trading model; obtaining an objective function based on the park comprehensive energy system operating cost and the total scheduling cost of new energy vehicles; constructing system constraints; based on the green hydrogen energy certificate trading mechanism model, the park comprehensive energy system framework, and the new energy vehicle carbon quota trading model, combining the system constraints and the objective function to obtain a park comprehensive energy system collaborative optimization scheduling strategy. The present invention comprehensively considers that the green hydrogen energy certificate trading mechanism and the new energy vehicle carbon quota trading mechanism can further improve the utilization rate of renewable energy, effectively reduce the system operating cost, reduce the system carbon emissions, and improve the utilization rate of renewable energy.

Description

Technical Field

[0001] The present invention belongs to the technical field of optimized operation of integrated energy systems, and in particular relates to an energy optimization scheduling method based on hydrogen energy green certificates and carbon quotas of new energy vehicles. Background Art

[0002] Promoting energy transformation and consumption revolution and building a green, low-carbon and safe energy system with renewable energy as the main body are important strategic goals for my country. Data show that carbon emissions from my country's transportation industry account for 11% of the national total, of which road traffic emissions account for 86% of the total emissions from the transportation sector. Carbon emission reduction in the automotive industry is crucial to achieving the "dual carbon" goals. Compared with traditional fuel vehicles, new energy vehicles (NEV) represented by electric vehicles (EV) and hydrogen fuel cell vehicles (HFCV) have significant advantages in reducing carbon emissions during the vehicle use phase, and are an important way to promote low-carbon transportation.

[0003] As a clean, zero-carbon fuel, green hydrogen plays a key role in promoting the deep decarbonization of terminal energy consumption and building a clean, low-carbon, safe and efficient energy system. However, due to the high electricity price restrictions, the current production cost of green hydrogen is 2 to 3 times that of gray hydrogen and blue hydrogen, making it difficult to achieve large-scale application. Therefore, it is necessary to explore the construction of a green hydrogen energy certificate trading market mechanism to promote the large-scale utilization of green hydrogen produced by renewable energy, fully tap the environmental benefits of green hydrogen, solve the problem of high cost of hydrogen production by electrolysis, and enhance the market competitiveness of the hydrogen energy industry. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes an energy optimization scheduling method based on hydrogen energy green certificates and new energy vehicle carbon quotas to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above objectives, the present invention provides an energy optimization scheduling method based on hydrogen energy green certificates and new energy vehicle carbon quotas, comprising:

[0006] Based on the composition of diversified terminal applications of hydrogen energy, a comprehensive energy system model for the park is constructed;

[0007] Construct a green hydrogen energy certificate trading mechanism model and a new energy vehicle carbon quota trading model;

[0008] Obtain the objective function based on the operation cost of the park's comprehensive energy system and the total dispatch cost of new energy vehicles; construct system constraints;

[0009] Based on the green hydrogen energy certificate trading mechanism model, the park integrated energy system framework, and the new energy vehicle carbon quota trading model, the system constraints and the objective function are combined to obtain the collaborative optimization scheduling strategy of the park integrated energy system.

[0010] Optionally, the park comprehensive energy system model includes: a two-stage power-to-gas model, a gas-hydrogen cogeneration model, a hydrogen fuel cell cogeneration model, a hydrogen refueling station hydrogen storage model, and an energy storage model.

[0011] Optionally, the green hydrogen energy certificate trading mechanism model includes:

[0012] Determine whether the actual value of the system's green hydrogen energy exceeds the fixed quota indicator. If it is less than the fixed quota indicator, purchase green hydrogen energy certificates; if it is greater than the fixed quota indicator, sell the difference between the fixed quota indicator and the actual value of the system's green hydrogen energy to obtain income. The model is expressed as follows:

[0013]

[0014] In the formula, C GHCT The transaction cost of green hydrogen energy certificates for the system, is the transaction price of green hydrogen energy certificates, N d The quota of green hydrogen energy certificates that the system needs to hold. is the system green hydrogen energy certificate quota coefficient, is the total hydrogen energy demand of the system during the scheduling period, N s The number of green hydrogen certificates obtained by the system through hydrogen production from renewable energy, The quantitative coefficient for converting the amount of hydrogen produced by renewable energy into the number of green hydrogen certificates. The amount of hydrogen produced by wind power in the system.

[0015] Optionally, the process of building a new energy vehicle carbon quota trading model includes:

[0016] The baseline method is used to take the difference in carbon emissions between electric vehicles, hydrogen fuel vehicles and traditional fuel vehicles under the same driving distance as the carbon emission quota obtained by the car owner. The proportion of clean energy is introduced to obtain the carbon quota trading model for new energy vehicles. The model is as follows:

[0017]

[0018] Where: CEA ev,ι , CEA hfcv,ι The carbon emissions of traditional fuel vehicles, electric vehicles and hydrogen fuel vehicles that can travel the same mileage after the total charging amount and hydrogen refueling amount participate in the dispatch; L is the charging power of the EV cluster during period t; ev , L hfcvE is the mileage of electric vehicles per unit of electricity and hydrogen fuel vehicles per unit of capacity; evgas 、E hfcvgas E is the carbon emission factor of the traditional fuel vehicle kilometer speed corresponding to the electric vehicle and hydrogen fuel vehicle respectively; c is the carbon emission factor per unit of electricity generation; RCE ev,t 、RCE hfcv,t are the carbon emissions generated by charging electric vehicles and hydrogen fuel vehicles during period t; k c is the proportion of thermal power and gas power generation in the power generation system, P c,t is the sum of gas-fired power generation and power purchase during period t; P res,t is the renewable energy output during period t; q ev ,q hfcv are the carbon quota trading prices for electric vehicles and hydrogen fuel vehicles respectively; C ev,t , C hfcv,t are the income obtained by electric vehicles and hydrogen fuel vehicles from trading carbon quotas during period t.

[0019] Optionally, the objective function is to minimize the sum of the operating costs of the park's comprehensive energy system and the total dispatching costs of new energy vehicles; the system operating costs include energy purchasing costs, wind power operating costs, wind power abandonment penalty costs, green hydrogen energy certificate trading costs, and hydrogen sales revenue at hydrogen refueling stations; the energy purchasing costs include electricity purchasing costs and gas purchasing costs; the total dispatching costs of new energy vehicles include the total dispatching costs of electric vehicles and the total dispatching costs of hydrogen fuel vehicles; the total dispatching costs of electric vehicles include charging costs, discharging revenues, and carbon quota revenues; the total dispatching costs of hydrogen fuel vehicles include hydrogen refueling costs and carbon quota revenues.

[0020] Optionally, the constraints include two-stage power-to-gas equipment operation constraints, gas-hydrogen cogeneration operation constraints, hydrogen fuel cell cogeneration operation constraints, hydrogen storage constraints at hydrogen refueling stations, energy storage equipment constraints, electric vehicle charging and discharging constraints, hydrogen fuel vehicle hydrogenation constraints, power balance constraints, wind power output constraints, and system energy purchase constraints; among them, the two-stage power-to-gas includes electrolyzer and methane reactor operation constraints.

[0021] Compared with the prior art, the present invention has the following advantages and technical effects:

[0022] Based on the composition of diversified terminal applications of hydrogen energy, a comprehensive energy system model of the park is constructed; a green hydrogen energy certificate trading mechanism model and a new energy vehicle carbon quota trading model are constructed; an objective function is obtained based on the operating cost of the park's comprehensive energy system and the total dispatch cost of new energy vehicles; system constraints are constructed; based on the green hydrogen energy certificate trading mechanism model, the park's comprehensive energy system framework, and the new energy vehicle carbon quota trading model, the system constraints and the objective function are combined to obtain a collaborative optimization dispatch strategy for the park's comprehensive energy system.

[0023] The green hydrogen energy certificate trading mechanism proposed in the present invention can effectively reduce the operating cost of the system, promote the consumption of renewable energy, reduce the carbon emissions of the system, and show good environmental benefits.

[0024] The new energy vehicle carbon quota trading mechanism proposed in the present invention can significantly increase the benefits of new energy vehicle users, reduce the charging costs of new energy vehicle users, and greatly enhance the enthusiasm of vehicle owners to participate in scheduling.

[0025] The green hydrogen energy certificate trading mechanism and the new energy vehicle carbon quota trading mechanism proposed in the present invention can further improve the utilization rate of renewable energy and reduce carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0027] Figure 1 A schematic diagram of an integrated energy system according to an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of a diversified terminal application of hydrogen energy according to an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of a green hydrogen energy certificate trading mechanism according to an embodiment of the present invention;

[0030] Figure 4 A schematic diagram of a carbon quota trading mechanism for new energy vehicles according to an embodiment of the present invention;

[0031] Figure 5 A wind power consumption diagram under different scenarios obtained by simulation according to an embodiment of the present invention;

[0032] Figure 6 The power balance diagrams of electricity, gas, heat and hydrogen obtained by simulation of the embodiments of the present invention, wherein (a) is the power balance diagram of electricity, gas, heat and hydrogen corresponding to scenario 1; (b) is the power balance diagram of electricity, gas, heat and hydrogen corresponding to scenario 2; (c) is the power balance diagram of electricity, gas, heat and hydrogen corresponding to scenario 3; (d) is the power balance diagram of electricity, gas, heat and hydrogen corresponding to scenario 4;

[0033] Figure 7 This is a diagram showing the proportion of green hydrogen in the system hydrogen supply source obtained by simulation of an embodiment of the present invention. DETAILED DESCRIPTION

[0034] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0035] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] Embodiment 1

[0037] like Figure 1-7 As shown, this embodiment provides an energy optimization scheduling method based on hydrogen energy green certificates and new energy vehicle carbon quotas, including:

[0038] Step 1: Build a comprehensive energy system model for the park based on the diversified terminal applications of hydrogen energy;

[0039] Step 2: Based on the green hydrogen energy certificate trading mechanism, build a green hydrogen energy certificate trading mechanism model;.

[0040] Step 3: Based on the carbon quota trading mechanism of new energy vehicles, build a new energy vehicle carbon quota trading model;

[0041] Step 4: Based on the green hydrogen energy certificate trading mechanism model, the park integrated energy system framework, and the new energy vehicle carbon quota trading model, the park integrated energy system operating cost and the lowest total dispatch cost of new energy vehicles are used as the objective function to obtain the low-carbon economic dispatch strategy of the park integrated energy system;

[0042] Step 5: Simulation verification;

[0043] The technical solution of the present invention is described in detail with reference to the above steps and the accompanying drawings:

[0044] The specific implementation steps of the energy optimization scheduling method based on hydrogen green certificates and new energy vehicle carbon quotas are as follows:

[0045] Step 1: If Figure 1 As shown in the figure, based on the diversified terminal application of hydrogen energy, a comprehensive energy system model of the park is constructed. Figure 2 shown.

[0046] (1) Two-stage power-to-gas conversion:

[0047] In the present invention, the two-stage power-to-gas conversion includes two processes: hydrogen generation and hydrogen consumption. In the first stage, high-intensity direct current is used to electrolyze water, and the water is decomposed into hydrogen and oxygen in the electrolyzer. In this stage, part of the generated hydrogen is stored in a hydrogen storage tank to improve the operational flexibility of the system. The second stage involves using the generated hydrogen for a variety of purposes, such as improving the fuel cleanliness of the cogeneration unit through a gas hydrogen blending device, or applying it to a methane reaction device to meet the system gas load requirements, thereby reducing the cost of purchasing natural gas. In addition, the generated hydrogen can also be supplied to hydrogen fuel cells for the system's electrical and thermal needs. In order to further improve the utilization rate of hydrogen energy, a hydrogen refueling station is set up in the park to provide hydrogen refueling services for hydrogen energy vehicles.

[0048] The electrolyzer device model is:

[0049]

[0050] Where: is the electrical power input to the electrolytic cell, is the hydrogen power output of the electrolyzer, η EL is the electricity-to-hydrogen conversion efficiency of the electrolyzer, and are the upper and lower limits of the electric power input to the electrolyzer, ΔP EL,max and ΔP EL,min They are respectively the upper and lower limits of the electrolytic cell power consumption ramp.

[0051] Methane Reactor Plant Model:

[0052]

[0053] Where: is the hydrogen power input to MR, is the natural gas power output by MR, η MR is the energy conversion efficiency of MR, and are the upper and lower limits of the input MR hydrogen power, ΔP MR,max and ΔP MR,min They are the upper and lower limits of MR hydrogen consumption power climbing respectively.

[0054] (2) Gas-hydrogen-blended cogeneration model

[0055]

[0056] Where P CHP,t is the mixed gas power input to the fuel gas hydrogen blending device during period t, δ mix is the lower calorific value of the mixed gas, are the hydrogen power and natural gas power input into the cogeneration unit through the fuel gas hydrogen blending device during period t, respectively, tis the hydrogen blending ratio of fuel gas in period t, They are the lower calorific values ​​of hydrogen and natural gas respectively.

[0057] The heat-to-power ratio adjustable cogeneration system can be dynamically adjusted according to the real-time electricity and heat demand to further improve the operating efficiency. Its working model is as follows:

[0058]

[0059] Where: is the natural gas power input to CHP during period t, and are the electrical power and thermal power output of the hydrogen fuel cell, and are CHP heat generation efficiency and power generation efficiency, and are the upper and lower limits of the input CHP natural gas power, and are the upper and lower limits of the CHP hydrogen power input, k CHP,max and k CHP,min are the upper and lower limits of CHP thermal power ratio, ΔP CHP,max and ΔP CHP,min They are the upper and lower limits of CHP climbing power respectively.

[0060] (3) Hydrogen fuel cell cogeneration model:

[0061]

[0062] Where: is the hydrogen power input to the hydrogen fuel cell during period t, and are the electrical power and thermal power output of the hydrogen fuel cell, and are the heat generation efficiency and electricity generation efficiency of hydrogen fuel cells, and are the upper and lower limits of the hydrogen power input to the hydrogen fuel cell, k HFC,max and k HFC,min They are the upper and lower limits of the thermal-electric ratio of hydrogen fuel cells, ΔP HFC,max and ΔP HFC,min They are the upper and lower limits of the climbing power of hydrogen fuel cells respectively.

[0063] (4) Hydrogen storage model of hydrogen refueling station:

[0064]

[0065]

[0066] Where: HHRS,t is the hydrogen storage capacity of the hydrogen refueling station during period t; H HRS,t-1 is the hydrogen storage capacity of the hydrogen refueling station during period t-1; is the hydrogen production of the power-to-hydrogen device for the hydrogen refueling station during period t; is the hydrogen consumption of the hydrogen refueling station during period t; They are the initial hydrogen capacity of the hydrogen storage tank at the hydrogen filling station and the hydrogen capacity at the end of the scheduling period; are the upper and lower limits of the hydrogen storage capacity of the hydrogen storage tank respectively; is the hydrogen energy demand of the hydrogen refueling station during period t, is the energy density of hydrogen.

[0067] (5) Energy storage model:

[0068] The characteristics of the energy storage equipment models of electricity, heat, and hydrogen are similar, so this embodiment uniformly models the energy storage equipment models of electricity, heat, gas, and hydrogen, and the model is:

[0069]

[0070] Where: are the charging and discharging power of the nth energy storage device in period t respectively; The upper limit of charging and discharging power of the nth type of energy storage device; are binary variables, which set the charging and discharging state parameters of the nth energy storage for the t period respectively, in order to avoid the energy storage device being in the charging and discharging state at the same time; P ES,t,n is the output power of the nth energy storage device during period t; are the charging and discharging efficiencies of the nth type of energy storage device; S n,t is the capacity of the nth type of energy storage device in period t; is the rated capacity of the nth type of energy storage device; are respectively the upper and lower limits of the capacity of the nth type of energy storage device.

[0071] Step 2: If Figure 3 As shown, a green hydrogen energy certificate trading model is constructed.

[0072] Green hydrogen certificates represent that the system's hydrogen production process meets certain environmental standards and sustainability requirements. The system's holding of green hydrogen certificates indicates that the hydrogen production energy comes from renewable energy. When the green hydrogen produced or used by the system fails to meet the government's quota indicators, it is necessary to purchase green hydrogen certificates, otherwise a fine must be paid; when the green hydrogen produced or used by the system exceeds the government's quota indicators, it can obtain a corresponding number of green hydrogen certificates, and then earn income by selling green hydrogen certificates.

[0073]

[0074] In the formula, CGHCT The transaction cost of green hydrogen energy certificates for the system, is the transaction price of green hydrogen energy certificates, N d The quota of green hydrogen energy certificates that the system needs to hold. is the system green hydrogen energy certificate quota coefficient, is the total hydrogen energy demand of the system during the scheduling period, N s The number of green hydrogen certificates obtained by the system through hydrogen production from renewable energy, It is the quantitative coefficient for converting the amount of hydrogen produced by renewable energy into the number of green hydrogen certificates. Assuming that 1 green hydrogen certificate corresponds to 1MWh of green hydrogen, The amount of hydrogen produced by wind power in the system.

[0075] Step 3: If Figure 4 As shown, a carbon quota trading model for new energy vehicles is constructed

[0076] (1) Electric vehicle charging and discharging model:

[0077]

[0078]

[0079]

[0080] In the formula, are the charging and discharging power of the i-th EV in period t, are the rated charging and discharging power of the i-th EV in period t, S i,t is the state of charge of the i-th EV during period t, are the upper and lower limits of EV state of charge, η c , η d are EV charging and discharging efficiency, is the rated capacity of the EV battery, t a ,t i,arr and t i,lea are the grid connection time, access time, and departure time of EV, are binary variables, representing the charging and discharging status of the i-th EV in period t. max is the maximum mileage that an EV can travel under ideal conditions; d is the daily driving distance of the EV; is the power consumption of the i-th EV when it joins the grid during period t, is the expected power of the i-th EV when it is off-grid in period t. Formula (12) represents the EV power demand constraint, that is, the power expected by the owner must be reached when the EV is off-grid.

[0081] The charging and discharging load of electric vehicle cluster is:

[0082]

[0083]

[0084]

[0085] Where N ev is the number of electric vehicles, are the charging and discharging power of the EV cluster during period t respectively.

[0086] (2) Hydrogen fuel vehicle refueling model:

[0087]

[0088]

[0089]

[0090] Where: M is the maximum hydrogen storage capacity of the hydrogen tank of the nth hydrogen fuel cell vehicle. H,n,t is the amount of hydrogen added to the nth hydrogen fuel cell vehicle during period t; SOH n,arr It is the hydrogen storage state of the nth hydrogen fuel vehicle participating in the dispatch when it arrives at the hydrogen refueling station. SOH n,exp M is the expected hydrogen storage state of the nth hydrogen fuel cell vehicle. HRS,t is the total hydrogenation load of the hydrogenation station during period t. N hfcv The number of hydrogen fuel cell vehicles.

[0091] (3) Carbon quota trading model for new energy vehicles:

[0092] The baseline method is adopted, with the carbon emissions of traditional fuel vehicles as the benchmark, and the difference in carbon emissions between electric vehicles, hydrogen fuel vehicles and traditional fuel vehicles under the same driving distance as the carbon emission quota obtained by the car owner.

[0093] In order to truly play the supporting role of new energy vehicles in carbon neutrality goals, it is necessary to ensure that the electricity and hydrogen energy used as the power of new energy vehicles come from renewable energy as much as possible, otherwise it is just transferring the carbon emissions during vehicle driving to the energy supply side. Therefore, this embodiment introduces the proportion of clean energy into the carbon quota trading model to guide electric vehicles and hydrogen fuel vehicles to choose to charge during the period of high output of renewable energy as much as possible.

[0094]

[0095] Where: CEA ev,ι , CEA hfcv,ιThe carbon emissions of traditional fuel vehicles, electric vehicles and hydrogen fuel vehicles that can travel the same mileage after the total charging amount and hydrogen refueling amount participate in the dispatch; L ev , L hfcv E is the mileage of electric vehicles per unit of electricity and hydrogen fuel vehicles per unit of capacity; evgas 、E hfcvgas E is the carbon emission factor of the traditional fuel vehicle kilometer speed corresponding to the electric vehicle and hydrogen fuel vehicle respectively; c is the carbon emission factor per unit of electricity generation; RCE ev,t 、RCE hfcv,t are the carbon emissions generated by charging electric vehicles and hydrogen fuel vehicles during period t; k c is the proportion of thermal power and gas power generation in the power generation system, P c,t is the sum of gas-fired power generation and power purchase during period t; P res,t is the renewable energy output during period t; q ev ,q hfcv are the carbon quota trading prices for electric vehicles and hydrogen fuel vehicles respectively; C ev,t , C hfcv,t are the income obtained by electric vehicles and hydrogen fuel vehicles from trading carbon quotas during period t.

[0096] Step 4: Based on the green hydrogen energy certificate trading mechanism model, the park comprehensive energy system framework, and the new energy vehicle carbon quota trading model, the park comprehensive energy system operating cost and the minimum total dispatch cost of new energy vehicles are taken as the objective function to obtain the low-carbon economic dispatch strategy of the park comprehensive energy system.

[0097] (1) Objective function

[0098] min F=F1+F2+F3 (20)

[0099] Where F1 is the system operation cost, F2 is the total dispatch cost of electric vehicles, and F3 is the total dispatch cost of hydrogen fuel vehicles.

[0100] The system operation cost is composed of energy purchase cost, wind power operation cost, wind power abandonment penalty cost, green hydrogen energy certificate transaction cost, and hydrogen sales revenue of hydrogen refueling stations. It is expressed as follows:

[0101]

[0102] The system energy purchase cost consists of electricity purchase cost and gas purchase cost:

[0103]

[0104] In the formula, C e , C g are the system electricity purchase price and gas purchase price during period t, They are the system's purchased electricity and gas volumes during period t respectively.

[0105] Wind power operation costs

[0106]

[0107] In the formula, C wind is the unit operating cost of wind power, P wind,t is the wind power output during period t.

[0108] Wind curtailment penalty costs

[0109]

[0110] In the formula, λ w is the penalty cost coefficient for wind curtailment, is the predicted value of wind power output in period t.

[0111] Hydrogen sales at hydrogen refueling stations

[0112]

[0113] In the formula, It is the unit hydrogen refueling price at the hydrogen refueling station.

[0114] Green hydrogen energy certificate transaction cost (see formula (9))

[0115] The total dispatch cost of electric vehicles is composed of charging cost, discharging income, and carbon quota income. The expression is as follows:

[0116]

[0117] In the formula, are the charging price and discharging price of electric vehicles in period t respectively.

[0118] The total dispatch cost of hydrogen fuel vehicles is composed of hydrogen refueling cost and carbon quota income. The expression is as follows:

[0119]

[0120] (2) Constraints

[0121] The constraints include two-stage power-to-gas equipment operation constraints, gas-hydrogen cogeneration operation constraints, hydrogen fuel cell cogeneration operation constraints, hydrogen storage constraints at hydrogen refueling stations, energy storage equipment constraints, electric vehicle charging and discharging constraints, hydrogen refueling constraints for hydrogen fuel vehicles, power balance constraints, wind power output constraints, and system energy purchase constraints. The two-stage power-to-gas includes electrolyzer and methane reactor operation constraints.

[0122] Power balance constraints

[0123] Electric power balance

[0124]

[0125] Where P e,load is the electricity load demand during period t; are the charging and discharging powers of the energy storage device during period t respectively.

[0126] Thermal power balance

[0127]

[0128] Where P h,load is the heat load demand during period t; are respectively the charging and discharging thermal power of the thermal energy storage device during period t.

[0129] Natural Gas Power Balance

[0130]

[0131] Where P g,load is the gas load demand during period t; are respectively the charging and discharging power of the gas energy storage device during period t.

[0132] Hydrogen power balance

[0133]

[0134] In the formula, are the charging and discharging power of the hydrogen energy storage device during period t respectively.

[0135] Wind power output constraints

[0136]

[0137] Where P wind,t is the actual output of the wind turbine during period t, The predicted output of wind turbines in period t.

[0138] Energy purchase constraints

[0139]

[0140] In the formula, They are the maximum power purchased by the system from the upper-level power grid and gas grid respectively.

[0141] Step 5: Simulation verification.

[0142] In order to verify the effectiveness of the strategy proposed in this paper, a hydrogen energy industrial park in a certain region is taken as an example, and a simulation analysis is carried out with a scheduling cycle of 24 hours. There are 200 electric vehicles and 50 hydrogen fuel vehicles in the park. The wind abandonment penalty cost coefficient is 0.15 yuan / (KW·h), the EV carbon quota trading price is 0.15 yuan / kg, and the HFCV carbon quota trading price is 0.3 yuan / kg. The example is run in MATLAB, and the model is solved using the commercial solver GUROBI based on YALMIP.

[0143] In order to verify the effectiveness of the low-carbon economy optimization scheduling strategy proposed in this invention, four operation scenarios are set for comparative analysis. Scenario 1: green hydrogen energy certificate trading mechanism and new energy vehicle carbon quota trading mechanism are not considered; Scenario 2: only new energy vehicle carbon quota trading mechanism is considered; Scenario 3: only green hydrogen energy certificate trading mechanism is considered; Scenario 4: comprehensive consideration of green hydrogen energy certificate trading mechanism and new energy vehicle carbon quota trading mechanism.

[0144] Table 1

[0145]

[0146] The simulation results are as follows: The dispatch results under different scenarios obtained according to the model are shown in Table 1. As can be seen from Table 1, compared with scenarios 2, 3, and 4, scenario 1 does not consider the green hydrogen energy certificate trading mechanism and the new energy vehicle carbon quota trading mechanism, and the system's energy purchase cost, wind abandonment penalty cost, operating cost, and carbon emissions are the highest. Compared with scenario 1, scenario 2 reduces the system operating cost by 1,052.15 yuan, and the wind abandonment penalty cost by 835.58 yuan. Compared with scenario 1, scenario 3 reduces the system operating cost by 8,347.97 yuan, the wind abandonment penalty cost by 3,821.49 yuan, and the system carbon emissions by 8,610.95 kg, indicating that the green hydrogen energy trading mechanism can effectively promote wind power output and reduce system operating costs and carbon emissions. Compared with Scenario 3, Scenario 4 comprehensively considers the green hydrogen energy certificate trading mechanism and the new energy vehicle carbon quota trading mechanism. The system operating cost, wind abandonment penalty cost, and system carbon emissions are reduced by 1,918.43 yuan, 948.04 yuan, and 263.06 kg, respectively, and the green hydrogen certificate trading income increases by 931.36 yuan, proving the effectiveness of comprehensively considering the green hydrogen energy certificate trading mechanism and the new energy vehicle carbon quota trading mechanism in further improving the utilization rate of renewable energy and reducing system operating costs and carbon emissions.

[0147] like Figure 6As shown in (d), during the high wind power output period at night, the electrolyzer device uses the surplus wind power to electrolyze water to produce hydrogen, and the hydrogen energy is distributed for multiple purposes: a part is supplied to HFC for cogeneration to meet the system's electricity and heat needs, a part is transported to the hydrogen refueling station to meet the hydrogen refueling needs of hydrogen vehicles in the park, a part is supplied to the CHP unit to improve its fuel cleanliness, and a part is stored in the hydrogen storage device to meet the system's hydrogen demand during the low wind power output period. Since the process of synthesizing natural gas in the MR device requires two energy conversion processes, the production efficiency of the MR device is greatly reduced. Therefore, in the model of this embodiment, the MR device is almost in a stopped state.

[0148] Table 2

[0149]

[0150] As shown in Table 2, after considering the carbon quota trading mechanism for new energy vehicles, the EV side revenue increased by 550.87 yuan, the unit equivalent charging cost of electric vehicles decreased by 68.83%, the HFCV side revenue increased by 880.42 yuan, and the unit hydrogenation cost of HFCV users decreased by 9.65% compared with the hydrogenation price at the hydrogenation station. It can be seen that with the introduction of the carbon quota trading mechanism for new energy vehicles, electric vehicle and hydrogen fuel vehicle users tend to choose to charge during the peak hours of wind power generation, thereby increasing the proportion of wind power in the system energy supply and reducing the amount of wind abandonment. It proves the positive role of the carbon quota trading mechanism in promoting wind power consumption and enhancing user participation in scheduling.

[0151] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An energy optimization scheduling method based on hydrogen energy green certificates and new energy vehicle carbon quotas, characterized in that: The following steps are involved: Based on the composition of diversified terminal applications of hydrogen energy, a comprehensive energy system model for the park is constructed; Construct a green hydrogen energy certificate trading mechanism model and a new energy vehicle carbon quota trading model; Obtain the objective function based on the operation cost of the park's comprehensive energy system and the total dispatch cost of new energy vehicles; construct system constraints; Based on the green hydrogen energy certificate trading mechanism model, the park integrated energy system framework, and the new energy vehicle carbon quota trading model, the system constraints and the objective function are combined to obtain the coordinated optimization scheduling strategy of the park integrated energy system; The park comprehensive energy system model includes: a two-stage power-to-gas model, a gas-hydrogen cogeneration model, a hydrogen fuel cell cogeneration model, a hydrogen refueling station hydrogen storage model, and an energy storage model; The green hydrogen energy certificate trading mechanism model includes: Determine whether the actual value of the system's green hydrogen energy exceeds the fixed quota indicator. If it is less than the fixed quota indicator, purchase green hydrogen energy certificates; if it is greater than the fixed quota indicator, sell the difference between the fixed quota indicator and the actual value of the system's green hydrogen energy to obtain income. The model is expressed as follows: In the formula, C GHCT The transaction cost of green hydrogen energy certificates for the system, is the transaction price of green hydrogen energy certificates, N d The quota of green hydrogen energy certificates that the system needs to hold. is the system green hydrogen energy certificate quota coefficient, is the total hydrogen energy demand of the system during the scheduling period, N s The number of green hydrogen certificates obtained by the system through hydrogen production from renewable energy, The quantitative coefficient for converting the amount of hydrogen produced by renewable energy into the number of green hydrogen certificates. The amount of hydrogen produced by wind power in the system; The process of building a new energy vehicle carbon quota trading model includes: The baseline method is used to take the difference in carbon emissions between electric vehicles, hydrogen fuel vehicles and traditional fuel vehicles under the same driving distance as the carbon emission quota obtained by the car owner. The proportion of clean energy is introduced to obtain the carbon quota trading model for new energy vehicles. The model is as follows: Where: CEA ev,ι , CEA hfcv,ι The carbon emissions of traditional fuel vehicles, electric vehicles and hydrogen fuel vehicles that can travel the same mileage after the total charging amount and hydrogen refueling amount participate in the dispatch; L is the charging power of the EV cluster during period t; ev , L hfcv E is the mileage of electric vehicles per unit of electricity and hydrogen fuel vehicles per unit of capacity; evgas 、E hfcvgas E is the carbon emission factor of the traditional fuel vehicle kilometer speed corresponding to the electric vehicle and hydrogen fuel vehicle respectively; c is the carbon emission factor per unit of electricity generation; RCE ev,t 、RCE hfcv,t are the carbon emissions generated by charging electric vehicles and hydrogen fuel vehicles during period t; k c is the proportion of thermal power and gas power generation in the power generation system, P c,t is the sum of gas-fired power generation and power purchase during period t; P res,t is the renewable energy output during period t; q ev ,q hfcv are the carbon quota trading prices for electric vehicles and hydrogen fuel vehicles respectively; C ev,t , C hfcv,t are the incomes obtained by electric vehicles and hydrogen fuel vehicles from trading carbon quotas during period t; The objective function is to minimize the sum of the operation cost of the park's comprehensive energy system and the total dispatch cost of new energy vehicles; the system operation cost includes energy purchase cost, wind power operation cost, wind power abandonment penalty cost, green hydrogen energy certificate transaction cost, and hydrogen sales revenue at hydrogen refueling stations; the energy purchase cost includes electricity purchase cost and gas purchase cost; the total dispatch cost of new energy vehicles includes the total dispatch cost of electric vehicles and the total dispatch cost of hydrogen fuel vehicles; the total dispatch cost of electric vehicles includes charging cost, discharge revenue, and carbon quota revenue; the total dispatch cost of hydrogen fuel vehicles includes hydrogen refueling cost and carbon quota revenue; The constraints include two-stage power-to-gas equipment operation constraints, gas-hydrogen cogeneration operation constraints, hydrogen fuel cell cogeneration operation constraints, hydrogen storage constraints at hydrogen refueling stations, energy storage equipment constraints, electric vehicle charging and discharging constraints, hydrogen fuel vehicle hydrogen refueling constraints, power balance constraints, wind power output constraints, and system energy purchase constraints; among them, the two-stage power-to-gas includes the operation constraints of the electrolyzer and the methane reactor.

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