Multi-objective optimization scheduling method for comprehensive stable hydrogen production system considering exergy analysis

Abstract

The present invention discloses a multi-objective optimization scheduling method for a comprehensive stable hydrogen production system taking into account analysis, which belongs to the field of electrical engineering. The method includes: establishing the relationship between the feed and output of the hydrogen production element according to the mass balance relationship and energy balance relationship of the hydrogen production element; establishing the mass balance equation and energy balance equation of the compression element and the heat exchange element; establishing the balance equation of each element; establishing the operation constraints of the hydrogen production element, the operation constraints of the energy storage element and the stable hydrogen production constraints; establishing a multi-objective optimization scheduling model with the goal of minimizing the total loss of the system and minimizing the total operating cost, and obtaining an optimization problem including the multi-objective optimization scheduling model and system constraints; linearizing the system constraints and scalarizing the multi-objective optimization scheduling model; solving the optimization problem after processing to obtain the optimal scheduling solution. While ensuring the green and stable hydrogen supply, the energy quality of the system is improved.

Description

Technical Field

[0001] The present invention belongs to the field of electrical engineering, and more specifically, to a method for Analyzed multi-objective optimization scheduling method for comprehensive stable hydrogen production system. Background Art

[0002] Hydrogen is the green secondary energy with the greatest development potential. At present, fossil fuels are still the main source of hydrogen, which will cause a lot of pollution and cannot meet the requirements of sustainable development. Using renewable energy to produce hydrogen is an important means to reduce carbon emissions. However, renewable energy is highly volatile and uncertain. How to ensure a stable supply of hydrogen is a problem that needs to be solved. In response to the problem of stable hydrogen production, existing studies have proposed a comprehensive hydrogen production system that couples multiple hydrogen production technologies to provide a solution for providing green and stable hydrogen.

[0003] The integrated hydrogen production system undertakes the important task of improving energy utilization efficiency. At present, most of the energy utilization indicators such as energy efficiency are proposed based on the first law of thermodynamics, which only considers the quantity of energy but not the quality of energy. It is a thermodynamic parameter based on the second law of thermodynamics, taking into account both the quantity and quality of energy. The analysis can reveal the size, location and influencing factors of energy quality loss, which is conducive to achieving energy quality matching and cascade utilization. There is still little research on the analysis of the system. In the integrated energy system, the constraints are mostly established based on the energy flow of the system, and the system modeling is completed by combining the output of the system components and their constraints. In addition, the current optimization goals are mostly to improve the economy and environmental protection of the system, but there is a lack of optimization from the perspective of The operation strategy is evaluated and analyzed from the perspective of Summary of the invention

[0004] In view of the defects and improvement needs of the prior art, the present invention provides a The purpose of the multi-objective optimization scheduling method for the comprehensive stable hydrogen production system analyzed is to solve the problem that the current optimization problem lacks consideration of the differences in quality of various forms of energy, resulting in poor overall performance of the system.

[0005] To achieve the above object, according to one aspect of the present invention, a method is provided that The multi-objective optimization scheduling method for the comprehensive stable hydrogen production system analyzed is as follows: the system includes hydrogen production elements, energy storage elements, compression elements and heat exchange elements, and the method includes: S1, according to the mass balance relationship and energy balance relationship of the hydrogen production elements, the relationship between the feed and the output of the hydrogen production elements is established; the mass balance equation and energy balance equation of the compression element and the heat exchange element are established; the hydrogen production element, the compression element and the heat exchange element are established Balance equation; S2, establish the operation constraints of hydrogen production components and energy storage components; establish stable hydrogen production constraints to make the sum of the hydrogen production of each hydrogen production module in the hydrogen production component within the stable hydrogen production range; S3, based on the total system With the goal of minimizing losses and minimizing total operating costs, a multi-objective optimization scheduling model is established to obtain an optimization problem including the multi-objective optimization scheduling model and system constraints. The system constraints include the relationships and equations established in S1 and the constraints established in S2. S4, linearizes the system constraints and scalarizes the multi-objective optimization scheduling model. S5, solves the processed optimization problem to obtain the optimal scheduling solution.

[0006] Furthermore, the hydrogen production element includes a water electrolysis hydrogen production module, a biomass gasification hydrogen production module and a natural gas reforming hydrogen production module, wherein the water electrolysis hydrogen production module The equilibrium equation is:

[0007]

[0008] in, They are the water intake, hydrogen production, and oxygen production of the water electrolysis hydrogen production module. They are water, hydrogen and oxygen in the water electrolysis hydrogen production module. The electricity consumed by the water electrolysis hydrogen production module, For water electrolysis hydrogen production module loss.

[0009] Furthermore, the biomass gasification hydrogen production module The equilibrium equation is:

[0010]

[0011] in,

[0012] is the biomass particle feed amount of the biomass gasification hydrogen production module, They are respectively the oxygen consumption, hydrogen production, carbon dioxide production, carbon monoxide production, and methane production of the biomass gasification hydrogen production module, ex BG , ex BG_CO , They are respectively the biomass, oxygen, hydrogen, carbon dioxide, carbon monoxide and methane in the biomass gasification hydrogen production module. Biomass gasification hydrogen production module loss.

[0013] Furthermore, the natural gas reforming hydrogen production module The equilibrium equation is:

[0014]

[0015] in, is the natural gas feed rate of the natural gas reforming hydrogen production module, They are the oxygen consumption, water consumption, water vapor production, hydrogen production, and carbon dioxide production of the natural gas reforming hydrogen production module, ex NGR , They are natural gas, oxygen, inlet water, outlet water, hydrogen and carbon dioxide of the natural gas reforming hydrogen production module. For natural gas reforming hydrogen production module loss.

[0016] Furthermore, the hydrogen production element includes a water electrolysis hydrogen production module, a biomass gasification hydrogen production module and a natural gas reforming hydrogen production module, the energy storage element includes an electricity storage device and an oxygen storage device, the compression element includes a compressor and a turbine, the heat exchange element includes a heat exchanger and a condenser, and the system is generally The loss is:

[0017]

[0018] in, For the system loss, For water electrolysis hydrogen production module loss, Biomass gasification hydrogen production module loss, For natural gas reforming hydrogen production module loss, For compressor loss, For turbine loss, For condenser loss.

[0019] Furthermore, the linearization processing in S4 refers to linearizing each bilinear term in the system constraints separately, specifically including: fitting one of the bilinear terms to a function linearly related to the temperature, and binary expanding the temperature in the function; and linearizing the bilinear term after the binary expansion using the big M method.

[0020] Furthermore, the bilinear term is When balancing bilinear terms, the linearized The balanced bilinear term is:

[0021]

[0022]

[0023]

[0024] in, is the amount of substance Y in the X element, is the feed amount, consumption or output of substance Y, any element other than the energy storage element in the X element system; ex X_Y is the Y substance in the X element k Y , b Y are the slope and intercept of the fitting, ΔT X The minimum adjustable unit of X element temperature control, N Bin is the number of digits in the binary expansion, is a variable of 0 or 1, M is a constant,

[0025] Furthermore, the multi-objective optimization scheduling model after scalarization is performed as follows:

[0026]

[0027]

[0028]

[0029] in, is the weight vector, is the vector of two objective functions, for Loss weight, λ Eco is the operating cost weight, For the system loss, is the total operating cost of the system.

[0030] Furthermore, the optimal scheduling scheme includes: the feed amount of the hydrogen production element and the heat exchange rate of the heat exchange element; after S5, it also includes: controlling the feed amount of the hydrogen production element and the heat exchange rate of the heat exchange element according to the optimal scheduling scheme.

[0031] According to another aspect of the present invention, a computer readable storage medium is provided on which a computer program is stored. When the program is executed by a processor, the above-mentioned calculation and Analyzed multi-objective optimization scheduling method for comprehensive stable hydrogen production system.

[0032] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects:

[0033] (1) Comprehensively consider the mass balance, energy balance and Balance, build considerations The multi-objective optimization scheduling model of the comprehensive stable hydrogen production system is analyzed to minimize the operating cost and system The goal is to minimize the loss, and it can take into account the overall system on the basis of the traditional economic dispatch model. While ensuring green and stable hydrogen supply, identify the weak links in energy use within the comprehensive hydrogen production system, select scheduling plans with better comprehensive performance in terms of economy and energy efficiency, improve the energy quality of the system, and provide a reference for the development and construction of an efficient and high-quality energy system;

[0034] (2) The original nonlinear problem is transformed into a mixed integer linear programming problem by a linearization method, and the objective function of the multi-objective problem is processed by a scalarization method, which makes it easy to directly use existing software to solve the optimization scheduling model. The difficulty of solving the problem is reduced while ensuring the accuracy of the solution, making the principle of the method clear and easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The embodiment of the present invention provides Flow chart of the multi-objective optimization scheduling method for the analyzed comprehensive stable hydrogen production system;

[0036] Figure 2 A structural diagram of a comprehensive stable hydrogen production system provided by an embodiment of the present invention;

[0037] Figure 3 The Pareto frontier of multi-objective optimization scheduling of the comprehensive stable hydrogen production system provided in the embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0039] In the present invention, the terms "first", "second", etc. (if any) in the present invention and the accompanying drawings are used to distinguish similar objects but not necessarily to describe a specific order or sequence.

[0040] Figure 1 The embodiment of the present invention provides Flow chart of the multi-objective optimization scheduling method for the comprehensive stable hydrogen production system analyzed. Figure 1 , combined with Figure 2-Figure 3, in this embodiment, The multi-objective optimization scheduling method of the analyzed comprehensive stable hydrogen production system is described in detail, and the method includes operation S1-operation S5.

[0041] Operation S1, according to the mass balance relationship and energy balance relationship of the hydrogen production element, establish the relationship between the feed and the output of the hydrogen production element; establish the mass balance equation and energy balance equation of the compression element and the heat exchange element; establish the hydrogen production element, the compression element and the heat exchange element Balance the equations.

[0042] The integrated stable hydrogen production system includes hydrogen production components, energy storage components, compression components and heat exchange components. The hydrogen production components include water electrolysis hydrogen production modules, biomass gasification hydrogen production modules and natural gas reforming hydrogen production modules; the energy storage components include power storage devices and oxygen storage devices; the compression components include compressors and turbines; and the heat exchange components include heat exchangers and condensers. The structure of the integrated stable hydrogen production system is as follows: Figure 2 shown.

[0043] Generally, for steady-state processes, the mass balance and energy balance equations can be written as follows:

[0044]

[0045]

[0046] in, are the mass flow rates of inlet and outlet materials, respectively, h in 、h out are the enthalpy of the inlet and outlet substances, is the thermal power, For power.

[0047] Ignoring the effects of the system's kinetic energy and potential energy, the The calculation of ex is shown in formula (3):

[0048] ex=ex ph +ex ch (3)

[0049]

[0050]

[0051] Among them, ex ph 、ex ch The physics of matter Chemical T0 is the standard condition, R is the ideal gas constant, e 0,i The standard chemical x i is the mole fraction of substance i,

[0052] 1) Water electrolysis hydrogen production module

[0053] The proton exchange membrane water electrolysis hydrogen production device has the characteristics of wide range of operating current density, fast start and stop, flexible power regulation, etc., and is highly adaptable to fluctuating and intermittent power sources, and is easy to combine with renewable energy sources such as wind and light. Therefore, this embodiment is based on proton exchange membrane electrolysis technology for research. The constraint relationship established based on mass balance and energy balance in the water electrolysis hydrogen production module includes formulas (6)-(11). Formula (6) is the power balance constraint of the water electrolysis hydrogen production module; formula (7) is the relationship between the power of the electrolyzer and the voltage and current; formula (8) is the composition of the electrolyzer voltage drop; formula (9) is the relationship between the electrolyzer current and the current density; formulas (10)-(11) are the calculated hydrogen production and oxygen production of the water electrolysis hydrogen production module.

[0054]

[0055]

[0056]

[0057]

[0058]

[0059]

[0060] in, is the photovoltaic power generation, is the abandoned light power, is the power stored in the storage device, To store the released electrical energy, The compressor consumes electrical energy. is the power provided to the water electrolysis hydrogen production module, k1 is the first unit conversion factor (W→MW), is the number of electrolysis chambers, is the working voltage of the water electrolysis hydrogen production module, is the working current of the electrolytic cell, E is the Nernst voltage, is the ohmic overvoltage, is the activation overvoltage, U rev is the reversible voltage, T cell is the operating temperature of the electrolytic cell, F is the Faraday constant, is the hydrogen partial pressure, is the partial pressure of oxygen, is the activity of water, R cell is the internal equivalent ohmic resistance, is the current density of the water electrolysis unit at time t, α anis the anode charge transfer coefficient, i an is the anode current density, α cat is the cathode charge transfer coefficient, i cat is the cathode current density, A cell is the effective reaction area, k2 is the second unit conversion factor (mol / s→Nm 3 / s), h F is the Faraday efficiency.

[0061] Water electrolysis hydrogen production module The equilibrium equation is:

[0062]

[0063] in, They are the water intake, hydrogen production, and oxygen production of the water electrolysis hydrogen production module. They are water, hydrogen and oxygen in the water electrolysis hydrogen production module. The electricity consumed by the water electrolysis hydrogen production module, For water electrolysis hydrogen production module loss.

[0064] 2) Biomass gasification hydrogen production module

[0065] The constraint relationships established based on mass balance and energy balance in the biomass gasification hydrogen production module include equations (13)-(17).

[0066]

[0067]

[0068]

[0069]

[0070]

[0071] in, c CO_BG They are the hydrogen production coefficient, oxygen consumption coefficient, methane production coefficient, carbon dioxide production coefficient, and carbon monoxide production coefficient of the biomass gasification hydrogen production module.

[0072] Biomass gasification hydrogen production module The equilibrium equation is:

[0073]

[0074] in, is the biomass particle feed amount of the biomass gasification hydrogen production module, They are respectively the oxygen consumption, hydrogen production, carbon dioxide production, carbon monoxide production, and methane production of the biomass gasification hydrogen production module, ex BG , ex BG_CO , They are respectively the biomass, oxygen, hydrogen, carbon dioxide, carbon monoxide and methane in the biomass gasification hydrogen production module. Biomass gasification hydrogen production module loss.

[0075] 3) Natural gas reforming hydrogen production module

[0076] The constraint relationships established based on mass balance and energy balance in the natural gas reforming hydrogen production module include equations (19)-(24).

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] in, They are the hydrogen production coefficient, oxygen consumption coefficient, water consumption coefficient, water production coefficient and carbon dioxide production coefficient of the natural gas reforming hydrogen production module respectively.

[0084] Natural gas reforming hydrogen production module The equilibrium equation is:

[0085]

[0086] in, is the natural gas feed rate of the natural gas reforming hydrogen production module, They are the oxygen consumption, water consumption, water vapor production, hydrogen production, and carbon dioxide production of the natural gas reforming hydrogen production module, ex NGR , They are natural gas, oxygen, inlet water, outlet water, hydrogen and carbon dioxide of the natural gas reforming hydrogen production module. For natural gas reforming hydrogen production module loss.

[0087] 4) Heat exchanger

[0088] The mass balance equation is:

[0089]

[0090]

[0091] in, are the mass flow rates of the thermal fluid inflow and outflow, are the mass flow rates of the cold fluid flowing in and out, respectively.

[0092] The energy balance equation is:

[0093]

[0094] Among them, h HE_hot_in 、h HE_cold_in are the enthalpy of the hot fluid and the cold fluid flowing in, respectively, h HE_hot_out 、h HE_cold_out are the enthalpies of the outflowing hot fluid and the outflowing cold fluid respectively.

[0095] The equilibrium equation is:

[0096]

[0097] Among them, ex HE_hot_in 、ex HE_cold_in The inflow of hot fluid and cold fluid are Value, ex HE_hot_out 、ex HE _cold_out The outflowing hot fluid and cold fluid are value.

[0098] 5) Condenser

[0099] The mass balance equation is:

[0100]

[0101] in, are the mass flow rates of substances flowing into and out of the condenser, respectively.

[0102] The energy balance equation is:

[0103]

[0104] Among them, h COOL_in 、h COOL_out are the enthalpy of the fluid flowing into and out of the condenser, respectively. The heat energy released by the condenser.

[0105] The equilibrium equation is:

[0106]

[0107] Among them, ex COOL_in 、ex COOL_out The flow rate of the fluid flowing into and out of the condenser is T0 is the temperature under standard conditions, T COOL is the condenser outlet temperature, For condenser loss.

[0108] 6) Compressor

[0109] The mass balance equation is:

[0110]

[0111] in, are the mass flow rates of the fluid flowing into and out of the compressor respectively.

[0112] The energy balance equation is:

[0113]

[0114] Among them, h COM_in 、h COM_out are the enthalpy of the fluid flowing into and out of the compressor, respectively. The electrical energy consumed by the compressor.

[0115] The equilibrium equation is:

[0116]

[0117] Among them, ex COM_in 、ex COM_out The fluid flowing into and out of the compressor For compressor loss.

[0118] 7)Turbine

[0119] The mass balance equation is:

[0120]

[0121] in, are the mass flow rates of the fluid flowing into and out of the turbine respectively.

[0122] The energy balance equation is:

[0123]

[0124] Among them, h TUR_in 、h TUR_out are the enthalpy of the fluid flowing into and out of the turbine, The mechanical energy generated by the turbine.

[0125] The equilibrium equation is:

[0126]

[0127] Among them, ex TUR_in 、ex TUR_out The fluids flowing into and out of the turbine are For turbine loss.

[0128] Operation S2, establishing the operation constraints of the hydrogen production element and the energy storage element; establishing the stable hydrogen production constraints so that the sum of the hydrogen production amounts of the hydrogen production modules in the hydrogen production element is within the stable hydrogen production range.

[0129] The operating constraints of hydrogen production components include:

[0130]

[0131] |R t -R t-1 |≤s t ΔR max +(1-s t )R max (40)

[0132] Among them, s t is the start and stop state of the hydrogen production element at time t, R is the feed rate of the unit, ΔR max is the maximum climbing vector of the hydrogen production element, R max , R min are the maximum and minimum output of the hydrogen production element, R t is the unit feed rate at time t. Formula (39) is the upper and lower limit constraints of the hydrogen production element output, and formula (40) is the output change constraint of the hydrogen production element in the time period.

[0133] The operating constraints of the energy storage device in the energy storage element include:

[0134]

[0135]

[0136]

[0137]

[0138]

[0139] Among them, η ES is the charging and discharging efficiency coefficient of the power storage device, is the capacity of the storage device at time t, is the upper limit of the capacity of the power storage device, is a 0-1 variable indicating the state of the power storage device at time t, It is the upper limit of storage / discharge power of the power storage device.

[0140] The operating constraints of the oxygen storage device in the energy storage element include:

[0141]

[0142]

[0143]

[0144]

[0145]

[0146] in, is the capacity of the oxygen storage device at time t, are the amount of oxygen stored and released by the oxygen storage device at time t, is the upper limit of the capacity of the oxygen storage device, is a 0-1 variable indicating the state of the oxygen storage device at time t, The upper limit of the rate at which oxygen can be stored / released from the oxygen storage device.

[0147] The constraints for stable hydrogen production include:

[0148]

[0149] in, It is a stable hydrogen production range.

[0150] Operation S3, with system total With the goal of minimizing losses and minimizing total operating costs, a multi-objective optimization scheduling model is established, and an optimization problem including the multi-objective optimization scheduling model and system constraints is obtained. The system constraints include the relationships and equations established in operation S1 and the constraints established in operation S2.

[0151] According to an embodiment of the present invention, the system The loss is:

[0152]

[0153] in, For the system loss, For water electrolysis hydrogen production module loss, for

[0154] Biomass gasification hydrogen production module loss, For natural gas reforming hydrogen production module loss, For compressor loss, For turbine loss, For condenser loss.

[0155] Total system operating cost for:

[0156]

[0157] in, is the unit price of biomass pellets, is the unit natural gas price, c ele For electricity price.

[0158] Multi-objective optimization scheduling model and The system constraints include equations (6) to (51).

[0159] Operation S4 is to linearize the system constraints and scalarize the multi-objective optimization scheduling model.

[0160] According to an embodiment of the present invention, the linearization processing in operation S4 refers to linearizing each bilinear term in the system constraint separately, specifically including: fitting one of the bilinear terms as a function linearly related to the temperature, and binary expanding the temperature in the function; and linearizing the bilinear term after the binary expansion using the big M method.

[0161] The bilinear term is The product terms in the equilibrium and energy balance are nonlinear terms, such as Bilinear Terms in Equilibrium

[0162] wait.

[0163] The bilinear term is As an example, the balanced bilinear term is linearized. The balanced bilinear term is:

[0164]

[0165]

[0166]

[0167] in, is the amount of substance Y in the X element, is the feed amount, consumption or output of substance Y, any element other than the energy storage element in the X element system; ex X_Y is the Y substance in the X element k Y , b Y are the slope and intercept of the fitting, ΔT X The minimum adjustable unit of X element temperature control, N Bin is the number of digits in the binary expansion, is a variable of 0 or 1, M is a constant, The X element is any one of a hydrogen production element, a compression element and a heat exchange element, and the Y substance is The substances involved in the balanced equation.

[0168] by For example, discuss The treatment method of bilinear terms in the equilibrium and energy balance equations. First, Fitting is a function of temperature, as shown in formula (57), and the temperature is binary expanded as shown in formula (58):

[0169]

[0170]

[0171] Considering that temperature control usually has a minimum unit, such as 10°C, equation (58) is reasonable. Substituting into equations (57)-(58), It can be expressed as formula (59), through binary expansion, a new bilinear term is introduced It can be linearized using the big M method, as shown in equations (60)-(61).

[0172]

[0173]

[0174]

[0175] The nonlinear terms in the system constraints mainly appear in the output constraints of the water electrolysis hydrogen production module, The nonlinear constraints lead to computational difficulties, so the nonlinear terms are linearized and the original nonlinear nonconvex optimization model is converted into a mixed integer linear programming model.

[0176] The output constraints of the water electrolysis hydrogen production module are piecewise linearized:

[0177]

[0178]

[0179]

[0180]

[0181]

[0182]

[0183] Among them, N is the total number of segments, g n 、h n is the main coefficient and constant coefficient of each segment, δ n,t is the state variable corresponding to each segment, is the inflection point of each segmented independent variable.

[0184] Scalarization is a standard technique for finding the Pareto frontier of vector optimization (multi-objective optimization) problems. For convex optimization problems, when the weight vector λ composed of multi-objective weights is non-negative, the scalarization method can obtain the optimal solution on all Pareto frontiers. In this embodiment, the multi-objective optimization scheduling model after scalarization is performed as follows:

[0185]

[0186]

[0187]

[0188] in, is the weight vector, is the vector of two objective functions, for Loss weight, λ Eco is the operating cost weight, For the system loss, is the total operating cost of the system. By traversing the weight λ Eco , we can find the optimal solution on all Pareto fronts.

[0189] Operation S5 is to solve the processed optimization problem and obtain the optimal scheduling solution.

[0190] Preferably, the processed optimization problem can be solved by commercial software GUROBI based on the MATLAB platform to obtain the optimal scheduling solution for the comprehensive stable hydrogen production system that takes into account both economy and energy efficiency.

[0191] According to an embodiment of the present invention, the optimal scheduling scheme includes: the feed amount of the hydrogen production element and the heat exchange rate of the heat exchange element. After operation S5, it also includes: controlling the feed amount of the hydrogen production element and the heat exchange rate of the heat exchange element according to the optimal scheduling scheme.

[0192] use Figure 2 The structure of the comprehensive stable hydrogen production system is shown, and the performance of the method provided in this embodiment is verified based on the parameters shown in Table 1. The computing environment is Win10 system, the CPU is AMD Ryzen 7PRO 4750U, the main frequency is 1.7GHz, the memory is 16GBRAM, Matlab R2022b is used to implement the proposed model, and the commercial software Gurobi is called for solution.

[0193] Table 1

[0194]

[0195] Compared with only cost as the goal, only The multi-objective optimization results with loss as the target and considering both at the same time illustrate the effectiveness of the model in this embodiment. The optimized scheduling results of the comprehensive stable hydrogen production system obtained by solving are shown in Table 2. The Pareto frontier obtained by interpolation fitting based on the Pareto optimal solution is shown in Figure 3 shown.

[0196] Table 2

[0197]

[0198] When only considering economic objectives, the system The loss differs from the minimum value by 12.85MW, accounting for 32% of the total loss. When only considering the energy efficiency target, the operating cost differs from the minimum cost by $839.51, accounting for 21%. The proposed method effectively balances the two aspects of economy and energy efficiency.

[0199] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the multi-objective optimization scheduling method for a comprehensive stable hydrogen production system taking into account the #imgpt286# analysis as described above is implemented.

[0200] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A consideration The multi-objective optimization scheduling method for the comprehensive stable hydrogen production system analyzed is characterized by: The system includes a hydrogen production element, an energy storage element, a compression element and a heat exchange element, and the method includes: S1. According to the mass balance relationship and energy balance relationship of the hydrogen production element, the relationship between the feed and output of the hydrogen production element is established; the mass balance equation and energy balance equation of the compression element and the heat exchange element are established; the Balance equations; S2, establishing operation constraints of the hydrogen production element and the energy storage element; establishing stable hydrogen production constraints so that the sum of the hydrogen production amounts of each hydrogen production module in the hydrogen production element is within the stable hydrogen production range; S3, based on the system total With the goal of minimizing losses and minimizing total operating costs, a multi-objective optimization scheduling model is established to obtain an optimization problem including the multi-objective optimization scheduling model and system constraints, wherein the system constraints include the relationships and equations established in S1 and the constraints established in S2; S4, performing linearization processing on the system constraints and scalarization processing on the multi-objective optimization scheduling model; S5, solving the processed optimization problem to obtain the optimal scheduling solution; Among them, the hydrogen production components include water electrolysis hydrogen production module, biomass gasification hydrogen production module and natural gas reforming hydrogen production module; The water electrolysis hydrogen production module The equilibrium equation is: in, They are the water intake, hydrogen production, and oxygen production of the water electrolysis hydrogen production module. They are water, hydrogen and oxygen in the water electrolysis hydrogen production module. , The electricity consumed by the water electrolysis hydrogen production module, For water electrolysis hydrogen production module loss; The biomass gasification hydrogen production module The equilibrium equation is: in, is the biomass particle feed amount of the biomass gasification hydrogen production module, They are respectively the oxygen consumption, hydrogen production, carbon dioxide production, carbon monoxide production, and methane production of the biomass gasification hydrogen production module, ex BG , ex BG_CO , They are respectively the biomass, oxygen, hydrogen, carbon dioxide, carbon monoxide and methane in the biomass gasification hydrogen production module. , Biomass gasification hydrogen production module loss; The natural gas reforming hydrogen production module The equilibrium equation is: in, is the natural gas feed rate of the natural gas reforming hydrogen production module, They are the oxygen consumption, water consumption, water vapor production, hydrogen production, and carbon dioxide production of the natural gas reforming hydrogen production module, ex NGR , They are natural gas, oxygen, inlet water, outlet water, hydrogen and carbon dioxide of the natural gas reforming hydrogen production module. , For natural gas reforming hydrogen production module loss; The stable hydrogen production constraint is: k2 is the second unit conversion factor (mol / s→Nm 3 / s), It is a stable hydrogen production range.

2. The method according to claim 1, characterized in that The hydrogen production components include water electrolysis hydrogen production module, biomass gasification hydrogen production module and natural gas reforming hydrogen production module, the energy storage components include power storage devices and oxygen storage devices, the compression components include compressors and turbines, the heat exchange components include heat exchangers and condensers, and the system is The loss is: in, For the system loss, For water electrolysis hydrogen production module loss, Biomass gasification hydrogen production module loss, For natural gas reforming hydrogen production module loss, For compressor loss, For turbine loss, For condenser loss.

3. The method according to claim 1, characterized in that The linearization processing in S4 refers to performing linearization processing on each bilinear term in the system constraint, specifically including: Fitting one of the bilinear terms to a function that is linearly related to temperature, and performing binary expansion on the temperature in the function; The big-M method is used to linearize the bilinear terms after binary expansion.

4. The method according to claim 3, characterized in that The bilinear term is When balancing bilinear terms, the linearized The balanced bilinear term is: in, is the amount of substance Y in the X element, is the feed amount, consumption or output of substance Y, any element other than the energy storage element in the X element system; ex X_Y is the Y substance in the X element ;k Y , b Y are the slope and intercept of the fitting, △T X The minimum adjustable unit of X element temperature control, N Bin is the number of digits in the binary expansion, is a variable of 0 or 1, M is a constant, 5. The method according to claim 1, characterized in that The multi-objective optimization scheduling model after scalarization is as follows: in, is the weight vector, is the vector of two objective functions, for Loss weight, λ Eco is the operating cost weight, For the system loss, is the total operating cost of the system.

6. The method according to any one of claims 1 to 5, characterized in that: The optimal scheduling scheme includes: the feed rate of the hydrogen production element and the heat exchange rate of the heat exchange element; After S5, the method further includes: controlling the feed amount of the hydrogen production element and the heat exchange rate of the heat exchange element according to the optimal scheduling scheme.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the calculation according to any one of claims 1 to 6 is realized. Analyzed multi-objective optimization scheduling method for comprehensive stable hydrogen production system.

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