Optimization control method, system, equipment and medium for wind-solar hydrogen production system

Abstract

The invention belongs to the technical field of wind and light hydrogen production system optimization, and discloses a wind and light hydrogen production system optimization control method, system, equipment and medium, and the method comprises the steps: obtaining historical cost data of a wind and light power generation hydrogen production system; project cost data of different hydrogen production modes and technical parameter prediction data of the hydrogen production device within set time are measured and calculated based on the historical cost data; calculating power generation cost prediction data of different power generation modes in a set time based on the historical cost data; calculating the hydrogen production cost of each hydrogen production mode under different power generation modes based on the power generation cost prediction data, the hydrogen production device technical parameter prediction data and the project cost data; key influence factor data of the hydrogen production cost is determined, sensitivity analysis is carried out on the hydrogen production cost based on the key influence factor data, and an optimization strategy is formulated. According to the technical scheme, optimization of the hydrogen production process is facilitated, the hydrogen production cost is reduced, and important support can be provided for sustainable development of the clean energy industry.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind-solar hydrogen production system optimization, and in particular relates to a wind-solar hydrogen production system optimization control method, system, equipment and medium. Background Art

[0002] Renewable energy and hydrogen energy have natural complementary advantages. The integration of wind and solar power to produce hydrogen is considered to be a relatively feasible new method of energy storage and conversion. As an emerging method of hydrogen energy production, it has attracted widespread attention due to its high renewable energy utilization rate, zero emissions in the production process, and environmental friendliness.

[0003] Renewable energy hydrogen production mainly uses water electrolysis to convert hydrogen into hydrogen. At present, the technical routes for water electrolysis hydrogen production mainly include alkaline water electrolysis (ALK), proton exchange membrane water electrolysis (PEM) and solid oxide water electrolysis (SOEC). Among them, alkaline (ALK) and proton exchange membrane (PEM) electrolyzer hydrogen production technology has entered the commercialization stage, and SOEC technology is still in the research and development stage. Due to its low operating current density, large equipment size, alkali corrosion, slow start and stop speed and other disadvantages, alkaline water electrolysis hydrogen production equipment has a slow response speed to renewable energy power generation waves, but its industrial application is early and the purchase cost is low. At present, its industrial application in China is relatively mature. The proton exchange membrane water electrolysis hydrogen production device has the advantages of small size, high current density and high hydrogen production efficiency while the equipment has a fast start and stop speed, and can respond quickly to the fluctuations of renewable energy power generation. However, due to the use of precious metals as catalysts, and the fact that components such as proton exchange membranes and precious metal catalysts have not yet been domestically produced, the equipment purchase cost is relatively high. At present, the main issues restricting the development of hydrogen production by water electrolysis are cost and lifespan, mainly because of its high investment cost and operation and maintenance cost. How to reduce the cost of wind and solar integrated hydrogen production technology has become the focus of current research.

[0004] Different new energy hydrogen production technologies have a huge impact on costs. Currently, there is a lack of general standards for the cost estimation methods of new energy power generation and hydrogen production. The research methods used include the full life cycle method, levelized cost of electricity (LCOE), learning curve method and prediction method. Due to the significant differences in the distribution of wind and light resource conditions, the technical processes of different projects, different application scenarios, construction scales, and corporate operation and management costs, the power generation or hydrogen production costs estimated by project data are difficult to reflect the overall industry or national cost level. Therefore, it is of great significance to conduct in-depth research on the coupling technology of wind and light integrated hydrogen production investment cost and operating cost, and explore ways to reduce production costs, improve energy efficiency, and promote the development of the hydrogen energy industry. Summary of the invention

[0005] The purpose of the present invention is to provide a method, system, equipment and medium for optimizing and controlling a wind-solar hydrogen production system to solve the problems existing in the above-mentioned prior art.

[0006] To achieve the above object, the present invention provides an optimization control method for a wind-solar hydrogen production system, comprising:

[0007] Obtain historical cost data for wind and solar power generation hydrogen production systems;

[0008] Calculate the project cost data of different hydrogen production methods and the forecast data of technical parameters of the hydrogen production device within a set time based on the historical cost data;

[0009] Calculate the power generation cost forecast data of different power generation modes within a set time based on the historical cost data;

[0010] Calculate the hydrogen production cost of each hydrogen production method under different power generation methods based on the power generation cost prediction data, the hydrogen production device technical parameter prediction data and the project cost data;

[0011] Determine the key influencing factor data of the hydrogen production cost, perform sensitivity analysis on the hydrogen production cost based on the key influencing factor data, and formulate an optimization strategy based on the sensitivity analysis results.

[0012] Optionally, the hydrogen production method includes alkaline water electrolysis hydrogen production technology and proton exchange membrane water electrolysis hydrogen production technology.

[0013] Optionally, the power generation method includes wind power generation technology and photovoltaic power generation technology.

[0014] Optionally, the project cost data of different hydrogen production methods are calculated based on the historical cost data, specifically including:

[0015] Based on the cost decomposition method, the costs of different hydrogen production methods are classified and analyzed by link, and the cost data of each link is obtained and summarized to obtain the project cost data corresponding to different hydrogen production methods.

[0016] Optionally, the predicted data of technical parameters of the hydrogen production device include power consumption, service life, device cost and operation and maintenance cost.

[0017] Optionally, based on the historical cost data, the power generation cost forecast data of different power generation modes within a set time is calculated, and the specific calculation formula is:

[0018]

[0019] In the formula, is the average power generation cost of the industry in year i; N ij is the average annual electricity cost of enterprise j in year i; C ijis the power generation cost announced by the enterprise; W ij It is the enterprise’s wind power or photovoltaic power generation this year.

[0020] Optionally, the key influencing factor data include wind and solar power generation costs and electrolysis equipment purchase and installation costs.

[0021] A wind-solar hydrogen production system optimization control system, comprising:

[0022] Data acquisition module, used to obtain historical cost data of wind and solar power generation hydrogen production system;

[0023] A cost calculation module is used to calculate the project cost data of different hydrogen production methods and the predicted data of technical parameters of the hydrogen production device within a set time based on the historical cost data; calculate the predicted data of power generation costs of different power generation methods within a set time based on the historical cost data; calculate the hydrogen production cost of each hydrogen production method under different power generation methods based on the predicted data of power generation costs, predicted data of technical parameters of the hydrogen production device and project cost data;

[0024] The sensitivity analysis module is used to determine the key influencing factor data of the hydrogen production cost, perform sensitivity analysis on the hydrogen production cost based on the key influencing factor data, and formulate an optimization strategy based on the sensitivity analysis results.

[0025] An electronic device includes a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute an optimization control method for a wind-solar hydrogen production system.

[0026] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the optimization control method for a wind-solar hydrogen production system.

[0027] The technical effects of the present invention are:

[0028] This paper calculates the cost of hydrogen production from the perspective of wind-solar power generation and hydrogen production integration, and obtains the cost of wind power generation and photovoltaic power generation and hydrogen production integration within a certain period, and intuitively obtains the cost change trend of the wind-solar hydrogen production industry from an overall level. Finally, by conducting a sensitivity analysis on the wind-solar hydrogen production cost model with the cost of hydrogen production equipment and hydrogen production power consumption as key factors, the impact of technological progress and industrial scale expansion on the cost of the two hydrogen production methods is further discussed, which is helpful to optimize the hydrogen production process, reduce the cost of hydrogen production, and provide important support for the sustainable development of the clean energy industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0031] Figure 1 This is a schematic diagram of the structure of a wind-solar power generation and hydrogen production integrated system in an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the cost composition of hydrogen production by electrolysis of water in an embodiment of the present invention;

[0033] Figure 3 Schematic diagram of the power generation cost estimation results of wind power and photovoltaic power generation industries in an embodiment of the present invention; wherein, Figure 3 (a) is a schematic diagram of the wind power industry power generation cost estimation result in an embodiment of the present invention, Figure 3 (b) is a schematic diagram of the power generation cost estimation result of the photovoltaic power generation industry in an embodiment of the present invention;

[0034] Figure 4 The following is a schematic diagram of the cost composition of hydrogen production in four combinations in the embodiments of the present invention; wherein: Figure 4 (a) is a schematic diagram of the hydrogen production cost composition of ALK wind power hydrogen production in an embodiment of the present invention, Figure 4 (b) is a schematic diagram of the hydrogen production cost composition of ALK photovoltaic hydrogen production in an embodiment of the present invention, Figure 4 (c) is a schematic diagram of the hydrogen production cost composition of PEM wind power hydrogen production in an embodiment of the present invention, Figure 4 (d) is a schematic diagram of the hydrogen production cost composition of the PEM photovoltaic hydrogen production in an embodiment of the present invention;

[0035] Figure 5 Schematic diagram of sensitivity analysis of four combination schemes in the embodiment of the present invention; wherein, Figure 5 (a) is a schematic diagram of sensitivity analysis of ALK wind power hydrogen production in an embodiment of the present invention, Figure 5 (b) is a schematic diagram of sensitivity analysis of ALK photovoltaic hydrogen production in an embodiment of the present invention, Figure 5 (c) is a schematic diagram of sensitivity analysis of PEM wind power hydrogen production in an embodiment of the present invention, Figure 5 (d) is a schematic diagram of sensitivity analysis of PEM photovoltaic hydrogen production in an embodiment of the present invention;

[0036] Figure 6 It is an implementation flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0037] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0038] It should be understood that the terms described in the present invention are only for describing special embodiments and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. Each smaller range between the intermediate value in any stated value or stated range and any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0039] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art generally understood by the present invention. Although the present invention describes only preferred methods, any method similar or equivalent to that described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods related to the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0040] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present application description and examples are exemplary only.

[0041] The words “include,” “including,” “have,” “contain,” etc. used in this article are open-ended terms, meaning including but not limited to.

[0042] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0043] Embodiment 1

[0044] like Figure 1 - Figure 6As shown, this embodiment provides an optimization control method for a wind-solar hydrogen production system, including: obtaining historical cost data of a wind-solar hydrogen production system; calculating project cost data of different hydrogen production methods and technical parameter prediction data of the hydrogen production device within a set time based on the historical cost data; calculating power generation cost prediction data of different power generation methods within a set time based on the historical cost data; calculating the hydrogen production cost of each hydrogen production method under different power generation methods based on the power generation cost prediction data, the technical parameter prediction data of the hydrogen production device and the project cost data; determining key influencing factor data of the hydrogen production cost, performing sensitivity analysis on the hydrogen production cost based on the key influencing factor data, and formulating an optimization strategy based on the sensitivity analysis results.

[0045] As the global demand for renewable energy continues to grow, the cost of new energy power generation continues to decrease, and the technical route of wind and solar power generation combined with water electrolysis to produce hydrogen is gradually maturing. This not only helps reduce dependence on fossil fuels, but also brings new development opportunities to the hydrogen energy industry.

[0046] This embodiment will start from the initial construction investment and operating costs of the wind and solar power generation integrated hydrogen production technology solution, explore the costs of four combination solutions: alkaline water electrolysis hydrogen production with wind power generation, alkaline water electrolysis hydrogen production with photovoltaic power generation, proton exchange membrane water electrolysis hydrogen production with wind power generation, and proton exchange membrane water electrolysis hydrogen production with photovoltaic power generation, and construct a corresponding dynamic cost calculation model. In the solution of alkaline water electrolysis hydrogen production with wind power generation, electricity costs and equipment costs dominate. With the continuous advancement of wind power generation technology and cost reduction, electricity costs are also gradually decreasing. At the same time, the maturity of alkaline water electrolysis technology also enables equipment costs to be effectively controlled. Therefore, the cost of this solution shows a significant downward trend within the set period. In order to more intuitively show the cost changes of the four solutions, a corresponding dynamic cost calculation model is constructed. The experimental results show that within the set period (2020-2030), the costs of the four solutions were reduced by 28%, 32%, 33%, and 36%, respectively. By 2030, the hydrogen production costs of each scheme will be 12.4 yuan / kg, 13.4 yuan / kg, 16.1 yuan / kg and 17.2 yuan / kg respectively.

[0047] The results show that with the continuous reduction of the cost of renewable energy power generation and the continuous maturity of water electrolysis hydrogen production technology, the wind and solar integrated hydrogen production solution has a high commercial value. Among the many cost components, electricity cost and equipment cost are the main factors for cost reduction. With the continuous advancement of renewable energy power generation technology and the scale effect, electricity costs will continue to decline. At the same time, the maturity and large-scale production of water electrolysis hydrogen production technology will also effectively control equipment costs. These factors have jointly promoted the reduction of the cost of wind and solar integrated hydrogen production solutions.

[0048] In practical applications, the investment cost and operating cost of key hydrogen production equipment have a decisive impact on the economy and feasibility of hydrogen production technology. Therefore, in-depth research on the coupling relationship between the investment cost and operating cost of key hydrogen production equipment will not only help optimize the hydrogen production process and reduce the cost of hydrogen production, but also provide important support for the sustainable development of the clean energy industry. Reasonable balance between investment cost and operating cost can not only reduce the overall cost of the hydrogen production process, but also improve the utilization rate and economic benefits of hydrogen production equipment, which will help to provide reasonable investment strategies and economic analysis, and improve the sustainable development of the industry.

[0049] In terms of cost, the hydrogen production method has a great impact on the cost of hydrogen production. According to the different materials of the electrolyzer diaphragm, water electrolysis is divided into alkaline (AWE) water electrolysis, proton exchange membrane (PEM) water electrolysis, anion exchange membrane (AEM) and high-temperature solid oxide (SOEC) water electrolysis. Currently, AWE and PEM water electrolysis are mainly used in commercial applications. The purchase cost of AWE equipment is low, but it requires alkaline solution circulation, and the electrolyte is corrosive. Its operating current density is low and the volume is large, so it responds slowly to power fluctuations. PEMEL uses a thinner ion-conducting diaphragm and a membrane electrode structure, so the operating current density is significantly improved, the volume is smaller, it has a fast response capability, and the hydrogen production efficiency is also improved. However, PEMEL uses precious metals as catalysts, which significantly increases the equipment cost.

[0050] Different new energy hydrogen production technologies have a huge impact on costs. Currently, there is a lack of general standards for estimating the cost of new energy power generation and hydrogen production. The research methods used include the full life cycle method, levelized cost of electricity (LCOE), learning curve method and prediction method. Due to the significant differences in the distribution of wind and light resource conditions, the technical processes of different projects, different application scenarios, construction scales, and corporate operation and management costs, the power generation or hydrogen production costs estimated by project data are difficult to reflect the overall industry or national cost level. It is necessary to clarify the production process, achieve unified evaluation through parameter differences, and comprehensively consider multiple factors to evaluate the hydrogen production-operation relationship. The main contents of the study:

[0051] Based on the power generation cost estimation method of the wind and solar power generation industry in Wuchangshi, Xinjiang;

[0052] The cost calculation method of hydrogen production by PEMEL water electrolysis based on cost decomposition method;

[0053] Technical parameter evaluation of PEMEL water electrolysis hydrogen production equipment based on learning curve.

[0054] Determine the combination of wind and solar energy and PEMEL electrolyzer technology, and from the perspective of integrated wind and solar power generation and hydrogen production, use industry power generation calculation methods to establish a unit dynamic electricity price model for the Xinjiang Wuchang wind and solar base; then combine the learning curve to dynamically fit the evaluation parameters of water electrolysis hydrogen production equipment, and conduct a more accurate dynamic evaluation of uncertain factors such as electricity price, electrolysis equipment, system scale, electrolyte volume, etc. that affect the project's net present value and internal rate of return; establish a dynamic coupling relationship between the investment cost and operating cost of key hydrogen production equipment, give a reasonable investment strategy and economic analysis, and determine the optimal investment plan for large-scale green electricity centralized hydrogen production under multiple influencing factors.

[0055] Research method for the integrated cost of wind and solar hydrogen production:

[0056] The wind-solar power generation hydrogen production system is a controllable independent hydrogen production system consisting of wind power generation equipment, photovoltaic power generation equipment, AC-DC converter, electrolyzer and hydrogen storage system. The overall structure of the system is as follows: Figure 1 shown.

[0057] The wind and solar power generation equipment is connected to the AC bus through an AC-DC converter, and the water electrolysis hydrogen production device makes full use of renewable energy to generate hydrogen, which can effectively reduce the phenomenon of wind and solar power abandonment. The system's workflow is that the wind turbine and photovoltaic array use natural wind and solar energy to convert into direct current, and the output electric energy is supplied to the hydrogen production and storage system through the control system. The direct current is converted into hydrogen by electrochemical reaction, which not only realizes the storage of electric energy, but also provides reliable energy support for hydrogen energy load. The generated hydrogen can be used for various types of hydrogen energy loads; this system can make full use of renewable energy and effectively reduce the phenomenon of wind and solar power abandonment.

[0058] In summary, this system workflow closely combines wind turbines, photovoltaic arrays and hydrogen production and storage systems, achieving efficient use of renewable energy and stable supply of hydrogen energy load. With the continuous advancement of technology and the continuous promotion of applications, it is believed that this system will play a more critical role in the future and make important contributions to promoting the construction of a clean, low-carbon and efficient energy system.

[0059] Cost calculation method for each link of hydrogen production by water electrolysis: This embodiment selects the cost decomposition method to calculate the project cost. The cost decomposition method divides the project cost according to different links and elements, and then analyzes the cost of each link in detail, and finally summarizes the total cost of the project. This method helps to have a more comprehensive understanding of the composition of project costs, so as to formulate a more accurate cost control strategy. To apply the cost decomposition method, it is first necessary to clarify that the project includes various links such as the startup phase, implementation phase and closing phase. Hydrogen production by water electrolysis is mainly divided into two major links: initial construction and later operation and maintenance. According to the cost decomposition method, the unit hydrogen production cost (C) of water electrolysis is mainly composed of the initial investment and construction cost (C1) and the later operation and maintenance cost (C2). The specific cost composition is as follows Figure 2 shown.

[0060] If divided in detail according to each production factor, the initial investment and construction costs include land purchase and plant construction costs (C3), electrolysis equipment purchase and installation costs (C4), hydrogen storage equipment purchase and installation costs (C5). Generally speaking, the unit cost of the civil engineering part is 13% of the total cost of the electrolysis hydrogen production project equipment.

[0061] The operation and maintenance cost of hydrogen production by electrolysis is calculated based on the unit H2 production cost, including the unit H2 production water consumption cost (C6), unit H2 production labor cost (C7), unit H2 production device operation and maintenance cost (C8), production power consumption cost (C9) and unit H2 storage power consumption cost (C 10 ). The specific calculation formula is:

[0062] C=C1+C2(1-1

[0063] C1=C3+C4+C5 (1-2)

[0064] C2=C6+C7+C8+C9+C 10 (1-3)

[0065] C3=C4×13% (1-4)

[0066]

[0067] C9=E1D1(1-8)

[0068] C 10 =E2D2 (1-9)

[0069] Where R1 is the cost of electrolysis equipment, RMB / kW; D1 is the unit H 2 The power consumption generated, kWh / kg; P is the unit price of hydrogen storage equipment, yuan; h′ is the use period of hydrogen storage equipment, the specific calculation method is depreciation period × annual operation time, h; V is the capacity of hydrogen compressor, m 3 / h; is the molar volume of H2, m 3 / kg; R2 is the operation and maintenance cost of the electrolysis device, RMB / kW; h is the service life of the battery pack, h; E1 is the price of photovoltaic or wind power required for hydrogen production, RMB·kWh -1 ; E2 is the price of ordinary electricity required to compress H2, yuan·kWh -1 ; D2 is the power consumption per kilogram of H2 compressed, kWh·kg -1 .

[0070] Estimation method of technical parameters of water electrolysis hydrogen production equipment: Under the influence of factors such as the continuous increase in industrial scale and the continuous development of equipment manufacturing technology, it is assumed that the technical parameters of water electrolysis hydrogen production related equipment change at a certain learning rate r, and the learning curve equation of electrolysis parameter change is established. Formula (1-10) describes the learning curve of the change of technical parameters y(x) of the electrolysis device: where x is the xth year; k is the baseline value of the technical parameters in the first year; b is the learning coefficient, which can be obtained by direct measurement. The learning coefficient b is converted to the learning rate r using formula (1-11)

[0071] y(x)=kx b (1-10)

[0072] r=1-2 b (1-11)

[0073] Annual industry wind and solar power generation cost estimation method:

[0074] Description of the annual wind and solar power generation cost estimation method: For the power industry, power generation cost estimation is not only a core issue related to the economic benefits of enterprises, but also a key factor affecting the stability and sustainable development of the entire energy market. With the continuous advancement of technology and the continuous changes in the market, how to accurately and efficiently estimate power generation costs has become a focus of widespread concern in the industry.

[0075] In the current research on the cost estimation of hydrogen production from wind and solar power generation, a generally applicable research method has not yet been formed. The research paths currently adopted by researchers include a variety of methods such as full life cycle cost assessment, levelized cost of electricity (LCOE) quantification, learning curve analysis, and prediction models. However, due to the significant differences in the regional distribution of wind and solar energy resources, and the differences in technical route selection and operation and management methods of different projects, the cost estimation of power generation or hydrogen production for specific projects is difficult to fully reflect the average cost situation of the entire industry.

[0076] The annual industry power generation cost estimation is mainly based on the annual cost data of representative listed companies in the industry. Based on the annual industry perspective, the cost change trend of the entire industry is dynamically analyzed to avoid the impact of the gap between the cost level of a specific project and the cost level of the entire industry caused by individual differences between different projects on the calculation results. Therefore, the overall cost level of the new energy power generation and hydrogen production industry can be more comprehensively understood.

[0077] Annual industry wind and solar power generation cost estimation model: Due to the competition between companies, key data such as the cost per kilowatt-hour of power generation is often regarded as sensitive information and is therefore not disclosed to the outside world. However, through in-depth mining of public data such as the annual financial reports published by different power generation groups and power companies, the company's cost per kilowatt-hour of power generation can be estimated through data such as power generation and power generation costs published in the financial reports. This method does not take into account the construction cost of the equipment during the initial construction, but only considers the operation and maintenance costs and equipment depreciation costs of the project during operation. This embodiment refers to the power generation costs of representative power generation companies in the wind and solar power generation industry, combined with the wind and solar power generation industry data in Wuchangshi, Xinjiang, and uses the average method to estimate the industry's annual power generation costs and establish a mathematical model. The specific formula is as follows:

[0078]

[0079] In the formula, is the average power generation cost of the industry in year i; N ij is the average annual electricity cost of enterprise j in year i; C ij is the power generation cost announced by the enterprise; W ij It is the enterprise’s wind power or photovoltaic power generation this year.

[0080] Data source: The research object is mainly the wind and solar power generation industry in Wuchangshi, Xinjiang, using continuous and non-abnormal data released by wind power and photovoltaic power generation companies in the region. At the same time, data released by some other companies whose main business is wind and solar power generation are also used. The data comes from the financial reports of various companies and the International Energy Agency (IEA) and the National Bureau of Statistics.

[0081] This example introduces and models the research methods of various components of the cost of wind and solar power generation hydrogen production system in detail, including the cost of each link of water electrolysis hydrogen production, parameter prediction of water electrolysis hydrogen production equipment, and the cost per kWh of wind power generation and photovoltaic power generation. The specific research contents are as follows:

[0082] By using the cost decomposition method, the cost of hydrogen production by water electrolysis is classified and analyzed by each link, and a mathematical model of the cost of hydrogen production by water electrolysis is obtained.

[0083] Use learning curves to establish a prediction model for the technical parameters of key equipment for hydrogen production by water electrolysis;

[0084] Annual industry power generation cost estimation method. The difference between it and other power generation cost estimation methods is analyzed, the reasons for choosing this method are explained, and an estimation model for annual industry power generation cost is established using this method.

[0085] The above work has established a model foundation for the subsequent research and related analysis on the coupling technology of investment cost and operating cost of integrated wind and solar hydrogen production. The subsequent analysis work will be carried out based on the above model.

[0086] Cost estimation of wind and solar power integrated hydrogen production:

[0087] Estimation results of annual industry power generation costs for wind power generation and photovoltaic power generation: Based on the annual photovoltaic and wind power generation and power generation costs and other corporate data published by some wind power companies and photovoltaic power generation companies, the costs of China's wind power and photovoltaic power generation industries from 2020 to 2023 were estimated based on the annual industry power generation cost estimation method. Figure 3 shown.

[0088] The results show that in 2020-2023, the overall cost of wind and photovoltaic power generation in China showed a downward trend year by year. Among them, the average cost of wind power generation decreased from 0.201 yuan / kWh to 0.178 yuan / kWh, and the cost of photovoltaic power generation decreased from 0.265 yuan / kWh to 0.170 yuan / kWh. Overall, the total power generation of wind power generation was higher than that of photovoltaic power generation, and the cost of photovoltaic power generation decreased more significantly. This may be because the scale of photovoltaic power generation industry of the selected sample companies has expanded rapidly in recent years, with the overall power generation increasing by 480%, while the growth rate of wind power generation was only 228%. The expansion of the industry scale has led to a reduction in average costs. The costs of wind power generation and photovoltaic power generation vary greatly among different companies due to factors such as different industrial scales, different regional resource distributions, and technological gaps between companies. From the perspective of power generation costs of different companies, there are obvious differences in the power generation costs and power generation of wind power companies, from which it can be seen that there are large differences between companies in the wind power industry. Among them, Jiaze New Energy Company, which has a relatively small scale of power generation industry, has a relatively higher power generation cost, while Inner Mongolia Wind Power, which has a similarly small scale of power generation, has a much lower wind power generation cost because it is located in Inner Mongolia, which is rich in wind resources. Taking photovoltaics as an example, the total photovoltaic power generation of China National Nuclear Corporation and Huaneng International, which have larger industrial scales, will be 23.474 billion kWh in 2023. Their photovoltaic power generation far exceeds the total of the other three companies. The industry concentration is relatively high. Compared with photovoltaic power generation, the concentration of wind power generation is lower. The total power generation of wind power in 2023 will be 65.97 billion kWh, while photovoltaic power generation will be only 27.99 billion kWh. The scale of wind power generation is much higher than that of photovoltaic power generation. Overall, the inter-enterprise differences in the cost of wind power generation are lower than those of photovoltaic power generation, and the maximum difference in the cost of wind power generation is 0.075 yuan·kWh. -1 , while the maximum difference in photovoltaic power generation is 0.101 yuan·kWh-1 .

[0089] According to the latest document released by the Xinjiang Uygur Autonomous Region Development and Reform Commission, the on-grid electricity price of renewable energy power generation after local financial subsidies is 0.262 yuan per kWh. -1 This price is higher than the cost of new energy power generation determined by using the industry's power generation cost, which shows that the estimated cost is more reasonable.

[0090] Estimation of investment parameters for hydrogen production by water electrolysis: The costs of hydrogen production, storage and auxiliary links are estimated, as shown in Table 1.

[0091] Table 1 Estimated parameters of investment cost for each link of water electrolysis

[0092]

[0093] Evaluation of technical parameters of water electrolysis hydrogen production equipment based on learning curve: The International Renewable Energy Agency IREN A has released a forecast of water electrolysis technical parameter data. It announced the changes in cost parameters of alkaline water electrolysis hydrogen production (ALK) and proton exchange membrane water electrolysis hydrogen production (PEM) equipment since 2017 and the forecast of parameters for 2025. The China Electricity Council has announced the cost parameters of alkaline water electrolysis hydrogen production (ALK) and proton exchange membrane water electrolysis hydrogen production (PEM) equipment in 2020. The International Renewable Energy Agency IRENA and the China Hydrogen Energy Alliance have released forecasts of water electrolysis technical parameter data. It predicts the predicted values ​​of changes in cost parameters of alkaline water electrolysis hydrogen production (ALK) and proton exchange membrane water electrolysis hydrogen production (PEM) equipment in 2060. According to the report, assuming that both devices change at a certain learning rate, the data of the two devices in 2017 are used as the baseline value, and the forecast value in 2060 is an estimated value. The learning curve method is used to predict the change trend of four parameters of the two devices from 2018 to 2030, including power consumption, service life, device cost and operation and maintenance cost. Specific parameters are shown in Table 2. The calculation results show that the learning rates of several parameters of the alkaline water electrolysis hydrogen production device are 1.3%, -3.8%, 13.1%, and 13.1%, respectively, while the learning rates of the proton exchange membrane water electrolysis hydrogen production device are 3.4%, -7.3%, 15.6%, and 15.6%. Obviously, the learning rate of the proton exchange membrane water electrolysis hydrogen production device is higher than that of the alkaline water electrolysis device, which may be related to the higher industrial application maturity of the alkaline electrolysis device compared with the proton exchange membrane electrolysis device.

[0094] Table 2 Estimation of technical parameters of 20MW hydrogen production unit

[0095]

[0096] The costs of various parts of the wind and solar power generation hydrogen production system were calculated, including the wind and solar power generation cost, the investment parameter estimation of water electrolysis hydrogen production, and the technical parameters of water electrolysis hydrogen production equipment. The specific research contents are as follows:

[0097] The annual industry power generation cost estimation method is used to calculate the average power generation cost of several wind and solar power generation companies in 2020-2023 in combination with relevant data.

[0098] Using the cost decomposition method, the cost of hydrogen production by water electrolysis was classified and analyzed by link, and the corresponding parameters of the cost of hydrogen production by water electrolysis were obtained.

[0099] The learning curve was used to predict the technical parameters of the two water electrolysis hydrogen production devices, and the changing trends of the technical parameters of the two water electrolysis devices from 2020 to 2030 were obtained.

[0100] Cost analysis of hydrogen production from wind and solar power: Annual industry power generation cost forecast for wind power generation and photovoltaic power generation. Assuming that the costs of wind power generation and photovoltaic power generation change according to a certain rule, China's wind power generation cost in 2015 was 0.510 yuan·kWh-1, and the photovoltaic power generation cost was 0.72 yuan·kWh-1. Taking the average power generation cost of the two power generation methods in 2015 as the benchmark value and the average power generation cost in 2023 as the estimated value, the exponential fitting method was used to predict the changing trend of the costs of the two power generation methods from 2020 to 2030.

[0101] Table 3 Prediction of the cost of two power generation methods

[0102]

[0103] Table 3 shows the predicted parameters. The predicted results are basically consistent with those obtained through the annual industry power generation cost estimation method, so the predicted results are credible. According to the predicted results, the costs of wind power generation and photovoltaic power generation show a clear downward trend year by year between 2020 and 2030. The reasons are related to the continuous technological innovation in the two renewable energy technology fields, the expansion of production scale and the overall optimization of the industrial chain.

[0104] In the wind power industry, the continuous updating and iteration of wind turbine technology and the expansion of production scale have gradually reduced the cost of wind power generation. At the same time, as the proportion of wind power generation in electricity supply continues to increase, the related operation and maintenance and management costs are also continuously optimized. These factors together will keep the cost of wind power generation at a low level in the next decade.

[0105] In the photovoltaic power generation industry, the improvement of photovoltaic cell efficiency and the reduction of photovoltaic material costs have driven the gradual decline in photovoltaic power generation costs. In addition, with the expansion of photovoltaic power station construction and the popularization of distributed photovoltaic applications, the cost of photovoltaic power generation has also shown a downward trend. It is expected that in the next few years, with further breakthroughs in photovoltaic power generation technology and the continued growth of market demand, the cost of photovoltaic power generation will continue to decline.

[0106] The cost of hydrogen production from the perspective of wind-solar power generation and hydrogen production integration: In order to obtain the cost of hydrogen production from the perspective of wind-solar power generation and hydrogen production integration, the photovoltaic power generation and wind power generation costs calculated in Table 3 are used as the electricity costs of the hydrogen production process. Combined with the cost data of each link of hydrogen production estimated in Table 1 and the technical parameters of the hydrogen production device estimated in Table 2, the cost of hydrogen production from the perspective of wind-solar power generation and hydrogen production integration is calculated. The hydrogen production costs of the two technologies of alkaline water electrolysis and proton exchange membrane water electrolysis in different scenarios of wind power generation and photovoltaic power generation in China from 2020 to 2030 are calculated, such as Figure 4 shown.

[0107] The results show that the costs of both hydrogen production methods are on a downward trend between 2020 and 2030, mainly due to the reduction in the costs of wind power generation and photovoltaic power generation and the reduction in the cost of electrolysis equipment. The main reasons for the reduction in power generation costs and equipment costs are the impact of industrial scale and the improvement and progress of technology and manufacturing processes. Among them, the cost of hydrogen production by ALK wind power generation dropped from 17.3 yuan / kg in 2020 to 12.4 yuan / kg in 2030, a decrease of 28% during this period. The cost of hydrogen production by ALK photovoltaic power generation dropped from 19.8 yuan / kg in 2020 to 13.4 yuan / kg, a decrease of 32%. The cost of hydrogen production by PEM wind power generation dropped from 24.3 yuan / kg in 2020 to 16.1 yuan / kg in 2030, a decrease of 33%. The cost of hydrogen production by PEM photovoltaic power generation dropped from 27.0 yuan / kg in 2020 to 17.2 yuan / kg in 2030, a decrease of 36%.

[0108] During 2020-2030, the cost reduction of PEM electrolysis hydrogen production equipment in combination with wind power generation and photovoltaic power generation is higher than that of ALK electrolysis hydrogen production equipment in combination with wind power generation and photovoltaic power generation, but due to its higher price, ALK electrolysis is still more economical at present. Compared with wind power generation, photovoltaic power generation has a greater cost reduction when used with the same electrolysis technology, but also due to its higher price, wind power generation combined with electrolysis is still more economical at present.

[0109] Hydrogen production cost sensitivity analysis: In order to further explore the specific impact of equipment technology factors and electricity costs on the ALK and PEM hydrogen production costs, according to Figure 4The cost structure of hydrogen production is shown, and the cost of wind and solar power generation and the cost of purchasing and installing electrolysis equipment are selected as key influencing factors. On this basis, using the various parameter data in 2020, a sensitivity analysis of the hydrogen production cost with a fluctuation range of 20% was conducted. The analysis results are as follows: Figure 5 As shown. Through analysis, we can intuitively see the sensitivity of the above two factors to the unit hydrogen production cost. The larger the absolute value of the slope of a certain influencing factor, the more significant and sensitive the impact of this factor on the unit hydrogen production cost, which provides important data support and theoretical basis for the subsequent optimization of hydrogen production costs and improvement of energy utilization efficiency. The results show that among the two water electrolysis hydrogen production methods, the ALK water electrolysis hydrogen production method is more sensitive to the electricity price cost in the hydrogen production process. Under the same conditions and the same fluctuation range, as the electricity cost decreases, the ALK water electrolysis hydrogen production cost decreases faster, while the sensitivity of PEM water electrolysis hydrogen production to electricity cost and hydrogen production equipment cost is basically similar.

[0110] This embodiment uses the exponential fitting method to fit the power generation cost of the wind and solar industry within a set period, and predicts the changes in the industry's power generation cost during the period 2023-2030. The final prediction results are basically consistent with the known situation, so it can be considered that this prediction is relatively accurate. Secondly, the cost of hydrogen production from the perspective of wind and solar power generation and hydrogen production integration is calculated, and the cost of wind power generation and photovoltaic power generation and hydrogen production integration within a certain period is obtained, and the cost change trend of the wind and solar hydrogen production industry is intuitively obtained from the overall level. Finally, by conducting a sensitivity analysis on the wind and solar hydrogen production cost model with the cost of hydrogen production equipment and hydrogen production power consumption as key factors, the impact of technological progress and industrial scale expansion on the cost of the two hydrogen production methods is further discussed.

[0111] This example provides a detailed introduction and modeling of the various components of the wind and solar power generation hydrogen production system cost, and mainly completes the following tasks:

[0112] The cost of wind and solar power generation is estimated using the power generation cost estimation method of Xinjiang Wuchangshi wind and solar power generation industry, a dynamic electricity price model is established, and the trend of power generation cost changes within the set period (2020-2030) is predicted; the factors affecting the cost of hydrogen production by electrolysis of water are predicted based on the cost decomposition method, and the cost is calculated; the technical parameters of hydrogen production equipment by electrolysis of water are evaluated based on the learning curve, and a more accurate dynamic evaluation is conducted on uncertain factors such as electricity price, electrolysis equipment, system scale, and electrolyte volume that affect the net present value and internal rate of return of the project. The costs of four combination schemes are discussed, including alkaline water electrolysis hydrogen production combined with wind power generation, alkaline water electrolysis hydrogen production combined with photovoltaic power generation, proton exchange membrane water electrolysis hydrogen production combined with wind power generation, and proton exchange membrane water electrolysis hydrogen production combined with photovoltaic power generation, and the corresponding dynamic cost estimation model is constructed.

[0113] A wind-solar hydrogen production system optimization control system, comprising:

[0114] Data acquisition module, used to obtain historical cost data of wind and solar power generation hydrogen production system;

[0115] A cost calculation module is used to calculate the project cost data of different hydrogen production methods and the predicted data of technical parameters of the hydrogen production device within a set time based on the historical cost data; calculate the predicted data of power generation costs of different power generation methods within a set time based on the historical cost data; calculate the hydrogen production cost of each hydrogen production method under different power generation methods based on the predicted data of power generation costs, predicted data of technical parameters of the hydrogen production device and project cost data;

[0116] The sensitivity analysis module is used to determine the key influencing factor data of the hydrogen production cost, perform sensitivity analysis on the hydrogen production cost based on the key influencing factor data, and formulate an optimization strategy based on the sensitivity analysis results.

[0117] An electronic device includes a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute an optimization control method for a wind-solar hydrogen production system.

[0118] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the optimization control method for a wind-solar hydrogen production system.

[0119] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A wind-solar hydrogen production system optimization control method, characterized in that: include: Obtain historical cost data for wind and solar power generation hydrogen production systems; Calculate the project cost data of different hydrogen production methods and the forecast data of technical parameters of the hydrogen production device within a set time based on the historical cost data; Calculate the power generation cost forecast data of different power generation modes within a set time based on the historical cost data; Calculate the hydrogen production cost of each hydrogen production method under different power generation methods based on the power generation cost prediction data, the hydrogen production device technical parameter prediction data and the project cost data; Determine the key influencing factor data of the hydrogen production cost, perform sensitivity analysis on the hydrogen production cost based on the key influencing factor data, and formulate an optimization strategy based on the sensitivity analysis results.

2. The optimization control method of a wind-solar hydrogen production system according to claim 1 is characterized in that: The hydrogen production methods include alkaline water electrolysis hydrogen production technology and proton exchange membrane water electrolysis hydrogen production technology.

3. The optimization control method of a wind-solar hydrogen production system according to claim 1 is characterized in that: The power generation methods include wind power generation technology and photovoltaic power generation technology.

4. The optimization control method for a wind-solar hydrogen production system according to claim 1 is characterized in that: Based on the historical cost data, the project cost data of different hydrogen production methods are calculated, including: Based on the cost decomposition method, the costs of different hydrogen production methods are classified and analyzed by link, and the cost data of each link is obtained and summarized to obtain the project cost data corresponding to different hydrogen production methods.

5. The optimization control method for a wind-solar hydrogen production system according to claim 1 is characterized in that: The predicted data of technical parameters of the hydrogen production device include power consumption, service life, device cost and operation and maintenance cost.

6. The optimization control method for a wind-solar hydrogen production system according to claim 1, characterized in that: Based on the historical cost data, the power generation cost forecast data of different power generation methods within a set time is calculated, and the specific calculation formula is: In the formula, is the average power generation cost of the industry in year i; N ij is the average annual electricity cost of enterprise j in year i; C ij is the power generation cost announced by the enterprise; W ij It is the wind power or photovoltaic power generation of the enterprise this year.

7. The optimization control method for a wind-solar hydrogen production system according to claim 1, characterized in that: The key influencing factors data include the cost of wind and solar power generation and the cost of purchasing and installing electrolysis equipment.

8. An optimization control system for a wind-solar hydrogen production system, characterized in that: include: Data acquisition module, used to obtain historical cost data of wind and solar power generation hydrogen production system; A cost calculation module is used to calculate the project cost data of different hydrogen production methods and the predicted data of technical parameters of the hydrogen production device within a set time based on the historical cost data; calculate the predicted data of power generation costs of different power generation methods within a set time based on the historical cost data; calculate the hydrogen production cost of each hydrogen production method under different power generation methods based on the predicted data of power generation costs, predicted data of technical parameters of the hydrogen production device and project cost data; The sensitivity analysis module is used to determine the key influencing factor data of the hydrogen production cost, perform sensitivity analysis on the hydrogen production cost based on the key influencing factor data, and formulate an optimization strategy based on the sensitivity analysis results.

9. An electronic device, characterized in that: It includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute a wind-solar hydrogen production system optimization control method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: It stores a computer program, which, when executed by a processor, implements an optimization control method for a wind-solar hydrogen production system as described in any one of claims 1-7.

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