An operating method for an electrical combined system considering the dynamic characteristics of hydrogen-doped gas components.

Abstract

The present invention relates to the field of electric joint system operation technology, and in particular to an electric joint system operation method considering the dynamic characteristics of hydrogen-doped gas components, the method comprising the following steps: defining the safe operation range of the electric-natural gas joint system after hydrogen is added; based on the safe operation range, designing an operation framework, controlling the injection and distribution of hydrogen in time periods through the operation framework, and establishing constraints for the operation framework; under the constraints, converting the non-convex problem of the operation framework into a second-order cone programming tractable problem, solving the second-order cone programming tractable problem, and obtaining an optimal electric joint system operation plan; using the optimal electric joint system operation plan, completing low-carbon and safe scheduling of the electric joint system. The present invention can achieve low-carbon scheduling of the electric joint system and ensure its safety during continuous operation.

Description

Technical Field

[0001] The present invention relates to the technical field of electric combined system operation, and in particular to an electric combined system operation method taking into account the dynamic characteristics of hydrogen-doped gas components. Background Art

[0002] Substitute gases, especially green hydrogen produced from surplus renewable energy through power-to-gas (PTG) facilities, provide new opportunities for the development of low-carbon energy systems. This technology not only broadens the transportation and utilization of green hydrogen by mixing it with natural gas, but also meets diversified energy needs. However, random renewable energy generation introduces substitute gas injection, resulting in fluctuations in gas composition in the natural gas network, which poses a huge challenge to the safe operation of the integrated electricity-gas system (IEGS).

[0003] High hydrogen concentration changes the gross calorific value of the gas mixture, affecting the heat energy produced by combustion and potentially shortening the service life of gas equipment. In addition, different hydrogen concentrations affect the physical properties of the gas mixture, such as relative density, leading to changes in gas flow and potential pipeline inventory fluctuations, increasing the complexity of natural gas system operation. Therefore, ensuring that the gas composition remains within a safe range is critical to safely operating IEGS under uncertain and dispersed hydrogen injection.

[0004] To date, most research efforts have been devoted to tracking gas concentrations in natural gas systems with alternative gas injection. However, these studies generally lack proactive measures to maintain system safety in the face of safety violations. Recently, some optimization-oriented studies have emerged to address this gap by studying optimal operating strategies for IEGS with varying gas composition. These studies with proactive decision-making can help system operators improve cost-effectiveness and safety under alternative gas injection.

[0005] However, a common shortcoming of the above studies is that their optimization models are based on steady-state and ignore the inherent dynamic characteristics of the natural gas system. The intermittency of renewable power generation introduces fluctuations in hydrogen injection and gas composition during operation. Since the dynamic characteristics of natural gas are much slower than those of the power system, it would be inaccurate to ignore the dynamic characteristics of natural gas if the optimization model is applied to the operating period. In this hydrogen-blended natural gas system, two types of natural gas dynamic characteristics are involved. The first is the dynamic characteristics of natural gas flow, which can be used as a flexible resource in IEGS operation and scheduling scenarios. The second type, the dynamic characteristics of gas composition, is a unique feature of natural gas systems with changing gas composition. It describes how a certain gas propagates in the natural gas network. For example, if hydrogen is injected at the pipeline inlet, it will take some time to be gradually transported to the outlet, during which time the gas concentration at the outlet remains unchanged.

[0006] Understanding these two dynamics is crucial for the optimal operation of IEGS in scenarios involving alternative gas injection. The temporal and spatial evolution of the gas composition must be considered to accurately capture the response of the system to changes introduced at various points in the network. The gas composition dynamics can be mathematically modeled by a set of nonlinear partial differential equations (PDEs). Incorporating these terms makes the optimization model non-convex and time-dependent. This not only greatly increases the computational burden but also makes the problem intractable. In addition, the propagation of gas composition also introduces inconsistencies in the relative density, calorific value, etc. of the gas mixture, as well as a high degree of non-convexity to the gas flow equations. Due to the above reasons, although the propagation of gas composition has been studied in traditional gas network simulation studies, it has not been incorporated into the optimization operation of IEGS. There is currently almost no feasible and efficient solution method to deal with optimization problems with dynamic gas composition. Summary of the invention

[0007] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the multi-period dynamic optimization energy flow calculation of the power and natural gas combined system is complex, resulting in low operating efficiency, under the condition of considering hydrogen gas injection.

[0008] In order to solve the above technical problems, the present invention provides an electric combined system operation method considering the dynamic characteristics of hydrogen-doped gas components, the method comprising the following steps:

[0009] S1: Define the safe operating range of the combined power-gas system after hydrogen is added;

[0010] S2: Based on the safe operating range, design an operating framework, control the injection and distribution of hydrogen in different time periods through the operating framework, and establish constraint conditions of the operating framework;

[0011] S3: Under the constraints, convert the non-convex problem of the operation framework into a problem that can be processed by second-order cone programming, solve the problem that can be processed by second-order cone programming, and obtain an optimal electrical joint system operation plan;

[0012] S4: Using the optimal electric power system operation plan, complete the low-carbon and safe dispatch of the electric power system.

[0013] In one embodiment of the present invention, the expression of the safe operating range is:

[0014]

[0015] Among them, H is the gas safety region under normal conditions, WI i，k represents the Wobbe index of node i at time k, ICF i，k represents the incomplete combustion factor of node i at time k, SIi，k represents the smoke index of node i at time k, FS i，k represents the flame speed of node i at time k, HV i，k represents the heat value of node i at time k; S i，k Indicates the relative density of the gas mixture; φ i，k is the set of gas components at node i at time k; and are the concentrations of hydrogen, propane and nitrogen respectively; WI min is the minimum value of the Wobbe index; ICF max 、SI max and FS max They are the maximum values ​​of incomplete combustion factor, smoke index and flame speed respectively; and are the collections of nodes and time respectively;

[0016] Among them, the Wobbe index WI of the node i at time k is i，k The calculation method is:

[0017]

[0018] Among them, S ng is the relative density of natural gas;

[0019] The incomplete combustion factor ICF of the node i at time k i，k The calculation method is:

[0020]

[0021] The smoke index SI of node i at time k i，k The calculation method is:

[0022]

[0023] The flame speed FS of the node i at time k i，k The calculation method is:

[0024]

[0025] Among them, fs n is the flame speed of gas component n in the fuel-air mixture, is the collection of gas components; φ i，k，n is the concentration of gas component n in the fuel-air mixture.

[0026] In one embodiment of the present invention, the heat value HV of the node i at time k is i，k The calculation method is:

[0027]

[0028] The relative density S of the gas mixture i，k The calculation method is:

[0029]

[0030] Among them, HV n is the calorific value of gas component n, M n and M air are the relative molecular masses of gas component n and air respectively.

[0031] The constraints of the operation framework include constraints of the natural gas system, constraints of the coupling elements and constraints of the power system;

[0032] The method for constructing the constraint conditions of the natural gas system includes:

[0033] In natural gas pipelines, the dynamic characteristics of gas components and natural gas flow are mathematically modeled through nonlinear partial differential equations to obtain a natural gas system model;

[0034] Discretizing the natural gas system model in terms of time t and length x to obtain a multi-period natural gas system model;

[0035] Since the gas composition changes and the gas thermal energy demand remains consistent, the gas composition of a specific node matches the gas composition of the gas demand of the node, and a model of natural gas load and natural gas source is constructed:

[0036]

[0037]

[0038] Among them, HV ng is the calorific value of natural gas; is the original natural gas demand flow at time k; is the required flow rate of gas component n at node i at time k;

[0039] Considering the different gas components of the gas source, it can be modeled as:

[0040]

[0041]

[0042] in, is the supply of component n of gas source l at node i at time k; is the concentration of component n in gas source l at node i; is the concentration of component n in gas source l at node i at time k; is the supply of gas source l at node i at time k; and are the maximum and minimum values ​​of gas supply respectively;

[0043] In the natural gas network, the gas from the upstream elements of the node is uniformly mixed at the natural gas node i according to the mixing ratio, and the uniformly mixed gas is delivered to the downstream elements. The upstream elements of the node include the upstream pipeline, the natural gas source and the power-to-gas facility, and the downstream elements include the downstream pipeline, the natural gas load and the gas generator set;

[0044] The calculation method of the mixing ratio is:

[0045]

[0046]

[0047] Among them, φ i,k,n is the concentration of gas component n in the fuel-air mixture, that is, the mixing ratio of each gas component n; represents the total gas injection amount of each gas component n at the natural gas node i, Q ij,1,k,n is the injection amount of gas component n in the first segment of pipeline ij at time k, Q ij,S,k,n is the injection amount of gas component n at the Sth segment of pipeline ij at time k, γ ji Indicates the direction of natural gas flow, is the set of power-to-gas facilities at node i, is the gas production of gas component n at power-to-gas facility l at natural gas node i at time k; represents the total gas injection amount of all gas components at natural gas node i, is the collection of gas components; is the set of natural gas sources at node i.

[0048] In one embodiment of the present invention, the multi-period natural gas system model includes continuity differential equations, motion equations, and convection transport equations;

[0049] Wherein, the expression of the continuity differential equation is:

[0050]

[0051] Among them, A ij is the cross-sectional area of ​​the pipe ij; represents the time difference of the gas density of the segment s in the pipeline ij at time k; represents the spatial difference of the gas flow rate of the segment s in the pipeline ij at time k; ρ0 is the density of pure natural gas under standard temperature and pressure conditions; Δt and Δx are the time and space resolutions respectively;

[0052] The expression of the motion equation is:

[0053]

[0054] in, represents the spatial difference of the gas pressure of the segment s in the pipeline ij at time k; represents the time difference of the gas flow rate of the segment s in the pipeline ij at time k; represents the average gas flow rate of segment s in pipeline ij at time k; represents the average value of the gas density of the segment s in the pipeline ij at time k;

[0055] The expression of the convective transport equation is:

[0056]

[0057] Among them, p ij , Q ij and ρ ij are respectively the air pressure, flow velocity and density in the pipe ij; φ ij,n is the proportion of gas component n in pipeline ij; f ij and D ij are the Fanning friction coefficient and diameter of the pipe ij, respectively; is a collection of pipeline fragments; is the direction of the natural gas flow at t = 0; sgn(·) is the sign function; represents the difference in the proportion of gas component n in segment s in pipeline ij at time k with respect to time; represents the spatial difference of the proportion of gas component n in segment s in pipeline ij at time k;

[0058] In the multi-period natural gas system model, the gas density ρ ij，s，k and pressure p ij，s，k Should be followed:

[0059] p ij，s，k =z ij，s，k r ij，s，k T0ρ ij，s，k

[0060] Among them, z ij，s，k and r ij，s，kdenote the compressibility factor and gas constant of the pipe segment ij at time k, respectively. R n is the gas constant of gas component n; T0 is the temperature of the gas mixture.

[0061] In one embodiment of the present invention, the method for constructing the multi-period natural gas system model further includes setting initial conditions, boundary conditions and terminal conditions; wherein the initial conditions are:

[0062]

[0063] Among them, p ij，s，1 is the initial gas pressure in the pipe segment ij, Q ij，s，1 represents the initial gas injection amount in the pipe ij segment s, φ ij，s，1，n represents the initial proportion of gas component n in the pipe ij segment s; and are the initial setting values ​​of the gas pressure, gas flow and proportion of gas component n on the segment s of the pipeline ij, respectively;

[0064] The boundary conditions of a natural gas pipeline are determined by the pipelines and other components it connects to, including:

[0065] Conditions for maintaining consistent air pressure at pipeline connection points:

[0066]

[0067]

[0068] Conditions for maintaining nodal conservation for each gas component:

[0069]

[0070] in, represents the supply flow of gas component n from the natural gas source at node i at time k;

[0071] The conditions to ensure that the gas composition of the pipeline at the connection point should be the same are:

[0072]

[0073]

[0074] Among them, p ij，1，k and p ij，S，k Respectively represent the air pressure of the first and Sth sections of the pipeline ij at time k; p ij′，1，k represents the air pressure of the first section of pipeline ij′ connected to node i of pipeline ij; pi′j，S，k represents the air pressure of the Sth section of pipeline i′j connected to the node j of pipeline ij; p i，k is the node pressure of node i at time k; p j，k is the node pressure of node j at time k; and are the sets of nodes connected to node i and node j respectively; is the demand for gas component n at node i; and are the sets of all gas-fired power generating units and power-to-gas facilities at node i; is the gas consumption of the gas generator set at node i at time k; is the gas production of the power-to-gas facility at node i at time k; Q ij，1,k，n represents the injection amount of gas component n in the first section of pipeline ij at time k; φ ij，1，k，n and φ ij，S，k，n are the proportions of gas component n in the 1st and Sth sections of pipeline ij at time k; φ i，k，n is the proportion of gas component n at node i at time k; φ j，k，n is the proportion of gas component n at node j at time k;

[0075] The terminal condition is set using the tube storage energy:

[0076]

[0077] ζ ij，K ≥(1-β lp ) ij，0

[0078] Among them, ij，k is the tube storage energy at time k; β lp is the threshold coefficient used to maintain the storage energy level; K is the total number of time periods, ζ ij，0 Represents the initial tube storage energy.

[0079] In one embodiment of the present invention, the constraints of the coupling element include constraints of the power-to-gas facility and constraints of the gas generator set; wherein the constraints of the power-to-gas facility are:

[0080]

[0081]

[0082]

[0083] in, is the power-to-gas facility, electricity consumption; and are the efficiencies of the electrolysis and methanogenesis processes, respectively; HV hy and HV me are the calorific values ​​of hydrogen and methane, respectively; and is the hydrogen and methane production of the power-to-gas facility at node i at time k; Indicates the maximum power consumption of the power-to-gas facility;

[0084] The constraints of the gas generator set are:

[0085]

[0086]

[0087] in, and They are the power generation and efficiency of gas generator sets; is the amount of gas component n consumed by the gas-fired generator set.

[0088] In one embodiment of the present invention, the constraints of the power system are:

[0089]

[0090] g ij，k =(θ i，k -θ j，k ) / X ij

[0091]

[0092]

[0093]

[0094]

[0095] in, represents the renewable generator set at node i, is its power generation capacity; is the power demand of node i at time k; g ij，k is the power flow on branch ij at time k; θ i，k is the phase angle of the voltage at node i; θ j，k is the phase angle of the voltage at node j; X ij is the reactance; is the transmission capacity; is the transmission capacity of the traditional generator set at node i at time k; and They are the upper and lower limits of the transmission capacity of traditional generator sets respectively; is the transmission capacity of the gas generator set at node i at time k, Know They are the upper and lower limits of the transmission capacity of the gas-fired generator set; is the transmission capacity of the renewable generator at node i at time k, and They are the upper and lower limits of the transmission capacity of renewable power generation units respectively.

[0096] In one embodiment of the present invention, the non-convex problem of the operation framework includes the non-convex problem of the motion equation and the convection transport equation, and the method for obtaining the optimal electrical joint system operation plan is:

[0097] S31: For the non-convex problem of the motion equation, set an auxiliary variable The motion equation is reconstructed by a second-order cone to obtain the first second-order cone constraint:

[0098]

[0099] And for the non-convex problem of the convection transport equation, set an auxiliary variable The convection transport equation is reconstructed by a second-order cone to obtain the second second-order cone constraint:

[0100]

[0101] S32: Add a penalty term to the objective function of the operating framework to make the second-order cone relaxation constraint tighter. By controlling the relaxation variable, the optimization problem is convexified to obtain a problem that can be handled by second-order cone programming, and its expression is:

[0102]

[0103] Among them, C T is the system operation cost, λ mo express The penalty coefficient of and are the relaxation variables of the Taylor remainders of the motion and convection transport equations, respectively; is the Taylor remainder; for The value of the vth iteration of ; for The value of the vth iteration; β se，(v) for The penalty coefficient at the vth iteration; λ at for The penalty coefficient of for The value of the vth iteration; β at，(v) for The penalty coefficient at the vth iteration; for The value of the vth iteration; β re，(v) for The penalty coefficient at the vth iteration;

[0104] S33: Iteratively calculate the second-order cone programming tractable problem to determine whether all state variables have not changed compared with the previous iteration and whether all Taylor remainders have converged to zero:

[0105] If yes, the iterative calculation is terminated and the solution is output as the final calculation result, i.e., the optimal electrical joint system operation plan;

[0106] Otherwise, the solution of the current iterative calculation is set as the reference value, the penalty coefficient is updated, and the process returns to step S32 to continue the iterative calculation;

[0107] Wherein, the method for updating the penalty coefficient is:

[0108]

[0109] in, is the multiplier of the penalty coefficient, β mo，(v) is the penalty coefficient for the vth iteration, β mo，(v+1) β mo，(v) The penalty coefficient after the next iteration.

[0110] In one embodiment of the present invention, the objective function is to minimize the system operation cost C within the safe operation range. T Constructed; wherein the system operating cost C T for:

[0111]

[0112] in, and are the sets of gas nodes and times respectively; and are the sets of traditional generators and natural gas sources at node i respectively; is the power generation of the traditional generator set at node i at time k; is the gas production of the gas source at node i at time k; cst i，l is the cost of the traditional generator set at node i; is the unit gas price.

[0113] The above technical solution of the present invention has the following advantages compared with the prior art:

[0114] (1) A multi-period optimized energy flow (MPOEF) model of hydrogen-doped IEGS considering the dynamic characteristics of gas components is proposed. Compared with the previous steady-state gas component tracking model: 1) This model accurately describes the real-time propagation of alternative gas concentrations in the natural gas network, while simulating the dynamic characteristics of natural gas flow and gas components. 2) Auxiliary variables are introduced to represent the dynamic characteristics of the physical properties of the gas mixture, fully revealing and controlling the impact of hydrogen doping behavior at the node scale. 3) The concept of pipeline storage energy is introduced to set terminal conditions, which enhances the flexibility of the natural gas system when hydrogen injection fluctuates, while maintaining robustness at the end of operation.

[0115] (2) A solution method for the highly non-convex MPOEF problem is proposed. A second-order cone (SOC) reconstruction is performed for the discretized motion and convection transport partial differential equations (PDEs) to convexify these constraints so as to fully exploit the second-order information of these constraints to improve computational efficiency. The advanced sequential SOC solution method and adaptive penalty factor also ensure convergence and optimality.

[0116] (3) A convex gas safety range is proposed based on multiple gas safety indicators such as the Wobbe index (WI). Compared with the traditional Dutton method, it can not only ensure the convexity of the MPOEF problem by linearizing the safety constraints, but also better control the combustion safety of IEGS in hydrogen mixing scenarios by introducing a new flame speed (FS) index. BRIEF DESCRIPTION OF THE DRAWINGS

[0117] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein

[0118] Figure 1 It is a basic structural diagram of the power and natural gas combined system under hydrogen mixing conditions;

[0119] Figure 2 It is a flow chart of an implementation method of an electrical combined system operation method considering the dynamic characteristics of hydrogen-doped gas components provided by an embodiment of the present invention;

[0120] Figure 3 It is the gas composition safety zone based on Dutton's method;

[0121] Figure 4 This is a structural diagram of the power-gas combined system consisting of the IEEE 24-node power system and the Belgian natural gas system;

[0122] Figure 5 is the relative error value at different natural gas nodes using the method of the present invention;

[0123] Figure 6 It is the comparison of the results of selecting different time and space steps using discretized partial differential equations (PDEs) in four scenarios S1 to S4;

[0124] Figure 7 It is the result of the propagation of hydrogen concentration at nodes of different levels;

[0125] Figure 8 is the gas production of the power-to-gas facility (PTG) in scenario S1;

[0126] Fig. 9 is the gas production of the power-to-gas facility (PTG) in scenario S2;

[0127] Fig.10 is the gas production of the power-to-gas facility (PTG) in scenario S3;

[0128] Fig.11 is the hydrogen concentration of natural gas nodes #1 to #4 and #14 to #16;

[0129] Fig.12 is the hydrogen concentration of natural gas nodes #8 to #14;

[0130] Fig.13 is the Wobbe Index (WI) on gas nodes #4 and #11;

[0131] Fig.14 is the flame speed (FS) on gas nodes #4 to 11;

[0132] Fig.15 is the storage capacity of natural gas pipeline #4-14;

[0133] Fig.16 It is the total storage energy of the entire natural gas system. DETAILED DESCRIPTION

[0134] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0135] The structure of the power-gas combined system considering hydrogen blending is as follows: Figure 1 As shown in Figure 1, the system mainly consists of two layers: the power system and the natural gas system. The power system includes traditional generators (generating electricity using fuels other than natural gas), renewable energy generators, and gas generators (GPP) to generate electricity. The natural gas system relies on natural gas and hydrogen and methane from power-to-gas (PTG) facilities. These gases of different components will be mixed in the pipeline and then transported to the downstream natural gas load.

[0136] Reference Figure 2 As shown, the present invention provides an electric combined system operation method considering the dynamic characteristics of hydrogen-doped gas components, the method comprising the following steps:

[0137] S1: Define the safe operating range of the power-gas combined system after hydrogen is added through the Dutton method;

[0138] S2: Based on the safe operating range, design an operating framework, control the injection and distribution of hydrogen in different time periods through the operating framework, and establish constraint conditions of the operating framework;

[0139] S3: Under the constraints, convert the non-convex problem of the operation framework into a problem that can be processed by second-order cone programming, solve the problem that can be processed by second-order cone programming, and obtain an optimal electrical joint system operation plan;

[0140] S4: Using the optimal electric power system operation plan, complete the low-carbon and safe dispatch of the electric power system.

[0141] In S1, gas safety requirements must be followed to ensure the safety of natural gas system components. The gas composition in the network may vary due to different gas sources and power-to-gas (PTG) facilities. The Dutton method is used to define a convex gas safety range, such as Figure 3 As shown in Figure 1, gas safety is limited by indicators including the incomplete combustion factor (ICF) and the smoke index (SI). In order to characterize the effect of the higher flame speed of hydrogen on the gas, the flame speed (FS) is introduced into Dutton. However, when the Dutton method is projected onto the plane formed by different gas components, it exhibits a non-convex characteristic, that is, there is at least one pair of points whose connecting line passes through the outside of the projected figure, which may make the subsequent optimization problem difficult to handle, such as Figure 3 shown.

[0142] In order to solve this problem, a convex gas safety range is formulated by linearizing the gas safety index, that is, the expression of the safe operating range is:

[0143]

[0144] Among them, H is the gas safety region under normal conditions, WI i，k represents the Wobbe index of node i at time k, ICF i，k represents the incomplete combustion factor of node i at time k, SI i，k represents the smoke index of node i at time k, FS i，k represents the flame speed of node i at time k, HV i，k represents the heat value of node i at time k; S i，kIndicates the relative density of the gas mixture; φ i，k is the set of gas components at node i at time k; and are the concentrations of hydrogen, propane and nitrogen respectively; WI min is the minimum value of the Wobbe index; ICF max 、SI max and FS max They are the maximum values ​​of incomplete combustion factor, smoke index and flame speed respectively; and are the collections of nodes and time respectively;

[0145] Among them, the Wobbe index WI of the node i at time k is i,k The calculation method is:

[0146]

[0147] Among them, S ng is the relative density of natural gas;

[0148] The incomplete combustion factor ICF of the node i at time k i,k The calculation method is:

[0149]

[0150] The smoke index SI of node i at time k i,k The calculation method is:

[0151]

[0152] The flame speed FS of the node i at time k i,k The calculation method is:

[0153]

[0154] Among them, fs n is the flame speed of gas component n in the fuel-air mixture, is the collection of gas components; φ i,k,n is the concentration of gas component n in the fuel-air mixture.

[0155] The calorific value and relative density of a natural gas node depend on the gas composition of the node, so the calorific value HV of the node i at time k is i,k The calculation method is:

[0156]

[0157] Among them, HV n is the calorific value of gas component n;

[0158] The relative density S of the gas mixture i,k The calculation method is:

[0159]

[0160] Among them, M n and M air are the relative molecular masses of gas component n and air respectively; φ i,k,n is the concentration of component n.

[0161] When renewable energy generation fluctuates, the amount of hydrogen injected will also fluctuate, which may cause the gas composition to exceed the safe range. Therefore, the MPOEF model is constructed to safely adapt to alternative gas injection. The goal of MPOEF is to minimize the total cost C during the entire operation period by changing the real-time operating status of gas sources, power-to-gas facilities (PTGs), gas power plants (GPPs), traditional power plants, and renewable power plants. T Therefore, the objective function of the operation framework is to minimize the system operation cost C within the safe operation range. T Constructed; wherein the system operating cost C T for:

[0162]

[0163] in, and are the sets of gas nodes and times respectively; and are the sets of traditional generators and natural gas sources at node i respectively; is the power generation of the traditional generator set l at node i at time k; is the gas production of source l at node i at time k; cst i,l is the cost of the traditional generator l at node i; is the unit gas price.

[0164] The constraints of the operation framework include constraints of the natural gas system, constraints of the coupling elements and constraints of the power system;

[0165] The method for constructing the constraint conditions of the natural gas system includes:

[0166] In a horizontal and constant temperature natural gas pipeline, the flow of gas mixtures is controlled by three sets of partial differential equations: continuity, motion and convection transport equations. The dynamic characteristics of gas components and natural gas flow are mathematically modeled through nonlinear partial differential equations to obtain the natural gas system model:

[0167]

[0168]

[0169]

[0170] Discretizing the natural gas system model in time t and length x to obtain a multi-period natural gas system model; specifically, the multi-period natural gas system model includes a continuity differential equation, a motion equation, and a convection transport equation;

[0171] Wherein, the expression of the continuity differential equation is:

[0172]

[0173] Among them, A ij is the cross-sectional area of ​​the pipe ij; represents the time difference of the gas density of the segment s in the pipeline ij at time k; represents the spatial difference of the gas flow rate of the segment s in the pipeline ij at time k; ρ0 is the density of pure natural gas under standard temperature and pressure conditions; Δt and Δx are the time and space resolutions respectively;

[0174] The expression of the motion equation is:

[0175]

[0176] in, represents the spatial difference of the gas pressure of the segment s in the pipeline ij at time k; represents the time difference of the gas flow rate of the segment s in the pipeline ij at time k; represents the average gas flow rate of segment s in pipeline ij at time k; represents the average value of the gas density of the segment s in the pipeline ij at time k;

[0177] The expression of the convective transport equation is:

[0178]

[0179] Among them, p ij , Q ij and ρ ij are respectively the air pressure, flow velocity and density in the pipe ij; φ ij,n is the proportion of gas component n in pipeline ij; f ij and D ij are the Fanning friction coefficient and diameter of the pipe ij, respectively; is a collection of pipeline fragments; is the direction of the natural gas flow at t = 0; sgn(·) is the sign function; represents the difference in the proportion of gas component n in segment s in pipeline ij at time k with respect to time; represents the spatial difference of the proportion of gas component n in segment s in pipeline ij at time k;

[0180] In the multi-period natural gas system model, the gas density ρ ij,s,k and pressure p ij,s,k Should be followed:

[0181] p ij，s，k =z ij，s，k r ij，s，k T0ρ ij，s，k

[0182] Among them, z ij，s，k and r ij，s，k denote the compressibility factor and gas constant of the pipe segment ij at time k, respectively. R n is the gas constant of gas component n; T0 is the temperature of the gas mixture.

[0183] The initial conditions, boundary conditions and terminal conditions of the multi-period natural gas system model are set, and the initial conditions are:

[0184]

[0185] Among them, p ij，s，1 is the initial gas pressure in the pipe segment ij, Q ij，s，1 represents the initial gas injection amount in the pipe ij segment s, φ ij，s，1，n represents the initial proportion of gas component n in the pipe ij segment s; and are the initial setting values ​​of the gas pressure, gas flow and proportion of gas component n on the segment s of the pipeline ij, respectively;

[0186] The boundary conditions of a natural gas pipeline are determined by the pipelines and other components it connects to, including:

[0187] Conditions for maintaining consistent air pressure at pipeline connection points:

[0188]

[0189]

[0190] Conditions for maintaining nodal conservation for each gas component:

[0191]

[0192] The conditions to ensure that the gas composition of the pipeline at the connection point should be the same are:

[0193]

[0194]

[0195] Among them, p ij，1，k and p ij，S，k Respectively represent the air pressure of the first and Sth sections of the pipeline ij at time k; p ij′，1，k represents the air pressure of the first section of pipeline ij′ connected to node i of pipeline ij; p i′j，S，k represents the air pressure of the Sth section of pipeline i′j connected to the node j of pipeline ij; p i，k is the node pressure of node i at time k; p j，k is the node pressure of node j at time k; and are the sets of nodes connected to node i and node j respectively; is the demand for gas component n at node i; and are the sets of all gas-fired power generating units and power-to-gas facilities at node i; is the gas consumption of the gas generator set at node i at time k; is the gas production of the power-to-gas facility at node i at time k; Q ij，1,k，n represents the injection amount of gas component n in the first section of pipeline ij at time k; φ ij,1,k，n and φ ij,S，k，n are the proportions of gas component n in the first and Sth sections of pipeline ij at time k; φ i，k，n is the proportion of component n of node i at time k; φ j，k，n is the proportion of gas component n at time node k.

[0196] Since the natural gas system operates continuously, it is crucial to ensure that the terminal state of the natural gas system should not deviate too much from the initial state. Otherwise, the natural gas system will become fragile and unable to maintain its flexibility to resist future risks. In traditional natural gas systems with constant gas composition, the volume of pipeline storage is usually used as the terminal condition of the natural gas system control problem. However, when the gas composition changes, the energy contained in the same volume of gas may be different. Therefore, the volume of pipeline storage is expanded to the pipeline storage energy indicator, so that the pipeline storage energy at the end time is maintained above a certain level in the MPOEF model. Taking the pipeline storage energy as the terminal condition of the natural gas system control problem is:

[0197]

[0198] ζ ij，K ≥(1-β lp ) ij，0

[0199] Among them, ij，k is the tube storage energy at time k; β lp is the threshold coefficient used to maintain the storage energy level; K is the total number of time periods, ζ ij，0 Represents the initial tube storage energy.

[0200] Considering that natural gas demand is mainly combustion, the thermal energy demand associated with the gas demand should remain consistent despite changes in gas composition. Since changes in gas composition and gas thermal energy demand remain consistent, the gas composition of a specific node matches the gas composition of the gas demand at that node, and a model of natural gas load and natural gas source is constructed:

[0201]

[0202]

[0203] Among them, HV ng is the calorific value of natural gas; is the original natural gas demand flow at time k; is the required flow rate of gas component n at node i at time k;

[0204] Considering the different gas components of the gas source, it can be modeled as:

[0205]

[0206]

[0207] in, is the supply of component n from the gas source at node i at time k; is the concentration of component n at node i gas source; is the concentration of component n at the gas source node i at time k; is the supply of gas source at node i at time k; and are the maximum and minimum values ​​of gas supply respectively;

[0208] The composition of the mixed gases from different sources is determined by their proportion in the total gas injection at the node. This approach ensures accurate calculation of the gas composition at the node and allows consideration of varying gas compositions input into the node from different sources.

[0209] Furthermore, in the natural gas network, the gas from the upstream elements of the node is evenly mixed according to the mixing ratio at the natural gas node i, and the evenly mixed gas is delivered to the downstream elements. The upstream elements of the node include upstream pipelines, natural gas sources and power-to-gas facilities, and the downstream elements include downstream pipelines, natural gas loads and gas generators.

[0210] The calculation method of the mixing ratio is:

[0211]

[0212]

[0213] Among them, φ i，k，n is the concentration of gas component n in the fuel-air mixture, that is, the mixing ratio of each gas component n; represents the total gas injection amount of each gas component n at the natural gas node i, Q ij,1,k，n is the injection amount of gas component n in the first segment of pipeline ij at time k, Q ij，S，k，n is the injection amount of gas component n at the Sth segment of pipeline ij at time k, γ ji Indicates the direction of natural gas flow, is the set of power-to-gas facilities at node i, is the gas production of gas component n at the power-to-gas facility at natural gas node i at time k; represents the total gas injection amount of all gas components at natural gas node i, is the collection of gas components; is the set of natural gas sources at node i.

[0214] In addition to the above constraints, solving the MPOEF problem for natural gas systems also requires some other basic constraints:

[0215]

[0216]

[0217]

[0218]

[0219] in, is the transmission capacity of pipeline ij; and are respectively the upper and lower limits of the air pressure in pipeline ij.

[0220] Power-to-gas (PTG) facilities play a key role in coupled integrated electricity and gas systems (IEGS) by converting excess renewable electricity into methane / hydrogen. The constraints of the coupling element include the constraints of the power-to-gas facility and the constraints of the gas generator set; wherein the constraints of the power-to-gas facility are:

[0221]

[0222]

[0223]

[0224] in, is the power-to-gas facility, electricity consumption; and are the efficiencies of the electrolysis and methanogenesis processes, respectively; HV hy and HV me are the calorific values ​​of hydrogen and methane, respectively; and is the hydrogen and methane production of the power-to-gas facility at node i at time k; Indicates the maximum power consumption of the power-to-gas facility;

[0225] The composition of the gas mixture consumed by the gas power plant (GPP) should be consistent with the gas composition of the corresponding gas node. The constraints of the gas power plant are:

[0226]

[0227]

[0228] in, Know They are the power generation and efficiency of gas generator sets; is the amount of gas component n consumed by the gas-fired generator set.

[0229] In this embodiment, the constraints of the power system are:

[0230]

[0231] g ij，k =(θ i，k -θ j，k ) / X ij

[0232]

[0233]

[0234]

[0235]

[0236] in, represents the renewable generator set at node i, is its power generation capacity; is the power demand of node i at time k; g ij，k is the power flow on branch ij at time k; θ i，k is the phase angle of the voltage at node i; θ j，k is the phase angle of the voltage at node j; X ij is the reactance; is the transmission capacity; is the transmission capacity of the traditional generator set at node i at time k; and They are the upper and lower limits of the transmission capacity of traditional generator sets respectively; is the transmission capacity of the gas generator set at node i at time k, and They are the upper and lower limits of the transmission capacity of the gas-fired generator set; is the transmission capacity of the renewable generator at node i at time k, and They are the upper and lower limits of the transmission capacity of renewable power generation units respectively.

[0237] In this embodiment, the non-convex problem of the operation framework means that the objective function of the operation framework is not a convex function, which is usually more challenging to solve than convex optimization problems because they may have multiple local optimal solutions, and the minimum value among these local optimal solutions is not necessarily the global optimal solution. Therefore, when solving non-convex problems, it is necessary to adopt appropriate algorithms and strategies to find the global optimal solution or satisfactory local optimal solution as much as possible. Specifically, the non-convex problem of the operation framework includes the non-convex problems of the motion equation and the convection transport equation, and the method for obtaining the optimal electrical joint system operation plan is:

[0238] S31: For the non-convex problem of the motion equation, set an auxiliary variable The motion equation is reconstructed by a second-order cone to obtain the first second-order cone constraint:

[0239]

[0240] The above is when γ ij = 1, a pair of SOC constraints for the equation of motion. If γ ij =-1, similar SOC constraints can also be derived.

[0241] For the non-convex problem of the convection transport equation, an auxiliary variable is set The convection transport equation is reconstructed by a second-order cone to obtain the second second-order cone constraint:

[0242]

[0243] S32: In order to make the relaxation tighter, two methods are designed, namely the penalty term method and sequential SOC planning.

[0244] Specifically, a penalty term is added to the objective function of the operating framework to make the second-order cone relaxation constraint tighter. The penalty term is selected as where λ mo and λ at are the penalty coefficients for the motion and convective transport equations, respectively.

[0245] In sequential SOC planning, the other side of the SOC inequality is approximated by a first-order Taylor series:

[0246]

[0247]

[0248] Among them, the symbol (·) * represents the reference value of the corresponding variable, which will be determined in each iteration of sequence planning, and are the relaxation variables of the Taylor remainder of the motion and convection transport equations, respectively. The bilinear term (gas pressure p ij,s，k ) is now approximated as:

[0249]

[0250] in, is the Taylor remainder, which can also be incorporated into the framework of sequence programming. Other bilinear constraints can be handled similarly.

[0251] By controlling the slack variables through sequential SOC planning and making the optimization problem convex, we can obtain a problem that can be handled by second-order cone programming, which is expressed as:

[0252]

[0253] Among them, C T is the system operation cost, λ mo express The penalty coefficient of and are the relaxation variables of the Taylor remainders of the motion and convection transport equations, respectively; is the Taylor remainder; for The value of the vth iteration of ; for The value of the vth iteration; β se,(v) for The penalty coefficient at the vth iteration; λ at for The penalty coefficient of for The value of the vth iteration; β at,(v) for The penalty coefficient at the vth iteration; for The value of the vth iteration; β re,(v) for The penalty coefficient at the vth iteration;

[0254] S33: Make the second-order cone programming tractable Iterate the problem while initially allowing some constraint violations, set the IEGS parameters and collect wind speed data. Initialize the length and time resolution of the partial differential equations. Initialize the penalty term β mo,(0) , β at,(0) , β at,(0) , β es,(0) and β re,(0) , and their upper limits β mo,max , β at,max , β es,max , β re,max , set the residual tolerance ∈ for sequence planning.

[0255] For each time point k, solve the problem of steady-state optimal energy flow with hydrogen injection according to the given wind speed. Use the solution when k = 1 as the initial condition of the partial differential equation. Set the solution at each time point k as the initial reference value for sequential programming. Set the iteration index v of the sequence programming to 1.

[0256] In the vth iteration, solve the above SOC optimization problem based on the given reference point. Determine whether all state variables have not changed compared with the previous iteration and whether all Taylor residuals have converged to zero:

[0257] |y (v) -y (v-1) | / (y (v) +y (v-1) )≤∈

[0258]

[0259] If yes, the iterative calculation of the sequence SOC planning is terminated, and the solution is output as the final calculation result, i.e., the optimal electrical joint system operation plan;

[0260] Otherwise, the solution of the current iterative calculation is set as the reference value, the penalty coefficient is updated, and the process returns to step S32 to continue the iterative calculation.

[0261] Furthermore, the method for updating the penalty coefficient is:

[0262]

[0263] in, is the multiplier of the penalty coefficient, β mo,(v) is the penalty coefficient for the vth iteration, β mo,(v+1) β mo,(v) The penalty coefficient after the next iteration.

[0264] The beneficial effects of the method of the present invention are further described below with reference to specific examples:

[0265] First, initialize the parameters of the power and gas combined system. First, initialize the parameters of the power and gas combined system. The structural diagram of the power and gas combined system is as follows: Figure 1 As shown, the original data of the power system and natural gas transmission system included in it are from public literature.

[0266] On this basis, this embodiment makes the following modifications:

[0267] 1) The power system and the natural gas system are connected through Figure 4 1) The 12MW, 20MW, and 100MW oil-fired units on power nodes 15, 13, 14, and 2 are respectively replaced with gas-fired units with the same capacity; 2) The parameters of the gas-fired units, the price of natural gas, and the calorific value of natural gas are set according to the existing technology. 3) The hydrogen production rate of the power-to-gas conversion is set to 0.5Mm3 / day; 4) The gas composition of the natural gas source is shown in Table 1.

[0268] Table 1

[0269]

[0270] Case 1: Verification of the effectiveness of the proposed solution

[0271] 1.1) Computing performance

[0272] First, the superiority of our approach is evaluated. In this case, a power-to-gas (PTG) facility located at gas node #8 is put into operation. The dispatch capacity of the renewable generation unit changes from zero at the beginning to 800MW after one hour. The proposed method (second-order cone programming using MOSEK solver) is compared with a traditional nonlinear solver (IPOPT), in this case, the optimization problem retains its original nonlinear form. By averaging the results in 100 random scenarios, the proposed method takes an average of 29.82 seconds, which is 42 times faster than IPOPT.

[0273] In addition, the solution of the nonlinear solver is regarded as the baseline, and the relative errors of the method of the present invention at different gas nodes are as follows: Figure 5 As shown. Figure 5 As shown in Figure 2, the errors of all nodes are controlled within 1.1%. The largest relative error occurs at natural gas node #14, where the gas is mixed.

[0274] 1.2) Choice of time and space step size

[0275] Four scenarios S1 to S4 are compared to determine the appropriate time and length steps for discretizing partial differential equations (PDEs). Figure 6 The calculation times of these four scenarios are 35.88 seconds, 29.82 seconds, 22.13 seconds, and 12.32 seconds respectively.

[0276] Taking S1 as the baseline, the relative error increases with the increase of the length step. The error in S2 is relatively small, with an average value of 5.30×10 -4 . However, when the length step is increased to 50000 m, the average relative error increases to 0.18% and oscillation occurs. It can also be observed that the maximum error occurs at the beginning, as shown by the dashed line in S3. The maximum error can be as high as 2.58%. In contrast, the dotted line in S2 remains very close to the baseline throughout the transition process. The calculation times of these three scenarios are relatively close. Therefore, based on the accuracy judgment, the length step Δx is selected to be 10000 m.

[0277] The choice of the time step depends mainly on the required time resolution, and it is also noted that there is a non-negligible error between S1 and S4, especially before the hydrogen concentration approaches the steady-state value. Therefore, in the following case study, the time step Δt is chosen to be 1800 seconds.

[0278] Case 2: The spread of hydrogen

[0279] Second, the performance of the MPOEF scheme in tracking the spread of alternative gas concentrations is studied. Similar to the previous case, the difference is that the wind power capacity is restored to 0 MW at t = 12 hours.

[0280] The propagation of hydrogen content along the key gas network branches, namely from gas nodes #8 to #12 and #17 to #20, is shown in Figure 7 It can be seen that the hydrogen injected into gas node #8 gradually propagates to distant locations along the pipeline route. The hydrogen concentration rises to 8.43% immediately after the injection of gas node #8 at t = 1 hour. In contrast, the hydrogen concentration at gas node #20 reaches its maximum value at t = 13.5 hours, and the total time to reach stability is 9 hours. This shows that it is very necessary to consider the propagation time of hydrogen concentration in MPOEF. Otherwise, it will lead to miscalculation of gas composition distribution in the gas system.

[0281] Case 3: Results of multi-period operation

[0282] After validating the MPOEF method of the present invention, it was applied to multi-period operation. All power-to-gas (PTG) facilities were available in this case, and three scenarios S1 to S3 were compared. In S1, safety constraints were not considered. In S2 and S3, the safety indicators were limited to ±10% and ±5% of the original natural gas value, respectively.

[0283] from Figures 8 to 10 It can be seen that, in general, in all scenarios, PTG's gas production is consistent with the wind speed trend. For example, from 10:30 to 17:30, PTG operates at maximum capacity at node #3 due to higher wind speeds. Comparing the different scenarios, it is found that as the safety restrictions are strengthened, PTG's hydrogen production decreases. Instead, they choose to convert more hydrogen into methane because methane is closer to natural gas in terms of interchangeability. For example, the total methane production in S1 is zero, while it increases to 9.85% in S2. This number further increases to 27.72% in S3.

[0284] In S1, the propagation and mixing process of hydrogen in different key pipeline routes is Figures 11 to 14The results show that the hydrogen concentration at the injection point is consistent with the hydrogen production of PTG. For example, the hydrogen concentration at gas node #1 increases immediately from zero to about 20% at 8:30, which is the moment when PTG starts to increase hydrogen production at node #3. Then, as the hydrogen propagates in the gas grid, its concentration will be diluted by pure natural gas mixing (such as the gas source of gas node #2) or by pipeline convection (such as gas nodes #3-4). It can also be diluted by the gas mixing process. For example, the hydrogen concentration peak at gas node #4 is 10.98% at 17:30, and it takes about 4.5 hours to be transmitted to gas node #14. By 22:00, it is diluted by the gas mixture from node #13 (containing 6.74% hydrogen). Then, the hydrogen concentration of the mixture at gas node #14 decreases to 7.82%.

[0285] The safety indicators in the three scenarios are Fig.13 and Fig.14 A comparison was made in . It was found that as the mixing of hydrogen increases, the WI will decrease, while the FS tends to increase. For example, the WI of natural gas node #4 in S1 is 2.25% lower than that in S3. In addition, FS is more critical than WI and is used to adjust the amount of hydrogen injection. Even in S1, the WI did not violate the lower limit. On the contrary, in S2 and S3, the FS of natural gas node #11 reached their upper limits, respectively. This verifies that the MPOEF of the present invention successfully keeps these indicators within a safe range while also accommodating green hydrogen to the maximum extent. This also verifies the necessity of adding FS as an additional indicator to the traditional Dutton method, while also ensuring the safety of the hydrogen mixed gas system.

[0286] Fig.15 and Fig.16 The changes in pipeline storage energy in these scenarios are shown. It can be seen that although the pipeline storage energy changes with wind power and hydrogen injection, it still remains within an acceptable range. For example, in the pipeline connecting natural gas nodes #4 to #14, Fig.15 As shown in Figure 2, the tube energy storage dropped sharply at 20:00 with the injection of a large amount of hydrogen. However, it returned to normal levels at the end of the run. We also found that the change in tube energy storage was smaller as the safety constraints were strengthened. For example, Fig.16 As shown in Figure 2, at 24:00, the total pipeline energy storage of the natural gas system in S3 was 4.07% higher than that in S1. Since pipeline energy storage is crucial to maintaining the robustness of the gas grid, hydrogen injection may in some sense jeopardize this flexibility. Therefore, in addition to safety indicators, pipeline energy storage should also be closely monitored when injecting hydrogen into the natural gas system.

[0287] This paper proposes a multi-period optimized energy flow (MPOEF) model for hydrogen blending in an integrated electricity and gas system (IEGS) and its feasible solution. The model describes the dynamic changes of gas composition in detail to reveal the propagation of hydrogen concentration and its impact on gas physical properties in real time. The above case study shows that the solution algorithm proposed in this paper is 97.64% faster than the general nonlinear solver, while the accuracy deviation is controlled within 1.1%. The MPOEF results show the necessity of considering the dynamics of gas composition. It takes about 12.5 hours for hydrogen to be transported from the injection point to the end of the pipeline route. If this significant transportation time is ignored, inaccuracies will result. In addition, the study found that the flame speed (FS) is a more critical factor than other safety indicators. Under different safety constraints, the accommodation of renewable energy, the gas production mode of PTG and the pipeline storage energy will be different. Looser safety constraints will lead to lower pipeline storage energy, which may affect the flexibility of the natural gas system.

[0288] As the use of alternative gases in low-carbon energy systems has received increasing attention, the MPOEF model proposed in this paper can provide decision makers with a powerful toolbox to regulate the safety of IEGS during continuous operation. It can also be extended to help short-term reliability assessment or deal with unit combination problems of hydrogen-containing hybrid energy systems while ensuring gas safety.

[0289] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0290] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0291] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0292] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0293] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.

Claims

1. A method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components, characterized in that: The following steps are involved: S1: Define the safe operating range of the combined power-gas system after hydrogen is added; S2: Based on the safe operating range, design an operating framework, control the injection and distribution of hydrogen in different time periods through the operating framework, and establish constraint conditions of the operating framework; S3: Under the constraints, convert the non-convex problem of the operation framework into a problem that can be processed by second-order cone programming, solve the problem that can be processed by second-order cone programming, and obtain an optimal electrical joint system operation plan; S4: using the optimal electric power system operation plan to complete low-carbon safety dispatching of the electric power system; The non-convex problems of the operation framework include the non-convex problems of the motion equation and the convection transport equation. The method for obtaining the optimal electrical joint system operation plan is: S31: For the non-convex problem of the motion equation, set an auxiliary variable The motion equation is reconstructed by a second-order cone to obtain the first second-order cone constraint: And for the non-convex problem of the convection transport equation, set an auxiliary variable The convection transport equation is reconstructed by a second-order cone to obtain the second second-order cone constraint: Among them, Δt and Δx are the temporal and spatial resolutions, respectively; represents the average value of the gas density of the segment s in the pipeline ij at time k; represents the spatial difference of the gas pressure of the segment s in the pipeline ij at time k; ρ0 is the density of pure natural gas under standard temperature and pressure conditions; f ij and D ij are the Fanning friction coefficient and diameter of the pipe ij; A ij is the cross-sectional area of ​​the pipe ij; represents the average gas flow rate of segment s in pipeline ij at time k; represents the difference in the proportion of gas component n in segment s in pipeline ij at time k with respect to time; represents the spatial difference of the proportion of gas component n in segment s in pipeline ij at time k; represents the time difference of the gas flow rate of the segment s in the pipeline ij at time k; S32: Add a penalty term to the objective function of the operating framework to make the second-order cone relaxation constraint tighter. By controlling the relaxation variable, the optimization problem is convexified to obtain a problem that can be handled by second-order cone programming, and its expression is: Among them, C T is the system operation cost, λ mo express The penalty coefficient of and are the relaxation variables of the Taylor remainders of the motion and convection transport equations, respectively; is the Taylor remainder; for The value of the vth iteration of ; for The value of the vth iteration; β se,(v) for The penalty coefficient at the vth iteration; λ at for The penalty coefficient of for The value of the vth iteration; β at,(v) for The penalty coefficient at the vth iteration; for The value of the vth iteration; β re,(v) for The penalty coefficient at the vth iteration; S33: Iteratively calculate the second-order cone programming tractable problem to determine whether all state variables have not changed compared with the previous iteration and whether all Taylor remainders have converged to zero: If yes, the iterative calculation is terminated and the solution is output as the final calculation result, i.e., the optimal electrical joint system operation plan; Otherwise, the solution of the current iterative calculation is set as the reference value, the penalty coefficient is updated, and the process returns to step S32 to continue the iterative calculation; Wherein, the method for updating the penalty coefficient is: in, is the multiplier of the penalty coefficient, β mo,(v) is the penalty coefficient for the vth iteration, β mo,(v+1) β mo,(v) The penalty coefficient after the next iteration of update; The objective function is to minimize the system operation cost C within the safe operation range. T Constructed; wherein the system operating cost C T for: in, and are the sets of gas nodes and times respectively; and are the sets of traditional generators and natural gas sources at node i respectively; is the power generation of the traditional generator set l at node i at time k; is the gas production of source l at node i at time k; cst i,l is the cost of the traditional generator l at node i; is the unit gas price.

2. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 1, characterized in that: The expression of the safe operating range is: Among them, H is the gas safety region under normal conditions, WI i,k represents the Wobbe index of node i at time k, ICF i,k represents the incomplete combustion factor of node i at time k, SI i,k represents the smoke index of node i at time k, FS i,k represents the flame speed of node i at time k, HV i,k represents the heat value of node i at time k; S i,k Indicates the relative density of the gas mixture; φ i,k is the set of gas components at node i at time k; and are the concentrations of hydrogen, propane and nitrogen respectively; WI min is the minimum value of the Wobbe index; ICF max 、SI max and FS max They are the maximum values ​​of incomplete combustion factor, smoke index and flame speed respectively; and are the sets of gas nodes and times respectively; Among them, the Wobbe index WI of the node i at time k is i,k The calculation method is: Among them, S ng is the relative density of natural gas; The incomplete combustion factor ICF of the node i at time k i,k The calculation method is: The smoke index SI of node i at time k i,k The calculation method is: The flame speed FS of the node i at time k i,k The calculation method is: Among them, fs n is the flame speed of gas component n in the fuel-air mixture, is the collection of gas components; φ i,k,n is the concentration of gas component n in the fuel-air mixture.

3. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 2, characterized in that: The heat value HV of node i at time k i,k The calculation method is: The relative density S of the gas mixture i,k The calculation method is: Among them, HV n is the calorific value of gas component n, M n and M air are the relative molecular masses of gas component n and air respectively.

4. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 1, characterized in that: The constraints of the operation framework include constraints of the natural gas system, constraints of the coupling elements and constraints of the power system; The method for constructing the constraint conditions of the natural gas system includes: In natural gas pipelines, the dynamic characteristics of gas components and natural gas flow are mathematically modeled through nonlinear partial differential equations to obtain a natural gas system model; Discretizing the natural gas system model in terms of time t and length x to obtain a multi-period natural gas system model; Since the gas composition changes and the gas thermal energy demand remains consistent, a model of natural gas load and natural gas source is constructed: Among them, HV ng is the calorific value of natural gas; is the original natural gas demand flow at time k; is the collection of gas components; φ i,k,n is the concentration of gas component n in the fuel-air mixture; is the required flow rate of gas component n at node i at time k; Considering the different gas components of the gas source, the model is: in, is the supply of component n of gas source l at node i at time k; is the concentration of component n in gas source l at node i; is the concentration of component n in gas source l at node i at time k; is the supply of gas source l at node i at time k; and are the maximum and minimum values ​​of gas supply respectively; In the natural gas network, the gas from the upstream elements of the node is uniformly mixed at the natural gas node i according to the mixing ratio, and the uniformly mixed gas is delivered to the downstream elements. The upstream elements of the node include the upstream pipeline, the natural gas source and the power-to-gas facility, and the downstream elements include the downstream pipeline, the natural gas load and the gas generator set; The calculation method of the mixing ratio is: Among them, φ i,k,n is the concentration of gas component n in the fuel-air mixture, that is, the mixing ratio of each gas component n; represents the total gas injection amount of each gas component n at the natural gas node i, Q ij,1,k,n is the injection amount of gas component n in the first segment of pipeline ij at time k, Q ij,S,k,n is the injection amount of gas component n at the Sth segment of pipeline ij at time k, γ ji Indicates the direction of natural gas flow, is the set of power-to-gas facilities at node i, is the gas production of gas component n at power-to-gas facility l at natural gas node i at time k; represents the total gas injection amount of all gas components at natural gas node i, is the collection of gas components; is the set of natural gas sources at node i.

5. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 4, characterized in that: The multi-period natural gas system model includes continuity differential equations, motion equations and convection transport equations; Wherein, the expression of the continuity differential equation is: Among them, A ij is the cross-sectional area of ​​the pipe ij; represents the time difference of the gas density of the segment s in the pipeline ij at time k; represents the spatial difference of the gas flow rate of the segment s in the pipeline ij at time k; ρ0 is the density of pure natural gas under standard temperature and pressure conditions; Δt and Δx are the time and space resolutions respectively; The expression of the motion equation is: in, represents the spatial difference of the gas pressure of the segment s in the pipeline ij at time k; represents the time difference of the gas flow rate of the segment s in the pipeline ij at time k; represents the average gas flow rate of segment s in pipeline ij at time k; represents the average value of the gas density of the segment s in the pipeline ij at time k; The expression of the convective transport equation is: Among them, p ij , Q ij and ρ ij are respectively the air pressure, flow velocity and density in the pipe ij; φ ij,n is the proportion of gas component n in pipeline ij; f ij and D ij are the Fanning friction coefficient and diameter of the pipe ij, respectively; is a collection of pipeline fragments; is the direction of the natural gas flow at t = 0; sgn(·) is the sign function; represents the difference in the proportion of gas component n in segment s in pipeline ij at time k with respect to time; represents the spatial difference of the proportion of gas component n in segment s in pipeline ij at time k; In the multi-period natural gas system model, the gas density ρ ij,s,k and pressure p ij,s,k Should be followed: p ij,s,k =zi j,s,k r ij,s,k T0r ij,s,k Among them, z ij,s,k and r ij,s,k denote the compressibility factor and gas constant of the pipe segment ij at time k, respectively. R n is the gas constant of gas component n; T0 is the temperature of the gas mixture.

6. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 5, characterized in that: The method for constructing the multi-period natural gas system model further includes setting initial conditions, boundary conditions and terminal conditions; wherein the initial conditions are: Among them, p ij,s,1 is the initial gas pressure in the pipe segment ij, Q ij,s,1 represents the initial gas injection amount in the pipe ij segment s, φ ij,s,1,n represents the initial proportion of gas component n in the pipe ij segment s; and are the initial setting values ​​of the gas pressure, gas flow and proportion of gas component n on the segment s of the pipeline ij, respectively; The boundary conditions of a natural gas pipeline are determined by the pipelines and other components it connects to, including: Conditions for maintaining consistent air pressure at pipeline connection points: Conditions for maintaining nodal conservation for each gas component: in, represents the supply flow of gas component n from natural gas source l at node i at time k; The conditions to ensure that the gas composition of the pipeline at the connection point should be the same are: Among them, p ij,1,k and p ij,S,k Respectively represent the air pressure of the first and Sth sections of the pipeline ij at time k; p ij′,1,k represents the air pressure of the first section of pipeline ij′ connected to node i of pipeline ij; p i′j,S,k represents the air pressure of the Sth section of pipeline i′j connected to the node j of pipeline ij; p i,k is the node pressure of node i at time k; p j,k is the node pressure of node j at time k; and are the sets of nodes connected to node i and node j respectively; is the demand for gas component n at node i; and are the sets of all gas-fired power generating units and power-to-gas facilities at node i; is the gas consumption of gas generator set l at node i at time k; is the gas production of power-to-gas facility l at node i at time k; Q ij,1,k,n represents the injection amount of gas component n in the first section of pipeline ij at time k; φ ij,1,k,n and φ ij,S,k,n are the proportions of gas component n in the first and Sth sections of pipeline ij at time k; φ i,k,n is the proportion of gas component n at node i at time k; φ j,k,n is the proportion of gas component n at node j at time k; The terminal condition is set using the tube storage energy: g ij,K ≥(1-β lp )g ij,0 Among them, ij,k is the tube storage energy at time k; β lp is the threshold coefficient used to maintain the storage energy level; K is the total number of time periods, ζ ij,0 Represents the initial tube storage energy.

7. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 4, characterized in that: The constraints of the coupling element include the constraints of the power-to-gas facility and the constraints of the gas generator set; wherein the constraints of the power-to-gas facility are: in, is the electricity consumption of the power-to-gas facility l; and are the efficiencies of the electrolysis and methanogenesis processes, respectively; HV hy and HV me are the calorific values ​​of hydrogen and methane, respectively; and is the hydrogen and methane production produced by the power-to-gas facility l at node i at time k; represents the maximum value of the power consumption of the power-to-gas facility l; The constraints of the gas generator set are: in, and are the power generation and efficiency of gas generator set l respectively; is the amount of gas component n consumed by gas generator set l.

8. The method for operating an electrical integrated system taking into account the dynamic characteristics of hydrogen-doped gas components according to claim 4, characterized in that: The constraints of the power system are: g ij,k =(θ i,k -θ j,k ) / X ij in, represents the renewable generator set at node i, is its power generation capacity; is the power demand of node i at time k; g ij,k is the power flow on branch ij at time k; θ i,k is the phase angle of the voltage at node i; θ j,k is the phase angle of the voltage at node j; X ij is the reactance; is the transmission capacity; is the transmission capacity of the conventional generator l at node i at time k; and They are the upper and lower limits of the transmission capacity of traditional generator sets; is the transmission capacity of gas generator set l at node i at time k, and They are the upper and lower limits of the transmission capacity of the gas generator set respectively; is the transmission capacity of renewable generator l at node i at time k, and They are the upper and lower limits of the transmission capacity of renewable power generation units respectively.

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