Capacity configuration method for park comprehensive energy system for efficient wind-solar hydrogen production

Abstract

The invention relates to a capacity configuration method for a park comprehensive energy system for efficient wind and light hydrogen production. The method comprises the following steps: determining factors influencing the hydrogen production efficiency in the hydrogen production process of a water electrolysis device; establishing a park comprehensive energy system mathematical model considering the influence of the equipment working temperature; constructing a function of annual investment cost and total operation cost of the wind-solar hydrogen production system; and solving the optimal configuration of the capacity of the hydrogen energy equipment in the park integrated energy system by using an improved CEEMDAN algorithm. The system operation characteristics are improved, the light abandoning phenomenon of the system is reduced, and the hydrogen energy storage system can effectively store excess wind and light electric power in the low-ebb electricity price period and release energy in the peak period, so that peak load shifting of the electric power is achieved, and the overall energy utilization efficiency and economical efficiency of the park are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of capacity configuration of wind-solar-hydrogen coupling systems, and in particular relates to a capacity configuration method for a park integrated energy system for efficient wind-solar-hydrogen production. Background Art

[0002] The energy transition from fossil fuels to zero-carbon technologies is an important measure to mitigate the impact of climate change. Wind and solar power generation will play a key role in this transition. In recent years, due to the rapid decline in production costs, the total installed capacity of photovoltaic and wind turbines has increased dramatically. However, wind and solar power have the intermittent characteristics, which makes power generation fluctuate considerably in the short and long term, which also limits the further development of renewable energy power generation.

[0003] In order to overcome the challenges of intermittent wind and solar power generation and improve the stability and economy of the energy system, it is particularly important to introduce hydrogen energy storage systems. Summary of the invention

[0004] In view of the deficiencies in the above-mentioned prior art, the present invention provides a capacity configuration method for a park integrated energy system for efficient wind-solar hydrogen production, the purpose of which is to improve the system operating characteristics, solve the volatility problems and abandoned light phenomenon of renewable energy power generation, and play a role in peak shaving and valley filling.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for configuring the capacity of a park integrated energy system for efficient wind-solar hydrogen production comprises the following steps:

[0007] Step 1, determining factors affecting hydrogen production efficiency in a hydrogen production process of a water electrolysis device;

[0008] Step 2: Establish a mathematical model of the park's integrated energy system that takes into account the impact of equipment operating temperature;

[0009] Step 3, construct the annual investment cost and total operating cost function of the wind-solar hydrogen production system;

[0010] Step 4: Use the improved CEEMDAN algorithm to solve the optimal configuration of hydrogen energy equipment capacity in the park's integrated energy system.

[0011] Furthermore, in step 1,

[0012] The factors affecting the hydrogen production efficiency during the hydrogen production process of the water electrolysis device include: the operating temperature and input power of the electrolytic cell. The equivalent circuit voltage calculation formula of the electrolytic chamber is as follows:

[0013] U Elec =U Rev +U Act +U Ohm

[0014] Among them, U Elec is the voltage across each electrolytic chamber; U Rev is the equilibrium voltage; U Act is the activation overvoltage; U Ohm It is the ohmic loss overvoltage;

[0015] The hydrogen production efficiency satisfies the following relationship:

[0016]

[0017] Among them, U HHV is the high heating value voltage of hydrogen; a, b, c are temperature coefficients, indicating the relationship between the operating temperature and U HHV The relationship between , T is the working temperature of the electrolytic cell;

[0018] Analyze the operating characteristics of the input and output ports of the electrolyzer and establish the power balance equation:

[0019]

[0020] in, is the electrical power input to the electrolyzer; P EC,e is the hydrogen power output by the electrolyzer.

[0021] Furthermore, in step 2, the mathematical model of the power generation system and the hydrogen energy system in the wind-solar hydrogen production and storage system includes: determining the overall operating characteristics of the system, clarifying the coupling relationship between the wind-solar power generation equipment, the hydrogen storage equipment and the hydrogen use equipment, clarifying the operating constraints of each device in the system and the system power balance equation, and establishing a mathematical model of the entire system based on this.

[0022] Furthermore, in step 2, the specific method is:

[0023] The wind-solar hydrogen energy storage system provides electricity to the entire system through wind turbines and solar photovoltaic panels. The wind turbines convert wind energy into electricity, and the solar photovoltaic panels absorb solar energy and convert it into electricity and store it in energy storage batteries.

[0024] The wind turbine converts wind energy into electrical energy. The power generation formula of the wind turbine is as follows:

[0025]

[0026] Among them, P WT is the power generated by the wind turbine, in W; ρ is the air density, in kg / m 3 ; A W is the leaf area in m 2 ; v is the actual wind speed at the input location, in m / s; C Pis the coefficient of wind energy utilization by the system, β is the power loss coefficient of wind turbine power generation, and its value is [0, 1];

[0027] The solar photovoltaic panel converts solar energy into electrical energy, and the calculation formula is as follows:

[0028]

[0029] Among them, P PV is the power generated by the solar photovoltaic panel, in W; f PV is the power derating factor, which is affected by factors such as equipment aging and cleanliness; P ref is the rated output power of the solar photovoltaic cell under standard conditions, in W; k is the power temperature coefficient;

[0030] Analyze the operating characteristics of the hydrogen storage tank, establish the charging and discharging model and constraint equations:

[0031]

[0032] in, is the energy storage capacity of the hydrogen storage tank; γ g is the correction coefficient of the hydrogen storage tank temperature, which corrects the capacity of the hydrogen storage tank at the previous moment according to the current temperature; η HES,chr , η HES,dis is the charging and discharging efficiency of the hydrogen storage tank; is the charging and discharging power of the hydrogen storage tank; It is the upper and lower limits of the ramp rate of the hydrogen storage tank charging power; It is the upper and lower limits of the ramp rate of the hydrogen storage tank’s energy release power;

[0033] The hydrogen-using equipment includes: a hydrogen fuel cell and a hydrogen methanation device; the mathematical model and constraint conditions of the hydrogen fuel cell meet the following requirements:

[0034]

[0035] in, It is the hydrogen energy input into the hydrogen fuel cell; is the hydrogen fuel cell electrical power conversion efficiency; γ T is the temperature correction factor, is the electricity generated by the hydrogen fuel cell; are the minimum and maximum values ​​of the input hydrogen energy respectively; It is the maximum and minimum value of the climbing rate of hydrogen energy;

[0036] The mathematical model and constraints of the hydrogen methanation unit meet the following requirements:

[0037]

[0038] in, are the gas production power and hydrogen consumption power of the hydrogen methanation device; π mol is the molar conversion coefficient of hydrogen to methane; η MR is the methanogenesis efficiency of the device; m CH4 is the amount of hydrogen input; It is the low calorific value of natural gas; are the minimum and maximum values ​​of hydrogen consumption power respectively; They are the minimum and maximum values ​​of the hydrogen consumption power ramp rate;

[0039] The relationship between the output power of the electric hydrogen production device and the input power of hydrogen energy storage, the input power of hydrogen fuel cell, and the input power of hydrogen methanation device is:

[0040]

[0041] Furthermore, in step 3, the annual investment and operating costs include: equipment investment cost, operation and maintenance cost, electricity purchase cost, gas purchase cost, loss cost and equipment start-up and shutdown cost, and the objective function is:

[0042] J ttl =J inv +J ope

[0043] J inv =C pv +C w +C elz +C ce +C cq +C qg +C hs +C bt

[0044] J ope =365×(C ope +C grid )

[0045] C ope =C ope,pv P pv +C ope,grid P pv,gird +C sh +C qt

[0046]

[0047] In the above formula, J inv represents the equipment investment cost; J ope represents the operating cost objective function; C pv represents the photovoltaic cost; C w represents the fan cost; Celz represents the cost of electrolytic cell; C ce Represents the cost of purchasing electricity; C cq Represents the gas purchase cost; C qg represents the cost of abandoned light; C hs represents the hydrogen storage cost; C bt represents the cost of electric energy storage; C ope represents the operating cost; C sh Represents the loss cost of the system; C qt represents the start-up and shutdown cost of the system; C grid+ represents the daily electricity purchase cost; C grid- Represents the daily electricity sales cost.

[0048] Furthermore, the step 4 is to use the improved CEEMAD iterative algorithm to solve the capacity allocation optimization model of the wind-solar hydrogen production and storage system considering the hydrogen production efficiency, and to calculate the cost J of the park's comprehensive energy system. ttl Minimization is the goal; for the original power Decompose and obtain the finite intrinsic mode function; calculate J through the cost formula of the park's comprehensive energy system ttl , and determine its corresponding mode function; introduce hydrogen production power η e , and according to the hydrogen power relationship between electric hydrogen production and input, solve the rated capacity of electric hydrogen production device, hydrogen fuel cell, hydrogen energy storage, and methanation device; calculate the economic cost of hydrogen energy storage system under different jm orders in turn; analyze and compare the economic cost and constraints of the park's comprehensive energy system to obtain the optimal order i=f; introduce the optimal order f into the capacity allocation optimization model of wind-solar hydrogen production and storage system for hydrogen production efficiency, and solve P EC,e ,

[0049]

[0050] Furthermore, the specific steps of step 4 are as follows:

[0051] 1) Calculate the local mean value through EMD and obtain the first residual value;

[0052] x k =x+(β0+n0)E1(w k )r1

[0053] r1=x k = <M(x k )>

[0054] In the above formula, x k is the local average; β0 is the signal-to-noise ratio between noise and analysis signal; n0 is the adjustable adaptive noise correction introduced to correct the error between white noise and signal according to the statistical characteristics of the original signal; w kis Gaussian white noise; E1(w k ) is an operator used to obtain the first mode of the modal component; M(x k ) is an operator that produces the local mean of the signal; r1 is the first residual value;

[0055] 2) In the first stage (i=1), the first mode is calculated;

[0056]

[0057] 3) The second residual value is estimated as the local average of r', and the second mode is defined. The second residual value is estimated as the local average of r';

[0058] r'=r1+(β1+n1)E2(w k )

[0059]

[0060] 4) Calculate the i-th residual value;

[0061] r i = <M(r i-1 +β i-1 E i (w k ))>

[0062] 5) Calculate the i-th mode;

[0063]

[0064] 6) Calculate the next residual value according to step 4);

[0065] 7) By adding all modal components and residual terms, the original signal time series can be obtained;

[0066]

[0067] In the above formula, x k is the local average; β is the signal-to-noise ratio between noise and analytical signal; w k is Gaussian white noise; E K (·) is an operator used to obtain the i-th mode of the modal component; M(·) is an operator that produces the local mean of the signal; r i is the i-th residual value; is the i-th mode; X(t) is the original signal time series; r n (t) is the residual modal component; is the global search coefficient.

[0068] Through the implementation of the above technical solution, the beneficial effects of the present invention are:

[0069] The present invention can reduce the phenomenon of abandoned solar power and improve the overall economic efficiency of the system. The penalty cost of abandoned solar power is introduced into the objective function of the system, and the optimal capacity configuration of hydrogen energy storage in the system is determined based on the annual investment and operating cost of the system.

[0070] The present invention introduces hydrogen production efficiency into the capacity allocation optimization model of the wind-solar hydrogen production and storage system, and analyzes the impact of the operating characteristics of the electric hydrogen production equipment on the hydrogen production efficiency, so as to improve the calculation speed and accuracy of the system hydrogen storage capacity configuration decision.

[0071] The present invention improves the system operation characteristics. The hydrogen energy storage system can effectively store excess wind and solar power during off-peak electricity price periods and release energy during peak periods, thereby achieving "peak shaving and valley filling" of electricity and improving the overall energy efficiency and economy of the park. Integrating the wind and solar power generation system with the hydrogen energy storage system can not only effectively solve the volatility problem of renewable energy generation, but also provide strong technical support for the transformation and upgrading of the energy structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 This is a schematic diagram of the structure of the wind-solar hydrogen production system in the park of the present invention;

[0073] Figure 2 It is a flow chart of the capacity configuration method of the wind-solar hydrogen production energy system of the present invention;

[0074] Figure 3 The present invention is an adaptive noise schematic diagram;

[0075] Figure 4 It is a schematic diagram of the improved CEEMDAN algorithm of the present invention. DETAILED DESCRIPTION

[0076] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention will be clearly and in detail described below in conjunction with the accompanying drawings and specific embodiments.

[0077] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0078] Refer to the following Figure 1-Figure 4 The technical solutions of some embodiments of the present invention are described.

[0079] The present invention is a method for configuring the capacity of a comprehensive energy system in a park for efficient wind and solar hydrogen production. Figure 1 As shown, Figure 1The wind-solar hydrogen production system of the present invention is a schematic diagram of the structure. The wind-solar hydrogen production system includes a wind-solar power generation system, an electric hydrogen production device, a hydrogen use device and an energy storage device. Figure 2 This is a flow chart of the capacity configuration method of the wind-solar hydrogen production energy system. First, a mathematical model of the wind-solar hydrogen production system is established, factors related to the efficiency of electric hydrogen production are analyzed, and a capacity optimization configuration model of the wind-solar hydrogen production system considering the hydrogen production efficiency is established. Then, the improved CEEMAD algorithm is used to solve the optimal capacity configuration of the wind-solar hydrogen production system. Figure 3 is a schematic diagram of the introduced adjustable adaptive noise. Figure 4 This is the schematic diagram of the improved CEEMDAN algorithm.

[0080] The present invention provides a method for optimizing the capacity configuration of an energy storage system considering the efficiency of photovoltaic hydrogen production, comprising the following steps:

[0081] Step 1. Determine the factors that affect the efficiency of hydrogen production in the hydrogen production process of the water electrolysis device.

[0082] The specific method is:

[0083] The water electrolysis device selects the proton exchange membrane electrolysis cell with the highest hydrogen production efficiency, considering that the electrolysis cell is composed of several electrolysis chambers connected in series. The operating characteristics of the water electrolysis device that affect the efficiency of hydrogen production include: the operating temperature and input power of the electrolysis cell. The equivalent circuit voltage calculation formula of the electrolysis chamber is as follows:

[0084] U Elec =U Rev +U Act +U Ohm

[0085] Among them, U Elec is the voltage across each electrolytic chamber; U Rev is the equilibrium voltage; U Act is the activation overvoltage; U Ohm It is the ohmic loss overvoltage.

[0086] The hydrogen production efficiency satisfies the following relationship:

[0087]

[0088] Among them, U HHV is the high heating value voltage of hydrogen; a, b, c are temperature systems, indicating the working temperature and U HHV The relationship between , T is the operating temperature of the electrolytic cell.

[0089] Analyze the operating characteristics of the input and output ports of the electrolyzer and establish the power balance equation:

[0090]

[0091] in, is the electrical power input to the electrolyzer; P EC,e is the hydrogen power output by the electrolyzer.

[0092] Step 2. The mathematical model of the power generation system and hydrogen energy system in the wind-solar hydrogen production system includes: determining the overall operating characteristics of the system, clarifying the coupling relationship between wind-solar power generation equipment, hydrogen storage equipment and hydrogen use equipment, clarifying the operating constraints of each device in the system and the system power balance equation, and establishing the mathematical model of the entire system based on this. The specific method is:

[0093] The wind-solar hydrogen energy storage system provides electricity to the entire system through wind turbines and solar photovoltaic panels. The wind turbine converts wind energy into electricity, and the solar photovoltaic panels absorb solar energy and convert it into electricity and store it in energy storage batteries.

[0094] The wind turbine converts wind energy into electrical energy. The power generation formula of the wind turbine is as follows:

[0095]

[0096] Among them, P WT W; ρ is the air density, unit is kg / m 3 ; A W is the blade area, in units; v is the actual wind speed at the input site, in units of m / s; C P is the coefficient of wind energy utilization by the system, and β is the power loss coefficient of wind turbine power generation, which takes a value of [0, 1].

[0097] The solar photovoltaic panel converts solar energy into electrical energy, and the calculation formula is as follows:

[0098]

[0099] Among them, P PV is the power generated by the solar photovoltaic panel, in W; f PV is the power derating factor, which is affected by factors such as equipment aging and cleanliness; P ref is the rated output power of the solar photovoltaic cell under standard conditions, in W; k is the power temperature coefficient.

[0100] Analyze the operating characteristics of the hydrogen storage tank, establish the charging and discharging model and constraint equations:

[0101]

[0102] in, is the energy storage capacity of the hydrogen storage tank; γ g It is the temperature correction system of the hydrogen storage tank, which corrects the capacity of the hydrogen storage tank at the previous moment according to the current temperature; η HES,chr , ηHES,dis is the charging and discharging efficiency of the hydrogen storage tank; is the charging and discharging power of the hydrogen storage tank; It is the upper and lower limits of the ramp rate of the hydrogen storage tank charging power; These are the upper and lower limits of the ramp rate of the hydrogen storage tank’s energy release power.

[0103] The hydrogen-using equipment includes: hydrogen fuel cells and hydrogen methanation devices. The mathematical model and constraints of hydrogen fuel cells meet the following requirements:

[0104]

[0105] in, It is the hydrogen energy input into the hydrogen fuel cell; is the hydrogen fuel cell electrical power conversion efficiency; γ T is the temperature correction factor, is the electricity generated by the hydrogen fuel cell; are the minimum and maximum values ​​of the input hydrogen energy respectively; These are the maximum and minimum values ​​of the ramp rate of hydrogen energy input.

[0106] The mathematical model and constraints of the hydrogen methanation unit meet the following requirements:

[0107] The relationship between the output power of the electric hydrogen production device and the input power of hydrogen energy storage, the input power of hydrogen fuel cell, and the input power of hydrogen methanation device is:

[0108]

[0109] Step 3. Establish the annual investment cost and total operating cost function of the wind-solar hydrogen production system.

[0110] The annual investment and operating costs include: equipment investment cost, operation and maintenance cost, electricity purchase cost, gas purchase cost, loss cost and equipment start-up and shutdown cost. The objective function is:

[0111] J ttl =J inv +J ope

[0112] J inv =C pv +C w +C elz +C ce +C cq +C qg +C hs +C bt

[0113] J ope =365×(C ope +C grid)

[0114] C ope =C ope,pv P pv +C ope,grid P pv,gird +C sh +C qt

[0115]

[0116] In the above formula, J inv represents the equipment investment cost; J ope represents the operating cost objective function; C pv represents the photovoltaic cost; C w represents the fan cost; C elz represents the cost of electrolytic cell; C ce Represents the cost of purchasing electricity; C cq Represents the gas purchase cost; C qg represents the cost of abandoned light; C hs represents the hydrogen storage cost; C bt represents the cost of electric energy storage; C ope represents the operating cost; C sh Represents the loss cost of the system; C qt represents the start-up and shutdown cost of the system; C grid+ represents the daily electricity purchase cost; C grid- Represents the daily electricity sales cost.

[0117] Step 4. The improved CEEMAD iterative algorithm refers to a fully integrated empirical mode decomposition algorithm with adaptive noise. The basic idea is to decompose complex signals into finite intrinsic mode functions by data characteristics. Adjustable adaptive noise is added, and the residual of each model is estimated to calculate the next mode. The specific steps are as follows:

[0118] 1) Calculate the local mean value through EMD and obtain the first residual value;

[0119] x k =x+(β0+n0)E1(w k )r1

[0120] r1=x k = <M(x k )>

[0121] In the above formula, x k is the local average; β0 is the signal-to-noise ratio between noise and analysis signal; n0 is the introduced adjustable adaptive noise; w k is Gaussian white noise; E1(w k ) is an operator used to obtain the first mode of the modal component; M(xk )It is an operator that produces the local mean of the signal; r1 is the first residual value.

[0122] 2) In the first stage (i=1), the first mode is calculated;

[0123]

[0124] 3) The second residual value is estimated as the local average of r', and the second mode is defined. The second residual value is estimated as the local average of r';

[0125] r'=r1+(β1+n1)E2(w k )

[0126]

[0127] 4) Calculate the i-th residual value;

[0128] r i = <M(r i-1 +β i-1 E i (w k ))>

[0129] 5) Calculate the i-th mode;

[0130]

[0131] 6) Calculate the next residual value according to step 4).

[0132] 7) By adding all modal components and residual terms, the original signal time series can be obtained.

[0133]

[0134] In the above formula, x k β0n0w k is Gaussian white noise; E1(w k ) is an operator used to obtain the first mode of the modal component; M(x k ) is an operator that produces the local mean of the signal; r1 is the first residual value.

[0135] The improved CEEMAD iterative algorithm is used to solve the capacity allocation optimization model of the wind-solar hydrogen production and storage system considering the hydrogen production efficiency. ttl The goal is to minimize the original power. Decompose and obtain the finite intrinsic mode function; calculate J through the cost formula of the park's comprehensive energy system ttl , and determine its corresponding mode function; introduce hydrogen production power ηe , and according to the hydrogen power relationship between electric hydrogen production and input, solve the rated capacity of electric hydrogen production device, hydrogen fuel cell, hydrogen energy storage, and methanation device; calculate the economic cost of hydrogen energy storage system under different jm orders in turn; analyze and compare the economic cost and constraints of the park's comprehensive energy system to obtain the optimal order i=f; introduce the optimal order f into the capacity allocation optimization model of wind-solar hydrogen production and storage system for hydrogen production efficiency, and solve P EC,e ,

[0136]

[0137] It should be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprising a reference structure" do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0138] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for configuring the capacity of a comprehensive energy system for efficient wind and solar hydrogen production in a park, characterized in that The following steps are involved: Step 1, determining factors affecting hydrogen production efficiency in a hydrogen production process of a water electrolysis device; Step 2: Establish a mathematical model of the park's integrated energy system that takes into account the impact of equipment operating temperature; Step 3, construct the annual investment cost and total operating cost function of the wind-solar hydrogen production system; Step 4: Use the improved CEEMDAN algorithm to solve the optimal configuration of hydrogen energy equipment capacity in the park's integrated energy system.

2. The method for configuring the capacity of a comprehensive energy system for a park with high efficiency of hydrogen production from wind and solar power according to claim 1 is characterized in that In the step 1, The factors affecting the hydrogen production efficiency during the hydrogen production process of the water electrolysis device include: the operating temperature and input power of the electrolytic cell. The equivalent circuit voltage calculation formula of the electrolytic chamber is as follows: IN Elec =U Rev +U Act +U Ohm Among them, U Elec is the voltage across each electrolytic chamber; U Rev is the equilibrium voltage; U Act is the activation overvoltage; U Ohm It is the ohmic loss overvoltage; The hydrogen production efficiency satisfies the following relationship: Among them, U HHV is the high heating value voltage of hydrogen; a, b, c are temperature coefficients, indicating the relationship between the operating temperature and U HHV The relationship between , T is the working temperature of the electrolytic cell; Analyze the operating characteristics of the input and output ports of the electrolyzer and establish the power balance equation: in, is the electrical power input to the electrolyzer; P EC,e is the hydrogen power output by the electrolyzer.

3. The method for configuring the capacity of a comprehensive energy system for a park with high efficiency of hydrogen production from wind and solar power according to claim 1 is characterized in that In step 2, the mathematical model of the power generation system and the hydrogen energy system in the wind-solar hydrogen production and storage system includes: determining the overall operating characteristics of the system, clarifying the coupling relationship between the wind-solar power generation equipment, the hydrogen storage equipment and the hydrogen use equipment, clarifying the operating constraints of each device in the system and the system power balance equation, and establishing a mathematical model of the entire system based on this.

4. The method for configuring the capacity of a park integrated energy system for efficient wind-solar hydrogen production according to claim 3 is characterized in that In the step 2, the specific method is: The wind-solar hydrogen energy storage system provides electricity to the entire system through wind turbines and solar photovoltaic panels. The wind turbines convert wind energy into electricity, and the solar photovoltaic panels absorb solar energy and convert it into electricity and store it in energy storage batteries. The wind turbine converts wind energy into electrical energy. The power generation formula of the wind turbine is as follows: Among them, P WT is the power generated by the wind turbine, in W; ρ is the air density, in kg / m 3 ; A W is the leaf area in m 2 ; v is the actual wind speed at the input location, in m / s; C P is the coefficient of wind energy utilization by the system, β is the power loss coefficient of wind turbine power generation, and its value is [0, 1]; The solar photovoltaic panel converts solar energy into electrical energy, and the calculation formula is as follows: Among them, P PV is the power generated by the solar photovoltaic panel, in W; f PV is the power derating factor, which is affected by factors such as equipment aging and cleanliness; P ref is the rated output power of the solar photovoltaic cell under standard conditions, in W; k is the power temperature coefficient; Analyze the operating characteristics of the hydrogen storage tank, establish the charging and discharging model and constraint equations: in, is the energy storage capacity of the hydrogen storage tank; γ g is the correction coefficient of the hydrogen storage tank temperature, which corrects the capacity of the hydrogen storage tank at the previous moment according to the current temperature; η HES,chr , η HES,dis is the charging and discharging efficiency of the hydrogen storage tank; is the charging and discharging power of the hydrogen storage tank; It is the upper and lower limits of the ramp rate of the hydrogen storage tank charging power; It is the upper and lower limits of the ramp rate of the hydrogen storage tank’s energy release power; The hydrogen-using equipment includes: a hydrogen fuel cell and a hydrogen methanation device; the mathematical model and constraint conditions of the hydrogen fuel cell meet the following requirements: in, It is the hydrogen energy input into the hydrogen fuel cell; is the hydrogen fuel cell electrical power conversion efficiency; γ T is the temperature correction factor, is the electricity generated by the hydrogen fuel cell; are the minimum and maximum values ​​of the input hydrogen energy respectively; It is the maximum and minimum value of the climbing rate of hydrogen energy; The mathematical model and constraints of the hydrogen methanation unit meet the following requirements: in, are the gas production power and hydrogen consumption power of the hydrogen methanation device; π mol is the molar conversion coefficient of hydrogen to methane; η MR is the methanogenesis efficiency of the device; m CH4 is the amount of hydrogen input; It is the low calorific value of natural gas; are the minimum and maximum values ​​of hydrogen consumption power respectively; They are the minimum and maximum values ​​of the hydrogen consumption power ramp rate; The relationship between the output power of the electric hydrogen production device and the input power of hydrogen energy storage, the input power of hydrogen fuel cell, and the input power of hydrogen methanation device is:

5. The method for configuring the capacity of a comprehensive energy system for a park with high efficiency of hydrogen production from wind and solar power according to claim 1 is characterized in that In step 3, the annual investment and operating costs include: equipment investment cost, operation and maintenance cost, electricity purchase cost, gas purchase cost, loss cost and equipment start-up and shutdown cost. The objective function is: mice ttl =J inv +J ope J inv =C pv +C w +C elz +C ce +C cq +C qg +C hs +C bt J ope =365×(C ope +C grid ) C ope =C ope,pv P pv +C ope,grid P pv,gird +C sh +C qt In the above formula, J inv represents the equipment investment cost; J ope represents the operating cost objective function; C pv represents the photovoltaic cost; C w represents the fan cost; C elz represents the cost of electrolytic cell; C ce Represents the cost of purchasing electricity; C cq Represents the gas purchase cost; C qg represents the cost of abandoned light; C hs represents the hydrogen energy storage cost; C bt represents the cost of electric energy storage; C ope Indicates the operating cost; C sh Represents the loss cost of the system; C qt represents the start-up and shutdown cost of the system; C grid+ represents the daily electricity purchase cost; C grid- Represents the daily electricity sales cost.

6. The method for configuring the capacity of a comprehensive energy system for a park with high efficiency of hydrogen production from wind and solar power according to claim 1 is characterized in that Step 4 is to use the improved CEEMAD iterative algorithm to solve the capacity allocation optimization model of the wind-solar hydrogen production and storage system considering the hydrogen production efficiency, and to calculate the cost J of the park's comprehensive energy system. ttl Minimization is the goal; for the original power Decompose and obtain the finite intrinsic mode function; calculate J through the cost formula of the park's comprehensive energy system ttl , and determine its corresponding mode function; introduce hydrogen production power η e , and according to the hydrogen power relationship between electric hydrogen production and input, solve the rated capacity of electric hydrogen production device, hydrogen fuel cell, hydrogen energy storage, and methanation device; calculate the economic cost of hydrogen energy storage system under different jm orders in turn; analyze and compare the economic cost and constraints of the park's comprehensive energy system to obtain the optimal order i=f; introduce the optimal order f into the capacity allocation optimization model of wind-solar hydrogen production and storage system for hydrogen production efficiency, and solve P EC,e , 7. The method for configuring the capacity of a park integrated energy system for efficient wind-solar hydrogen production according to claim 6 is characterized in that The specific steps of step 4 are as follows: 1) Calculate the local mean value through EMD and obtain the first residual value; x k =x+(β0+n0)E1(w k )r1 r1=x k =<M(x k )> In the above formula, x k is the local average; β0 is the signal-to-noise ratio between noise and analysis signal; n0 is the adjustable adaptive noise correction introduced to correct the error between white noise and signal according to the statistical characteristics of the original signal; w k is Gaussian white noise; E1(w k ) is an operator used to obtain the first mode of the modal component; M(x k ) is an operator that produces the local mean of the signal; r1 is the first residual value; 2) In the first stage (i=1), the first mode is calculated; 3) The second residual value is estimated as the local average of r', and the second mode is defined. The second residual value is estimated as the local average of r'; r'=r1+(β1+n1)E2(w k ) 4) Calculate the i-th residual value; r i h <M(r i-1 +β i-1 E i (w k ))> 5) Calculate the i-th mode; 6) Calculate the next residual value according to step 4); 7) By adding all modal components and residual terms, the original signal time series can be obtained; In the above formula, x k is the local average; β is the signal-to-noise ratio between noise and analytical signal; w k is Gaussian white noise; E K (·) is an operator used to obtain the i-th mode of the modal component; M(·) is an operator that produces the local mean of the signal; r i is the i-th residual value; is the i-th mode; X(t) is the original signal time series; r n (t) is the residual modal component; is the global search coefficient.

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