Intelligent flexible carbon scheduling system adapted to industrial load based on improved Warhawk optimizer

Abstract

The present invention discloses an intelligent flexible carbon dispatching system adapted to industrial loads based on an improved war hawk optimizer, including a photovoltaic array, a wind turbine, a DC / AC converter, an electrolytic cell, a hydrogen storage tank, a user supply end, a hydrogen fuel cell, a carbon emission metering module, an intelligent carbon emission dispatching center, a power grid, and a DC / DC converter; the generated voltage is converted into a fixed voltage through a DC / AC converter and output to the power grid, and the excess electricity is decomposed into hydrogen through an electrolytic cell and input into the hydrogen storage tank; when the power of the power grid cannot be met, hydrogen is used as an output material to generate electricity for the hydrogen fuel cell, and the fixed voltage is output through a DC / DC converter and transmitted to the power grid; the carbon emissions generated by photovoltaic power generation are calculated in real time through an intelligent carbon emission dispatching center, and the current carbon emission price, hydrogen storage capacity, and the price of hydrogen and electricity are calculated. The present invention can greatly reduce the emission of carbon dioxide and reduce the harm caused by the greenhouse effect, and can also alleviate the problem of the gradual depletion of primary energy.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-energy utilization, and in particular to an intelligent flexible carbon scheduling system for adapting to industrial loads based on an improved Warhawk optimizer. Background Art

[0002] Energy depletion and environmental pollution have become problems that today's society has to face and urgently needs to solve. New energy systems have gradually become the mainstream of social development energy. With the depletion of primary energy and the greenhouse effect caused by the combustion of primary energy, the production capacity modules in the existing scheduling technology still mainly use primary energy as the power generation module. The proportion of new energy use is relatively low, and it cannot respond well to the dual-carbon policy promulgated and implemented by the country. At the same time, in the dual-carbon and dual-reduction environment, carbon emissions have gradually shown an increasingly important position. At present, the focus of the energy scheduling system is mainly on energy consumption scheduling. The present invention, combined with the current environment, belongs to the first innovative technical content of carbon scheduling technology for dual-carbon and dual-reduction in the field. There is currently no similar technology.

[0003] The existing energy consumption dispatching systems mainly include the following two types: Virtual power plant optimization dispatching can call output and electric and thermal load forecast values ​​to meet the market's maximum operating benefits and user satisfaction. The energy dispatching of the base station photovoltaic diesel power supply system consists of a photovoltaic power generation system, energy storage batteries, and a diesel generator system in order to maximize the use of solar energy and minimize operating costs.

[0004] The above two energy systems have various problems, and they cannot make good use of various new energy sources to maximize value creation. The first optimization scheduling system has the following problems: facing the problem of primary energy depletion, the use of primary energy should be minimized and the utilization rate of renewable energy should be increased. The use of fuel not only accelerates the depletion of primary energy, but also generates gases that cause considerable pollution and damage to the current environment and greenhouse effect; the second optimization scheduling system has problems: other types of new energy power generation systems should be added to vigorously develop clean energy to replace diesel generators and maximize the use of new energy.

[0005] Therefore, an intelligent and flexible carbon scheduling system is needed, which can not only make full use of clean energy to delay the depletion of primary energy, but also improve energy utilization, break through the bottleneck of traditional corporate energy supply ignoring the value of carbon scheduling, and realize the recycling of hydrogen energy. It has pioneered the invention of an intelligent carbon scheduling method that can adapt to the latest low-carbon policies to plan the energy supply distribution and operation logic of the enterprise. Summary of the invention

[0006] Purpose of the invention: In view of the problems existing in the prior art, the present invention provides an intelligent flexible carbon scheduling system based on the improved Warhawk optimizer that adapts to industrial loads, which can greatly reduce carbon dioxide emissions and alleviate the harm caused by the greenhouse effect, while also alleviating the problem of gradual depletion of primary energy.

[0007] Technical solution: The present invention provides an intelligent flexible carbon dispatching system adapted to industrial loads based on an improved Warhawk optimizer, including a photovoltaic array, a wind turbine, a DC / AC converter, an electrolytic cell, a hydrogen storage tank, a user supply end, a hydrogen fuel cell, a carbon emission metering module, an intelligent carbon emission dispatching center, a power grid, and a DC / DC converter;

[0008] The output ends of the photovoltaic array and the wind turbine are connected to the output end of the DC / AC converter and the input end of the carbon emission metering module; the output end of the carbon emission metering module is connected to the input end of the intelligent carbon emission dispatching center, the output end of the DC / AC converter connected to the output end of the photovoltaic array and the wind turbine is connected to the output end of the power grid, the output end of the electrolytic cell is connected to the output end of the hydrogen storage tank, the output end of the hydrogen storage tank is connected to the input and output ends of the hydrogen fuel cell on one side and to the input end of the user supply end on the other side; the output end of the hydrogen fuel cell is connected to the output end of the DC / DC converter, and the output end of the DC / DC converter is connected to the input end of the power grid; the input end of the intelligent carbon emission dispatching center is connected to the output ends of the power grid and the user supply end.

[0009] Furthermore, the photovoltaic array and wind turbine generator set are composed of multiple solar panels and rotating blades. When the blades are exposed to sunlight and the wind blows the blades, the solar panels absorb sunlight and convert solar radiation into electrical energy directly or indirectly through the photoelectric effect or the photochemical effect. The wind drives the windmill blades to rotate, and then the speed of rotation is increased through the speed increaser to prompt the generator to generate electricity. The electrical energy generated by the two is converted into an effective fixed output voltage through a DC / AC converter to be transmitted to the power plant for power supply. When there is excess electricity generated by new energy power generation, the excess electricity is transported to the electrolytic cell to be decomposed into hydrogen and transported to the hydrogen storage tank for storage. When the hydrogen user needs to use hydrogen, the hydrogen in the hydrogen storage tank is transported to the hydrogen user. In addition, when the new energy power generation cannot meet the power generation grid, the hydrogen in the hydrogen storage tank is used as a power generation material to be transported to the hydrogen fuel cell to generate electricity. The generated electricity is converted into a fixed effective voltage through a DC / DC converter and transported to the power grid to meet the power supply demand.

[0010] Furthermore, wind turbines and photovoltaic arrays are connected to the carbon emission metering module, which calculates the carbon dioxide generated by wind and solar power generation in real time and transmits the production capacity to the power grid; the power grid is connected to the intelligent carbon emission dispatching center, and the other end is connected to the electrolytic cell to produce redundant power and hydrogen. One end of the electrolytic cell is also connected to the carbon emission metering module. The carbon dioxide generated in the process of water electrolysis is calculated in real time by the carbon emission metering module, and the hydrogen produced by power generation is flexibly controlled and transmitted to the user end which is also connected to the intelligent carbon emission dispatching center; the intelligent carbon emission dispatching center calculates the carbon dioxide generated by the company's self-consumption in real time. While meeting the company's low-carbon operation, the intelligent carbon emission dispatching center calculates the current power generation, hydrogen production, unit price of electricity, unit price of hydrogen and carbon emission capacity of the carbon emission metering module, and calculates the income from power generation and hydrogen production and the income from selling the remaining carbon emissions.

[0011] Furthermore, the implementation process of the intelligent carbon emission dispatching center is as follows:

[0012] S1: Improve initialization, initialize the corresponding benefits of each optimized eagle population; each improved eagle population has a set of corresponding values ​​of the objective function, and the initialization process is improved by using Logistic chaos mapping;

[0013] S2: Calculate the fitness of each population, that is, the objective function. The objective function is the optimal benefit value of the system. The calculation formula is as follows:

[0014]

[0015] C=αC self +βC H +χC grid +δC money

[0016] Where:

[0017]

[0018] Among them, C is carbon emissions, and F is the optimal profit under the lowest carbon emissions. The optimal profit is the maximum profit of "electricity * unit price of electricity + hydrogen volume * unit price of hydrogen" and the sales price of the remaining carbon emissions. The larger the F value, the better, and the smaller the C value is subject to constraints, the better;

[0019] S3: In the process of searching for prey, the war eagle expands the search range by soaring vertically. The expression for hunting birds in flight is as follows:

[0020]

[0021] Where X(t) and X(t+1) represent the individual positions of the AO algorithm in the tth iteration and the t+1th iteration, respectively, including the objective functions F and C. best (t) represents the best individual obtained by the algorithm up to the tth iteration, that is, the maximum profit of selling electric hydrogen compared with carbon emissions, X m (t) represents the average position of the population at the tth iteration, and T represents the maximum number of iterations of the algorithm. The eagle continuously seeks the best way to approach the prey, and when the prey is captured, it is the optimal reward.

[0022] S4: When the eagle finds prey in the sky, it will circle around the target prey in a spiral, prepare to land, and then attack. The expression is:

[0023]

[0024] Where Levy(D) represents the Levy flight distribution strategy, s is a constant, and u and v are random numbers between 0 and 1;

[0025]

[0026] Z, W represent the shape of the eagle during the flight according to the capture memory, and the fast flight according to the capture memory to approach the prey, that is, the objective functions F and C:

[0027] w=a×tan(θ)

[0028] z=a×cot(θ)

[0029] a=a 1 +D×U 1

[0030] θ=-ω×D 1 +θ 1

[0031]

[0032] Where r is the search step length, ranging from 1 to 20, U is 0.00565, and w is 0.005;

[0033] S5: When the Eagle is in the prey area and ready to land and attack, it will take a vertical descent to make a preliminary attack and get closer to the prey. The expression is:

[0034]

[0035] In the formula, α and β represent development adjustment parameters, which take smaller values;

[0036] S6: The eagle approaches the prey and launches a random attack on the prey. The prey that receives the attack is the target function. The expression of walking and grabbing the prey is:

[0037]

[0038] Where AB represents the quality function value used to balance the search strategy, Z1 represents the various movements of AO in the process of tracking prey, that is, the local optimal solution and the global optimal solution, and Z2 represents the linearly decreasing flight slope value, ranging from [0,2]. The calculation formula of the relevant parameters is as follows:

[0039]

[0040] Z 1 =2×rand()-1

[0041]

[0042] S7: Determine whether the maximum number of iterations has been reached. If yes, proceed to S8; if not, return to S4;

[0043] S8: Output the optimal profit strategy suitable for the system.

[0044] Furthermore, the process of improving the initialization process by using Logistic chaotic mapping is as follows:

[0045] Logistic chaotic mapping has the function of making the system in a chaotic state and achieving the ultimate uniformity of mapping distribution. The specific formula is as follows:

[0046] X n+1 =βX n (1-X n )

[0047] In the formula, X n ∈[0,1]; β∈[0,3] is the Logistic parameter.

[0048] Beneficial effects: Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. The electricity generated by the photovoltaic array and the wind turbine is converted into an effective fixed output voltage through a DC / AC converter and transmitted to the power plant for power supply. When there is excess electricity generated by renewable energy power generation, the excess electricity is transmitted to the electrolytic cell to be decomposed into hydrogen and transmitted to the hydrogen storage tank for storage. When the hydrogen user needs hydrogen, the hydrogen in the hydrogen storage tank can be transmitted to the hydrogen user. In addition, when renewable energy power generation cannot meet the needs of the power plant, the hydrogen in the hydrogen storage tank can be used as a power generation material and transmitted to the hydrogen fuel cell to generate electricity. The generated electricity is converted into a fixed effective voltage through a DC / DC converter and transmitted to the power plant to meet the power supply needs.

[0050] 2. Based on the calculation of the current power generation, hydrogen production, unit price of electricity, unit price of hydrogen and carbon emission capacity of the carbon emission storage tank by the intelligent carbon emission dispatching center, the income obtained from power generation and hydrogen production is compared with the income obtained from selling the remaining carbon emissions. If the current market government's requirements for carbon emissions are lowered, some factories may be in short supply of carbon emissions required for combustion power generation. At this time, when the income obtained from selling carbon emissions is greater than the income from power generation and hydrogen production by the system, the carbon emissions are sold to obtain the maximum income. If the opposite is true, continue to generate electricity and produce hydrogen, which can not only meet its own electricity needs but also sell for profit. This design effectively reduces carbon dioxide emissions and promotes the country to achieve its dual carbon goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the framework of the present invention;

[0052] Figure 2 Classify the carbon emissions of each module during operation;

[0053] Figure 3 A flow chart of the improved Warhawk algorithm used by the carbon emission dispatch center proposed in the present invention to achieve intelligent control;

[0054] Figure 4 A price map for a comparative regional power grid using the present invention;

[0055] Figure 5 A comparison chart of the carbon emission utilization rate and the carbon emission selling utilization rate using the present invention;

[0056] Figure 6 The load self-satisfaction rate curve diagram of the present invention is shown in FIG. DETAILED DESCRIPTION

[0057] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0058] The present invention discloses an intelligent flexible carbon scheduling system for industrial load adaptation based on an improved warhawk optimizer, such as Figure 1As shown, it includes photovoltaic arrays, wind turbines, DC / AC converters, electrolytic cells, hydrogen storage tanks, user supply ends, hydrogen fuel cells, carbon emission metering modules, intelligent carbon emission dispatching centers, power grids, and DC / DC converters.

[0059] The output ends of the photovoltaic array and the wind turbine are connected to the output end of the DC / AC converter and the input end of the carbon emission metering module, the output end of the carbon emission storage tank is connected to the input end of the intelligent carbon emission dispatching center, the output end of the DC / AC converter connected to the output end of the photovoltaic array and the wind turbine is connected to the output end of the power grid, the output end of the electrolytic cell is connected to the output end of the hydrogen storage tank, the output end of the hydrogen storage tank is connected to the input and output ends of the hydrogen fuel cell on one side and to the input end of the user supply end on the other side, the output end of the hydrogen fuel cell is connected to the output end of the DC / DC converter, the output end of the DC / DC converter is connected to the input end of the power grid, and the input end of the intelligent carbon emission dispatching center is connected to the output end of the power grid and the output end of the user supply end.

[0060] Photovoltaic arrays and wind turbines are composed of multiple solar panels and rotating blades. When exposed to sunlight and the wind blows the blades, the solar panels absorb sunlight and convert solar radiation directly or indirectly into electrical energy through the photoelectric effect or photochemical effect. The wind drives the windmill blades to rotate, and then the speed of rotation is increased through the speed increaser to prompt the generator to generate electricity. The electricity generated by the two is converted from the input voltage to an effective fixed output voltage through the DC / AC converter and transmitted to the power grid for power supply. When there is excess electricity generated by renewable energy power generation, the excess electricity is delivered to the electrolytic cell to be decomposed into hydrogen and transported to the hydrogen storage tank for storage. When the user supply side needs to use hydrogen, the hydrogen in the hydrogen storage tank can be delivered to the user supply side. In addition, when renewable energy power generation cannot meet the power grid, the hydrogen in the hydrogen storage tank can be used as a power generation material to be delivered to the hydrogen fuel cell to generate electricity. The generated electricity is converted into a fixed effective voltage through the DC / DC11 converter and transmitted to the power grid to meet the power supply needs.

[0061] One end of the green energy wind and solar power generation module composed of photovoltaic arrays and wind turbines is connected to the carbon emission metering module, which calculates the carbon dioxide generated by wind and solar power generation in real time. The module mainly transmits the production capacity to the power grid, which is connected to the intelligent carbon emission dispatching center. The other end is connected to the electrolytic cell to produce redundant hydrogen through power generation. One end of the electrolytic cell is also connected to the carbon emission metering module. The carbon dioxide generated in the process of water electrolysis is calculated in real time by the carbon emission metering module. The hydrogen produced by power generation is flexibly controlled and delivered to the user end, which is also connected to the intelligent carbon emission dispatching center; the intelligent carbon emission dispatching center also controls the carbon dioxide generated by the company's self-consumption in real time. Carbon oxides, while meeting the low-carbon operation of the enterprise, the system calculates the income from power generation and hydrogen production and the income from selling the remaining carbon emissions based on the calculation of the current power generation, hydrogen production, unit price of electricity, unit price of hydrogen and the carbon emission capacity of the carbon emission metering module by the intelligent carbon emission dispatching center. If the current market government's requirements for carbon emissions are lowered, some factories may be in short supply of carbon emissions required for combustion power generation, and at this time the income from selling carbon emissions is greater than the income from power generation and hydrogen production by the system, then selling carbon emissions can not only meet the low-carbon operation of the enterprise but also enable the enterprise to obtain profits.

[0062] like Figure 2 As shown, according to the calculation of the carbon emission dispatching center, when wind and solar power generation is used for self-consumption (i.e. daily electricity consumption within the company), the carbon emissions produced are at a relatively low stage, that is, low carbon. When the electricity generated by new energy is transmitted to the power grid to obtain income, the carbon emissions of wind and solar power generation are also relatively low, that is, low carbon. When there is excess electricity, water will be electrolyzed to produce hydrogen, which will be stored in hydrogen storage tanks and transported to the user supply end. Water electrolysis to produce hydrogen does not produce carbon dioxide, which is low carbon. When the carbon emission dispatching center calculates that the profit obtained by selling carbon emissions is the optimal profit, the use of carbon emissions after being sold will consume a lot of energy, which is high carbon.

[0063] The present invention uses the improved Warhawk algorithm controller (intelligent carbon emission dispatch center) to output the optimal benefit, such as Figure 3 As shown, it mainly includes the following steps:

[0064] Step 1: Improve initialization, initialize the corresponding benefits of each optimized eagle population; each improved eagle population has a set of corresponding values ​​of the objective function, and the initialization process is improved by using Logistic chaotic mapping. Logistic chaotic mapping has the function of making the system in a chaotic state, and the mapping distribution uniformity reaches the extreme. The specific formula is as follows:

[0065] X n+1 =βX n (1-X n )

[0066] Where: X n∈[0,1]; β∈[0,3] is the Logistic parameter.

[0067] Step 2: Calculate the fitness of each population, that is, the objective function. The objective function is the optimal benefit value of the system. The calculation formula is as follows:

[0068]

[0069] C-=αC self +βC H +χC grid +δC money

[0070] Where:

[0071]

[0072] Optimal profit = the maximum profit among (electricity quantity * unit price of electricity + hydrogen quantity * unit price of hydrogen) and the sales price of the remaining carbon emissions. The larger the F value, the better, and the smaller the C value is subject to constraints, the better.

[0073] Step 3: The eagle expands its search range by soaring vertically while searching for prey. The expression for hunting birds in flight is as follows:

[0074]

[0075] Where X(t) and X(t+1) represent the individual positions of the AO algorithm in the tth iteration and the t+1th iteration, respectively, including the objective functions F and C. best (t) represents the best individual obtained by the algorithm up to the tth iteration (i.e., the maximum profit from selling electric hydrogen compared with carbon emissions, the current optimal F value), X m (t) represents the average position of the population at the tth iteration, and T represents the maximum number of iterations of the algorithm. The eagle continuously seeks the best way to get closer to the prey, and when it catches the prey, it is the optimal reward.

[0076] Step 4: When the eagle finds prey in the sky, it will circle around the target prey in a spiral, prepare to land, and then attack. The expression is:

[0077]

[0078] Where Levy(D) represents the Levy flight distribution strategy, s is a constant, which is 0.01, and u and v are random numbers between 0 and 1;

[0079]

[0080] Z, W represent the shape of the eagle in the process of flight according to the capture memory, and the fast flight according to the capture memory to approach the prey, that is, the objective function F and C:

[0081] w=a×tan(θ)

[0082] z=a×cot(θ)

[0083] a=a 1 +D×U 1

[0084] θ=-ω×D 1 +θ 1

[0085]

[0086] Where r is the search step size, ranging from 1 to 20, U is 0.00565, and w is 0.005.

[0087] Step 5: When the eagle is in the prey area and ready to land and attack, it will take a vertical descent to make a preliminary attack and get closer to the prey (i.e., the objective function) as follows:

[0088]

[0089] Where α and β represent development adjustment parameters and take smaller values ​​(0.1).

[0090] Step 6: The eagle approaches the prey and launches a random attack on the prey. The prey that receives the attack is the target function. The expression of walking and grabbing the prey is:

[0091]

[0092] Where AB(t) represents the quality function value used to balance the search strategy, Z1 represents the various movements of AO in the process of tracking prey (i.e., local optimal solution and global optimal solution), and Z2 represents the linearly decreasing flight slope value, ranging from [0,2]. The calculation formulas of the relevant parameters are as follows:

[0093]

[0094] Z 1 =2×rand()-1

[0095]

[0096] Step 7: Determine whether the maximum number of iterations has been reached. If yes, go to step 11. If not, return to step 4.

[0097] Step 8: Output the optimal profit strategy suitable for the system.

[0098] For the simulation results of the improved method of optimizing the scheduling system by the Warhawk algorithm controller, see Figures 4 to 6 As shown, compared with the regional power grid system, the price of electricity generated by the present invention using new energy capacity is not necessarily based on the daily weather conditions, so that the price of electricity is sometimes high and sometimes low compared with the regional power grid. The present invention combines the actual operating conditions of the enterprise, breaks through the bottleneck of traditional enterprises ignoring the value of carbon scheduling, and invents a smart carbon scheduling method that is adapted to the latest low-carbon policy to plan the energy supply distribution and operation logic of the enterprise. In response to the dual-carbon policy promoted by the country, the present invention vigorously develops new energy. The design uses solar panels and wind blades to generate electricity, which can not only greatly reduce the emission of carbon dioxide and reduce the harm caused by the greenhouse effect, but also alleviate the problem of primary energy gradually facing exhaustion. While meeting the electricity demand, the use of electrolytic cells to decompose excess electricity into hydrogen can not only provide hydrogen for users, but also can be used as a material input for hydrogen fuel cells to meet the insufficient gap in electricity in case of emergency, and play a recycling utilization of resources with the maximum benefit. On the other hand, according to the calculation of electricity prices, hydrogen prices and carbon emission surpluses by the Warhawk algorithm optimizer, the maximum benefit can be obtained.

[0099] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent transformation or modification made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent flexible carbon scheduling system for industrial load adaptation based on improved Warhawk optimizer, characterized in that: Including photovoltaic arrays, wind turbines, DC / AC converters, electrolytic cells, hydrogen storage tanks, user supply terminals, hydrogen fuel cells, carbon emission metering modules, intelligent carbon emission dispatching centers, power grids, and DC / DC converters; The output ends of the photovoltaic array and the wind turbine are connected to the output end of the DC / AC converter and the input end of the carbon emission metering module; the output end of the carbon emission metering module is connected to the input end of the intelligent carbon emission dispatching center, the output end of the DC / AC converter connected to the output end of the photovoltaic array and the wind turbine is connected to the output end of the power grid, the output end of the electrolytic cell is connected to the output end of the hydrogen storage tank, the output end of the hydrogen storage tank is connected to the input and output end of the hydrogen fuel cell on one side and to the input end of the user supply end on the other side; the output end of the hydrogen fuel cell is connected to the output end of the DC / DC converter, and the output end of the DC / DC converter is connected to the input end of the power grid; the input end of the intelligent carbon emission dispatching center is connected to the output ends of the power grid and the user supply end; Wind turbines and photovoltaic arrays are connected to the carbon emission metering module, which calculates the carbon dioxide generated by wind and solar power generation in real time and transmits the production capacity to the power grid; the power grid is connected to the intelligent carbon emission dispatching center, and the other end is connected to the electrolytic cell to produce redundant hydrogen from power generation. One end of the electrolytic cell is also connected to the carbon emission metering module. The carbon dioxide generated in the process of electrolysis of water is calculated in real time by the carbon emission metering module. The hydrogen produced by power generation is flexibly controlled and transmitted to the user end, which is also connected to the intelligent carbon emission dispatching center; the intelligent carbon emission dispatching center calculates the carbon dioxide generated by the company's self-consumption in real time. While meeting the company's low-carbon operation, the intelligent carbon emission dispatching center calculates the current power generation, hydrogen production, unit price of electricity, unit price of hydrogen, and carbon emission capacity of the carbon emission metering module, and obtains the profit value calculated by the improved Warhawk optimizer. The implementation process of the intelligent carbon emission dispatch center is as follows: S1: Improve initialization, initialize the corresponding benefits of each optimized eagle population; each improved eagle population has a set of corresponding values ​​of the objective function, and the initialization process is improved by using Logistic chaos mapping; S2: Calculate the fitness of each population, that is, the objective function. The objective function is the optimal benefit value of the system. The calculation formula is as follows: C=αC self +βC H +χC grid +δC money Where: Among them, C is carbon emissions, and F is the optimal profit under the lowest carbon emissions. The optimal profit is the maximum profit between "electricity volume*unit price of electricity+hydrogen volume*unit price of hydrogen" and the sales price of the remaining carbon emissions. The larger the F value, the better, and the smaller the C value is subject to constraints, the better. S3: In the process of searching for prey, the war eagle expands the search range by soaring vertically. The expression for hunting birds in flight is as follows: In the formula, X(t) and X(t+1) respectively represent the individual positions of the AO algorithm in the t-th iteration and the t+1-th iteration, which contain the objective functions F and C. represents the best individual obtained by the algorithm up to the tth iteration, that is, the maximum profit of selling electric hydrogen compared with carbon emissions, X M (t) represents the average position of the population at the tth iteration, and T represents the maximum number of iterations of the algorithm. The eagle continuously seeks the best way to approach the prey, and when the prey is captured, it is the optimal reward. S4: When the eagle finds prey in the sky, it will circle around the target prey in a spiral, prepare to land, and then attack. The expression is: Where Levy(D) represents the Levy flight distribution strategy, s is a constant, y and x are random numbers between 0 and 1; z, w represent the shape of the eagle during the flight according to the capture memory, and the eagle flies quickly according to the capture memory to get close to the prey, that is, the objective functions F and C: w=a×tan(θ) z=a×cot(θ) a=a1+D×U1 θ=-ω×D1+θ1 Where a is the search step length, ranging from 1 to 20, U is 0.00565, and w is 0.005; S5: When the Eagle is in the prey area and ready to land and attack, it will take a vertical descent to make a preliminary attack and get closer to the prey. The expression is: S6: The eagle approaches the prey and launches a random attack on the prey. The prey that receives the attack is the target function. The expression of walking and grabbing the prey is: Where AB represents the mass function value used to balance the search strategy, Z1 represents the various movements of AO in the process of tracking prey, that is, the local optimal solution and the global optimal solution, and Z2 represents the linearly decreasing flight slope value in the range of [0,2]. The calculation formulas of the relevant parameters are as follows: Z1=2×rand-1 S7: Determine whether the maximum number of iterations has been reached. If yes, proceed to S8; if not, return to S4; S8: Output the optimal profit strategy suitable for the system.

2. The intelligent flexible carbon scheduling system for adapting industrial load based on the improved Warhawk optimizer according to claim 1 is characterized in that: The photovoltaic array and wind turbine generator set are composed of multiple solar panels and rotating blades. When the blades are exposed to sunlight and the wind blows the blades, the solar panels absorb sunlight and convert solar radiation into electrical energy directly or indirectly through the photoelectric effect or the photochemical effect. The wind drives the windmill blades to rotate, and then the speed of rotation is increased through the speed increaser to prompt the generator to generate electricity. The electrical energy generated by the two is converted into an effective fixed output voltage by a DC / AC converter to be transmitted to the power plant for power supply. When there is excess electricity generated by new energy power generation, the excess electricity is transported to the electrolytic cell to be decomposed into hydrogen and transported to the hydrogen storage tank for storage. When the hydrogen user needs to use hydrogen, the hydrogen in the hydrogen storage tank is transported to the hydrogen user. In addition, when the new energy power generation cannot meet the power generation grid, the hydrogen in the hydrogen storage tank is used as a power generation material and transported to the hydrogen fuel cell to generate electricity. The generated electricity is converted into a fixed effective voltage by a DC / DC converter and transported to the power grid to meet the power supply demand.

3. The intelligent flexible carbon scheduling system for adapting industrial load based on the improved Warhawk optimizer according to claim 1 is characterized in that: The process of improving the initialization process by using Logistic chaotic mapping is as follows: Logistic chaotic mapping has the function of making the system in a chaotic state and achieving the ultimate uniformity of mapping distribution. The specific formula is as follows: X n+1 =βX n (1-X n ) In the formula, X n ∈[0,1]; β∈[0,3] is the Logistic parameter.

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