Method for scheduling of an electric-hydrogen integrated energy system based on pipe-road collaborative hydrogen transportation

Abstract

The method comprises the following steps: establishing a variable hydrogen blending ratio natural gas hydrogen blending transportation model based on flow balance; establishing a variable hydrogen blending ratio natural gas hydrogen blending transportation linear model; establishing a long tube trailer hydrogen transportation model; considering the relevant constraints of the power system and the coupling constraints between the natural gas system and the road system and between the power system and the natural gas system, combining the variable hydrogen blending ratio natural gas hydrogen blending transportation linear model and the long tube trailer hydrogen transportation model, and establishing an electric hydrogen comprehensive energy system scheduling model based on pipe-road collaborative hydrogen transportation; on the basis of the electric hydrogen comprehensive energy system scheduling model, an electric hydrogen comprehensive energy system distribution robust scheduling model is established, the opportunity constraints in the distribution robust scheduling model are re-expressed as linear constraints, and the converted electric hydrogen comprehensive energy system scheduling linear model is solved. The scheduling method reduces the difficulty of solving, reduces the transportation of hydrogen, increases the accuracy of the transportation of hydrogen, and performs peak shaving and valley filling on the electric load.

Description

Technical Field

[0001] The present invention relates to the technical field of electric-hydrogen integrated energy scheduling, and in particular to a method for scheduling an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation. Background Art

[0002] In recent years, to address energy and environmental challenges caused by overconsumption of traditional fossil fuels, the installed capacity of renewable energy, including photovoltaics, wind power, and hydropower, has grown rapidly. However, due to the volatility and instability of renewable energy, as well as its distribution in remote areas, it is difficult to absorb large amounts of renewable energy. Combining power systems with hydrogen energy systems, including water electrolysis plants, is an effective way to address the issue of surplus renewable energy. Hydrogen can be used not only in fuel cell vehicles but also in a wide range of applications, including power generation, industrial production, and heating.

[0003] However, since hydrogen production plants need to be built near renewable energy power plants, most renewable energy hydrogen production plants are located in remote areas, while most hydrogen users are in economically developed areas. This requires transporting hydrogen from the hydrogen production plants to hydrogen users. Hydrogen can be transported by ships, hydrogen tube trailers, and pipelines. For example, [1]: C.Shao, C.Feng, M.Shahidehpour, Q.Zhou, X.Wang, and X.Wang. Optimal Stochastic Operation of Integrated Electric Power and Renewable Energy With Vehicle-Based HydrogenEnergy System[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2021, 36(5): 4310-4321.

[0004] Ship transportation is mainly applicable to water areas such as river networks or oceans, and is subject to greater geographical restrictions. Hydrogen in trailer transportation can be transported in gaseous, liquid, or solid forms. Reference [2]: Cheng Huan, Ren Zhouyang, Sun Zhiyuan, et al. Electricity-hydrogen coupling system scheduling under cross-regional coordinated transportation of electricity and methanol [J]. Transactions of the Chinese Society of Electrotechnical Engineering, 2024, 39(3): 731-744.

[0005] Document [3]: H.Tan, Y.Wang, Q.Wang, and Z.Lin. Day-ahead dispatch of electricity-hydrogen systems under solid-state transportation mode ofhydrogen energy via FV-IGDT approach [J]. ENERGY, 2024, 300.

[0006] However, these methods are only suitable for short-distance transport within cities or between adjacent cities. Long-distance, large-scale hydrogen transportation significantly increases transportation costs. Pipeline transportation includes both hydrogen pipelines and natural gas pipelines. The former is currently not considered due to its high construction costs and relatively short construction lengths. The latter, given the vast existing natural gas pipeline network and the maturing pipeline hydrogen blending technology, can be used for large-scale hydrogen transportation. However, due to the hydrogen blending ratio, it cannot accurately meet user hydrogen load requirements. Summary of the Invention

[0007] To solve the above technical problems, the present invention provides a method for scheduling an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation. First, based on the steady-state model of the natural gas pipeline, by taking into account hydrogen injection and pipeline storage, a natural gas hydrogen transportation model with a variable hydrogen blending ratio based on flow balance is proposed; secondly, a natural gas hydrogen transportation linear model is derived based on piecewise linearization, piecewise McCormick technology, and equivalent substitution method; finally, natural gas hydrogen transportation is combined with trailer transportation to propose a pipeline-road coordinated hydrogen transportation mode, and the electric-hydrogen integrated energy system is scheduled. This scheduling method reduces the difficulty of solving the problem, reduces the amount of hydrogen transported, and increases the accuracy of hydrogen transportation; it also takes advantage of the characteristics of hydrogen energy storage to smooth the peaks and fill the valleys of the electric load.

[0008] The technical solution adopted by the present invention is:

[0009] The method for dispatching an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation includes the following steps:

[0010] Step 1: Based on the steady-state model of the natural gas pipeline, taking into account hydrogen injection and pipeline storage, a natural gas hydrogen blending transportation model with variable hydrogen blending ratio based on flow balance is established;

[0011] Step 2: Linearize the natural gas hydrogen transportation model with variable hydrogen blending ratio in step 1 based on piecewise linearization, piecewise McCormick technique and equivalent substitution method to establish a linear model for natural gas hydrogen transportation with variable hydrogen blending ratio;

[0012] Step 3: Establish a hydrogen transportation model for a tube trailer by simulating the spatiotemporal dynamics of the tube trailer;

[0013] Step 4: Considering the constraints related to the power system and the coupling constraints between the natural gas system and the road system, as well as between the power system and the natural gas system, and combining the linear model of natural gas hydrogen transportation with variable hydrogen blending ratio in step 2 and the long tube trailer hydrogen transportation model in step 3, a dispatch model for an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation is established;

[0014] Step 5: Based on the electric-hydrogen integrated energy system scheduling model in step 4, considering the uncertainty of wind power, a distributed robust scheduling model of the electric-hydrogen integrated energy system is established, and the opportunity constraints in the distributed robust scheduling model are re-expressed as linear constraints. Finally, the GUROBI solver is called on the MATLAB platform to solve the converted electric-hydrogen integrated energy system scheduling linear model.

[0015] In step 1, the natural gas hydrogen blending transportation model with variable hydrogen blending ratio based on flow balance is established as follows:

[0016]

[0017] In formula (1): Ω SG is the natural gas source point set; Ω SH is the hydrogen source point set; Ω in is the set of pipes flowing into node m; Ω out is the set of pipes flowing out of node m; are the volume flow rates of natural gas and hydrogen injected at node m at time t, respectively; are the volume flow rates of the mixed gas flowing out of the pipeline and into the node m at time t, respectively; is the volume flow rate of the mixed gas flowing out of the node m at time t;

[0018]

[0019] In formula (2): are the volume flow rates of hydrogen flowing out of the pipeline and into node m at time t, respectively; is the volume flow rate of the mixed gas flowing out of the node m at time t;

[0020]

[0021] In formula (3): m,t is the volume ratio of hydrogen in the mixed gas at node m at time t;

[0022]

[0023] In formula (4): is the natural gas load at node m at time t;

[0024]

[0025] In formula (5): mn,t is the volume ratio of hydrogen in the mixed gas in the pipeline (m,n) at time t;

[0026]

[0027] ω m,t =ω mn,t (7);

[0028]

[0029] In formula (8): is the average volume flow rate of the pipeline (m,n) at time t; p m,t and p n,t are the pressures at nodes m and n at time t; is the Weymouth coefficient of the pipe (m,n);

[0030]

[0031] In formula (10): and are the upper and lower limits of the hourly volume flow rate of the pipeline (m,n);

[0032]

[0033] In formula (11): is the maximum pressure ratio at both ends of the pipe; p m,t and p n,t are the pressures at nodes m and n at time t;

[0034]

[0035] In formula (12): Minimum allowable pressure at pipeline nodes; The maximum allowable pressure at the pipeline node.

[0036]

[0037] In formula (13): B mn,t and B mn,t-1 is the pipe inventory of pipeline (m,n) at time t and t-1;

[0038]

[0039] In formula (14): is the pipe storage coefficient of pipeline (m,n);

[0040]

[0041] In formula (15): Ω pipe is the collection of all natural gas pipelines; B min Indicates the minimum value of the sum of all pipeline inventories.

[0042]

[0043] In formula (16): and is the maximum and minimum volume flow rate of natural gas that can be injected into node m; is the volume flow rate of natural gas injected at node m at time t.

[0044]

[0045] In formula (17): and is the maximum and minimum volume flow rate of natural gas that can be injected into node m; is the volume flow rate of hydrogen injected at node m at time t.

[0046] are the Weymouth coefficient and pipe storage coefficient of the pipeline (m,n), respectively, and their expressions are as follows:

[0047]

[0048] In formula (18) and formula (19), D mn 、l mn 、f mn are the diameter, length and friction coefficient of the pipe (m,n) respectively; π is the circumference of a circle; and are the specific gas constant and density of the mixed gas respectively; The compression factor and mixed gas density of the pipeline (m, n) when hydrogen is injected are taken into account; and are the specific gas constant and density of natural gas, respectively; is the compression coefficient of the pipeline (m, n) without taking into account the hydrogen injection; the present invention assumes that the influence of temperature change on gas flow is negligible, that is, T0 is the ambient temperature.

[0049] Considering that the gap between gas molecules is large, the actual pressure has little effect on the compressibility coefficient, so the average value of the upper and lower pressure limits of each node is used. Instead of the actual pressure, Since the hydrogen content in pipeline is relatively small, the change of compression coefficient with hydrogen content ratio can be ignored. The absolute temperature of natural gas T c NG and absolute pressure P cNG Instead of the absolute temperature and absolute pressure of the mixed gas, the compressibility coefficients of the mixed gas and natural gas are equal, that is, Since the amount of hydrogen added is relatively small and has little effect on the friction coefficient of the pipeline, this effect can be ignored, that is, the friction coefficient is only related to the pipeline diameter. The expression of the mixed gas compressibility factor is:

[0050]

[0051] In formula (20): Indicates the mixed gas compressibility factor; T c NG Indicates absolute temperature; Represents the average value of the upper and lower limits of pressure at each node; represents the average value of the upper and lower limits of the pressure at node n; P c NG represents absolute pressure;

[0052]

[0053] In formula (21): D mn is the diameter of the pipe (m,n); Indicates D mn 1 / 6 of the power.

[0054] Specific gas constant of mixed gas It is related to the hydrogen doping ratio and the molar coefficient of each gas component, and its expression is shown in formula (22):

[0055]

[0056] In formula (22), r is the universal gas constant, is the molar coefficient of the mixed gas in the pipeline (m,n); M NG 、M H2 are the molar coefficients of natural gas and hydrogen, respectively.

[0057] Density of mixed gas It is a function of hydrogen doping ratio, and its expression is:

[0058]

[0059] In formula (24), ρ NG , ρ H2 are the standard densities of natural gas and hydrogen respectively.

[0060]

[0061] The natural gas steady-state model includes not only the natural gas flow balance, equation (24), but also equations (8), (10), (11), and (12).

[0062] In step 2, the nonlinear terms of the variable hydrogen blending ratio natural gas hydrogen blending transportation model are formula (3), formula (4), formula (5), formula (8), and formula (17). Among them, formula (3), formula (4), and formula (5) all contain bilinear terms, which can be directly linearized using the segmented McCormick technique. Taking formula (3) as an example, the node outflow volume flow rate is selected As the variable to be divided, it can be converted into:

[0063]

[0064] In formula (25): S is the number of segments; and are the minimum and maximum values ​​of hydrogen doping ratio respectively; and are the minimum and maximum volume flow rates of the mixed gas flowing out of node m, respectively; and are the minimum and maximum values ​​of the volume flow rate of the mixed gas flowing out of node m in segment s respectively; is the value of the mixed gas volume flow rate of the sth segment out of the node m; ω m,s,t is the value of the hydrogen doping ratio of segment s at node m at time t; is the auxiliary 0-1 variable introduced; is the volume flow rate of the mixed gas flowing out of the node m at time t;

[0065] Equations (8) and (17) contain highly nonlinear terms, which need to be replaced first. Then, the piecewise linearization method and the piecewise McCormick technique are used to transform them into linear terms. Taking Equation (8) as an example, the equivalent replacement is first performed as follows:

[0066]

[0067] Where, χ mn,t 、 K m,t , K n,t They are all introduced intermediate auxiliary variables.

[0068] Among them, equations (27) and (28) can be linearized using the piecewise McCormick technique. Equations (29), (30), and (31) are obviously monotonically increasing functions and can be linearized using the piecewise linearization method. Taking equation (29) as an example, it can be converted to:

[0069]

[0070] In formula (32), Np is the total number of segments; is the slope of the volume flow rate of the pipe (m,n) in the kth segment; is the actual volume flow rate of the kth segment of the pipeline (m,n) during period t; Minimum volume flow rate of pipe (m,n); is the maximum volume flow rate of the pipeline (m,n) in the kth segment.

[0071] Weymouth coefficient of pipe mn can be restated as:

[0072]

[0073] In formula (33), X1, X2, and X3 are intermediate auxiliary variables introduced; X1 is a constant, and X2 and X3 are both about ω. m,t A positive increasing function; ρ NG , ρ H2 are the standard densities of natural gas and hydrogen respectively. It is also a positive increasing function and can be linearized using piecewise linearization. From then on, all nonlinear terms are linearized.

[0074] In step 3, the established long-tube trailer hydrogen transportation model includes trailer operation constraints and hydrogen interaction constraints between the trailer and each hydrogen energy user. The trailer operation constraint expression is:

[0075]

[0076] In formula (34), Ω RN represents the set of nodes in the traffic network; Ω Road Represents the set of traffic network paths. c,m,t represents the parking state of trailer c at time t, μ c,m,t = 1, at time t, trailer c is located at node m in the traffic network; v c,mn,t represents the driving state of trailer c at time t, v c,mn,t = 1, at time t, trailer c is located on the traffic network path mn;

[0077] η c,m,t -κ c,m,t =μ c,m,t -μ c,m,t-1 (35);

[0078] In formula (35), η c,m,t is the state variable of trailer c arriving at node m at time t; κ c,m,t is the state variable of trailer c leaving node m at time t; μ c,m,t-1 represents the parking state of trailer c at time t-1;

[0079]

[0080] In the above formula, η c,n,t is the state variable of trailer c arriving at node n at time t; θ c,n,t is the auxiliary 0-1 variable introduced;

[0081]

[0082] In formula (39), η c,m,t is the state variable of trailer c arriving at node m at time t; θ c,m,t is the auxiliary 0-1 variable introduced;

[0083]

[0084] In formula (40), v c,mn,t-1 represents the driving state of trailer c at time t-1; Indicates tt min The driving status of trailer c at the moment;

[0085] t min =[L mn / V c ] + (41);

[0086] In formula (41), define [i] + is the rounding symbol, t min V is the shortest time required for the trailer to pass through the path mn; c is the average speed of the trailer; L mn Represents the length of the road between node m and node n.

[0087] The hydrogen interaction constraints between the trailer and each hydrogen energy user are:

[0088]

[0089] Where, and are the mass of hydrogen transported by trailer c at time t and t-1 respectively; is the maximum mass of hydrogen that trailer c can transport; is the mass of hydrogen loaded by trailer c from hydrogen energy users at node m at time t; is the maximum mass of hydrogen that trailer c can load from hydrogen energy user at node m in one hour.

[0090] In step 4, the power system-related constraints include power balance constraints, unit start-stop constraints, and active power upper and lower limit constraints. Reserve capacity constraints, ramp constraints, and line transmission capacity constraints can be provided. The expressions are as follows:

[0091]

[0092] In formula (45), N g 、N w 、N d 、N H2 They are respectively a collection of conventional units, wind farms, power loads, and electrolyzers; is the predicted power generation of unit i during period t; Forecast output for wind farms; is the power load; is the input power of the electrolytic cell; t represents a time period; N t represents the set of time periods t.

[0093]

[0094] In formula (46), are the start and stop state variables of unit i during period t; u i,t is the operating state variable of unit i during period t;

[0095]

[0096] In formula (47), T i on The minimum start and stop time for conventional units;

[0097]

[0098] In formula (48), T i off is the minimum shutdown time of conventional units;

[0099]

[0100] In the above formula, and are the predicted power generation of unit i at time periods t and t-1 respectively; and are the downward reserve capacity provided by unit i during periods t and t-1 respectively; and are the upward reserve capacity provided by unit i during periods t and t-1 respectively; is the predicted power generation of wind farm i during period t; is the active load of wind farm i; is the input power of electrolytic cell i during period t. i G,min 、P i G,max are the minimum and maximum output of conventional units respectively; Ri UP,max 、R i DN,max They are the maximum upward and downward reserve capacities that conventional units can provide, respectively; They are the maximum upward and downward climbing powers of conventional units respectively; is the maximum transmission capacity of line ij; matrix M ij is the transfer power matrix between line power flow and node power injection; matrix A G 、A W 、A L 、A H2 They are bus-generator, bus-wind farm, bus load correlation matrix, and bus-electrolyzer correlation matrix respectively.

[0101] The power system and the natural gas system are coupled through the electrolyzer and hydrogen storage tank in the hydrogen production plant, with the following constraints:

[0102]

[0103] In the above formula: η p2h is the electricity-to-hydrogen conversion efficiency of the electrolyzer; H v is the lower calorific value of hydrogen; and are the hydrogen storage capacity of the gas tank at time periods t and t-1 respectively; and are the minimum and maximum hydrogen storage capacity of the gas tank respectively; is the output hydrogen volume of electrolyzer i during period t. is the volume flow rate of hydrogen injected at node i at time t.

[0104] The coupling between the natural gas system and the road system is achieved through the hydrogen balance, which is expressed as:

[0105]

[0106] Where, is the hydrogen load; is the hydrogen load removal amount; Ω HT for the collection of trailers; represents the amount of hydrogen exchanged between the tube trailer c and the hydrogen energy user at the natural gas system node m during period t; represents the hydrogen load of node m during period t.

[0107] The dispatch model of the electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation aims to minimize the total operating cost, specifically including: the power system operating cost F om , trailer hydrogen transportation cost F HT , whose expression is:

[0108] minF=F om +F HT +F cut (58);

[0109] Where, F represents the total operating cost of EHIES; F om 、F HT and F cut They are the power system operating cost, the hydrogen transportation cost by tube trailer and the hydrogen load removal cost.

[0110]

[0111]

[0112] In the above formula, are the unit power generation cost, startup cost coefficient, shutdown cost coefficient, and no-load cost coefficient of unit i respectively; is the upper and lower reserve capacity cost coefficient of unit i; c fix is the fixed cost of HT per hour; c cha Ω is the driving cost per kilometer of HT; DH2 is the hydrogen load set. N t represents the set of time periods t; Ω Road Represents a set of traffic network paths; represents the cost coefficient of hydrogen load removal at node m; Represents the hydrogen load removal amount at node m.

[0113] In step 5, first, define the wind power output real distribution P and the empirical distribution The Wasserstein distance between:

[0114]

[0115] Where, Represents the true distribution P and the empirical distribution Wasserstein distance between 2 is the support set of the random variable ξ; Represents ξ and The first-order norm between ; Represents ξ and The joint distribution of ; inf is the infimum function.

[0116] Then construct the fuzzy set Y based on Wasserstein distance:

[0117]

[0118] Where: Ο(Ψ) represents the set of all values ​​of the true distribution P in the support set; ρ is the radius of the Wasserstein sphere.

[0119] Then, the conventional unit dispatch capacity cost and related constraints are added to the objective function (54):

[0120]

[0121] In formula (64): Y t The fuzzy set representing the wind power error distribution in period t; Cost coefficient for adjusting active power output for conventional units; Active power output adjusted for conventional units; express expected value.

[0122]

[0123] In formula (65): express The probability of this event; α is the allowed constraint violation probability.

[0124]

[0125]

[0126] Where: It is the actual active power output of conventional units; The actual output of the wind farm;

[0127] Finally, the nonlinear term in the objective function (64) and the opportunity constraint in the constraint conditions are transformed: Equations (65) to (68). Among them, the opportunity constraint takes Equation (65) as an example:

[0128] First, yes Make the following equivalent substitutions:

[0129]

[0130] Where, ξ i,t represents the prediction error of wind farm i at time t; τ t represents the total wind power prediction error; I is a unit column vector; the superscript T represents the transpose of the matrix; β i,t Indicates the error ratio of each unit adjustment.

[0131] The objective function in the distributed robust scheduling model of the electric-hydrogen integrated energy system of the present invention can be re-expressed as:

[0132]

[0133] In formula (72), Y t The fuzzy set representing the wind power error distribution in period t; express expected value.

[0134] make Under the fuzzy set Y, we can is equivalent to:

[0135]

[0136]

[0137] In the above formula, K is the number of sample sets; represents the kth sample; λ, ε k , γ k 、ω 1,i,t ,λ 1,i,t , ε 1,i,t,n , γ 11,i,t,n , γ 12,i,t,n is an auxiliary variable introduced and has no practical significance; G and s are known matrices and vectors related to setting boundary conditions; ρ is the radius of the Wasserstein sphere; is an intermediate auxiliary matrix; is the auxiliary matrix γ k The transpose of N k Represents a collection of samples; Indicates that λ is a real number; Represents a positive, real vector of length 2K. represents the kth sample in time period t; G T Represents the transpose of the constant matrix G.

[0138] All nonlinear terms in the distributed robust model for the electric-hydrogen integrated energy system dispatch are linearized. The converted mixed integer programming model can be solved directly on the MATLAB platform using the CPLEX commercial solver. The solution includes the following steps:

[0139] Step 1: Program the input parameters of the mixed integer programming model on the MATLAB platform;

[0140] Step 2: Define the decision variables of the mixed integer programming model on the MATLAB platform;

[0141] Step 3: Program the objective function of the mixed integer programming model on the MATLAB platform;

[0142] Step 4: Program the constraints of the mixed integer programming model on the MATLAB platform;

[0143] Step 5: Call the CPLEX solver on the MATLAB platform to solve the mixed integer programming model.

[0144] Step 6: Output relevant parameters of the power system, natural gas system and road system on the MATLAB platform.

[0145] The present invention provides a method for dispatching an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation, and the technical effects are as follows:

[0146] 1) The present invention introduces pipeline storage characteristics into the traditional pipeline hydrogen transportation model, so that the hydrogen storage capacity of the pipeline is effectively simulated, thereby more realistically reflecting the operational flexibility of the pipeline under different loads and the changing laws of hydrogen transportation.

[0147] 2) In the scheduling method of the present invention, for problems that are difficult to solve with traditional models, the model is linearized to greatly reduce the complexity of the calculation and effectively improve the solution speed.

[0148] 3) The present invention develops a special long-tube trailer hydrogen transportation model that can accurately simulate the spatiotemporal dynamic characteristics of the long-tube trailer during transportation.

[0149] 4) The present invention achieves multi-system coordinated operation by coupling the power system, natural gas system and road transportation system, thereby improving the renewable energy absorption capacity and the economy of the system.

[0150] 5) The distributed robust model of the present invention, by modeling the uncertain parameters in the system and performing robust optimization, ensures that the system can maintain efficient and stable operation in different scenarios, thereby balancing the relationship between economy and reliability. This approach not only improves the system's anti-interference ability, but also ensures that the system can still operate stably under extreme conditions, avoiding potential risks caused by uncertain factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0151] The present invention will be further described below with reference to the accompanying drawings and examples:

[0152] Figure 1 This is the operational framework diagram of the electric-hydrogen integrated energy system.

[0153] Figure 2 This is the topological structure diagram of the electric-hydrogen integrated energy system.

[0154] Figure 3 This is the scheduling result diagram of hydrogen production, hydrogen injection and hydrogen storage capacity of the hydrogen production plant.

[0155] Figure 4 This is the diagram of load hydrogen blending ratio and scheduling result hydrogen blending ratio.

[0156] Figure 5This is the hydrogen doping ratio error diagram.

[0157] Figure 6 Schematic diagram of the impact of the number of segments on model error and solution time.

[0158] Figure 7 Flowchart for solving the mixed integer programming model. DETAILED DESCRIPTION

[0159] The method for dispatching an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation includes the following steps:

[0160] Step 1: Based on the steady-state model of the natural gas pipeline, a natural gas hydrogen transportation model with variable hydrogen blending ratio based on flow balance was established by taking into account hydrogen injection and pipeline storage.

[0161] Step 2: Linearize the natural gas hydrogen transportation model with variable hydrogen blending ratio in step 1 based on piecewise linearization, piecewise McCormick technique and equivalent substitution method to establish a linear model for natural gas hydrogen transportation with variable hydrogen blending ratio;

[0162] Step 3: Establish a hydrogen transportation model for a tube trailer by simulating the spatiotemporal dynamics of the tube trailer;

[0163] Step 4: Considering the constraints related to the power system and the coupling constraints between the natural gas system and the road system, as well as between the power system and the natural gas system, and combining the linear model of natural gas-hydrogen transportation with variable hydrogen blending ratio in step 2 and the long-tube trailer hydrogen transportation model in step 3, a dispatch model for an integrated electric-hydrogen energy system based on pipeline-road coordinated hydrogen transportation is established;

[0164] Step 5: Based on the dispatching model of the electric-hydrogen integrated energy system in step 4, considering the uncertainty of wind power, a distributed robust dispatching model of the electric-hydrogen integrated energy system is established. Then, the opportunity constraints in the model are re-expressed as linear constraints. Finally, the GUROBI solver is called on the MATLAB platform to solve the converted linear model of the electric-hydrogen integrated energy system dispatching.

[0165] The present invention proposes a pipeline-road coordinated hydrogen transportation mode, which can economically and flexibly transport hydrogen from the hydrogen production plant to various hydrogen energy users, and coordinately optimize the power system, natural gas system and road system, which can effectively improve the renewable energy consumption and system economy.

[0166] In step 1, the natural gas hydrogen blending transportation model with variable hydrogen blending ratio based on flow balance is established as follows:

[0167]

[0168] In formula (1): Ω SG is the natural gas source point set; ΩSH is the hydrogen source point set; Ω in is the set of pipes flowing into node m; Ω out is the set of pipes flowing out of node m; are the volume flow rates of natural gas and hydrogen injected at node m at time t, respectively; are the volume flow rates of the mixed gas flowing out of the pipeline and into the node m at time t, respectively; is the volume flow rate of the mixed gas flowing out of the node m at time t;

[0169]

[0170] In formula (2): are the volume flow rates of hydrogen flowing out of the pipeline and into node m at time t, respectively; is the volume flow rate of the mixed gas flowing out of the node m at time t;

[0171]

[0172] In formula (3): m,t is the volume ratio of hydrogen in the mixed gas at node m at time t;

[0173]

[0174] In formula (4): is the natural gas load at node m at time t;

[0175]

[0176] In formula (5): mn,t is the volume ratio of hydrogen in the mixed gas in the pipeline (m,n) at time t;

[0177]

[0178] ω m,t =ω mn,t (7);

[0179]

[0180] In formula (8): is the average volume flow rate of the pipeline (m,n) at time t; p m,t and p n,t are the pressures at nodes m and n at time t; is the Weymouth coefficient of the pipe (m,n);

[0181]

[0182]

[0183] In formula (10): and are the upper and lower limits of the hourly volume flow rate of the pipeline (m,n);

[0184]

[0185] In formula (11): is the maximum pressure ratio at both ends of the pipe; p m,t and p n,t are the pressures at nodes m and n at time t;

[0186]

[0187] In formula (12): Minimum allowable pressure at pipeline nodes; The maximum allowable pressure at the pipeline node.

[0188]

[0189] In formula (13): B mn,t and B mn,t-1 is the pipe inventory of pipeline (m,n) at time t and t-1;

[0190]

[0191] In formula (14): is the pipe storage coefficient of pipeline (m,n);

[0192]

[0193] In formula (15): Ω pipe is the collection of all natural gas pipelines; B min Indicates the minimum value of the sum of all pipeline inventories.

[0194]

[0195] In formula (16): and is the maximum and minimum volume flow rate of natural gas that can be injected into node m; is the volume flow rate of natural gas injected at node m at time t.

[0196]

[0197] In formula (17): and is the maximum and minimum volume flow rate of natural gas that can be injected into node m; is the volume flow rate of hydrogen injected at node m at time t.

[0198] are the Weymouth coefficient and pipe storage coefficient of the pipeline (m,n), respectively, and their expressions are as follows:

[0199]

[0200] In formula (18) and formula (19), D mn 、l mn 、f mn are the diameter, length and friction coefficient of the pipe (m,n) respectively; π is the circumference of a circle; and are the specific gas constant and density of the mixed gas respectively; The compression factor and mixed gas density of the pipeline (m, n) when hydrogen is injected are taken into account; and are the specific gas constant and density of natural gas, respectively; is the compression coefficient of the pipeline (m, n) without taking into account the hydrogen injection; the present invention assumes that the influence of temperature change on gas flow is negligible, that is, T0 is the ambient temperature.

[0201] Considering that the gap between gas molecules is large, the actual pressure has little effect on the compressibility coefficient, so the average value of the upper and lower pressure limits of each node is used. Instead of the actual pressure, Since the hydrogen content in pipeline is relatively small, the change of compression coefficient with hydrogen content ratio can be ignored. The absolute temperature of natural gas T c NG and absolute pressure P c NG Instead of the absolute temperature and absolute pressure of the mixed gas, the compressibility coefficients of the mixed gas and natural gas are equal, that is, Since the amount of hydrogen added is relatively small and has little effect on the friction coefficient of the pipeline, this effect can be ignored, that is, the friction coefficient is only related to the pipeline diameter. The expression of the mixed gas compressibility factor is:

[0202]

[0203] In formula (20): Indicates the mixed gas compressibility factor; T c NG Indicates absolute temperature; Represents the average value of the upper and lower limits of pressure at each node; represents the average value of the upper and lower limits of the pressure at node n; P c NG represents absolute pressure;

[0204]

[0205] In formula (21): D mn is the diameter of the pipe (m,n); Indicates D mn 1 / 6 of the power.

[0206] Specific gas constant of a gas mixture It is related to the hydrogen doping ratio and the molar coefficient of each gas component, and its expression is shown in formula (22):

[0207]

[0208] In formula (22), r is the universal gas constant, is the molar coefficient of the mixed gas in the pipeline (m,n); M NG 、M H2 are the molar coefficients of natural gas and hydrogen, respectively.

[0209] Density of mixed gas It is a function of hydrogen doping ratio, and its expression is:

[0210]

[0211] In formula (24), ρ NG , ρ H2 are the standard densities of natural gas and hydrogen respectively.

[0212]

[0213] The natural gas steady-state model includes not only the natural gas flow balance, equation (24), but also equations (8), (10), (11), and (12).

[0214] In step 2, the nonlinear terms of the variable hydrogen blending ratio natural gas hydrogen blending transportation model are formula (3), formula (4), formula (5), formula (8), and formula (17). Among them, formula (3), formula (4), and formula (5) all contain bilinear terms, which can be directly linearized using the segmented McCormick technique. Taking formula (3) as an example, the node outflow volume flow rate is selected As the variable to be divided, it can be converted into:

[0215]

[0216] In formula (25): S is the number of segments; and are the minimum and maximum values ​​of hydrogen doping ratio respectively; and are the minimum and maximum volume flow rates of the mixed gas flowing out of node m, respectively; and are the minimum and maximum values ​​of the volume flow rate of the mixed gas flowing out of node m in segment s respectively; is the value of the mixed gas volume flow rate of the sth segment out of the node m; ω m,s,t is the value of the hydrogen doping ratio of segment s at node m at time t; is the auxiliary 0-1 variable introduced; is the volume flow rate of the mixed gas flowing out of the node m at time t;

[0217] Equations (8) and (17) contain highly nonlinear terms, which need to be replaced first. Then, the piecewise linearization method and the piecewise McCormick technique are used to transform them into linear terms. Taking Equation (8) as an example, the equivalent replacement is first performed as follows:

[0218]

[0219]

[0220] Where, χ mn,t 、 K m,t , K n,t They are all introduced intermediate auxiliary variables.

[0221] Among them, equations (27) and (28) can be linearized using the piecewise McCormick technique. Equations (29), (30), and (31) are obviously monotonically increasing functions and can be linearized using the piecewise linearization method. Taking equation (29) as an example, it can be converted to:

[0222]

[0223] In formula (32), Np is the total number of segments; is the slope of the volume flow rate of the pipeline (m,n) in the kth segment; is the actual volume flow rate of the kth segment of the pipeline (m,n) during period t; Minimum volume flow rate of pipe (m,n); is the maximum volume flow rate of the pipeline (m,n) in the kth segment.

[0224] Weymouth coefficient of pipe mn can be restated as:

[0225]

[0226] In formula (33), X1, X2, and X3 are intermediate auxiliary variables introduced; X1 is a constant, and X2 and X3 are both about ω. m,t A positive increasing function; ρ NG , ρ H2The standard densities of natural gas and hydrogen, respectively. Therefore is also a positive increasing function, which can be linearized by piecewise linearization method. From this, all nonlinear terms are linearized.

[0227] In step 3, the established long tube trailer hydrogen transport model includes trailer operation constraints and hydrogen interaction constraints between the trailer and each hydrogen energy user. The trailer operation constraint expression is:

[0228]

[0229] In formula (34), Ω RN represents the set of traffic network nodes; Ω Road represents the set of traffic network paths. μ c,m,t represents the parking state of trailer c at time t, μ c,m,t = 1, trailer c is located on traffic network node m at time t; v c,mn,t represents the driving state of trailer c at time t, v c,mn,t = 1, trailer c is located on traffic network path mn at time t;

[0230] η c,m,t - κ c,m,t = μ c,m,t - μ c,m,t-1 (35);

[0231] In formula (35), η c,m,t is the state variable of trailer c arriving at node m at time t; κ c,m,t is the state variable of trailer c leaving node m at time t; μ c,m,t-1 represents the parking state of trailer c at time t-1;

[0232]

[0233] In the above formula, η c,n,t is the state variable of trailer c arriving at node n at time t; θ c,n,t is an auxiliary 0-1 variable introduced;

[0234]

[0235] In formula (39), η c,m,t is the state variable of trailer c arriving at node m at time t; θ c,m,t is an auxiliary 0-1 variable introduced;

[0236]

[0237] In formula (40), v c,mn,t-1 represents the driving state of trailer c at time t-1; represents the driving state of trailer c at time t-tmin The driving status of trailer c at the moment;

[0238] t min =[L mn / V c ] + (41);

[0239] In formula (41), define [i] + is the rounding symbol, t min V is the shortest time required for the trailer to pass through the path mn; c is the average speed of the trailer; L mn Represents the length of the road between node m and node n.

[0240] The hydrogen interaction constraints between the trailer and each hydrogen energy user are:

[0241]

[0242] Where, and are the mass of hydrogen transported by trailer c at time t and t-1 respectively; is the maximum mass of hydrogen that trailer c can transport; is the mass of hydrogen loaded by trailer c from hydrogen energy users at node m at time t; is the maximum mass of hydrogen that trailer c can load from hydrogen energy user at node m in one hour.

[0243] In step 4, the power system-related constraints include power balance constraints, unit start-stop constraints, and active power upper and lower limit constraints. Reserve capacity constraints, ramp constraints, and line transmission capacity constraints can be provided. The expressions are as follows:

[0244]

[0245] In formula (45), N g 、N w 、N d 、N H2 They are respectively a collection of conventional units, wind farms, power loads, and electrolyzers; is the predicted power generation of unit i during period t; Forecast output for wind farms; is the power load; is the input power of the electrolytic cell; t represents a time period; N t represents the set of time periods t.

[0246]

[0247] In formula (46), are the start and stop state variables of unit i during period t; u i,t is the operating state variable of unit i during period t;

[0248]

[0249] In formula (47), T i on The minimum start and stop time for conventional units;

[0250]

[0251] In formula (48), T i off is the minimum shutdown time of conventional units;

[0252]

[0253]

[0254] In the above formula, and are the predicted power generation of unit i at time periods t and t-1 respectively; and are the downward reserve capacity provided by unit i during periods t and t-1 respectively; and are the upward reserve capacity provided by unit i during periods t and t-1 respectively; is the predicted power generation of wind farm i during period t; is the active load of wind farm i; is the input power of electrolytic cell i during period t. i G,min 、P i G,max are the minimum and maximum output of conventional units respectively; R i UP,max 、R i DN,max They are the maximum upward and downward reserve capacities that conventional units can provide, respectively; They are the maximum upward and downward climbing powers of conventional units respectively; is the maximum transmission capacity of line ij; matrix M ij is the transfer power matrix between line power flow and node power injection; matrix A G 、A W 、A L 、A H2 They are bus-generator, bus-wind farm, bus load correlation matrix, and bus-electrolyzer correlation matrix respectively.

[0255] The power system and the natural gas system are coupled through the electrolyzer and hydrogen storage tank in the hydrogen production plant, with the following constraints:

[0256]

[0257] In the above formula: η p2h is the electricity-to-hydrogen conversion efficiency of the electrolyzer; H v is the lower calorific value of hydrogen; and are the hydrogen storage capacity of the gas tank at time periods t and t-1 respectively; and are the minimum and maximum hydrogen storage capacity of the gas tank respectively; is the output hydrogen volume of electrolyzer i during period t. is the volume flow rate of hydrogen injected at node i at time t.

[0258] The coupling between the natural gas system and the road system is achieved through the hydrogen balance, which is expressed as:

[0259]

[0260] Where, is the hydrogen load; is the hydrogen load removal amount; Ω HT for the collection of trailers; represents the amount of hydrogen exchanged between the tube trailer c and the hydrogen energy user at the natural gas system node m during period t; represents the hydrogen load of node m during period t.

[0261] The dispatch model of the electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation aims to minimize the total operating cost, specifically including: the power system operating cost F om , trailer hydrogen transportation cost F HT , whose expression is:

[0262] minF=F om +F HT +F cut (58);

[0263] Where, F represents the total operating cost of EHIES; F om 、F HT and F cut They are the power system operating cost, the hydrogen transportation cost by tube trailer and the hydrogen load removal cost.

[0264]

[0265] In the above formula, are the unit power generation cost, startup cost coefficient, shutdown cost coefficient, and no-load cost coefficient of unit i respectively; is the upper and lower reserve capacity cost coefficient of unit i; c fix is the fixed cost of HT per hour; c cha Ω is the driving cost per kilometer of HT; DH2 is the hydrogen load set. N t represents the set of time periods t; Ω Road Represents a set of traffic network paths; represents the cost coefficient of hydrogen load removal at node m; Represents the hydrogen load removal amount at node m.

[0266] In step 5, first, define the wind power output real distribution P and the empirical distribution The Wasserstein distance between:

[0267]

[0268] Where, Represents the true distribution P and the empirical distribution Wasserstein distance between 2 is the support set of the random variable ξ; Represents ξ and The first-order norm between ; Represents ξ and The joint distribution of ; inf is the infimum function.

[0269] Then construct the fuzzy set Y based on Wasserstein distance:

[0270]

[0271] Where: Ο(Ψ) represents the set of all values ​​of the true distribution P in the support set; ρ is the radius of the Wasserstein sphere.

[0272] Then, the conventional unit dispatch capacity cost and related constraints are added to the objective function (54):

[0273]

[0274] In formula (64): Y t The fuzzy set representing the wind power error distribution in period t; Cost coefficient for adjusting active power output for conventional units; Active power output adjusted for conventional units; express expected value.

[0275]

[0276] In formula (65): express The probability of this event; α is the allowed constraint violation probability.

[0277]

[0278] Where: It is the actual active power output of conventional units; The actual output of the wind farm;

[0279] Finally, the nonlinear term in the objective function (64) and the chance constraint in the constraint conditions are transformed into (65) to (68), where the chance constraint is taken as an example.

[0280] First, yes Make the following equivalent substitutions:

[0281]

[0282] Where, ξ i,t represents the prediction error of wind farm i at time t; τ t represents the total wind power prediction error; I is a unit column vector; the superscript T represents the transpose of the matrix; β i,t Indicates the error ratio of each unit adjustment.

[0283] The objective function in the distributed robust scheduling model of the electric-hydrogen integrated energy system of the present invention can be re-expressed as:

[0284]

[0285] In formula (72), Y t The fuzzy set representing the wind power error distribution in period t; express expected value.

[0286] make Under the fuzzy set Y, we can is equivalent to:

[0287]

[0288] In the above formula, K is the number of sample sets; represents the kth sample; λ, ε k , γ k 、ω 1,i,t ,λ 1,i,t , ε 1,i,t,n , γ 11,i,t,n , γ 12,i,t,n is an auxiliary variable introduced and has no practical significance; G and s are known matrices and vectors related to setting boundary conditions; ρ is the radius of the Wasserstein sphere; is an intermediate auxiliary matrix; is the auxiliary matrix γ k The transpose of N k Represents a collection of samples; Indicates that λ is a real number; Represents a positive, real vector of length 2K. represents the kth sample in time period t; G T Represents the transpose of the constant matrix G.

[0289] All nonlinear terms in the distributed robust model for the electric-hydrogen integrated energy system dispatch are linearized. The converted mixed integer programming model can be solved directly on the MATLAB platform using the CPLEX commercial solver. The solution includes the following steps:

[0290] Step 1: Program the input parameters of the mixed integer programming model on the MATLAB platform;

[0291] Step 2: Define the decision variables of the mixed integer programming model on the MATLAB platform;

[0292] Step 3: Program the objective function of the mixed integer programming model on the MATLAB platform;

[0293] Step 4: Program the constraints of the mixed integer programming model on the MATLAB platform;

[0294] Step 5: Call the CPLEX solver on the MATLAB platform to solve the mixed integer programming model.

[0295] Step 6: Output relevant parameters of the power system, natural gas system and road system on the MATLAB platform.

[0296] Example:

[0297] The present invention is based on the improved IEEE 5-node power network, 8-node natural gas system and 5-node transportation network, and constructs an EHIES (energy system) based on pipeline-road coordinated hydrogen transportation. In this power system, a hydrogen production plant is set up at node 5, and the produced hydrogen is injected through node 2 of the natural gas network. A wind farm with a capacity of 180MW is established at node 5, and conventional power plant 1, conventional power plant 2 and conventional power plant 3 are set up at nodes 1, 3 and 4 respectively. A natural gas source is connected to node 1 of the natural gas system, and hydrogen refueling stations are established at nodes 5, 6, 7 and 8 respectively. The topological structure diagram of the entire system is shown as follows: Figure 2 In this system, the daily gas demand is 5.3830 Mm 3 Natural gas and 0.6355Mm 3Hydrogen. The upper limit for hydrogen blending into natural gas pipelines is 20%. Appendix C shows the 24-hour hydrogen load, the wind farm's predicted output curve, and the total daily electricity load. The system is equipped with six dispatchable hydrogen transport vehicles, each with a maximum hydrogen transport capacity of 200 kg, a travel speed of 50 km / h, a fixed cost of 600 yuan per vehicle, and a transport cost coefficient of 8 yuan per kilometer. The modified McCormick technique and the number of segments for piecewise linearization were both set to 10. The simulation was performed on the MATLAB 2022a platform using the Yalmip toolbox and the Gurobi solver.

[0298] 1: Analysis of the dispatch of the electric-hydrogen integrated energy system:

[0299] First, without considering the uncertainty of wind power output, the scheduling results of the model proposed in this invention are analyzed. Taking the hydrogen production plant as the object, the hydrogen production, hydrogen energy reserves and hydrogen injection amount of the hydrogen production plant are as follows: Figure 3 As shown in the figure, during the hours of 1:00-6:00, 9:00, 12:00-1:00, and 23:00-24:00, the power load and load are relatively low, the wind power output is high, the electrolyzer input power is high, and the hydrogen energy reserves in the hydrogen production plant increase rapidly. At other times, especially during the peak hydrogen load period of 18:00-19:00, the hydrogen production volume is far less than the hydrogen injection volume, and the hydrogen energy reserves in the hydrogen production plant decrease rapidly. This shows that hydrogen production can effectively absorb wind power and effectively eliminate the power imbalance caused by the anti-peaking characteristics of wind power output and the ramping constraints of conventional units.

[0300] The required gas load hydrogen ratio of each gas load node and the scheduling result of hydrogen mixing, for example Figure 4 As shown, the ratio of hydrogen to natural gas required by each gas load node is different, and the gas ratio required by the same load node is also different at different times. If hydrogen is transported solely through natural gas pipelines, a large number of load shedding events will occur. The total hydrogen load shedding per day reaches 12.866 tons, accounting for 22.68% of the total hydrogen load. After adopting the hydrogen transportation mode proposed by this invention, the load shedding amount is reduced to 0. This is because trailers can transport hydrogen between various hydrogen loads, compensating for the supply and demand imbalance caused by pipeline transportation. As can be seen from Table 1, the total cost of Scenario 1 is 3.50% lower than that of Scenario 2. This is because Scenario 2 has a larger amount of hydrogen load shedding and a higher load shedding cost. The transportation cost and the number of trailers required for Scenario 3 are much greater than those for Scenario 1, which shows that trailers are not suitable for scenarios with large-scale hydrogen transportation and long transportation distances. Comparing Scenario 1 and Scenario 4, Scenario 1 has significantly lower transportation costs, and its total cost is 5.95% lower than that of Scenario 4, which illustrates the importance of using the hydrogen blending ratio as a variable for optimized scheduling.

[0301] Table 1 Comparison of hydrogen load removal percentage and total cost in four scenarios

[0302]

[0303]

[0304] 2: Model error analysis:

[0305] In order to analyze the linearization error of the linear quasi-dynamic model proposed in the present invention, with the goal of minimizing the sum of the hydrogen purchase cost and the hydrogen abandonment load penalty cost, the gurobi solver was used on the MATLAB platform to solve the linear model proposed in Section 2.2 of the present invention (Model 1), in which the improved McCormick technique and the number of segments of the piecewise linearization were both set to 10; the IPOPT solver was used to solve the proposed nonlinear programming model (Model 2). The IPOPT solver uses the interior point method. The interior point method is a type of optimization method that searches for the optimal solution by step-by-step iteration within the feasible domain, which is different from traditional methods such as the simplex method (usually starting from the boundary of the feasible domain). The interior point method introduces a "barrier function" or "penalty function" to gradually approach the boundary constraints during the iteration process, and finally converges to the optimal solution.

[0306] The solution time of model 1 is 0.23s, and the solution time of model 2 is 18.52s. The hydrogen mixing ratio and error of model 1 and model 2 are as follows: Figure 5 As shown, the left vertical axis represents the pipeline hydrogen blending ratio, and the right vertical axis represents the error percentage. The hydrogen blending ratios of the two models are very close, and the error is almost 0 at some moments. The maximum error is obtained at 23:00, which is about 0.95%.

[0307] Figure 6 It represents the influence of the number of segments of the McCormick technique and the piecewise linearization method on the solution accuracy and solution time. The value of S has a greater influence on the model solution accuracy and solution time, while the value of Np has a smaller influence on the model solution accuracy and solution time. When S and Np continue to increase from 10, the solution accuracy is not significantly lower, but the solution time increases exponentially. Therefore, S = 10 and Np = 10 are better values ​​for the number of segments.

[0308] In summary, the model of the present invention has a smaller error than the nonlinear model, and the solution time is only 1 / 80 of the latter, which greatly improves the solution efficiency. In particular, when solving large-scale examples, nonlinear models often cannot be solved.

Claims

1. A dispatching method for an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation, characterized by: The following steps are involved: Step 1: Based on the steady-state model of the natural gas pipeline, taking into account hydrogen injection and pipeline storage, a natural gas hydrogen blending transportation model with variable hydrogen blending ratio based on flow balance is established; Step 2: Linearize the natural gas hydrogen transportation model with variable hydrogen blending ratio in step 1 based on piecewise linearization, piecewise McCormick technique and equivalent substitution method to establish a linear model for natural gas hydrogen transportation with variable hydrogen blending ratio; Step 3: Establish a hydrogen transportation model for a tube trailer by simulating the spatiotemporal dynamics of the tube trailer; Step 4: Considering the constraints related to the power system and the coupling constraints between the natural gas system and the road system, as well as between the power system and the natural gas system, and combining the linear model of natural gas hydrogen transportation with variable hydrogen blending ratio in step 2 and the long tube trailer hydrogen transportation model in step 3, a dispatch model for an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation is established; Step 5: Based on the dispatch model of the electric-hydrogen integrated energy system in step 4, considering the uncertainty of wind power, a distributed robust dispatch model of the electric-hydrogen integrated energy system is established. The opportunity constraints in the distributed robust dispatch model are re-expressed as linear constraints, and the converted linear dispatch model of the electric-hydrogen integrated energy system is solved; In step 1, the natural gas hydrogen blending transportation model with variable hydrogen blending ratio based on flow balance is established as follows: (1)； In formula (1): It is a collection of natural gas source points; is a collection of hydrogen source points; Inflow node A collection of pipelines; Outflow node A collection of pipelines; 、 They are Time Node Volume flow rates of natural gas and hydrogen injected at 、 They are Flowing out of the pipe and into the node at all times Volume flow rate of the mixed gas; for Time Node Outflowing mixed gas volume flow rate; (2)； In formula (2): 、 They are Flowing out of the pipe and into the node at all times Volume flow rate of hydrogen; for Time Node Outflowing mixed gas volume flow rate; (3)； In formula (3): for Time Node The volume ratio of hydrogen in the mixed gas; (4)； In formula (4): for Time Node Natural gas load at (5)； In formula (5): for Time Pipeline The volume ratio of hydrogen in the mixed gas; (6)； (7)； (8)； In formula (8): for Time Pipeline The average volume flow rate; and They are Time Node and pressure; For pipelines Weymouth coefficient; (9) (10)； In formula (10): and For pipelines Upper and lower limits for hourly volume flow rate; (11)； In formula (11): is the maximum pressure ratio at both ends of the pipeline; and They are Time Node and pressure; (12)； In formula (12): Minimum allowable pressure at pipeline nodes; The maximum allowable pressure at the pipeline node; (13)； In formula (13): and for and Time Pipeline of pipe inventory; (14)； In formula (14): For pipelines The pipe storage coefficient; (15)； In formula (15): is the collection of all natural gas pipelines; Indicates the minimum value of the sum of all pipeline inventories; (16)； In formula (16): and For nodes The maximum and minimum volume flow rates of natural gas that can be injected; for Time Node The volume flow rate of natural gas injected at (17)； In formula (17): and For nodes The maximum and minimum volume flow rates of natural gas that can be injected; for Time Node The volume flow rate of hydrogen injected at 、 Pipeline The Weymouth coefficient and pipe storage coefficient are expressed as follows: (18)； (19)； In formula (18) and formula (19), 、 、 Pipeline diameter, length and coefficient of friction; is pi; and are the specific gas constant and density of the mixed gas respectively; For pipelines Taking into account the compressibility factor and mixed gas density when hydrogen is injected; and are the specific gas constant and density of natural gas, respectively; For pipelines The compression factor during hydrogen injection is not taken into account; is the ambient temperature; The expression of the mixed gas compressibility factor is: (20)； In formula (20): Indicates the mixed gas compressibility factor; Indicates absolute temperature; Represents the average value of the upper and lower limits of pressure at each node; Representation node The average value of the upper and lower pressure limits; represents absolute pressure; (21)； In formula (21): For pipelines diameter; express 1 / 6 power; Specific gas constant of mixed gas It is related to the hydrogen doping ratio and the molar coefficient of each gas component, and its expression is shown in formula (22): (22)； In formula (22), is the universal gas constant, For pipelines The molar coefficient of the mixed gas; 、 are the molar coefficients of natural gas and hydrogen, respectively; Density of mixed gas It is a function of hydrogen doping ratio, and its expression is: (23)； In formula (23), 、 are the standard densities of natural gas and hydrogen respectively; (24) ； The natural gas steady-state model includes the natural gas flow balance of equation (24), as well as equations (8), (10), (11), and (12); In step 2, the nonlinear terms of the variable hydrogen blending ratio natural gas hydrogen blending transportation model are formula (3), formula (4), formula (5), formula (8), and formula (17). Among them, formula (3), formula (4), and formula (5) all contain bilinear terms, which can be directly linearized using the segmented McCormick technique. Based on formula (3), the node outflow volume flow rate is selected As the variable to be divided, it can be converted into: (25)； In formula (25): is the number of segments; and are the minimum and maximum values ​​of hydrogen doping ratio respectively; and Node The minimum and maximum volume flow rates of the outflowing mixed gas; and Node The volume flow rate of the mixed gas outflow Segment minimum and maximum values; For nodes The volume flow rate of the mixed gas outflow The value of the segment; for Time Node Hydrogen doping ratio The value of the segment; is the auxiliary 0-1 variable introduced; for Time Node Outflowing mixed gas volume flow rate; In step 3, the established long-tube trailer hydrogen transportation model includes trailer operation constraints and hydrogen interaction constraints between the trailer and each hydrogen energy user; The trailer operation constraint expression is: (34)； In formula (34), Represents a set of traffic network nodes; Represents a set of traffic network paths; express Time trailer The parking status, hour, Time trailer Located at a transportation network node superior; express Time trailer driving status, hour, Time trailer Located on the traffic network path superior; (35)； In formula (35), for Time trailer Arrival Node state variables; for Time trailer Leave the node state variables; express Time trailer Parking status; (36)； (37)； (38)； In the above formula, for Time trailer Arrival Node state variables; is the auxiliary 0-1 variable introduced; (39)； In formula (39), for Time trailer Arrival Node state variables; is the auxiliary 0-1 variable introduced; (40)； In formula (40), express Time trailer Driving status; express Time trailer Driving status; (41)； In formula (41), we define is the rounding symbol, Passage path for trailers Minimum time required; is the average speed of the trailer; Representation node With node Length of road between The hydrogen interaction constraints between the trailer and each hydrogen energy user are: (42)； (43)； (44)； Where, and They are and Time trailer The quality of hydrogen transported; For trailers The maximum mass of hydrogen that can be transported; for Time trailer At the node The quality of hydrogen loaded from hydrogen users; Towing in one hour Slave nodes The maximum mass of hydrogen loaded in hydrogen energy users; In step 4, the power system-related constraints include power balance constraints, unit start-stop constraints, and active power upper and lower limit constraints. Reserve capacity constraints, ramp constraints, and line transmission capacity constraints can be provided. The expressions are as follows: (45)； In formula (45), 、 、 、 They are respectively a collection of conventional units, wind farms, power loads, and electrolyzers; for Time period unit The predicted power generation capacity; Forecast output for wind farms; is the power load; Input power to the electrolyzer; Indicates a period of time; Indicates time period A collection of (46)； In formula (46), 、 They are Time period unit Start and stop state variables; for Time period unit Running state variables; (47)； In formula (47), The minimum start and stop time for conventional units; (48)； In formula (48), is the minimum shutdown time of conventional units; (49)； (50)； (51)； (52)； (53)； In the above formula, and They are and Time period unit The predicted power generation capacity; and They are and Time period unit The downward reserve capacity provided; and They are and Time period unit Upward reserve capacity provided; for Wind farm during the period The predicted power generation capacity; for wind farm Active load; for Time-slot electrolyzer Input power; 、 are the minimum and maximum output of conventional units respectively; 、 They are the maximum upward and downward reserve capacities that conventional units can provide, respectively; 、 They are the maximum upward and downward climbing powers of conventional units respectively; For the line The maximum transmission capacity of the matrix is the transfer power matrix between line power flow and node power injection; matrix 、 、 、 They are bus-generator, bus-wind farm, bus load correlation matrix, and bus-electrolyzer correlation matrix respectively; The power system and the natural gas system are coupled through the electrolyzer and hydrogen storage tank in the hydrogen production plant, with the following constraints: (54)； (55)； (56)； In the above formula: is the electricity-to-hydrogen conversion efficiency of the electrolyzer; is the lower calorific value of hydrogen; and They are and The hydrogen storage capacity of the gas storage tank during the period; and are the minimum and maximum hydrogen storage capacity of the gas tank respectively; for Time-slot electrolyzer Output hydrogen volume; for Time Node The volume flow rate of hydrogen injected at The coupling between the natural gas system and the road system is achieved through the hydrogen balance, which is expressed as: (57)； Where, is the hydrogen load; is the hydrogen load removal amount; for the collection of trailers; express Period long tube trailer At the natural gas system node The amount of hydrogen interacting with hydrogen energy users; express Time period node The hydrogen load; In step 5, first, define the actual distribution of wind power output and experience distribution The Wasserstein distance between: (62)； Where, Represents the true distribution and experience distribution Wasserstein distance between them; is a random variable The support set of express and The first-order norm between ; express and The joint distribution of is the infimum function; Then construct the fuzzy set based on Wasserstein distance : (63)； Where: represents the true distribution in the support set The set of all values; is the radius of the Wasserstein sphere; Then, the conventional unit dispatch capacity cost and related constraints are added to the objective function (54): (64)； In formula (64): express Fuzzy set of wind power error distribution in different time periods; Cost coefficient for adjusting active power output for conventional units; Active power output adjusted for conventional units; express expected value; (65)； In formula (65): express The probability of this event; is the allowed constraint violation probability; (66)； (67)； (68) Where: It is the actual active power output of conventional units; The actual output of the wind farm; Finally, the nonlinear terms in the objective function (64) and the chance constraints (65) to (68) in the constraints are transformed; In the opportunity constraint of formula (65): First, yes Make the following equivalent substitutions: (69)； (70)； (71)； Where, express Shike Wind Farm The prediction error of represents the total error of wind power prediction; is a unit column vector; the superscript Represents the transpose of a matrix; Indicates the error ratio of each unit adjustment; The objective function in the distributed robust scheduling model of the electric-hydrogen integrated energy system can be re-expressed as: (72)； In formula (72), express Fuzzy set of wind power error distribution in different time periods; express expected value; make , in the fuzzy set Next, you can is equivalent to: (73)； (74)； In the above formula, is the number of sample sets; Indicates the samples; 、 、 、 、 、 、 、 It is an auxiliary variable introduced and has no practical significance; and are the known matrices and vectors related to setting boundary conditions; is the radius of the Wasserstein sphere; , is an intermediate auxiliary matrix; is the auxiliary matrix The transpose of Represents a collection of samples; express is a real number; Represents a positive, length A real vector of ; express The first period samples; Represents a constant matrix The transpose of .

2. The method for dispatching an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation according to claim 1 is characterized in that: Equation (8) and Equation (17) contain highly nonlinear terms. They are first replaced by equivalent terms, and then linearly transformed using the piecewise linearization method and the piecewise McCormick technique. Based on Equation (8), they are first replaced by equivalent terms: (26)； (27)； (28)； (29)； (30)； (31)； Where, 、 、 、 、 They are all introduced intermediate auxiliary variables; Among them, equations (27) and (28) can be linearized using the piecewise McCormick technique. Equations (29), (30), and (31) are monotonically increasing functions and can be linearized using the piecewise linearization method. Equation (29) can be converted to: (32)； In formula (32), is the total number of segments; For pipelines The volume flow rate of Slope of the segments; For pipelines exist Time period Actual volume flow rate of the segment; pipeline Minimum volume flow rate; For pipelines In the Maximum volume flow rate of the segment; pipeline Weymouth coefficient can be restated as: (33)； In formula (33), 、 、 is the introduced intermediate auxiliary variable; is a constant, and It's all about A positive increasing function of 、 are the standard densities of natural gas and hydrogen respectively; is a positive increasing function and can be linearized using piecewise linearization methods.

3. The method for dispatching an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation according to claim 1 is characterized in that: The dispatch model of the electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation aims to minimize the total operating cost, specifically including: power system operating cost , the cost of transporting hydrogen by trailer , whose expression is: (58)； Where, represents the total operating cost of EHIES; 、 and They are the power system operation cost, the hydrogen transportation cost by tube trailer and the hydrogen load removal cost; (59)； (60)； (61)； In the above formula, 、 、 、 Respectively for units Unit power generation cost, startup cost coefficient, shutdown cost coefficient, and no-load cost coefficient; 、 For the crew The upper and lower reserve capacity cost coefficients; is the fixed cost of HT per hour; is the driving cost per kilometer of HT; is the hydrogen load set; Indicates time period A collection of Represents a set of traffic network paths; Representation node Cost coefficient for hydrogen load removal; Representation node Hydrogen load removal amount.

4. The method for dispatching an electric-hydrogen integrated energy system based on pipeline-road coordinated hydrogen transportation according to claim 1 is characterized in that: All nonlinear terms in the distributed robust model for the electric-hydrogen integrated energy system dispatch are linearized. The converted mixed integer programming model can be solved directly on the MATLAB platform using the CPLEX commercial solver. The solution includes the following steps: Step 1: Program the input parameters of the mixed integer programming model on the MATLAB platform; Step 2: Define the decision variables of the mixed integer programming model on the MATLAB platform; Step 3: Program the objective function of the mixed integer programming model on the MATLAB platform; Step 4: Program the constraints of the mixed integer programming model on the MATLAB platform; Step 5: Call the CPLEX solver on the MATLAB platform to solve the mixed integer programming model; Step 6: Output relevant parameters of the power system, natural gas system and road system on the MATLAB platform.

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