A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit

Abstract

The present invention provides a two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit. First, the method obtains the basic data of the gas-electricity integrated energy system coupled with the hydrogen storage unit, introduces the carbon emission reduction coefficient in the upper-level fixed capacity optimization stage, and designs a multi-objective optimization model for fixed capacity of the hydrogen storage unit that considers carbon emissions. The ε constraint method and the great cane rat optimization algorithm are used to solve the model to form the optimal configuration scheme of the hydrogen storage unit. In the lower-level operation optimization stage, an operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit is designed, and the model is solved by the great cane rat optimization algorithm to form an operation scheme of the gas-electricity integrated energy system. The method adopts a two-stage optimization model, which effectively solves the problems of fixed capacity configuration and operation strategy optimization of the gas-electricity integrated energy system coupled with the hydrogen storage unit, provides effective guidance for on-site work, and is conducive to stable and efficient operation of the system.

Description

Technical Field

[0001] The present invention relates to the field of operation optimization of a gas-electricity integrated energy system, and in particular to a two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit. Background Art

[0002] The use of gas turbines in the traditional mode realizes the conversion of natural gas into electricity, but it also limits the flexibility and sustainability of the system. When the problem of wind and power abandonment is prominent, the traditional one-way coupling method not only fails to effectively utilize the excess electricity, but also leads to the aggravation of energy waste and carbon emissions. Therefore, optimizing the dual-grid coupling mode has become the focus of current research and application. In order to solve the above problems, the industry has proposed a new dual-grid coupling strategy, that is, introducing a power-to-hydrogen device and a hydrogen storage unit between the natural gas system and the power system. The power-to-hydrogen device uses the remaining electricity to convert it into hydrogen, which not only effectively reduces the phenomenon of wind and power abandonment, but also realizes the efficient use of electricity. The produced hydrogen can be injected into the natural gas pipeline network to replace part of the natural gas, thereby achieving the goal of reducing carbon emissions. The hydrogen storage unit can store hydrogen energy in a timely and safe manner, and flexibly adjust its operating status according to the system operation status and user needs to ensure efficient and stable hydrogen supply.

[0003] Subsequently, the problem of fixed capacity configuration of hydrogen storage units and the problem of adjusting the operation strategy of the dual-grid coupled gas-electricity integrated energy system have become a major problem facing the industry. It is difficult to achieve the goal of efficient utilization of natural gas, electricity and hydrogen energy and reduction of carbon emissions by directly giving the device operation capacity and determining the operation strategy only through experience. Therefore, it is very necessary to study the role of power-to-hydrogen devices in the integrated energy system and the energy exchange and scheduling methods within the natural gas-electricity interconnection system, and then propose the fixed capacity and optimized operation strategy of power-to-hydrogen devices in the gas-electricity integrated energy system. Summary of the invention

[0004] The present invention provides a two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit, characterized in that it comprises the following steps:

[0005] S1: Obtain basic data of the gas-electricity integrated energy system coupled with the hydrogen storage unit;

[0006] S2: In the upper-level fixed capacity optimization stage, the carbon emission reduction coefficient w is introduced to design a multi-objective fixed capacity optimization model for hydrogen storage units that takes carbon emissions into consideration;

[0007] S3: Using the ε constraint method and the great cane rat optimization algorithm to solve the multi-objective constant capacity optimization model of the hydrogen storage unit, and form the optimal configuration plan of the hydrogen storage unit;

[0008] S4: In the lower-level operation optimization stage, an operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit is designed;

[0009] S5: The large cane rat optimization algorithm is used to solve the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit to form an operation plan for the gas-electricity integrated energy system.

[0010] Furthermore, the gas-electricity integrated energy system coupled with the hydrogen storage unit described in step S1 is composed of a natural gas unit, an electric power unit, an electric-to-hydrogen conversion device, a gas turbine and a hydrogen storage unit;

[0011] The basic data include comprehensive gas-electricity energy structure data, user natural gas demand, user electricity demand, electricity transmission cost, electricity price, generator set operating parameters, power-to-hydrogen unit hydrogen production rate, hydrogen storage tank capacity, hydrogen storage tank unit construction cost and hydrogen storage unit inventory range.

[0012] Furthermore, the carbon emission reduction coefficient w described in step S2 is used to characterize the degree of implementation of the emission reduction target; the objective function of the multi-objective constant capacity optimization model for the hydrogen storage unit includes minimizing the operating cost of the power-to-hydrogen unit and maximizing the user's carbon emission reduction, and the expressions are respectively:

[0013]

[0014] Where N P2H is the number of power-to-hydrogen devices; C G is the unit replacement price of the power-to-hydrogen device; C Y is the unit operating price of the power-to-hydrogen device; β is the unit capital recovery coefficient of the power-to-hydrogen device; d is the annual operating time of the power-to-hydrogen device, which is 350 days; C D,t is the unit power generation price at time t; C N is the natural gas sales price; η is the electricity transmission cost coefficient; P t is the operating power of the power-to-hydrogen device at time t; λ is the natural gas emission factor; Q N，t is the volume flow rate of natural gas in the pipeline at time t; Q P，t is the volume flow rate of hydrogen in the pipeline at time t;

[0015] The constraints of the multi-objective optimization model for hydrogen storage unit volume determination include power constraints of the power-to-hydrogen conversion device, hydrogen production constraints of the power-to-hydrogen conversion device, natural gas supply and demand balance constraints, hydrogen blending constraints, hydrogen production balance constraints, pipeline gas volume balance constraints, hydrogen storage tank operation status constraints, hydrogen storage tank inventory constraints and hydrogen storage unit capacity constraints;

[0016] The power constraint of the power-to-hydrogen device requires that the total operating power of the power-to-hydrogen device must be within the system limit, and the expression is:

[0017]

[0018] In the formula, The minimum operating power of the power-to-hydrogen device; is the maximum operating power of the power-to-hydrogen device; P P2H,t is the operating power of the power-to-hydrogen device at time t;

[0019] The constraint expression of hydrogen production of the power-to-hydrogen device is:

[0020] Q P2H，t =ρ×P P2H,t

[0021] Where, ρ is the hydrogen conversion coefficient of the power-to-hydrogen device; Q P2H，t is the amount of hydrogen produced by the power-to-hydrogen device at time t;

[0022] The natural gas supply and demand balance constraint stipulates that the total gas volume formed after the hydrogen generated by the power-to-hydrogen device is injected into the natural gas system should meet the user's hourly natural gas demand, expressed as:

[0023] Q D,t =Q L,t +Q N，t

[0024] In the formula, Q D,t is the natural gas demand of users at time t; Q L,t is the amount of hydrogen entering the pipeline at time t; Q N，t is the volume flow rate of natural gas in the pipeline at time t;

[0025] The hydrogen blending constraint stipulates that the pipeline hydrogen injection amount is less than the maximum allowable hydrogen blending amount, and the expression is:

[0026] In the formula, is the hydrogen doping ratio coefficient, which is 5%;

[0027] The hydrogen production balance constraint stipulates that there is a balance between the amount of hydrogen produced by the power-to-hydrogen device and the amount of hydrogen entering the natural gas pipeline and the hydrogen storage unit, and the expression is:

[0028]

[0029] In the formula, is the amount of hydrogen entering the hydrogen storage unit at time t;

[0030] The pipeline hydrogen balance constraint stipulates that the amount of hydrogen in the pipeline is equal to the sum of the hydrogen output of the hydrogen storage unit and the hydrogen output of the electric-to-hydrogen device, and the expression is:

[0031]

[0032] In the formula, Q PP,t is the amount of hydrogen directly input into the pipeline by the power-to-hydrogen conversion device at time t; is the amount of hydrogen directly input into the pipeline from the hydrogen storage unit at time t;

[0033] The operating state constraint of the hydrogen storage tank stipulates the operating state of the hydrogen storage unit closing, gas injection and gas extraction, and the expression is:

[0034]

[0035] 0≤a t +b t ≤1

[0036] a t ∈{0,1}

[0037] b t ∈{0,1}

[0038] In the formula, a t is the decision variable for the process of injecting hydrogen into the hydrogen storage unit at time t. If it is 1, it means that hydrogen is injected into the hydrogen storage unit at time t, otherwise, the value is 0; b t is the decision variable of the process of extracting hydrogen from the hydrogen storage unit at time t;

[0039] The hydrogen storage tank storage constraint stipulates that the total volume of hydrogen stored in the hydrogen storage unit should be equal to the volume of hydrogen in the hydrogen storage pipe at time t-1 plus the volume of hydrogen injected into the hydrogen storage tank at time t, expressed as:

[0040] In the formula, S GC,t-1 is the hydrogen storage volume in the hydrogen storage unit at time t-1; S GC,t is the hydrogen stock in the hydrogen storage unit at time t;

[0041] The hydrogen storage unit capacity constraint expression is:

[0042]

[0043] Where N g is the number of hydrogen storage tanks; The maximum tank capacity of a single hydrogen storage tank; It is the minimum tank capacity of a single hydrogen storage tank.

[0044] Furthermore, the ε constraint method described in S3 takes minimizing the operating cost as the main objective function and converts the carbon emission target into a constraint condition; the optimal configuration plan of the hydrogen storage unit includes the scale and number of power-to-hydrogen devices, the capacity and number of hydrogen storage tanks, the operating cost of the power-to-hydrogen devices and the carbon emission reduction.

[0045] Furthermore, the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit described in S4 takes minimizing the operation cost of the gas-electricity integrated energy system as the objective function. The operation cost includes the gas source purchase cost, the power generation cost of the generator set, the wind abandonment penalty cost and the hydrogen sales income. The objective function expression is:

[0046]

[0047] In the formula, a g , b g 、c g is the power generation cost coefficient of generator set g; P G,g,t The power provided by the conventional generator connected to node i at time t; C wc P is the wind power plant’s wind abandonment penalty coefficient; wc,k,t is the wind abandonment volume of wind power plant k at time t;

[0048] The constraints of the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit include natural gas unit constraints, power unit constraints, hydrogen production constraints of the power-to-hydrogen device, and natural gas consumption constraints of the gas turbine;

[0049] The natural gas unit constraints include node flow balance constraints, node pressure constraints and gas source supply constraints;

[0050] The node flow balance constraint expression is:

[0051]

[0052] In the formula, Q GT,g,t is the active power converted by the gas turbine g at time t;

[0053] The node pressure constraint expression is:

[0054]

[0055] In the formula, The upper pressure limit of node i; The lower limit of pressure at node i;

[0056] The gas source supply quantity constraint expression is:

[0057]

[0058] In the formula, is the minimum gas supply volume of gas source node n; Q N,n,t is the gas supply volume of gas source node n at time t; is the maximum gas supply of gas source node n;

[0059] The power unit constraints include node power balance constraints, line power constraints, generator set ramp constraints and wind abandonment constraints;

[0060] The node power balance constraint expression is:

[0061]

[0062] Where P G,g,t P is the power provided by the conventional generator connected to node i at time t; w,k,t is the active power output of wind farm k at time t; P D,i,t is the power demand of the user at grid node i at time t; P i,j,t is the active power transmitted by the transmission line between node i and node j at time t;

[0063] The line power constraint is expressed as:

[0064]

[0065] In the formula, is the maximum transmission power of transmission line i to j; is the minimum transmission power of transmission line i to j;

[0066] The generator set climbing constraint is expressed as:

[0067]

[0068] Where P G,e,t-1 is the power generation of generator set g at time t-1; is the upper limit of the climbing slope of the generator set g; R e min is the lower limit of the climbing slope of the generator set g;

[0069] The wind abandonment constraint stipulates that when using wind energy for power generation, the amount of wind power that cannot be absorbed is regarded as abandoned wind power, and the abandoned wind power shall not exceed the total amount of wind power, expressed as:

[0070]

[0071] In the formula, is the available wind power of wind farm k at time t;

[0072] The constraint expression of hydrogen production of the power-to-hydrogen device is:

[0073] Q P2H =μ P2H P P2H,p,t

[0074] In the formula, μ P2H P is the unit hydrogen production efficiency of the power-to-hydrogen device;P2H,p,t is the operating power of the power-to-hydrogen device p at time t;

[0075] The gas turbine natural gas consumption constraint expression is:

[0076]

[0077] In the formula, μ GT,g is the conversion efficiency of the gas turbine g; Q GT,g,t is the active power converted by the gas turbine g at time t; H g is the calorific value of natural gas, which is 39MJ / m 3 .

[0078] Furthermore, the solution process of the optimization algorithm for the cane rat described in S3 and S5 includes:

[0079] S301: Set the maximum number of iterations to T, the initial population size of cane rats to N, the GCR parameter ρ to 0.5, and randomly initialize in the algorithm search space to generate an initial population of cane rats, each of which represents a feasible solution to the optimization problem;

[0080] S302: Calculate the fitness of the population according to the model objective function, determine the individual with the highest fitness as the optimal individual, and define its position in the solution space as x k,j , the remaining individuals update their positions according to the optimal individual, and the update formula is:

[0081]

[0082] In the formula, is the updated individual position; x i,j is the individual position before updating;

[0083] S303: Calculate the food attraction coefficient r, food reduction coefficient α and population movement coefficient according to the current number of iterations, and generate a random number σ in the range of [0,1] and a random number μ in the range of [1,4] for subsequent individual position updates. The calculation formula is:

[0084]

[0085] α=r(2σ-1)

[0086] β=r(2μ-1)

[0087] In the formula, is the population fitness of the optimal individual; t is the current number of iterations; T is the maximum number of iterations;

[0088] S304: If σ<ρ, the algorithm enters the exploration phase, and the formula for updating the position of the individual cane rat is:

[0089]

[0090] Where C is a random number defined within the boundary of the search space;

[0091] If σ≥ρ, the algorithm enters the development stage, and the formula for updating the position of the individual cane rat is:

[0092]

[0093] S305: Check the algorithm boundary conditions, calculate the updated fitness of the large cane rat individual population, and update the optimal individual X according to the fitness calculation results. k,j ;

[0094] S306: If t≥T, the algorithm is terminated and the optimal individual is output as the optimal solution of the model. Otherwise, it returns to S302 to continue iterating.

[0095] Furthermore, the operation plan of the gas-electricity integrated energy system includes system operating costs, system carbon emissions, injection and production status and periodic reserves of the hydrogen storage unit, and hydrogen production and power of the power-to-hydrogen device. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 Flow chart of the present invention

[0097] Figure 2 Optimizing the algorithm flow chart for the greater cane rat

[0098] Figure 3 The hourly hydrogen injection and production flow rate of the hydrogen storage unit and the change curve of the hydrogen storage unit tank

[0099] Figure 4 The hydrogen flow rate injected into the natural gas pipeline under the non-tank 5% scenario

[0100] Figure 5 The hydrogen flow rate injected into the natural gas pipeline under the tank 5% scenario

[0101] Figure 6 Hydrogen production capacity of power-to-hydrogen devices in different scenarios

[0102] Figure 7 The hydrogen production power of the power-to-hydrogen device in different scenarios. DETAILED DESCRIPTION

[0103] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0104] like Figure 1 As shown, the present invention provides a two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit, characterized in that it includes the following steps:

[0105] S1: Obtain basic data of the gas-electricity integrated energy system coupled with the hydrogen storage unit;

[0106] S2: In the upper-level fixed capacity optimization stage, the carbon emission reduction coefficient w is introduced to design a multi-objective fixed capacity optimization model for hydrogen storage units that takes carbon emissions into consideration;

[0107] S3: Using the ε constraint method and the great cane rat optimization algorithm to solve the multi-objective constant capacity optimization model of the hydrogen storage unit, and form the optimal configuration plan of the hydrogen storage unit;

[0108] S4: In the lower-level operation optimization stage, an operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit is designed;

[0109] S5: The large cane rat optimization algorithm is used to solve the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit to form an operation plan for the gas-electricity integrated energy system.

[0110] In one embodiment, the gas-electricity integrated energy system coupled with the hydrogen storage unit described in step S1 is composed of a natural gas unit, an electric power unit, an electric-to-hydrogen conversion device, a gas turbine and a hydrogen storage unit;

[0111] The basic data include comprehensive gas-electricity energy structure data, user natural gas demand, user electricity demand, electricity transmission cost, electricity price, generator set operating parameters, power-to-hydrogen unit hydrogen production rate, hydrogen storage tank capacity, hydrogen storage tank unit construction cost and hydrogen storage unit inventory range.

[0112] In one embodiment, the carbon emission reduction coefficient w described in step S2 is used to characterize the degree of implementation of the emission reduction target; the objective function of the multi-objective constant capacity optimization model for the hydrogen storage unit includes minimizing the operating cost of the power-to-hydrogen unit and maximizing the user's carbon emission reduction, and the expressions are respectively:

[0113]

[0114] Where N P2H is the number of power-to-hydrogen devices; C Gis the unit replacement price of the power-to-hydrogen device; C Y is the unit operating price of the power-to-hydrogen device; β is the unit capital recovery coefficient of the power-to-hydrogen device; d is the annual operating time of the power-to-hydrogen device, which is 350 days; C D,t is the unit power generation price at time t; C N is the natural gas sales price; η is the electricity transmission cost coefficient; P t is the operating power of the power-to-hydrogen device at time t; λ is the natural gas emission factor; Q N，t is the volume flow rate of natural gas in the pipeline at time t; Q P，t is the volume flow rate of hydrogen in the pipeline at time t;

[0115] The constraints of the multi-objective optimization model for hydrogen storage unit volume determination include power constraints of the power-to-hydrogen conversion device, hydrogen production constraints of the power-to-hydrogen conversion device, natural gas supply and demand balance constraints, hydrogen blending constraints, hydrogen production balance constraints, pipeline gas volume balance constraints, hydrogen storage tank operation status constraints, hydrogen storage tank inventory constraints and hydrogen storage unit capacity constraints;

[0116] The power constraint of the power-to-hydrogen device requires that the total operating power of the power-to-hydrogen device must be within the system limit, and the expression is:

[0117]

[0118] In the formula, The minimum operating power of the power-to-hydrogen device; is the maximum operating power of the power-to-hydrogen device; P P2H,t is the operating power of the power-to-hydrogen device at time t;

[0119] The hydrogen production constraint expression of the power-to-hydrogen device is:

[0120] Q P2H，t =ρ×P P2H,t

[0121] Where, ρ is the hydrogen conversion coefficient of the power-to-hydrogen device; Q P2H，t is the amount of hydrogen produced by the power-to-hydrogen device at time t;

[0122] The natural gas supply and demand balance constraint stipulates that the total gas volume formed after the hydrogen generated by the power-to-hydrogen device is injected into the natural gas system should meet the user's hourly natural gas demand, expressed as:

[0123] Q D,t =Q L,t +Q N，t

[0124] In the formula, Q D,t is the natural gas demand of users at time t; Q L,tis the amount of hydrogen entering the pipeline at time t; Q N，t is the pipeline natural gas flow at time t;

[0125] The hydrogen blending constraint stipulates that the pipeline hydrogen injection amount is less than the maximum allowable hydrogen blending amount, and the expression is:

[0126] In the formula, is the hydrogen doping ratio coefficient, which is 5%;

[0127] The hydrogen production balance constraint stipulates that there is a balance between the amount of hydrogen produced by the power-to-hydrogen device and the amount of hydrogen entering the natural gas pipeline and the hydrogen storage unit, and the expression is:

[0128]

[0129] In the formula, is the amount of hydrogen entering the hydrogen storage unit at time t;

[0130] The pipeline hydrogen balance constraint stipulates that the amount of hydrogen in the pipeline is equal to the sum of the hydrogen output of the hydrogen storage unit and the hydrogen output of the electric-to-hydrogen device, and the expression is:

[0131]

[0132] In the formula, Q PP,t is the amount of hydrogen directly input into the pipeline by the power-to-hydrogen conversion device at time t; is the amount of hydrogen directly input into the pipeline from the hydrogen storage unit at time t;

[0133] The operating state constraint of the hydrogen storage tank stipulates the operating state of the hydrogen storage unit closing, gas injection and gas extraction, and the expression is:

[0134]

[0135] 0≤a t +b t ≤1

[0136] a t ∈{0,1}

[0137] b t ∈{0,1}

[0138] In the formula, a t is the decision variable for the process of injecting hydrogen into the hydrogen storage unit at time t. If it is 1, it means that hydrogen is injected into the hydrogen storage unit at time t, otherwise, the value is 0; b t is the decision variable of the process of extracting hydrogen from the hydrogen storage unit at time t;

[0139] The hydrogen storage tank storage constraint stipulates that the total volume of hydrogen stored in the hydrogen storage unit should be equal to the volume of hydrogen in the hydrogen storage pipe at time t-1 plus the volume of hydrogen injected into the hydrogen storage tank at time t, expressed as:

[0140] In the formula, S GC,t-1 is the hydrogen storage volume in the hydrogen storage unit at time t-1; S GC,t is the hydrogen stock in the hydrogen storage unit at time t;

[0141] The hydrogen storage unit capacity constraint expression is:

[0142]

[0143] Where N g is the number of hydrogen storage tanks; The maximum tank capacity of a single hydrogen storage tank; It is the minimum tank capacity of a single hydrogen storage tank.

[0144] In one embodiment, the ε constraint method described in S3 takes minimizing the operating cost as the main objective function and converts the carbon emission target into a constraint condition; the optimal configuration plan of the hydrogen storage unit includes the scale and number of power-to-hydrogen devices, the capacity and number of hydrogen storage tanks, the operating cost of the power-to-hydrogen devices and the carbon emission reduction.

[0145] In one embodiment, the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit described in S4 takes minimization of the operation cost of the gas-electricity integrated energy system as the objective function, and the operation cost includes the gas source purchase cost, the power generation cost of the generator set, the wind abandonment penalty cost and the hydrogen sales income. The objective function expression is:

[0146]

[0147] In the formula, a g , b g 、c g is the power generation cost coefficient of generator set g; P G,g,t The power provided by the conventional generator connected to node i at time t; C wc P is the wind power plant’s wind abandonment penalty coefficient; wc,k,t is the wind abandonment volume of wind power plant k at time t;

[0148] The constraints of the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit include natural gas unit constraints, power unit constraints, hydrogen production constraints of the power-to-hydrogen device, and natural gas consumption constraints of the gas turbine;

[0149] The natural gas unit constraints include node flow balance constraints, node pressure constraints and gas source supply constraints;

[0150] The node flow balance constraint expression is:

[0151]

[0152] In the formula, Q GT,g,t is the active power converted by the gas turbine g at time t;

[0153] The node pressure constraint expression is:

[0154]

[0155] In the formula, The upper pressure limit of node i; The lower limit of pressure at node i;

[0156] The gas source supply quantity constraint expression is:

[0157]

[0158] In the formula, is the minimum gas supply volume of gas source node n; Q N,n,t is the gas supply volume of gas source node n at time t; is the maximum gas supply of gas source node n;

[0159] The power unit constraints include node power balance constraints, line power constraints, generator set ramp constraints and wind abandonment constraints;

[0160] The node power balance constraint expression is:

[0161]

[0162] Where P G,g,t P is the power provided by the conventional generator connected to node i at time t; w,k,t is the active power output of wind farm k at time t; P D,i,t is the power demand of the user at grid node i at time t; P i,j,t is the active power transmitted by the transmission line between node i and node j at time t;

[0163] The line power constraint is expressed as:

[0164]

[0165] In the formula, is the maximum transmission power of transmission line i to j; is the minimum transmission power of transmission line i to j;

[0166] The generator set climbing constraint is expressed as:

[0167]

[0168] Where P G,e,t-1 is the power generation of generator set g at time t-1; is the upper limit of the climbing slope of the generator set g; is the lower limit of the climbing slope of the generator set g;

[0169] The wind abandonment constraint stipulates that when using wind energy for power generation, the amount of wind power that cannot be absorbed is regarded as abandoned wind power, and the abandoned wind power shall not exceed the total amount of wind power, expressed as:

[0170]

[0171] In the formula, is the available wind power of wind farm k at time t;

[0172] The hydrogen production constraint expression of the power-to-hydrogen device is:

[0173] Q P2H =μ P2H P P2H,p,t

[0174] In the formula, μ P2H P is the unit hydrogen production efficiency of the power-to-hydrogen device; P2H,p,t is the operating power of the power-to-hydrogen device p at time t;

[0175] The gas turbine natural gas consumption constraint expression is:

[0176]

[0177] In the formula, μ GT,g is the conversion efficiency of the gas turbine g; Q GT,g,t is the active power converted by the gas turbine g at time t; H g is the calorific value of natural gas, which is 39MJ / m 3 .

[0178] In one embodiment, the process of solving the optimization algorithm for the cane rat described in S3 and S5 includes:

[0179] S301: Set the maximum number of iterations to T, the initial population size of cane rats to N, the GCR parameter ρ to 0.5, and randomly initialize in the algorithm search space to generate an initial population of cane rats, each of which represents a feasible solution to the optimization problem;

[0180] S302: Calculate the fitness of the population according to the model objective function, determine the individual with the highest fitness as the optimal individual, and define its position in the solution space as x k,j , the remaining individuals update their positions according to the optimal individual, and the update formula is:

[0181]

[0182] In the formula, is the updated individual position; x i,j is the individual position before updating;

[0183] S303: Calculate the food attraction coefficient r, food reduction coefficient α and population movement coefficient according to the current number of iterations, and generate a random number σ in the range of [0,1] and a random number μ in the range of [1,4] for subsequent individual position updates. The calculation formula is:

[0184]

[0185] α=r(2σ-1)

[0186] β=r(2μ-1)

[0187] In the formula, is the population fitness of the optimal individual; t is the current number of iterations; T is the maximum number of iterations;

[0188] S304: If σ<ρ, the algorithm enters the exploration phase, and the formula for updating the position of the individual cane rat is:

[0189]

[0190] Where C is a random number defined within the boundary of the search space;

[0191] If σ≥ρ, the algorithm enters the development stage, and the formula for updating the position of the individual cane rat is:

[0192]

[0193] S305: Check the algorithm boundary conditions, calculate the updated fitness of the large cane rat individual population, and update the optimal individual X according to the fitness calculation results. k,j ;

[0194] S306: If t≥T, the algorithm is terminated and the optimal individual is output as the optimal solution of the model. Otherwise, it returns to S302 to continue iterating.

[0195] In one embodiment, the operation plan of the gas-electricity integrated energy system includes system operation costs, system carbon emissions, injection and production status and periodic reserves of the hydrogen storage unit, and hydrogen production and power of the power-to-hydrogen device.

[0196] In order to prove that the two-stage operation optimization method of the gas-electricity integrated energy system coupled with the hydrogen storage unit can effectively realize the fixed capacity configuration of the hydrogen storage unit and the adjustment of the operation strategy of the gas-electricity integrated energy system, an example study was carried out with reference to the setting scenario of a domestic gas-electricity integrated energy system.

[0197] The hydrogen electrolysis device considered in the example has a rated hydrogen production rate of about 4.21m at a rated power of 290kW and a load power of 10%. 3 / h(61.388Nm 3 / h), the parameters of the hydrogen storage unit are shown in Table 1, and the user's natural gas demand and electricity price within 24 hours are shown in Table 2.

[0198] Table 1 Summary of hydrogen storage tank parameters

[0199]

[0200] Table 2 Natural gas demand and electricity price of users within 24 hours

[0201]

[0202]

[0203] The carbon emission reduction coefficient w is set to 0.1, 0.3, 0.5, 0.7, 0.9 and 1.0 respectively, and the multi-objective constant capacity optimization model of the hydrogen storage unit is solved through the upper constant capacity optimization stage to form the optimal configuration scheme of the hydrogen storage unit as shown in Table 3. Figure 3 It can be seen that as the carbon reduction coefficient w increases, the system's carbon reduction target gradually increases, which means that more hydrogen is needed to replace the natural gas in the pipeline, resulting in the number of P2H devices and hydrogen storage tanks required to be installed in the system in the configuration plan gradually increasing, and the device scale and hydrogen storage tank capacity also gradually increasing; when the carbon reduction coefficient w is greater than 0.7, blindly installing a power-to-hydrogen device will not increase the emission reduction, so at this time, not only a power-to-hydrogen device but also a hydrogen storage tank is required. Because additional hydrogen is produced when electricity costs are low, when natural gas prices or power generation costs are high, the hydrogen stored in the hydrogen storage tank is extracted and injected into the natural gas system. Thereby achieving a higher emission reduction target.

[0204] Table 3 Optimal configuration of hydrogen storage unit

[0205]

[0206] Based on the configuration scheme when the carbon emission reduction coefficient w is 0.9, a gas-electric integrated energy system coupled with a hydrogen storage unit is constructed. The parameters of the gas turbine and conventional generator set in the system are shown in Table 4.

[0207] Table 4 Gas turbine parameters

[0208]

[0209]

[0210] In order to analyze the role of hydrogen storage unit in gas-electric integrated energy system, two scenarios are set for comparative analysis, and the two scenarios are named as follows: ① non-Tank-5% refers to the gas-electric integrated energy system installing a power-to-hydrogen device, but without considering the introduction of hydrogen storage tanks, hydrogen is injected at 5% of the natural gas volume flow in the pipe; ② Tank-5% refers to the gas-electric integrated energy system installing a power-to-hydrogen device, and installing the introduction of hydrogen storage tanks at the same time, and hydrogen is injected at 5% of the natural gas volume flow in the pipe. After the lower-level operation optimization stage, the model solves the operating cost distribution and emission reduction under the two scenarios as shown in Table 5. As can be seen from Table 5, after the installation of the hydrogen storage unit, the total operating cost of the system is 17.6909 million yuan, which is 5.96% lower than when only the power-to-hydrogen device is introduced. Among them, the gas source purchase cost is reduced by 71,900 yuan, the hydrogen sales income is increased to 688,900 yuan, and the wind abandonment penalty cost is reduced by 566,800 yuan, proving the economic feasibility of the optimization method.

[0211] Table 5 Distribution of operating costs and emission reduction under different scenarios

[0212]

[0213] Figure 3 The hourly hydrogen injection and production flow rate of the hydrogen storage unit and the change curve of the hydrogen storage unit tank storage are shown. Figure 4 It can be seen that the periods t1 to t6 and t21 to t24 are the stages of injecting hydrogen into the hydrogen storage unit for storage. This is because the amount of hydrogen produced by the power-to-hydrogen device during these periods exceeds the upper limit of the amount of hydrogen required in the pipeline, and the excess hydrogen enters the hydrogen storage tank unit for storage. Therefore, the tank storage of the hydrogen storage unit is also in a state of rising; and during the period t10 to t20, the hydrogen storage unit is in a state of extracting hydrogen. This is because there is no remaining wind energy to be used during these periods, the power-to-hydrogen device stops working, and the source of hydrogen in the pipeline depends on the hydrogen extracted from the hydrogen storage unit to meet the needs. Therefore, the tank storage of the hydrogen storage unit has been decreasing; at t7 to t9, the hydrogen storage unit does not work, that is, neither extracting nor injecting hydrogen. This is because the hydrogen contained in the hydrogen storage unit has reached its upper limit of volume at this time. The hydrogen produced by the power-to-hydrogen device is all injected into the pipeline and no longer enters the hydrogen storage unit, and its tank storage remains unchanged. At the end of a day's operation, there is still tank storage in the hydrogen storage unit, and there is still a considerable amount of hydrogen left to be sold.

[0214] Figure 4 and Figure 5The hydrogen flow rate injected into the natural gas pipeline in different scenarios is shown. In the non-Tank-5% scenario, hydrogen is injected into the pipeline only during the periods of t1 to t9 and t20 to t24. At t20, the hydrogen flow rate in the pipeline did not reach the upper limit of the hydrogen injection amount due to the low remaining wind energy. At other times, the hydrogen flow rate in the pipeline was 0. In the Tank-5% scenario, since the hydrogen storage unit stores additional hydrogen and injects it into the pipeline when there is no remaining wind power, the hourly hydrogen flow rate in the pipeline reaches the upper limit of its allowable injection. It can be seen that in the scenario with hydrogen storage units, more natural gas in the gas grid is replaced by hydrogen, which can reduce the carbon emissions of the system to a greater extent.

[0215] Figure 6 and Figure 7 The hydrogen production volume and power under different scenarios are shown respectively. At t1-t6 and t21-t24, when the hydrogen storage unit is present, the power-to-hydrogen device can produce more hydrogen at a higher operating power, which means that when the hydrogen storage unit is present, the power-to-hydrogen device can use more surplus electricity and improve the wind power absorption capacity of the integrated energy system. At t7-t9 and t20, the hydrogen production volume and power of the two scenarios are the same. This is because the tank storage in the hydrogen storage unit has reached the upper limit. To further increase the power of the power-to-hydrogen device, the hydrogen produced cannot be stored, so only the amount of hydrogen required by the pipeline is required at this time.

[0216] The above are only examples of specific implementations in this specification and are not intended to limit the embodiments of this specification. For those skilled in the art, various changes and variations may be made to the embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of this specification shall be included in the scope of the claims of the embodiments of this specification.

Claims

1. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit, characterized in that: The following steps are involved: S1: Obtain basic data of the gas-electricity integrated energy system coupled with the hydrogen storage unit; S2: In the upper-level fixed capacity optimization stage, the carbon emission reduction coefficient w is introduced to design a multi-objective fixed capacity optimization model for hydrogen storage units that takes carbon emissions into consideration; The carbon emission reduction coefficient w is used to characterize the degree of implementation of the emission reduction target; the objective function of the multi-objective constant capacity optimization model for the hydrogen storage unit includes minimizing the operating cost of the power-to-hydrogen unit and maximizing the user's carbon emission reduction, and the expressions are: Where N P2H is the number of power-to-hydrogen devices; C G is the unit replacement price of the power-to-hydrogen device; C Y is the unit operating price of the power-to-hydrogen device; β is the unit capital recovery coefficient of the power-to-hydrogen device; d is the annual operating time of the power-to-hydrogen device, which is 350 days; C D,t is the unit power generation price at time t; C N is the natural gas sales price; η is the electricity transmission cost coefficient; P t is the operating power of the power-to-hydrogen device at time t; λ is the natural gas emission factor; Q N，t is the volume flow rate of natural gas in the pipeline at time t; Q P，t is the volume flow rate of hydrogen in the pipeline at time t; The constraints of the multi-objective optimization model for hydrogen storage unit volume determination include power constraints of the power-to-hydrogen conversion device, hydrogen production constraints of the power-to-hydrogen conversion device, natural gas supply and demand balance constraints, hydrogen blending constraints, hydrogen production balance constraints, pipeline gas volume balance constraints, hydrogen storage tank operation status constraints, hydrogen storage tank inventory constraints and hydrogen storage unit capacity constraints; S3: Using the ε constraint method and the great cane rat optimization algorithm to solve the multi-objective constant capacity optimization model of the hydrogen storage unit, and form the optimal configuration plan of the hydrogen storage unit; S4: In the lower-level operation optimization stage, an operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit is designed; S5: The large cane rat optimization algorithm is used to solve the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit to form an operation plan for the gas-electricity integrated energy system.

2. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit as claimed in claim 1, characterized in that: The gas-electricity integrated energy system coupled with the hydrogen storage unit described in step S1 is composed of a natural gas unit, an electric power unit, an electric-to-hydrogen conversion device, a gas turbine and a hydrogen storage unit; The basic data include comprehensive gas-electricity energy structure data, user natural gas demand, user electricity demand, electricity transmission cost, electricity price, generator set operating parameters, power-to-hydrogen unit hydrogen production rate, hydrogen storage tank capacity, hydrogen storage tank unit construction cost and hydrogen storage unit inventory range.

3. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit as claimed in claim 1, characterized in that: The power constraint of the power-to-hydrogen device requires that the total operating power of the power-to-hydrogen device must be within the system limit, and the expression is: In the formula, The minimum operating power of the power-to-hydrogen device; is the maximum operating power of the power-to-hydrogen device; P P2H,t is the operating power of the power-to-hydrogen device at time t; The constraint expression of hydrogen production of the power-to-hydrogen device is: Q P2H，t =ρ×P P2H,t Where, ρ is the hydrogen conversion coefficient of the power-to-hydrogen device; Q P2H，t is the amount of hydrogen produced by the power-to-hydrogen device at time t; The natural gas supply and demand balance constraint stipulates that the total gas volume formed after the hydrogen generated by the power-to-hydrogen device is injected into the natural gas system should meet the user's hourly natural gas demand, expressed as: Q D,t =Q L,t +Q N，t In the formula, Q D,t is the natural gas demand of users at time t; Q L,t is the amount of hydrogen entering the pipeline at time t; Q N，t is the volume flow rate of natural gas in the pipeline at time t; The hydrogen blending constraint stipulates that the pipeline hydrogen injection amount is less than the maximum allowable hydrogen blending amount, and the expression is: In the formula, is the hydrogen doping ratio coefficient, which is 5%; The hydrogen production balance constraint stipulates that there is a balance between the amount of hydrogen produced by the power-to-hydrogen device and the amount of hydrogen entering the natural gas pipeline and the hydrogen storage unit, and the expression is: In the formula, is the amount of hydrogen entering the hydrogen storage unit at time t; The pipeline hydrogen balance constraint stipulates that the amount of hydrogen in the pipeline is equal to the sum of the hydrogen output of the hydrogen storage unit and the hydrogen output of the electric-to-hydrogen device, and the expression is: In the formula, Q PP,t is the amount of hydrogen directly input into the pipeline by the power-to-hydrogen conversion device at time t; is the amount of hydrogen directly input into the pipeline from the hydrogen storage unit at time t; The operating state constraint of the hydrogen storage tank stipulates the operating state of the hydrogen storage unit closing, gas injection and gas extraction, and the expression is: 0≤a t +b t ≤1 a t ∈{0,1} b t ∈{0,1} In the formula, a t is the decision variable for the process of injecting hydrogen into the hydrogen storage unit at time t. If it is 1, it means that hydrogen is injected into the hydrogen storage unit at time t, otherwise, the value is 0; b t is the decision variable of the process of extracting hydrogen from the hydrogen storage unit at time t; The hydrogen storage tank storage constraint stipulates that the total volume of hydrogen stored in the hydrogen storage unit should be equal to the volume of hydrogen in the hydrogen storage pipe at time t-1 plus the volume of hydrogen injected into the hydrogen storage tank at time t, expressed as: In the formula, S GC,t-1 is the hydrogen storage volume in the hydrogen storage unit at time t-1; S GC,t is the hydrogen stock in the hydrogen storage unit at time t; The hydrogen storage unit capacity constraint expression is: Where N g is the number of hydrogen storage tanks; The maximum tank capacity of a single hydrogen storage tank; It is the minimum tank capacity of a single hydrogen storage tank.

4. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit as claimed in claim 1, characterized in that: The ε constraint method described in S3 takes minimizing operating costs as the main objective function and converts the carbon emission target into a constraint condition; the optimal configuration plan of the hydrogen storage unit includes the scale and number of power-to-hydrogen devices, the capacity and number of hydrogen storage tanks, the operating cost of the power-to-hydrogen devices and the carbon emission reduction.

5. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit as claimed in claim 1, characterized in that: The operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit described in S4 takes the minimization of the operation cost of the gas-electricity integrated energy system as the objective function. The operation cost includes the gas source purchase cost, the power generation cost of the generator set, the wind abandonment penalty cost and the hydrogen sales income. The objective function expression is: In the formula, a g 、b g 、c g is the power generation cost coefficient of generator set g; P G,g,t The power provided by the conventional generator connected to node i at time t; C wc P is the wind power plant’s wind abandonment penalty coefficient; wc,k,t is the wind abandonment volume of wind power plant k at time t; The constraints of the operation optimization model of the gas-electricity integrated energy system coupled with the hydrogen storage unit include natural gas unit constraints, power unit constraints, hydrogen production constraints of the power-to-hydrogen device, and natural gas consumption constraints of the gas turbine; The natural gas unit constraints include node flow balance constraints, node pressure constraints and gas source supply constraints; The node flow balance constraint expression is: In the formula, Q GT,g,t is the active power converted by the gas turbine g at time t; The node pressure constraint expression is: In the formula, The upper pressure limit of node i; The lower limit of pressure at node i; The gas source supply quantity constraint expression is: In the formula, is the minimum gas supply volume of gas source node n; Q N,n,t is the gas supply volume of gas source node n at time t; is the maximum gas supply of gas source node n; The power unit constraints include node power balance constraints, line power constraints, generator set ramp constraints and wind abandonment constraints; The node power balance constraint expression is: Where P G,g,t P is the power provided by the conventional generator connected to node i at time t; w,k,t is the active power output of wind farm k at time t; P D,i,t is the power demand of the user at grid node i at time t; P i,j,t is the active power transmitted by the transmission line between node i and node j at time t; The line power constraint is expressed as: In the formula, is the maximum transmission power of transmission line i to j; is the minimum transmission power of transmission line i to j; The generator set climbing constraint is expressed as: Where P G,e,t-1 is the power generation of generator set g at time t-1; is the upper limit of the climbing slope of the generator set g; is the lower limit of the climbing slope of the generator set g; The wind abandonment constraint stipulates that when using wind energy for power generation, the amount of wind power that cannot be absorbed is regarded as abandoned wind power, and the abandoned wind power shall not exceed the total amount of wind power, expressed as: In the formula, is the available wind power of wind farm k at time t; The constraint expression of hydrogen production of the power-to-hydrogen device is: Q P2H =μ P2H P P2H,p,t In the formula, μ P2H P is the unit hydrogen production efficiency of the power-to-hydrogen device; P2H,p,t is the operating power of the power-to-hydrogen device p at time t; The gas turbine natural gas consumption constraint expression is: In the formula, μ GT,g is the conversion efficiency of the gas turbine g; Q GT,g,t is the active power converted by the gas turbine g at time t; H g is the calorific value of natural gas, which is 39MJ / m 3 .

6. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit as claimed in claim 1, characterized in that: The solution process of the cane rat optimization algorithm described in S3 and S5 includes: S301: Set the maximum number of iterations to T, the initial population size of cane rats to N, the GCR parameter ρ to 0.5, and randomly initialize in the algorithm search space to generate an initial population of cane rats, each of which represents a feasible solution to the optimization problem; S302: Calculate the fitness of the population according to the model objective function, determine the individual with the highest fitness as the optimal individual, and define its position in the solution space as x k,j , the remaining individuals update their positions according to the optimal individual, and the update formula is: In the formula, is the updated individual position; x i,j is the individual position before updating; S303: Calculate the food attraction coefficient r, food reduction coefficient α and population movement coefficient according to the current number of iterations, and generate a random number σ in the range of [0,1] and a random number μ in the range of [1,4] for subsequent individual position updates. The calculation formula is: α=r(2σ-1) β=r(2μ-1) In the formula, is the population fitness of the optimal individual; t is the current number of iterations; T is the maximum number of iterations; S304: If σ<ρ, the algorithm enters the exploration phase, and the formula for updating the position of the individual cane rat is: Where C is a random number defined within the boundary of the search space; If σ≥ρ, the algorithm enters the development stage, and the formula for updating the position of the individual cane rat is: S305: Check the algorithm boundary conditions, calculate the updated fitness of the large cane rat individual population, and update the optimal individual X according to the fitness calculation results. k,j ; S306: If t≥T, the algorithm is terminated and the optimal individual is output as the optimal solution of the model. Otherwise, it returns to S302 to continue iterating.

7. A two-stage operation optimization method for a gas-electricity integrated energy system coupled with a hydrogen storage unit as claimed in claim 1, characterized in that: The operation plan of the gas-electricity integrated energy system includes system operating costs, system carbon emissions, injection and production status of the hydrogen storage unit and periodic reserves, and hydrogen production and power of the power-to-hydrogen conversion device.

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