Optimization method and optimization device of clean energy preparation system and preparation system

Abstract

The invention provides an optimization method and an optimization device of a clean energy preparation system and the preparation system. According to the optimization method, a clean energy preparation system comprises a clean energy power generation system, an energy storage system for storing power generated by the clean energy power generation system, and a clean energy synthesis system for preparing clean energy; the optimization method comprises the following steps: obtaining the unit capacity construction cost of each of the clean energy power generation system, the energy storage system and the clean energy synthesis system; according to the construction cost, an upper-layer model with the lowest production cost of clean energy production of the clean energy preparation system as a first objective function is established; establishing a lower-layer model by taking the maximum amount of clean energy produced and transported by the clean energy synthesis system as a second objective function; and performing iterative solution on the upper-layer model and the lower-layer model to obtain the optimal construction capacity which enables the production cost of clean energy production of the clean energy preparation system to be the lowest. According to the optimization method disclosed by the invention, the capacity configuration of the clean energy preparation system can be optimized.

Description

Technical Field

[0001] The present disclosure generally relates to the field of clean energy, and more specifically, to an optimization method, an optimization device and a preparation system for a clean energy preparation system. Background Art

[0002] Methanol is an important chemical raw material and an important fuel. It is currently mainly produced by synthesis from natural gas or coal. From the perspective of the process of preparing methanol from coal chemical industry, coal-to-hydrogen has the highest carbon emissions, while methanol carbon emissions are relatively low. However, in the carbon emissions of the modern coal chemical industry, methanol has become the main source of carbon dioxide emissions due to its huge annual output.

[0003] Large-scale development of clean energy is the main direction of future energy development. In recent years, with the large-scale construction and access to the power grid of intermittent renewable energy, mainly wind power and photovoltaic power, it has caused great challenges and impacts on the power system. Therefore, further converting renewable energy into renewable fuels or raw materials such as hydrogen energy has become a promising solution.

[0004] Green electricity gas production is not only an important means to improve the level of renewable energy consumption, but also a core way to effectively reduce the carbon emission intensity of coal chemical industry. By combining clean energy and chemical industry to produce hydrogen and methanol, and matching fuel cells and electrochemical energy storage, the overall self-consumption ratio of the project can be comprehensively improved, and the purpose of off-grid operation can be achieved.

[0005] However, due to the volatility of green electricity and the lack of grid support, there are various problems with the safety, sustainability and stability of the project system. The construction cost of the related system is high and the economic benefits are low. Summary of the invention

[0006] One of the purposes of exemplary embodiments of the present disclosure is to optimize the construction capacity of a clean energy production system.

[0007] According to one aspect of the present disclosure, there is provided an optimization method for a clean energy preparation system, wherein the clean energy preparation system comprises a clean energy power generation system, an energy storage system for storing power generated by the clean energy power generation system, and a clean energy synthesis system for preparing clean energy and receiving power from the clean energy power generation system and / or the energy storage system, and the optimization method comprises: obtaining the unit capacity construction cost of each of the clean energy power generation system, the energy storage system and the clean energy synthesis system; establishing an upper model with the lowest production cost of clean energy produced by the clean energy preparation system as a first objective function according to the construction cost; establishing a lower model with the maximum amount of clean energy produced and transported by the clean energy synthesis system as a second objective function; and iteratively solving the upper model and the lower model to obtain the optimal construction capacity with the lowest production cost of clean energy produced by the clean energy preparation system.

[0008] According to an embodiment of the present disclosure, the step of iteratively solving the upper model and the lower model to obtain the optimal construction capacity that minimizes the production cost of the clean energy preparation system in producing clean energy may include: an upper model solving step, solving the upper model to obtain a first optimization result as a decision variable of the upper model; a lower model solving step, solving the lower model based on the first optimization result to obtain a first optimization configuration result as the decision variable of the lower model and solving the upper model using the first optimization configuration result to obtain a second optimization result; repeating the upper model solving step and the lower model solving step to obtain N optimization results, and determining the optimization result corresponding to the lowest production cost of the clean energy preparation system in producing clean energy as the optimal construction capacity, wherein N is a positive integer greater than or equal to 2.

[0009] According to an embodiment of the present disclosure, a clean energy synthesis system may include a hydrogen production system, a carbon dioxide capture system, and a methanol synthesis system. The clean energy preparation system may also include a fuel cell system that uses methanol synthesized by the methanol synthesis system as fuel and provides energy when the clean energy preparation system lacks energy; the optimal construction capacity includes the rated output power of the clean energy power generation system, the maximum power of the energy storage system, the maximum power of the hydrogen production system, the maximum operating power of the carbon dioxide capture system, the rated power of the methanol synthesis system, and the maximum power of the fuel cell system.

[0010] According to an embodiment of the present disclosure, the second objective function may be obtained through the hydrogen production of the hydrogen production system, the carbon dioxide capture amount of the carbon dioxide capture system, and the amount of formaldehyde stored in the methanol synthesis system.

[0011] According to an embodiment of the present disclosure, the second objective function can use the output power of the clean energy power generation system, energy storage system and fuel cell as a constraint condition that is greater than or equal to the power demand of the hydrogen production system, carbon dioxide capture system and methanol synthesis system.

[0012] According to an embodiment of the present disclosure, the clean energy production system may be an off-grid clean energy production system.

[0013] According to an embodiment of the present disclosure, the optimization method may further include: in response to determining that the power generation of the clean energy power generation system meets the power demand of the hydrogen production system, judging whether there is remaining space in the hydrogen storage subsystem of the hydrogen production system; in response to determining that there is remaining space in the hydrogen storage subsystem of the hydrogen production system, judging whether the hydrogen storage capacity of the hydrogen storage subsystem and the carbon dioxide capture capacity of the carbon dioxide capture system meet the minimum raw material demand; in response to determining that the hydrogen storage capacity of the hydrogen storage subsystem and the carbon dioxide capture capacity of the carbon dioxide capture system meet the minimum raw material demand, judging whether there is remaining space in the methanol storage subsystem of the methanol synthesis system; in response to determining that there is remaining space in the methanol storage subsystem of the methanol synthesis system, judging whether the power generation of the clean energy power generation system can further meet the power demand of the carbon dioxide capture system and the methanol synthesis system; in response to determining that the power generation of the clean energy power generation system can further meet the power demand of the carbon dioxide capture system and the methanol synthesis system, controlling the operation of the methanol synthesis system and synthesizing formaldehyde.

[0014] According to an embodiment of the present disclosure, the optimization method may further include: in response to determining that the clean energy power generation system cannot further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, judging whether both the power generation power of the clean energy power generation system and the discharge power of the energy storage system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; in response to determining that both the power generation power of the clean energy power generation system and the discharge power of the energy storage system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, controlling the operation of the methanol synthesis system and synthesizing formaldehyde.

[0015] According to an embodiment of the present disclosure, the optimization method may further include: in response to determining that both the power generation power of the clean energy power generation system and the discharge power of the energy storage system cannot further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, judging whether the power generation power of the clean energy power generation system, the discharge power of the energy storage system, and the power generation power of the fuel cell system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; in response to determining that the power generation power of the clean energy power generation system, the discharge power of the energy storage system, and the power generation power of the fuel cell system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, controlling the operation of the methanol synthesis system and synthesizing formaldehyde.

[0016] According to an embodiment of the present disclosure, the optimization method may also include: judging whether the sum of the storage capacity of the methanol synthesis system and the production capacity of the methanol synthesis system is greater than or equal to a predetermined threshold value; in response to determining that the sum of the storage capacity of the methanol synthesis system and the production capacity of the methanol synthesis system is greater than or equal to the predetermined threshold value, determining that the conditions for methanol export are met.

[0017] According to a second aspect of the present disclosure, there is provided an optimization device for a clean energy preparation system, wherein the clean energy preparation system comprises a clean energy power generation system, an energy storage system for storing power generated by the clean energy power generation system, and a clean energy synthesis system for preparing clean energy and receiving power from the clean energy power generation system and / or the energy storage system, and the optimization device comprises: an acquisition module for obtaining the unit capacity construction cost of each of the clean energy power generation system, the energy storage system, and the clean energy synthesis system; a first modeling module for establishing an upper model according to the construction cost with the first objective function of minimizing the production cost of clean energy produced by the clean energy preparation system; a second modeling module for establishing a lower model with the second objective function of maximizing the amount of clean energy produced and transported by the clean energy synthesis system; and a solution module for iteratively solving the upper model and the lower model to obtain the optimal construction capacity for minimizing the production cost of clean energy produced by the clean energy preparation system.

[0018] According to an embodiment of the present disclosure, the solution module can be configured to perform the following steps: an upper-level model solution step, solving the upper-level model to obtain a first optimization result as a decision variable of the upper-level model; a lower-level model solution step, solving the lower-level model based on the first optimization result to obtain a first optimization configuration result as a decision variable of the lower-level model and using the first optimization configuration result to solve the upper-level model to obtain a second optimization result; repeating the upper-level model solution step and the lower-level model solution step to obtain N optimization results, and determining the optimization result corresponding to the lowest production cost of the clean energy preparation system for producing clean energy as the optimal construction capacity, wherein N is a positive integer greater than or equal to 2.

[0019] According to a third aspect of the present disclosure, a computer-readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the above-mentioned optimization method of the clean energy production system is implemented.

[0020] According to a third aspect of the present disclosure, a clean energy production system is provided, the optimal construction capacity of the clean energy production system is determined by the above-mentioned optimization method. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other objects and features of the exemplary embodiments of the present disclosure will become more apparent through the following description in conjunction with the accompanying drawings which exemplarily illustrate the embodiments, in which:

[0022] Figure 1 is a schematic diagram showing a clean energy production system according to an embodiment of the present disclosure;

[0023] Figure 2 is a block diagram illustrating a clean energy production system according to an embodiment of the present disclosure;

[0024] Figure 3is a flow chart showing an optimization method according to a first embodiment of the present disclosure;

[0025] Figure 4 is a flow chart showing an optimization method according to a second embodiment of the present disclosure;

[0026] Figure 5 is a flow chart showing an energy control strategy of a clean energy production system according to an embodiment of the present disclosure; and

[0027] Figure 6 is a block diagram illustrating an optimization apparatus according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] The following detailed description is provided to help gain a comprehensive understanding of the methods, devices and / or systems described herein. However, the order of operations described herein is only an example and is not limited to those orders set forth herein, but may be equivalently replaced or changed except for operations that must occur or be performed in a specific order. In addition, for greater clarity and simplicity, the description of content known in the art will be omitted or simplified.

[0029] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by a person of ordinary skill in the art to which the present disclosure belongs after understanding the present disclosure. Unless explicitly defined as such herein, terms (such as those defined in a general dictionary) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and should not be interpreted in an idealized or overly formal manner.

[0030] Unless otherwise specified, the same reference numerals generally refer to the same elements (e.g., components, steps, and methods). Reference numerals described in the previous embodiments may be omitted if they appear again in the subsequent embodiments. In addition, the technical features described in different or the same embodiments may be combined in any manner, as long as the combined embodiments or technical solutions are complete and can solve the technical problems of the present application or achieve the technical effects described or not described in the present application but can be determined based on the above complete technical solutions.

[0031] Figure 1 is a schematic diagram showing a clean energy production system according to an embodiment of the present disclosure, Figure 2 is a block diagram illustrating a clean energy production system according to an embodiment of the present disclosure.

[0032] The clean energy preparation system disclosed in the present invention may include a clean energy power generation system, an energy storage system and a clean energy synthesis system. The energy storage system may store the power generated by the clean energy power generation system, and the clean energy synthesis system may prepare clean energy and receive power from the clean energy power generation system and / or the energy storage system, that is, the clean energy synthesis system uses the clean energy power generation system and / or the energy storage system as energy.

[0033] The clean energy power generation system here can be a clean energy power generation system such as a green energy power generation system. The clean energy power generation system can use wind turbines, solar photovoltaic cells, etc. to convert renewable energy such as wind energy and solar energy into electrical energy and can include wind power generation systems, photovoltaic power generation systems, etc.

[0034] The energy storage system may include an electrochemical energy storage system, and the clean energy synthesis system may include a methanol synthesis system, a hydrogen production system, a carbon dioxide capture system, and the like. The clean energy preparation system may also include a fuel cell system that uses methanol synthesized by the methanol synthesis system as fuel and provides energy when the clean energy preparation system lacks energy. The systems included in the clean energy synthesis system may vary depending on the clean energy synthesized.

[0035] The clean energy synthesis system may also include other types of green gas (e.g., ammonia) synthesis systems. Taking methanol as an example, the clean energy synthesis system may also include a water recovery system, a hydrogen storage system (or hydrogen storage system), and a methanol storage system. Figure 1 and Figure 2 Describe in detail.

[0036] Figure 1 is a schematic diagram showing a clean energy production system according to an embodiment of the present disclosure, Figure 2 is a block diagram illustrating a clean energy production system according to an embodiment of the present disclosure.

[0037] Reference Figure 1 The electricity provided by the clean energy power generation system can be provided to the hydrogen production system, the methanol synthesis system and the energy storage system. The hydrogen production system can produce hydrogen produced by the methanol synthesis system. The methanol synthesis system can prepare methanol using the hydrogen produced by the hydrogen production system and the carbon dioxide produced by the carbon dioxide capture system as raw materials. The water recovery system can provide the water required for hydrogen production to the hydrogen production system. The methanol produced by the methanol synthesis system can be stored in the methanol storage system for later use (for example, external transportation or combustion). The clean energy preparation system disclosed in the present invention can be an off-grid clean energy preparation system, and can also receive a small amount of electricity from the main power grid or provide electricity to the main power grid when needed.

[0038] Reference Figure 2The clean energy preparation system of the present disclosure may include a clean energy power generation system 1 (e.g., a photovoltaic power generation system 1.2 and a wind power generation system 1.1), an energy storage system 2, and a clean energy synthesis system, and the clean energy synthesis system may include a hydrogen production system 3, a carbon dioxide capture system 4, and a methanol synthesis system 7. The clean energy synthesis system may also include a hydrogen storage system 5, a water recovery system 6, a methanol storage system 8, and a fuel cell system 9.

[0039] The specific operation mode can be described as follows: When the current wind speed reaches the cut-in wind speed, the photovoltaic power generation system 1.2 and the wind power generation system 1.1 start to operate and generate electricity, and perform AC / DC, DC / DC, DC / AC and other conversions according to downstream needs through the conversion part 1.3 of the wind-solar coupling power generation module, and are transported to the hydrogen production system 3 and the energy storage system 2 after rectification and filtering. The electric energy of the clean energy power generation system 1 and the water of the circulating water pump are supplied to the electrolytic water hydrogen production tank of the hydrogen production system 3, and the oxygen produced by electrolysis is supplied to the oxygen purifier 3.3 of the hydrogen production system 3, and the produced hydrogen is supplied to the hydrogen purifier 3.2 of the hydrogen production system 3. The purified oxygen is supplied according to the needs of the fuel cell system 9 stack 9.1, and the excess is emptied and processed. The hydrogen storage system 5 receives hydrogen from the hydrogen production system 3 and stores it in the hydrogen storage tank 5.1 of the hydrogen storage system 5. The dust-removed flue gas enters the carbon dioxide capture system 4, passes through the carbon dioxide absorption tower 4.1 of the carbon dioxide capture system 4 and the carbon dioxide regeneration tower 4.2 of the carbon dioxide capture system 4, and passes through the carbon dioxide compressor 4.3 of the carbon dioxide capture system 4 to produce carbon dioxide gas. The carbon dioxide from the carbon dioxide capture system 4 is mixed with the hydrogen from the hydrogen storage system 5 in the gas mixer 7.1 of the methanol synthesis system 7, and the mixed gas is compressed by the mixed gas compressor 7.2 of the methanol synthesis system 7 and enters the electric thermal catalytic reactor to produce crude methanol. The crude methanol enters the first distillation tower 7.4 of the methanol synthesis system 7 to separate the light components, and the remaining part enters the second distillation tower 7.5 of the methanol synthesis system 7 to separate the refined methanol and heavy components such as water. The separated heavy components such as water enter the water recovery system 6, and are purified by the purifier 6.1 of the water recovery system 6 to produce circulating water. The refined methanol enters the methanol storage system 8 and is stored in the methanol storage tank 8.1 of the methanol storage system 8. When the system lacks energy, the fuel cell system 9 will draw methanol from the methanol storage system 8 and enter the fuel cell stack 9.1 of the fuel cell system 9 to react and supply energy to the system, and the generated water will enter the purifier 6.1 for circulation.

[0040] The above-mentioned operation mode is merely an operation example based on a specific system of the clean energy production system, and the operation mode may change when the structure of the clean energy production system changes or the type of green gas produced changes.

[0041] The present disclosure can establish a double-layer model, and can adopt a nonlinear optimization algorithm and use a CPLEX solver to solve the problem, thereby obtaining the capacity configuration or capacity information of the optimized clean energy production system.

[0042] Figure 3 is a flowchart showing an optimization method according to a first embodiment of the present disclosure, Figure 4 is a flow chart illustrating an optimization method according to a second embodiment of the present disclosure.

[0043] Reference Figure 3 , the optimization method according to an embodiment of the present disclosure may include step S10, step S20, step S30 and step S40.

[0044] In step S10 , the unit capacity construction cost of each of the clean energy power generation system, the energy storage system, and the clean energy synthesis system is obtained.

[0045] Here, the unit capacity construction cost of the clean energy power generation system may refer to the construction cost per kilowatt (unit power). The unit capacity construction cost of the energy storage system may refer to the construction cost per kilowatt. The unit capacity construction cost of the clean energy synthesis system may refer to the construction cost of the unit volume of clean energy, etc., or the unit power of the relevant subsystem of the clean energy synthesis system or the unit storage capacity of the relevant subsystem. As an example, the construction cost of each system can be determined based on the product of the unit capacity construction cost and the capacity information (e.g., power, storage capacity, etc.).

[0046] The unit capacity construction cost of the clean energy power generation system, the unit capacity construction cost of the energy storage system and the unit capacity construction cost of the clean energy synthesis system can all be determined in advance.

[0047] In step S20, an upper model is established based on the construction cost, with the lowest production cost of the clean energy production system as the first objective function. The lowest production cost here can refer to the production cost per unit volume (for example, the price of clean energy per cubic meter (yuan / m 3 )).

[0048] The first objective function can be determined according to the adaptability such as the type of clean energy produced by the clean energy production system and the type and number of systems included in the clean energy production system.

[0049] As an example, an upper-level model with the lowest production cost as the goal can be established based on the unit capacity construction cost of the clean energy power generation system, the unit capacity construction cost of the energy storage system, and the unit capacity construction cost of the clean energy synthesis system. For example, the first objective function can be shown in the following formula (45), but is not limited thereto.

[0050] In the present disclosure, the upper model can be used for capacity planning, and the lower model can be used for running simulations. For example, the upper model determines capacity information (i.e., power information) while minimizing construction costs, and the lower model uses the capacity information of the upper model to determine the actual operational power of each system, the capacity of the storage tank, and other information while maximizing the amount of methanol shipped out, and this information can be further used to adjust the capacity information of the upper model. For example, when the actual operational power is low relative to the previously determined capacity information (rated power), the rated power can be reduced, etc., thereby reducing the construction cost of clean energy per unit volume (e.g., the cost of methanol per cubic meter). Thus, the first optimization result (capacity information) as the decision variable of the upper model can be obtained through the upper model and the lower model, that is, the construction scale or construction capacity of each system of the clean energy preparation system can be obtained. That is, the lower model can be used to run the simulation, and the lower model can be solved based on the first optimization result of the upper model to obtain the first optimization configuration result as the decision variable of the lower model, and the first optimization configuration result can be input into the upper model for solving the upper model, that is, the first optimization configuration result of the lower model can be used for solving the upper model, thereby obtaining the second optimization result, and iterating in sequence to obtain multiple optimization results. The constraints of the decision variables can be determined according to the model of the relevant subsystem (which will be described in detail later). The initial solution of the upper model can be performed based on the default optimization configuration result. The default optimization configuration result here can be set as needed.

[0051] The multiple optimization results here can be the capacity information or construction capacity of each subsystem in the clean energy preparation system. The capacity information or construction capacity of each subsystem may include the rated output power of the clean energy power generation system, the maximum power of the energy storage system, the rated power of the subsystem of the clean energy synthesis system, or the storage capacity of the related subsystem.

[0052] For example, the rated output power of the photovoltaic power generation system, the rated output power of the wind power generation system, the maximum power of the energy storage system, the maximum power of the hydrogen production system, the maximum operating power of the carbon dioxide capture system, the gas storage tank capacity of the hydrogen production system, the water storage tank capacity of the water recovery system, the rated power of the methanol synthesis system, the storage tank capacity of the methanol storage system, the maximum power of the fuel cell system, etc. As an example, the rated output power of the photovoltaic power generation system is multiplied by the construction cost per unit rated output power (unit capacity construction cost) to obtain the construction cost of the photovoltaic power generation system.

[0053] In step S30, a lower model is established with the maximum amount of clean energy produced and transported by the clean energy synthesis system as the second objective function. The amount of clean energy generated and transported by the clean energy synthesis system can be determined based on the power required by the clean energy synthesis system or the power that the clean energy power generation system can provide. The model of the relevant system can be described as follows. In the present disclosure, the optimal construction capacity can be determined with the lowest construction cost per unit of clean energy. The system model involved in the capacity planning of the upper model of the present disclosure and the operation simulation of the lower model will be combined below.

[0054] Clean Energy Power Generation System Model

[0055] The method for calculating clean energy power generation based on wind speed data and solar irradiance is as follows:

[0056]

[0057]

[0058]

[0059]

[0060] S pv is the predicted value of solar irradiance, in W / ㎡; S r is the rated value of solar irradiance, in W / ㎡; α PV is the power temperature coefficient of the photovoltaic power generation system; T PV is the actual operating temperature of the photovoltaic power generation system, in °C; T r is the rated operating temperature of the photovoltaic power generation system, in °C; v pv Predicted speed of wind turbines for wind power generation system, m / s; is the fan cut-off speed of the wind power generation system, m / s; is the wind turbine cut-in speed of the wind power generation system, m / s; v r is the rated speed of the wind turbine in the wind power generation system, m / s; is the output power of the photovoltaic power generation system, in kW; P PV-max is the rated output power of the photovoltaic power generation system, in kW; is the output power of the wind power generation system, in kW; is the rated output power of the wind power generation system, in kW; is the power generation capacity of the clean energy power station, in kW; T is the time period of a year divided into 8760; E Energy It is the total power generation of new energy power stations (including wind power and photovoltaic power), in kWh. PVThe above clean energy power generation system model is only an example, and the specific model may vary according to the type of clean energy included in the clean energy power generation system.

[0061] Energy storage system model:

[0062] P BESS-max =N BESS *P BESS-S (5)

[0063] P BESS-max is the maximum power of the energy storage system, in kW; N BESS is the number of energy storage systems;

[0064] P BESS-S It is the power of a single energy storage system, in kW.

[0065] E BESS-max =P BESS-max ×H BESS (6)

[0066] E BESS-max is the maximum storage capacity of the energy storage system, in kWh; H BESS It is the continuous energy storage time of the energy storage system, in h.

[0067]

[0068] is the input power of the energy storage system, in kWh;

[0069] is the charging power of the energy storage system, in kW;

[0070] η BESS-in The charging efficiency of the energy storage system;

[0071]

[0072] is the output power of the energy storage system, in kWh;

[0073] is the discharge power of the energy storage system, in kW;

[0074] η BESS-out is the discharge efficiency of the energy storage system;

[0075]

[0076] is the total storage capacity of the energy storage system, in kWh;

[0077]

[0078] As an example, the current storage or discharge capacity cannot exceed the rated capacity E of the energy storage system. BESS-max Because modular battery packs are used, charging and discharging operations can occur at the same time, but they cannot exceed the remaining power space and power at the previous moment. The above energy storage system model is only an example, and the energy storage system model can be changed according to the type of energy storage system and its specific configuration.

[0079] Hydrogen production system model

[0080] The hydrogen production system adopts an alkaline water electrolysis hydrogen production system, so there is a minimum operating power, a maximum operating power, and a maximum power conversion rate.

[0081] P AWE-max =N AWE ×P AWE-S (11)

[0082] P AWE-max The maximum power of the water electrolysis hydrogen production equipment of the hydrogen production system, in kW;

[0083] N AWE is the number of alkaline electrolytic cells, in units;

[0084] P AWE-S is the rated power of a single alkaline electrolyzer, in kW;

[0085]

[0086] The hydrogen output of the water electrolysis hydrogen production equipment, in Nm 3 ;

[0087] The power of the water electrolysis hydrogen production equipment, in kW;

[0088] is the energy conversion efficiency of the water electrolysis hydrogen production equipment, in kWh / Nm 3 ;

[0089]

[0090] is the oxygen production of the hydrogen production system, in Nm 3 ;

[0091] is the water consumption of the hydrogen production system, in Nm 3 ;

[0092]

[0093]

[0094] is the amount of oxygen vented from the hydrogen production system, is the oxygen consumption of the fuel cell system, in Nm 3 ; and The meanings are as follows;

[0095]

[0096] η AWE-max With η AWE-min They are respectively the highest operating power ratio and the lowest operating power ratio of the water electrolysis hydrogen production equipment;

[0097]

[0098] is the power consumption of the hydrogen production system, in kWh;

[0099]

[0100] η AWE-change The above hydrogen production system model is only an example, and the hydrogen production system model can be changed according to the specific configuration of the hydrogen production system.

[0101] CO2 capture system model

[0102]

[0103] is the CO2 capture capacity of the CO2 capture system, in Nm 3 ;

[0104] is the amount of carbon dioxide entering the carbon dioxide capture system, in Nm 3 ;

[0105] The carbon capture efficiency of the CO2 capture system;

[0106]

[0107] is the electricity consumption of the CO2 capture system, in kWh;

[0108] is the operating power of the CO2 capture system, in kW;

[0109] is the energy consumption per unit of carbon capture, in kWh / Nm 3 ;

[0110]

[0111] P CCS-max is the maximum operating power of the CO2 capture system, in kW;

[0112] P CCS-min is the minimum operating power of the CO2 capture system, in kW;

[0113]

[0114] η CCS-change is the maximum power change rate of the CO2 capture system;

[0115]

[0116] is the total storage capacity of carbon dioxide in the carbon dioxide storage tank, in Nm 3 ;

[0117] η HCCS-max With η HCCS-min They are the highest ratio and the lowest ratio of carbon dioxide in the carbon dioxide storage tank, respectively;

[0118] is the carbon dioxide storage capacity in the carbon dioxide storage tank, in Nm 3 ;

[0119]

[0120] is the carbon dioxide emission from the carbon dioxide capture system, in Nm 3 .

[0121] is the amount of CO2 released from the CO2 storage tank in the CO2 capture system, in Nm 3 The above carbon dioxide capture system model is merely an example, and the carbon dioxide capture system model may be changed according to the specific configuration of the carbon dioxide capture system.

[0122] Hydrogen Storage System Model

[0123]

[0124] is the hydrogen storage capacity in the hydrogen storage tank, in Nm 3 ;

[0125] and They are respectively the amount of hydrogen stored and released, in Nm 3 ;

[0126]

[0127] is the total storage capacity of hydrogen in the hydrogen storage tank, in Nm 3 ;

[0128] η HS-max With η HS-min They are the highest ratio and the lowest ratio of hydrogen in the hydrogen storage tank respectively.

[0129] The above hydrogen storage system model is merely an example, and the hydrogen storage system model may be changed according to the specific configuration of the hydrogen storage system.

[0130] Recycled water system model

[0131]

[0132] The total storage capacity of water in the storage tank of the recycled water system, in Nm 3 ;

[0133] η re-max With η re-min They are the highest and lowest ratios of water in the storage tank of the recycled water system, respectively;

[0134]

[0135] is the total water volume of the recycled water system, in Nm 3 ;

[0136] The amount of water purchased, in Nm 3 ;

[0137] The amount of water produced by the methanol synthesis system, in Nm 3 ;

[0138] The amount of water delivered by the recycled water system, in Nm 3 The above-mentioned recycled water system model is merely an example, and the above-mentioned recycled water system model may be changed according to the specific configuration of the recycled water system.

[0139] Methanol Synthesis System Model

[0140]

[0141] The hydrogen required for the methanol synthesis system, in Nm 3 ;

[0142]

[0143] The carbon dioxide required for the methanol synthesis system, in Nm 3 ;

[0144]

[0145] and The methanol volume generated by the methanol synthesis system and the water volume required by the methanol synthesis system may be respectively;

[0146]

[0147] The power consumption of the methanol synthesis system, in kWh;

[0148] The power consumption per unit volume of methanol produced is expressed in kW / Nm 3 ;

[0149] is the rated power of the methanol synthesis system;

[0150]

[0151]

[0152] is the maximum power change rate of the methanol synthesis system model;

[0153]

[0154] and They are the maximum safe operating condition ratio and the minimum safe operating condition ratio of the methanol synthesis system respectively;

[0155]

[0156] Methanol production, unit: kW / Nm 3 ;

[0157] is the conversion rate from hydrogen to methanol; the above methanol synthesis system model is only an example, and the above methanol synthesis system model can be changed according to the specific configuration of the methanol synthesis system.

[0158] Methanol Storage System Model

[0159]

[0160] C CHOS is the total storage capacity of methanol in the methanol storage tank, in Nm 3 ;

[0161] η CHOS-max With η CHOS-min are the highest and lowest ratios of methanol storage volume in the methanol storage tank, respectively;

[0162]

[0163] and They are respectively the methanol storage volume and the methanol transport volume, in Nm 3 ;

[0164] is the amount of methanol in the methanol storage tank, in Nm 3 ;

[0165]

[0166] The above-mentioned methanol storage system model is merely an example, and the above-mentioned methanol storage system model may be changed according to the specific configuration of the methanol storage system.

[0167] Fuel cell system model

[0168]

[0169] and Respectively, the amount of methane and oxygen consumed by the fuel cell system, in Nm 3 ;

[0170] and are the amount of water and carbon dioxide produced by the fuel cell system, in Nm 3 ;

[0171]

[0172] is the discharge capacity of the fuel cell system, in kWh;

[0173] is the energy conversion efficiency of the fuel cell system, expressed in kWh / Nm 3 ;

[0174]

[0175] ηDMFC-change is the maximum power change rate of the fuel cell system;

[0176]

[0177] P DMFC-max is the maximum power of the fuel cell system, in kW;

[0178]

[0179] η DMFC-max is the maximum safe operating condition ratio of the fuel cell system;

[0180] P DMFC-max is the maximum power of the fuel cell system, in kW; the above fuel cell system model is only an example, and the above fuel cell system model may be changed according to the specific configuration of the methanol storage system, etc.

[0181] It should be noted that the same variables in different system models have the same meaning, so they will not be described repeatedly.

[0182] The optimization method disclosed in the present invention does not rely on the system model described by the above equations (1) to (44), and can also be optimized using the models of various existing systems.

[0183] Based on the above models of each subsystem or existing models, the first objective function and the second objective function can be obtained.

[0184] The first objective function:

[0185] As an example, the clean energy production system only sells methanol as a single source of income, and an economic analysis model is established with the goal of minimizing the production cost of methanol or minimizing the production cost of clean energy generated by the clean energy production system.

[0186]

[0187]

[0188]

[0189]

[0190]

[0191] In formula (45), i is the expected service life of each system (e.g., methanol synthesis system, hydrogen production system, etc.) for producing methanol by hydrogen production, in years; n is the service life of each system for producing methanol by hydrogen production, in years; r DR is the project discount rate; r SVis the estimated residual value rate of the project; r tax is the corporate income tax rate; LCOD is the levelized methanol production cost, in yuan / Nm 3 ; The initial investment of each system for producing methanol from hydrogen (e.g., methanol synthesis system, hydrogen production system, etc.), in Yuan; The annual depreciation cost (straight-line method) of each system for producing methanol from hydrogen by electricity is in Yuan; The annual operation and maintenance costs of each system for producing synthetic methanol from hydrogen by electricity, including fuel, insurance costs, management costs, operation and maintenance costs, employee wages and welfare costs, consumables costs, land rent and other daily operating costs, in RMB; The residual value of each system for producing methanol from hydrogen (e.g., methanol synthesis system, hydrogen production system, etc.), in Yuan; The equipment purchase cost of each system for producing synthetic methanol from hydrogen produced by electricity, in Yuan; The installation engineering cost of each system for producing synthetic methanol from hydrogen by electricity, in Yuan; The structural engineering costs of each system for producing synthetic methanol from hydrogen by electricity, in Yuan; Other engineering costs for various systems of producing methanol from hydrogen generated by electricity, in Yuan; The fuel, insurance, management costs, operation and maintenance costs, employee wages and welfare costs, consumables costs, land rent and other daily operating costs of the clean energy power generation system, energy storage system, water electrolysis hydrogen production system, carbon dioxide capture system, hydrogen storage system, water recovery system, methanol synthesis system, methanol storage system, and fuel cell system are respectively, in yuan. Part of the production costs or subsidy costs of the clean energy preparation system to generate clean energy can be ignored to simplify the first objective function. In other words, at least one item in the LCOD in the calculation formula (45) can be omitted.

[0192] The second objective function

[0193] The second objective function can be determined by the following formula 46.

[0194]

[0195] As mentioned above, Q CHOmax It can be the maximum value of the total amount of methanol shipped out. The amount of methanol exported.

[0196] The above first objective function and second objective function are merely examples, and the above first objective function and second objective function may also be changed according to the type of clean energy produced, etc.

[0197] As an example, the second objective function may be obtained by the hydrogen production of the hydrogen production system, the carbon dioxide capture amount of the carbon dioxide capture system, and the amount of formaldehyde stored in the methanol synthesis system.

[0198] In addition, the second objective function can be based on the output power of the clean energy power generation system, the energy storage system and the fuel cell being greater than or equal to the power demand of the hydrogen production system, the carbon dioxide capture system and the methanol synthesis system as a constraint condition, but this is only an example. The constraints of the first objective function and the second objective function can be determined based on at least one of the above formulas.

[0199] In step S40, the upper model and the lower model are iteratively solved to obtain the optimal construction capacity that minimizes the production cost of the clean energy production system. As described above, the optimal construction capacity may include the rated output power of the clean energy power generation system, the maximum power of the energy storage system, the maximum power of the hydrogen production system, the maximum operating power of the carbon dioxide capture system, the rated power of the methanol synthesis system, the maximum power of the fuel cell system, etc.

[0200] As an example, a two-layer mixed integer nonlinear optimization algorithm (DOMINO) can be used and solved on a Matlab platform using a CPLEX solver to obtain the optimal construction capacity, but this is only an example and other algorithms can be used for the solution.

[0201] Reference Figure 4 The step of iteratively solving the upper model and the lower model to obtain the optimal construction capacity that minimizes the production cost of the clean energy production system to produce clean energy may include an upper model solving step S410 and a lower model solving step S420.

[0202] In step S410, the upper model is solved to obtain a first optimization result as a decision variable of the upper model.

[0203] In step S420, the lower model is solved based on the first optimization result to obtain a first optimization configuration result as a decision variable of the lower model, and the upper model is solved using the first optimization configuration result to obtain a second optimization result.

[0204] As an example, steps S410 and S420 may be repeated to obtain N optimization results, and the optimization result corresponding to the lowest production cost of the clean energy production system for producing clean energy may be determined as the optimal construction capacity, where N is a positive integer greater than or equal to 2.

[0205] As an example, the optimization method according to an embodiment of the present disclosure may also include: in response to determining that the power generation of the clean energy power generation system meets the power demand of the hydrogen production system, judging whether there is remaining space in the hydrogen storage subsystem of the hydrogen production system; in response to determining that there is remaining space in the hydrogen storage subsystem of the hydrogen production system, judging whether the hydrogen storage capacity of the hydrogen storage subsystem and the carbon dioxide capture capacity of the carbon dioxide capture system meet the minimum raw material demand; in response to determining that the hydrogen storage capacity of the hydrogen storage subsystem and the carbon dioxide capture capacity of the carbon dioxide capture system meet the minimum raw material demand, judging whether there is remaining space in the methanol storage subsystem of the methanol synthesis system; in response to determining that there is remaining space in the methanol storage subsystem of the methanol synthesis system, judging whether the power generation of the clean energy power generation system can further meet the power demand of the carbon dioxide capture system and the methanol synthesis system; in response to determining that the power generation of the clean energy power generation system can further meet the power demand of the carbon dioxide capture system and the methanol synthesis system, controlling the methanol synthesis system to operate and synthesize formaldehyde.

[0206] In addition, the optimization method according to the embodiment of the present disclosure may also include: in response to determining that the clean energy power generation system cannot further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, judging whether both the power generation power of the clean energy power generation system and the discharge power of the energy storage system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; in response to determining that both the power generation power of the clean energy power generation system and the discharge power of the energy storage system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, controlling the operation of the methanol synthesis system and synthesizing formaldehyde.

[0207] In addition, the optimization method according to the embodiment of the present disclosure may also include: in response to determining that the power generation power of the clean energy power generation system and the discharge power of the energy storage system cannot further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, judging whether the power generation power of the clean energy power generation system, the discharge power of the energy storage system, and the power generation power of the fuel cell system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; in response to determining that the power generation power of the clean energy power generation system, the discharge power of the energy storage system, and the power generation power of the fuel cell system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, controlling the operation of the methanol synthesis system and synthesizing formaldehyde.

[0208] Therefore, the various energy sources disclosed in the present invention can be utilized in a cascade manner, thereby making full use of green energy.

[0209] In addition, the optimization method according to the embodiment of the present disclosure may further include: determining whether the sum of the storage capacity of the methanol synthesis system and the production capacity of the methanol synthesis system is greater than or equal to a predetermined threshold value, and in response to determining that the sum of the storage capacity of the methanol synthesis system and the production capacity of the methanol synthesis system is greater than or equal to the predetermined threshold value, determining that the methanol export condition is met. Figure 5 The energy control strategy of the present disclosure is described in detail.

[0210] Figure 5 is a flow chart illustrating an energy control strategy of a clean energy production system according to an embodiment of the present disclosure.

[0211] The optimization method according to an embodiment of the present disclosure may also include step S110, step S120, step S130, step S140, step S150, step S160, step S170, step S180, step S190, step S131, step S181, step S182, step S183, step S184, step S185, step S186, step S187, step S188, step S220, step S230 and step S240.

[0212] In step S110 , the clean energy power generation system is started and operates.

[0213] In step S120, it is determined whether the clean energy power generation system can meet the power demand of the hydrogen production system.

[0214] If the clean energy power generation system cannot meet the power demand of the hydrogen production system, then in step S131 , the hydrogen production system is controlled not to operate.

[0215] If the clean energy power generation system can meet the power demand of the hydrogen production system, then in step S130, it is further determined whether there is remaining space in the hydrogen storage system.

[0216] If there is remaining space, the hydrogen production system and the hydrogen storage system are controlled to operate in step S140 and step S150 respectively.

[0217] In step 160, it is determined whether the hydrogen storage system and the carbon dioxide capture system ( and ) can meet the minimum raw material requirements of the methanol synthesis system.

[0218] In step S187, the methanol synthesis system is controlled to be inoperative.

[0219] If the minimum raw material requirement is met, then in step S170, it is further determined whether there is remaining space in the methanol storage system.

[0220] In step S170, it is determined whether there is any remaining space in the methanol storage system.

[0221] If there is remaining space in the methanol storage system, then in step S180, it is further determined whether the clean energy power generation system can meet the power demand of the methanol synthesis system. If so, in step S190, the methanol synthesis system is controlled to operate.

[0222] In step S184, it is further determined whether the energy storage system can meet the power demand of the methanol synthesis system. If so, in step S188, the energy storage system is controlled to discharge. If not, in step S185, it is further determined whether the fuel cell system can meet the power demand of the methanol synthesis system. If so, in step S186, the fuel cell system is controlled to operate. If not, the methanol synthesis system is controlled not to operate.

[0223] If the clean energy power generation system can meet the power demand of the methanol synthesis system, then in step S181, it is further determined whether the clean energy power generation system can meet the power demand of the energy storage system, and then in step S183, the energy storage system is controlled to charge.

[0224] If the clean energy power generation system cannot meet the power demand of the methanol synthesis system, then in step S182, the energy storage system is controlled not to operate.

[0225] In step S220, the methanol storage system is controlled to work. In step S230, it is determined whether the conditions for transporting methanol out are met. If so, in step S240, the methanol is transported out. If not, the process returns to step S120.

[0226] Figure 6 is a block diagram illustrating an optimization apparatus according to an embodiment of the present disclosure.

[0227] Reference Figure 6 According to an embodiment of the present disclosure, the optimization device may include an acquisition module 610, a first modeling module 620, a second modeling module 630 and a solution module 640.

[0228] The acquisition module 610 can obtain the unit capacity construction cost of each of the clean energy power generation system, the energy storage system, and the clean energy synthesis system.

[0229] The first modeling module 620 can establish an upper model with the lowest production cost of clean energy produced by the clean energy preparation system as the first objective function according to the construction cost.

[0230] The second modeling module 630 establishes a lower-level model with the maximum amount of clean energy produced and exported by the clean energy synthesis system as the second objective function.

[0231] The solution module 640 can iteratively solve the upper model and the lower model to obtain the optimal construction capacity that minimizes the production cost of the clean energy production system to produce clean energy.

[0232] Specifically, the solution module may be configured to execute step S410 and step S420.

[0233] In S410, the upper model is solved to obtain a first optimization result as a decision variable of the upper model; in S420, the lower model is solved based on the first optimization result to obtain a first optimization configuration result as a decision variable of the lower model and the upper model is solved using the first optimization configuration result to obtain a second optimization result.

[0234] The solution module 640 can repeat steps S410 and S420 to obtain N optimization results, and determine the optimization result corresponding to the lowest production cost of the clean energy production system for producing clean energy as the optimal construction capacity, where N is a positive integer greater than or equal to 2.

[0235] In addition to the above modules, the solution module 640 can also execute at least one of the above steps, which will not be repeated here.

[0236] It should be understood that the various units or modules in the control device according to the exemplary embodiments of the present disclosure may be implemented as hardware components and / or software components. Those skilled in the art may implement the various units according to the processing performed by the defined various units, for example, using a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a software algorithm, etc.

[0237] Each operation of the above steps can be written as a software program or instruction. Therefore, the optimization method according to the exemplary embodiment of the present disclosure can be implemented via software. The computer-readable storage medium of the exemplary embodiment of the present disclosure can store a computer program. When the computer program is executed by a processor, the optimization method as described in the above exemplary embodiment is implemented.

[0238] According to various embodiments of the present disclosure, a device (e.g., a module or their functions) or a method may be implemented by a program or instruction stored in a computer-readable storage medium. When the instruction is executed by a processor, the processor may perform a function corresponding to the instruction or perform a method corresponding to the instruction. At least a portion of a module may be implemented (e.g., executed) by a processor. At least a portion of a programming module may include a module, a program, a routine, an instruction set, and a process for performing at least one function. In one example, an instruction or software includes a machine code (such as a machine code generated by a compiler) directly executed by one or more processors or computers. In another example, an instruction or software includes a higher level code executed by one or more processors or computers using an interpreter. Instructions or software may be written in any programming language based on the block diagrams and flow charts shown in the accompanying drawings and the corresponding descriptions in the specification.

[0239] Computer-readable storage media include non-transitory computer-readable storage media, for example, magnetic media such as floppy disks and tapes, optical media (including compact disks (CD) ROMs and DVD ROMs), magneto-optical media such as floppy disks, hardware devices such as ROMs, RAMs, and flash memories designed to store and execute program commands. The program commands include language codes executable by a computer using an interpreter and machine language codes generated by a compiler. The above-mentioned hardware devices can be implemented by one or more software modules for performing the operations of the various embodiments of the present disclosure.

[0240] The module or programming module of the present disclosure may include at least one of the aforementioned components when some components are omitted or other components are added. The operation of the module, programming module or other components may be performed sequentially, in parallel, in a loop or in a tentative manner. In addition, some operations may be performed in different orders, may be omitted or extended with other operations.

[0241] According to an exemplary embodiment of the present disclosure, an optimization device may include: a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program or instructions, and when the computer program or instructions are executed by the processor, the optimization method described in the above exemplary embodiment is implemented.

[0242] The optimization device and optimization method according to the embodiments of the present disclosure can optimize the capacity configuration of the clean energy production system.

[0243] The optimization device and optimization method according to the embodiments of the present disclosure can be used to construct an off-grid source-grid-load-storage integrated clean energy production system.

[0244] According to the optimization device and optimization method of the embodiments of the present disclosure, new energy or green energy is combined with chemical industry, thereby reducing the cost of the clean energy preparation system.

[0245] In addition, the optimization device and optimization method according to the embodiments of the present disclosure can also expand the proportion of new energy consumption, alleviate the pressure on the power grid or reduce carbon emissions, and can provide a new path for the development of green chemical industry.

[0246] In addition, the optimization device and optimization method according to the embodiments of the present disclosure can perform cascade utilization of energy according to the characteristics of different energy supply equipment, and couple new energy with hydrogen production and downstream industries.

[0247] Although some exemplary embodiments of the present disclosure have been shown and described, it will be understood by those skilled in the art that modifications may be made to these embodiments without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents; for example, the technical features of different embodiments may be combined.

Claims

1. A method for optimizing a clean energy production system, characterized in that: The clean energy preparation system includes a clean energy power generation system, an energy storage system that stores the power generated by the clean energy power generation system, and a clean energy synthesis system that prepares clean energy and receives power from the clean energy power generation system and / or the energy storage system. The optimization method includes: obtaining a unit capacity construction cost of each of the clean energy power generation system, the energy storage system, and the clean energy synthesis system; According to the construction cost, an upper model is established with the lowest production cost of clean energy produced by the clean energy production system as the first objective function; Establishing a lower model with the maximum amount of clean energy produced and transported by the clean energy synthesis system as the second objective function; The upper model and the lower model are iteratively solved to obtain the optimal construction capacity that minimizes the production cost of the clean energy production system in producing clean energy.

2. The optimization method of the clean energy production system according to claim 1, characterized in that: The steps of iteratively solving the upper model and the lower model to obtain the optimal construction capacity that minimizes the production cost of the clean energy production system for producing clean energy include: An upper-layer model solving step, solving the upper-layer model to obtain a first optimization result as a decision variable of the upper-layer model; A lower-level model solving step, solving the lower-level model based on the first optimization result to obtain a first optimization configuration result as a decision variable of the lower-level model and solving the upper-level model using the first optimization configuration result to obtain a second optimization result; Repeat the upper model solving steps and the lower model solving steps to obtain N optimization results, and determine the optimization result corresponding to the lowest production cost of the clean energy preparation system for producing clean energy as the optimal construction capacity, where N is a positive integer greater than or equal to 2.

3. The optimization method of the clean energy production system according to claim 2, characterized in that: The clean energy synthesis system includes a hydrogen production system, a carbon dioxide capture system, and a methanol synthesis system. The clean energy production system also includes a fuel cell system that uses methanol synthesized by the methanol synthesis system as fuel and provides energy when the clean energy production system lacks energy; The optimal construction capacity includes the rated output power of the clean energy power generation system, the maximum power of the energy storage system, the maximum power of the hydrogen production system, the maximum operating power of the carbon dioxide capture system, the rated power of the methanol synthesis system, and the maximum power of the fuel cell system.

4. The method for optimizing the clean energy production system according to claim 3, characterized in that: The second objective function is obtained by the hydrogen production of the hydrogen production system, the carbon dioxide capture amount of the carbon dioxide capture system, and the amount of formaldehyde stored in the methanol synthesis system.

5. The method for optimizing the clean energy production system according to claim 4, characterized in that: The second objective function uses the output power of the clean energy power generation system, the energy storage system and the fuel cell as a constraint condition that is greater than or equal to the power requirements of the hydrogen production system, the carbon dioxide capture system and the methanol synthesis system.

6. The method for optimizing the clean energy production system according to claim 5, characterized in that: The clean energy production system is an off-grid clean energy production system.

7. The method for optimizing the clean energy production system according to claim 3, characterized in that: The optimization method further comprises: In response to determining that the power generation of the clean energy power generation system meets the power demand of the hydrogen production system, determining whether there is remaining space in the hydrogen storage subsystem of the hydrogen production system; In response to determining that there is remaining space in the hydrogen storage subsystem of the hydrogen production system, determining whether the hydrogen storage capacity of the hydrogen storage subsystem and the carbon dioxide capture capacity of the carbon dioxide capture system meet the minimum raw material requirement; In response to determining that the hydrogen storage capacity of the hydrogen storage subsystem and the carbon dioxide capture capacity of the carbon dioxide capture system meet the minimum feedstock requirement, determining whether there is remaining space in the methanol storage subsystem of the methanol synthesis system; In response to determining that there is remaining space in the methanol storage subsystem of the methanol synthesis system, determining whether the power generation power of the clean energy power generation system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; In response to determining that the power generated by the clean energy power generation system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, the methanol synthesis system is controlled to operate and synthesize formaldehyde.

8. The method for optimizing the clean energy production system according to claim 7, characterized in that: The optimization method further comprises: In response to determining that the clean energy power generation system cannot further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, determining whether both the power generation power of the clean energy power generation system and the discharge power of the energy storage system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; In response to determining that both the power generation power of the clean energy power generation system and the discharge power of the energy storage system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, the methanol synthesis system is controlled to operate and synthesize formaldehyde.

9. The method for optimizing the clean energy production system according to claim 8, characterized in that: The optimization method further comprises: In response to determining that both the power generation power of the clean energy power generation system and the discharge power of the energy storage system cannot further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, determining whether the power generation power of the clean energy power generation system, the discharge power of the energy storage system, and the power generation power of the fuel cell system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system; In response to determining that the power generation power of the clean energy power generation system, the discharge power of the energy storage system, and the power generation power of the fuel cell system can further meet the power requirements of the carbon dioxide capture system and the methanol synthesis system, the methanol synthesis system is controlled to operate and synthesize formaldehyde.

10. The method for optimizing the clean energy production system according to claim 9, characterized in that: The optimization method further comprises: Determine whether the sum of the storage capacity of the methanol synthesis system and the production capacity of the methanol synthesis system is greater than or equal to a predetermined threshold value, and in response to determining that the sum of the storage capacity of the methanol synthesis system and the production capacity of the methanol synthesis system is greater than or equal to the predetermined threshold value, determine that the conditions for methanol export are met.

11. An optimization device for a clean energy production system, characterized in that: The clean energy preparation system includes a clean energy power generation system, an energy storage system for storing the power generated by the clean energy power generation system, and a clean energy synthesis system for preparing clean energy and receiving power from the clean energy power generation system and / or the energy storage system. The optimization device includes: An acquisition module is used to obtain the unit capacity construction cost of each of the clean energy power generation system, the energy storage system, and the clean energy synthesis system; A first modeling module is used to establish an upper model with the lowest production cost of clean energy produced by the clean energy production system as a first objective function according to the construction cost; A second modeling module establishes a lower model with the maximum amount of clean energy produced and transported by the clean energy synthesis system as the second objective function; The solution module iteratively solves the upper model and the lower model to obtain the optimal construction capacity that minimizes the production cost of the clean energy production system.

12. The optimization device for the clean energy production system according to claim 11, characterized in that: The solution module is configured to perform the following steps: An upper-layer model solving step, solving the upper-layer model to obtain a first optimization result as a decision variable of the upper-layer model; A lower-level model solving step, solving the lower-level model based on the first optimization result to obtain a first optimization configuration result as a decision variable of the lower-level model and solving the upper-level model using the first optimization configuration result to obtain a second optimization result; The upper model solving step and the lower model solving step are performed to obtain N optimization results, and the optimization result corresponding to the lowest production cost of the clean energy preparation system for producing clean energy is determined as the optimal construction capacity, wherein N is a positive integer greater than or equal to 2.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or instruction, which, when executed by a processor, implements the optimization method for a clean energy production system according to any one of claims 1 to 10.

14. A clean energy production system, characterized in that: The optimal construction capacity of the clean energy production system is determined by the optimization method according to any one of claims 1-10.

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