Capacity planning method and device for light hydrogen storage integrated energy system

Abstract

The invention relates to a capacity planning method and device for a light hydrogen storage integrated energy system. The method comprises the following steps: acquiring energy data of the photo-hydrogen storage integrated energy system; the energy data comprises the power of equipment in the light-hydrogen storage integrated energy system and the load demand for the light-hydrogen storage integrated energy system; inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the light-hydrogen storage integrated energy system; and inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the light-hydrogen storage integrated energy system, and returning to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the light-hydrogen storage integrated energy system. By adopting the method, the capacity planning accuracy of the light-hydrogen storage integrated energy system can be improved.

Description

Technical Field

[0001] The present application relates to the field of energy technology, and in particular to a capacity planning method, apparatus, computer equipment, computer-readable storage medium and computer program product for a photovoltaic hydrogen storage integrated energy system. Background Art

[0002] With the development of renewable energy technology, how to build a comprehensive energy system that is multi-energy coupled, flexible, efficient, clean and low-carbon, promote the efficient conversion and utilization of energy, and promote the low-carbon (zero-carbon) development of urban regional comprehensive energy systems has become a focus of common concern in academia and industry. As a model of clean and renewable energy, hydrogen energy has demonstrated great potential for environmental benefits through the electrolysis of green electricity (solar energy, wind energy, etc.), providing a new direction for energy transformation. In addition, compared with electrochemical energy storage, hydrogen energy storage has the advantages of long-term energy storage, large-scale storage and flexible transportation.

[0003] However, due to the randomness and intermittent nature of renewable energy generation such as photovoltaics, the existing capacity planning methods for integrated photovoltaic, hydrogen and storage energy systems do not pay attention to the coordinated planning of multi-energy coupling, resulting in the inability to accurately plan the capacity of integrated photovoltaic, hydrogen and storage energy systems. Summary of the invention

[0004] Based on this, it is necessary to provide a capacity planning method, device, computer equipment, computer-readable storage medium and computer program product for a photo-hydrogen storage integrated energy system that can improve the accuracy of capacity planning of the photo-hydrogen storage integrated energy system in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a capacity planning method for a photovoltaic hydrogen storage integrated energy system, comprising:

[0006] Obtaining energy data of the photovoltaic hydrogen storage integrated energy system; the energy data includes the power of equipment in the photovoltaic hydrogen storage integrated energy system and the load demand for the photovoltaic hydrogen storage integrated energy system;

[0007] Inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the solar-hydrogen storage integrated energy system;

[0008] The equipment capacity is input into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and the process returns to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system.

[0009] In one embodiment, the energy data also includes value description data of the photovoltaic hydrogen storage integrated energy system; the first-stage planning optimization model includes an annual economic value calculation model, an annual carbon emission calculation model, and an annual energy shortage rate calculation model; the energy data is input into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system, including:

[0010] Inputting the value description data into the annual economic value calculation model to obtain the annual economic value;

[0011] Inputting the power of the device into the annual carbon emissions calculation model to obtain annual carbon emissions;

[0012] Inputting the load demand into the annual energy shortage rate calculation model to obtain the annual energy shortage rate;

[0013] Under the condition that the constraints of the first-stage planning optimization model are met, the equipment capacity that minimizes the annual economic value, the annual carbon emissions and the annual energy shortage rate is determined as the equipment capacity of the solar-hydrogen storage integrated energy system; the constraints of the first-stage planning optimization model include the installation constraints of the equipment, the capacity constraints of the equipment and the load demand constraints.

[0014] In one embodiment, before inputting the power of the device into the annual carbon emissions calculation model to obtain the annual carbon emissions, the method further includes:

[0015] Obtain the equipment cycle carbon emissions and energy cycle carbon emissions of the photohydrogen storage integrated energy system; the equipment cycle carbon emissions include the carbon emissions of the equipment in the photohydrogen storage integrated energy system during the three stages of production, operation and disposal; the energy cycle carbon emissions include the carbon emissions of the three stages of mining, operation and disposal during the process of the photohydrogen storage integrated energy system consuming external energy;

[0016] The step of inputting the power of the device into the annual carbon emission calculation model to obtain the annual carbon emission comprises:

[0017] The power input of the equipment, the equipment cycle carbon emissions and the energy cycle carbon emissions are input into the annual carbon emissions calculation model to obtain the annual carbon emissions.

[0018] In one embodiment, inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the solar-hydrogen storage integrated energy system includes:

[0019] Inputting the equipment capacity into the annual operation value calculation model to obtain the annual operation value;

[0020] Under the condition that the constraints of the second-stage operation optimization model are met, the power of the equipment that minimizes the annual operation value is determined as the power of the equipment after update; the constraints of the second-stage operation optimization model include power balance constraints, energy network transmission power constraints, and equipment power constraints.

[0021] In one embodiment, obtaining energy data of the solar-hydrogen storage integrated energy system includes:

[0022] Inputting the photovoltaic component description data of the photovoltaic hydrogen storage integrated energy system into the photovoltaic power generation model to obtain the power of the photovoltaic components in the photovoltaic hydrogen storage integrated energy system;

[0023] The energy data of the photovoltaic hydrogen storage integrated energy system is determined according to the power of the photovoltaic module.

[0024] In one embodiment, before inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, the method further includes:

[0025] Inputting the hydrogen storage device description data of the light-hydrogen storage integrated energy system into the hydrogen storage device model to obtain the hydrogen description data of the hydrogen storage device in the light-hydrogen storage integrated energy system; the hydrogen description data includes the hydrogen storage capacity of the hydrogen storage device;

[0026] The step of inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system includes:

[0027] The equipment capacity and the hydrogen description data are input into the second-stage operation optimization model to obtain the updated power of the equipment in the solar-hydrogen storage integrated energy system.

[0028] In a second aspect, the present application also provides a capacity planning device for a photovoltaic hydrogen storage integrated energy system, comprising:

[0029] A data acquisition module, used to acquire energy data of the photovoltaic hydrogen storage integrated energy system; the energy data includes the power of equipment in the photovoltaic hydrogen storage integrated energy system and the load demand for the photovoltaic hydrogen storage integrated energy system;

[0030] A capacity planning module, used to input the energy data into the first-stage planning optimization model to obtain the equipment capacity of the solar-hydrogen storage integrated energy system;

[0031] The power update module is used to input the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and return to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system.

[0032] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0033] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0034] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0035] The above-mentioned capacity planning method, device, computer equipment, computer-readable storage medium and computer program product of the photovoltaic hydrogen storage integrated energy system obtain energy data of the photovoltaic hydrogen storage integrated energy system, and the energy data includes the power of the equipment in the photovoltaic hydrogen storage integrated energy system and the load demand for the photovoltaic hydrogen storage integrated energy system; input the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system; input the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and return to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system. By inputting energy data such as equipment power and load demand into the first-stage planning optimization model, the capacity allocation of each device in the system can be optimized, the accuracy of capacity planning of the photovoltaic, hydrogen and storage integrated energy system can be improved, and the equipment can be ensured to avoid excessive or small equipment capacity while meeting load demand, thereby improving the overall economy and operation efficiency of the system; the second-stage operation optimization model further utilizes the equipment capacity data of the first stage to adjust the power output of the equipment, thereby outputting the updated and optimized equipment capacity. Through two-stage optimization planning, it is ensured that the photovoltaic, hydrogen and storage integrated energy system can flexibly adjust the equipment capacity according to actual operating conditions, further improving the accuracy of capacity planning of the photovoltaic, hydrogen and storage integrated energy system, thereby improving the stability of system operation and resource utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0037] FIG1 is an application environment diagram of a capacity planning method for a photovoltaic hydrogen storage integrated energy system in one embodiment;

[0038] FIG2 is a schematic flow chart of a capacity planning method for a photovoltaic hydrogen storage integrated energy system in one embodiment;

[0039] FIG3 is an architecture diagram of a solar-hydrogen storage integrated energy system in one embodiment;

[0040] FIG4 is a flow chart of a bidirectional interaction between electricity and hydrogen in a photovoltaic hydrogen storage integrated energy system according to an embodiment;

[0041] FIG5 is a logic diagram of a two-stage capacity planning method in one embodiment;

[0042] FIG6 is a logic diagram of another two-stage capacity planning method in one embodiment;

[0043] FIG7 is a flow chart of a capacity planning method for a photovoltaic hydrogen storage integrated energy system in another embodiment;

[0044] FIG8 is a structural block diagram of a capacity planning device for a photovoltaic hydrogen storage integrated energy system in one embodiment;

[0045] FIG. 9 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] The capacity planning method of the photo-hydrogen storage integrated energy system provided in the embodiment of the present application can be applied to the application environment shown in Figure 1. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 obtains the energy data of the photo-hydrogen storage integrated energy system; the energy data includes the power of the equipment in the photo-hydrogen storage integrated energy system and the load demand for the photo-hydrogen storage integrated energy system; the terminal 102 inputs the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photo-hydrogen storage integrated energy system; the equipment capacity includes the rated power of the equipment; the terminal 102 inputs the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photo-hydrogen storage integrated energy system, and returns to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photo-hydrogen storage integrated energy system. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices, etc. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0048] In an exemplary embodiment, as shown in FIG2 , a capacity planning method for a photovoltaic hydrogen storage integrated energy system is provided, which is described by taking the method applied to the terminal in FIG1 as an example, including:

[0049] Step S202, obtaining energy data of the solar-hydrogen storage integrated energy system.

[0050] Among them, the energy data includes the power of the equipment in the photovoltaic, hydrogen and storage integrated energy system and the load demand for the photovoltaic, hydrogen and storage integrated energy system.

[0051] In specific implementation, energy data may include relevant data on the operation of each device in the solar-hydrogen storage integrated energy system, such as the power output or input of each device, and the load demand in the system (i.e., the electricity, heat and other energy required by the entire system in a certain period of time).

[0052] The power of the device may include the rated power of the device, that is, the maximum power that the device can stably output or process under standard operating conditions, and may also include the actual power.

[0053] Among them, the load demand may include the actual demand for different types of load energy, such as electricity load demand, thermal load demand, cooling load demand and hydrogen load demand.

[0054] Among them, the integrated energy system of photo-hydrogen storage can be an energy system that combines solar power generation with hydrogen production and storage technology. Solar energy is converted into electrical energy through photovoltaic power generation, and the excess electricity is used to electrolyze water to generate hydrogen. The hydrogen is stored and used to generate electricity or supply other applications through fuel cells when needed. The system can balance the volatility of photovoltaic power generation and achieve efficient utilization of energy and low-carbon supply.

[0055] To facilitate the understanding of those skilled in the art, FIG3 exemplarily provides an architecture diagram of a comprehensive energy system of light, hydrogen and storage. The comprehensive energy system of light, hydrogen and storage can be an energy system covering energy production, conversion, storage and consumption. By integrating multiple energy sources in the region, it realizes coordinated planning, operation optimization and complementary assistance among heterogeneous energy subsystems. As shown in FIG3, the system is mainly composed of electricity, heat, cold, gas and hydrogen networks. It not only integrates solar photovoltaic power generation technology, hydrogen production and storage technology, but also incorporates efficient energy conversion and distribution mechanisms, aiming to achieve efficient use of energy, reduce carbon emissions, and enhance the security and stability of energy supply. On the basis of traditional energy systems, the system further expands the diversification and flexibility of the energy structure, and is one of the key paths to achieve energy transformation and sustainable development goals.

[0056] In one embodiment, key equipment (photovoltaic components, hydrogen storage equipment) of the photovoltaic hydrogen storage integrated energy system can be modeled. The photovoltaic hydrogen storage integrated energy system can include a photovoltaic power generation model and a hydrogen storage equipment model.

[0057] Among them, the output power of photovoltaic power generation is mainly affected by factors such as ambient temperature and solar radiation intensity. The photovoltaic power generation model can be described as:

[0058] ;

[0059] ;

[0060] Where: is the actual output power of the photovoltaic panel; is the number of PV panels; is the rated power of the PV module; and They represent the solar radiation intensity and ambient temperature under standard ambient conditions. , the ambient temperature is 25℃; is the power temperature coefficient, which reflects the influence of temperature on photovoltaic modules; and are the actual solar radiation intensity and actual operating temperature of the photovoltaic module respectively; is the actual ambient temperature.

[0061] Among them, the photohydrogen storage integrated energy system mainly selects hydrogen storage equipment based on the power-to-gas technology. In order to facilitate the understanding of those skilled in the art, Figure 4 exemplarily provides a flow chart of the two-way interaction of electricity and hydrogen in a photohydrogen storage integrated energy system. The installed capacity of renewable energy can be more effectively utilized through the two-way interaction of electricity and hydrogen, thereby reducing the abandonment of renewable energy. Among them, the hydrogen storage equipment includes an electrolyzer, a fuel cell and a hydrogen storage tank. When the electrolyzer is started, an oxidation reaction occurs at the interface between the anode and the solution, and a reduction reaction occurs at the interface between the cathode and the solution, thereby producing hydrogen. The fuel cell directly converts the chemical energy of hydrogen and oxygen into electrical energy, and performs the reverse reaction of electrolyzing water. The hydrogen storage tank is used to store hydrogen to achieve energy storage.

[0062] The hydrogen storage device model can be described as:

[0063] ;

[0064] ;

[0065] ;

[0066] Where: Indicates that the electrolytic cell Hydrogen production at the time; Indicates that the electrolytic cell The electrical power consumed at any given moment; is the conversion efficiency of the electrolyzer; The fuel cell Hydrogen consumption at each time; The fuel cell Output power at the moment; is the conversion efficiency of the fuel cell; , and Respectively represent the hydrogen storage tank The amount of hydrogen stored, injected and consumed at each moment.

[0067] In order to further reduce the curtailment of renewable energy and improve energy efficiency, when the photovoltaic output (photovoltaic power generation) exceeds the current electrical load demand, the electrolyzer uses the excess electricity to produce hydrogen. Conversely, when the photovoltaic output (photovoltaic power generation) is not enough to meet the electrical load demand, the fuel cell is activated or the electricity is purchased to fill the power gap.

[0068] In order to further reduce the curtailment of renewable energy and improve energy efficiency, when the photovoltaic output exceeds the current electricity load demand, the electrolyzer uses the excess electricity to produce hydrogen. Conversely, when the photovoltaic output is not enough to meet the electricity load demand, the fuel cell is activated or the electricity is purchased to fill the power gap. Therefore, the amount of hydrogen injected and hydrogen consumption Can be expressed as:

[0069]

[0070]

[0071] ;

[0072] Where: represents the electrical load demand at time t; represents the electric power delivered by the external power grid at time t; It indicates the amount of hydrogen supplied by the hydrogen storage tank to the hydrogen load at time t; and 0,1 variables.

[0073] It can be seen that on the basis of the existing power system, natural gas system, cooling / heating system and other structures, a hydrogen energy subsystem consisting of key components such as electrolyzers, hydrogen storage tanks, and hydrogen fuel cells was introduced to build a complete topological structure of the photovoltaic hydrogen storage integrated energy system. Through in-depth analysis of the coupling and interactive relationship between the key equipment in the system, the key equipment of the photovoltaic power generation and hydrogen energy subsystems was refined modeling, laying a solid foundation for system integration and performance improvement.

[0074] Step S204, input the energy data into the first stage planning optimization model to obtain the equipment capacity of the solar hydrogen storage integrated energy system.

[0075] Among them, the first-stage planning optimization model can optimize the equipment capacity of each device in the solar-hydrogen storage integrated energy system based on energy data.

[0076] Equipment capacity may refer to installed capacity, which may include the rated capacity or rated power of the equipment. In specific implementation, the equipment capacity of each device in the photovoltaic hydrogen storage integrated energy system may include the installed capacity of photovoltaic modules, electrolyzers, hydrogen fuel cells, hydrogen storage tanks, combined heat and power units, electric boiler equipment, electric refrigeration equipment, and electric and thermal energy storage equipment.

[0077] In one embodiment, the energy data also includes value description data of the photovoltaic hydrogen storage integrated energy system; the first-stage planning optimization model includes an annual economic value calculation model, an annual carbon emissions calculation model and an annual energy shortage rate calculation model; the energy data is input into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system, including: inputting the value description data into the annual economic value calculation model to obtain the annual economic value; inputting the power of the equipment into the annual carbon emissions calculation model to obtain the annual carbon emissions; inputting the load demand into the annual energy shortage rate calculation model to obtain the annual energy shortage rate; under the condition of satisfying the constraints of the first-stage planning optimization model, determining the equipment capacity that minimizes the annual economic value, annual carbon emissions and annual energy shortage rate as the equipment capacity of the photovoltaic hydrogen storage integrated energy system; the constraints of the first-stage planning optimization model include equipment installation constraints, equipment capacity constraints and load demand constraints.

[0078] Among them, the value description data may include data describing the economic benefits of the integrated solar-hydrogen storage energy system, such as equipment purchase cost, operation and maintenance cost, natural gas purchase cost, electrolysis water cost, electricity purchase cost, hydrogen purchase cost, etc.

[0079] The annual economic value calculation model can determine the annual economic value based on the above value description data, wherein the annual economic value may include the annual economic cost.

[0080] The annual carbon emissions calculation model can determine the annual carbon emissions based on the power of the equipment, including the carbon emissions directly or indirectly generated by the equipment during operation, such as the carbon emissions of fuel cells, photovoltaic power generation, etc. For example, the power of the equipment can reflect the actual electricity consumed or generated by the equipment during actual operation. For example, in the process of converting hydrogen into electrical energy, fuel cells consume energy and may cause certain carbon emissions.

[0081] The annual energy shortage rate calculation model can calculate the energy gap that may occur when the system matches supply and demand based on the load demand. The higher the energy shortage rate, the greater the degree to which the system cannot meet the load demand. The lower the energy shortage rate, the higher the stability of the system, ensuring that the system can provide stable power and energy.

[0082] While satisfying the constraints of the first-stage planning optimization model (installation constraints, capacity constraints, and load demand constraints), the goal is to find an optimal equipment capacity so that the system's annual economic value, annual carbon emissions, and annual energy shortage rate all reach the lowest values.

[0083] The installation constraints may include space, technology and other limitations imposed on the system during the installation of the equipment, such as the physical size of the equipment and the available space.

[0084] The capacity constraint may include a maximum or minimum capacity limit of a device, such as a maximum power output that each device can support.

[0085] The load demand constraint condition may include that the output power of the equipment can meet the actual load demand of the system.

[0086] By comprehensively considering the annual economic value, carbon emissions and energy shortage rate, the first-stage planning optimization model will give an optimal equipment capacity configuration plan. Under such equipment capacity configuration, the system can not only meet the current load demand, but also achieve stable operation under low carbon and low cost conditions.

[0087] Step S206, input the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and return to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system.

[0088] The second-stage operation optimization model can dynamically adjust the power output of the equipment based on the equipment capacity, combined with load fluctuations, energy input (such as changes in photovoltaic power generation) and other external factors in the actual operation of the system. Through this optimization process, the optimal output power of the equipment under different load conditions can be determined to ensure the stability and flexibility of the system operation.

[0089] The power of the equipment after the equipment is updated in the hydrogen storage integrated energy system is obtained through the second-stage operation optimization model, which can be regarded as the operation adjustment process of the equipment, ensuring that the equipment can flexibly output the appropriate power under different actual needs, and after obtaining the updated equipment power in the second stage, the system returns the operation results to the first stage. This feedback mechanism can further optimize the installed capacity of the equipment, so that the system can continuously adjust according to the actual operation conditions, thereby gradually approaching the optimal capacity configuration plan. Therefore, not only can the equipment capacity be optimized in the initial planning stage, but the power output of the equipment can also be adjusted according to the actual operation conditions, thereby adjusting the equipment capacity, improving the capacity planning accuracy of the light hydrogen storage integrated energy system, and forming a dynamic optimization cycle. By continuously iteratively optimizing the equipment capacity and power output, it is ensured that the system achieves the lowest energy consumption and operating costs while meeting the load requirements.

[0090] In one of the embodiments, the equipment capacity is input into the second-stage operation optimization model to obtain the updated power of the equipment in the solar-hydrogen storage integrated energy system, including: inputting the equipment capacity into the annual operation value calculation model to obtain the annual operation value; under the condition that the constraints of the second-stage operation optimization model are met, determining the power of the equipment that makes the annual operation value the lowest as the updated power of the equipment; the constraints include power balance constraints, energy network transmission power constraints, and equipment power constraints.

[0091] In the first stage, the equipment capacity has been determined through the planning optimization model. The task of the second stage is to further optimize the power output of the equipment in actual operation based on these determined equipment capacities.

[0092] The annual operating value can be a comprehensive indicator to measure the operating cost and economic benefits of the solar-hydrogen storage integrated energy system in a year, such as the energy consumption cost of the equipment in a whole year, equipment maintenance costs, external energy purchase costs, etc., as well as the economic benefits brought by the ability of some equipment (such as photovoltaic power generation or hydrogen energy) to export electricity or hydrogen energy to the outside world.

[0093] Among them, the power balance constraint condition can mean that the energy supply and energy consumption in the system must be balanced, that is, the energy produced by the system must match the load demand.

[0094] The energy network transmission power constraint condition may refer to the power limitation to which the energy in the system is subject when it is transmitted in the network.

[0095] The equipment power constraint condition may refer to that the actual power output of the equipment cannot exceed its designed maximum capacity. Even if the capacity of the equipment has been planned in the first stage, the output power of the equipment is still constrained by its technical parameters and physical limitations in the actual operation of the second stage.

[0096] By combining the annual operation value calculation model with the above constraints, the second-stage operation optimization model will calculate the lowest annual operation value under the premise of satisfying the constraints of power balance, network transmission power and equipment power to determine the power after the equipment is updated. The updated power represents the optimal output power of the equipment in the current operating environment and can be used to continuously adjust the planned capacity.

[0097] In the above-mentioned capacity planning method of the photovoltaic, hydrogen storage integrated energy system, energy data of the photovoltaic, hydrogen storage integrated energy system is obtained, and the energy data includes the power of the equipment in the photovoltaic, hydrogen storage integrated energy system and the load demand for the photovoltaic, hydrogen storage integrated energy system; the energy data is input into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic, hydrogen storage integrated energy system; the equipment capacity is input into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic, hydrogen storage integrated energy system, and the method returns to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic, hydrogen storage integrated energy system. By inputting energy data such as equipment power and load demand into the first-stage planning optimization model, the capacity allocation of each device in the system can be optimized, the accuracy of capacity planning of the photovoltaic, hydrogen and storage integrated energy system can be improved, and the equipment can be ensured to avoid excessive or small equipment capacity while meeting load demand, thereby improving the overall economy and operation efficiency of the system; the second-stage operation optimization model further utilizes the equipment capacity data of the first stage to adjust the power output of the equipment, thereby outputting the updated and optimized equipment capacity. Through two-stage optimization planning, it is ensured that the photovoltaic, hydrogen and storage integrated energy system can flexibly adjust the equipment capacity according to actual operating conditions, further improving the accuracy of capacity planning of the photovoltaic, hydrogen and storage integrated energy system, thereby improving the stability of system operation and resource utilization efficiency.

[0098] In another embodiment, before inputting the power of the equipment into the annual carbon emissions calculation model to obtain the annual carbon emissions, it also includes: obtaining the equipment cycle carbon emissions and energy cycle carbon emissions of the light hydrogen storage integrated energy system; inputting the power of the equipment into the annual carbon emissions calculation model to obtain the annual carbon emissions, including: inputting the power input of the equipment, the equipment cycle carbon emissions and the energy cycle carbon emissions into the annual carbon emissions calculation model to obtain the annual carbon emissions.

[0099] Various production, conversion and storage equipment in the photo-hydrogen storage integrated energy system not only directly emits carbon dioxide during the operation stage, but also produces carbon dioxide during the manufacturing and recycling stages. Therefore, the total carbon emissions of the photo-hydrogen storage integrated energy system include the carbon emissions directly or indirectly generated by each equipment body. In order to achieve the green and low-carbon operation of the photo-hydrogen storage integrated energy system, research on the carbon emissions of the photo-hydrogen storage integrated energy system throughout its life cycle will promote more accurate carbon management and promote the photo-hydrogen storage integrated energy system to move in a greener and lower-carbon direction. Therefore, on the basis of considering economy and stability, the full life cycle evaluation method can be used to comprehensively analyze the carbon emissions of the photo-hydrogen storage integrated energy system, including equipment cycle carbon emissions and energy cycle carbon emissions.

[0100] Among them, the equipment cycle carbon emissions include the carbon emissions of the equipment in the light hydrogen storage integrated energy system in the three links of production, operation and disposal. In specific implementation, the measurement scope of equipment cycle carbon emissions includes the three links of equipment production, operation and retirement, and can mainly calculate carbon dioxide.

[0101] Among them, energy cycle carbon emissions include carbon emissions from the three links of mining, operation and waste treatment in the process of external energy consumption in the photohydrogen storage integrated energy system. In specific implementation, energy cycle carbon emissions include the three links of fuel mining, operation and waste treatment. These fuels can be carbon emissions caused by external energy consumed in the photohydrogen storage integrated energy system. For example, when the system needs to purchase electricity from an external power grid, the production of electricity may cause carbon emissions. If the system relies on natural gas, coal-fired power or other fossil energy for auxiliary energy supply, the carbon emissions in these processes also belong to energy cycle carbon emissions. By calculating energy cycle carbon emissions, while accounting for carbon dioxide, other greenhouse gas emissions can be considered at the same time and standardized as carbon dioxide emissions.

[0102] The carbon emissions of the entire life cycle of the solar-hydrogen storage integrated energy system can be determined through the equipment cycle carbon emissions and energy cycle carbon emissions.

[0103] The annual carbon emissions calculation model can calculate annual carbon emissions based on equipment power, equipment cycle carbon emissions and energy cycle carbon emissions, which enhances the comprehensiveness and accuracy of carbon emissions accounting and helps improve the accuracy of subsequent capacity planning.

[0104] In one embodiment, the equipment cycle process includes three stages: equipment production, operation and retirement. Therefore, the carbon emissions of the equipment in each stage are added together to obtain the equipment cycle carbon emissions.

[0105] The calculation method of equipment cycle carbon emissions is as follows:

[0106] ;

[0107] Where: Indicates the device Equipment cycle carbon emissions; Indicates the device Carbon emissions during production; Indicates the device Carbon emissions during operation; Indicates the device Carbon emissions during decommissioning.

[0108] In one embodiment, the energy involved in the energy cycle process mainly includes natural gas and electricity purchased from the energy market. Therefore, the energy cycle carbon emissions may include the sum of the natural gas energy cycle carbon emissions and the coal-fired power energy cycle carbon emissions. The natural gas energy cycle carbon emissions can be calculated based on the carbon emission coefficient of natural gas power generation. The carbon emission coefficient of natural gas power generation can be used to link the consumption of natural gas with carbon dioxide emissions and quantify the carbon emissions caused by the use of natural gas. The coal-fired power energy cycle carbon emissions can be calculated based on the carbon emission coefficient of coal-fired power generation. The carbon emission coefficient of coal-fired power generation can be used to link the consumption of coal with carbon dioxide emissions and quantify the carbon emissions caused by the use of coal.

[0109] Among them, the carbon emission coefficient of natural gas power generation is calculated as follows:

[0110] ;

[0111] ;

[0112] Where: is the carbon emission coefficient per kilowatt-hour of natural gas in the extraction process; For the Conversion factors of greenhouse gases to carbon dioxide; For the Carbon emission intensity of greenhouse gases; is the escape rate during natural gas extraction; is the carbon intensity of natural gas; is the carbon emission coefficient of natural gas per kilowatt-hour in the operation stage; For the The carbon emission coefficient of each kilowatt-hour of electricity used by the natural gas-using equipment during operation; is the carbon emission coefficient of electricity used in the processing stage; is the carbon emission coefficient of natural gas power generation.

[0113] Among them, the carbon emission coefficient of coal-fired power generation is calculated as follows:

[0114] ;

[0115] ;

[0116] Where: The carbon emission coefficient per kilowatt-hour of coal in the production and mining process; is the unit coal production loss; The conversion efficiency of coal; the carbon intensity of coal production; is the unit power loss rate caused by spontaneous combustion of raw coal; is the unit power loss rate caused by raw coal washing; is the carbon emission coefficient per kilowatt-hour of operation; is the unit coal consumption of the operation link; is the carbon emission intensity of the cth greenhouse gas per unit of standard coal equivalent of coal-fired power generation units; is the carbon emission coefficient of electricity used in the processing stage; is the carbon emission coefficient of coal-fired power generation.

[0117] It can be seen that carbon emissions accounting for the photovoltaic, hydrogen and storage integrated energy system is carried out from the two aspects of equipment cycle and energy cycle. The system carbon emissions accounting boundaries are clarified through the carbon emissions principle of the entire life cycle, which can improve the comprehensiveness and accuracy of carbon emissions accounting to achieve the green, low-carbon and environmental protection of the photovoltaic, hydrogen and storage integrated energy system. Moreover, through the full life cycle carbon emissions assessment and the efficient use of photovoltaic and hydrogen energy, the capacity planning of the photovoltaic, hydrogen and storage integrated energy system can be carried out, which can realize the optimization of system capacity configuration, improve the accuracy of system capacity planning, achieve stability and economy goals, and meet low-carbon and environmental protection requirements.

[0118] In another embodiment, the energy data also includes value description data of the photohydrogen storage integrated energy system; the first-stage planning optimization model includes an annual economic value calculation model, an annual carbon emissions calculation model and an annual energy shortage rate calculation model; the energy data is input into the first-stage planning optimization model to obtain the equipment capacity of the photohydrogen storage integrated energy system, including: inputting the value description data into the annual economic value calculation model to obtain the annual economic value; inputting the power input of the equipment, the equipment cycle carbon emissions and the energy cycle carbon emissions into the annual carbon emissions calculation model to obtain the annual carbon emissions; inputting the load demand into the annual energy shortage rate calculation model to obtain the annual energy shortage rate; under the condition of satisfying the constraints of the first-stage planning optimization model, determining the equipment capacity that minimizes the annual economic value, annual carbon emissions and annual energy shortage rate as the equipment capacity of the photohydrogen storage integrated energy system; the constraints of the first-stage planning optimization model include equipment installation constraints, equipment capacity constraints and load demand constraints.

[0119] The first phase planning optimization model focuses on the economic, green and stable characteristics of energy. Therefore, the first phase planning optimization model aims to calculate the annual economic value, annual carbon emissions and annual energy shortage rate, aiming to achieve a balance between the three.

[0120] In specific implementation, the annual economic value calculation model can be expressed as the objective function for calculating the annual economic value:

[0121] ;

[0122] Where: is the annual economic value; The cost of purchasing the equipment; For operation and maintenance costs; The cost of purchasing natural gas; The cost of water for electrolysis; The cost of purchasing electricity; is the cost of purchasing hydrogen. and The economic properties of are highly related to the equipment type and are calculated as follows:

[0123] ;

[0124] ;

[0125] Where: is the installed capacity of each device; and The unit purchase cost and operation and maintenance cost of each equipment respectively; is the device type; is the cost sharing coefficient. is the bank loan interest rate, For the repayment period.

[0126] It can be seen that in the first stage, which is the planning optimization stage, economic cost is the primary consideration for the photovoltaic hydrogen storage integrated energy system, because it can fully reflect the economic situation of the system. In order to reflect the economic efficiency of the photovoltaic hydrogen storage integrated energy system, the annual economic value is selected as the optimization target reflecting the system economy. The lower the annual economic value, the more the photovoltaic hydrogen storage integrated energy system can meet the economic requirements.

[0127] In specific implementation, the annual carbon emissions calculation model can be expressed as the objective function for calculating annual carbon emissions:

[0128] ;

[0129] Where: is the annual carbon emissions; For the The age of the equipment; is the type of equipment; is the carbon emission coefficient of energy cycle electricity of equipment i; For the Equipment in the scene The power at the next moment t; Indicates the number of typical scenarios; Representation scene probability; The above equipment Carbon emissions in operation . is the carbon emission of purchased electricity, that is, based on the carbon emission coefficient of coal-fired power generation mentioned above The calculated value; is the carbon emission of purchased natural gas, that is, the carbon emission coefficient of natural gas power generation mentioned above The calculated value.

[0130] in:

[0131] ;

[0132] ;

[0133] Where: For external grid in the scene Down The power delivered at any time; The carbon emission coefficient of purchased natural gas over its entire life cycle; Indicates in the scene Down The amount of natural gas purchased at any given moment.

[0134] It can be seen that the annual carbon emissions are used to reflect the impact of the system on the environment. The lower the annual carbon emissions, the closer the solar hydrogen storage integrated energy system is to the green requirements. Based on the research on carbon emissions throughout the life cycle, the above objective function for calculating annual carbon emissions was constructed.

[0135] In the specific implementation, the annual energy shortage rate calculation model can be expressed as the objective function for calculating the annual energy shortage rate:

[0136] ;

[0137] Where: It indicates the annual capacity shortage rate; , , Represent the energy deficit of heat, cold and hydrogen load respectively; , and They represent the total energy demand of heat, cold and hydrogen loads, that is, the load demand.

[0138] It can be seen that, taking into account user needs, load reduction can be allowed at a certain ratio. Considering the core position of electricity in the photovoltaic hydrogen storage integrated energy system, its energy real-time supply and demand balance requirements are more stringent than other energy subsystems in the photovoltaic hydrogen storage integrated energy system, so priority is given to meeting the balance of electricity supply and demand. Other energy subsystems have a certain buffering capacity, and energy gaps are allowed to exist to a certain extent. Therefore, the annual energy shortage rate is used to indicate the proportion of energy shortage in the photovoltaic hydrogen storage integrated energy system to the total energy demand. The lower the annual energy shortage rate, the closer the system is to the stability requirement.

[0139] In the specific implementation, since the first stage planning optimization model is affected by many factors during the planning optimization process, including installation conditions, site area, and factory property rights, the installation requirements of each device must meet the corresponding constraints.

[0140] The constraints of the first-stage planning optimization model can be expressed as:

[0141] ;

[0142] Where: and Equipment Minimum and maximum installation capacities.

[0143] In one of the embodiments, the equipment capacity is input into the second-stage operation optimization model to obtain the updated power of the equipment in the light-hydrogen storage integrated energy system, including: inputting the equipment capacity into the annual operation value calculation model to obtain the annual operation value; under the condition that the constraints of the second-stage operation optimization model are met, determining the power of the equipment that makes the annual operation value the lowest as the updated power of the equipment; the constraints of the second-stage operation optimization model include power balance constraints, energy network transmission power constraints, and equipment power constraints.

[0144] In the specific implementation, the second-stage operation optimization model can be expressed as the objective function for calculating the annual operation value:

[0145] ;

[0146] Where: is the annual operating value; , , , Respectively for scenes The natural gas purchase cost, electrolysis water cost, electricity purchase cost, and hydrogen purchase cost are as follows.

[0147] The constraints of the second-stage operation optimization model may include power balance constraints, energy network transmission power constraints, and equipment power constraints.

[0148] In a specific implementation, the power balance constraints may include electric power balance constraints, heat and cold power balance constraints, hydrogen balance constraints, and natural gas balance constraints.

[0149] Among them, the electric power balance constraint can be expressed as:

[0150] ;

[0151] Where: Indicates that the external power grid is in the scene The electric power delivered at time t; Indicates that the fuel cell is in the scene The power at the next moment t; Indicates in the scene The electrical load at time t; Indicates that the electrolyzer is in the scene The electrical power consumed at time t.

[0152] The power subsystem in the solar-hydrogen storage integrated energy system must maintain electric power balance under various typical scenarios, that is, the production of electricity must be equal to the consumption of electricity.

[0153] Among them, the heat and cold power balance constraints can be expressed as:

[0154] ;

[0155] ;

[0156] Where: Indicates that the gas boiler is in the scene Down The amount of heat supplied at any time; Indicates that the heat storage tank is in the scene Down The amount of heat supplied at any time; and Indicates in the scene Down Heating and cooling loads at all times.

[0157] The supply and demand balance requirements of the heat and cooling subsystems are more flexible than those of the power subsystem, allowing the heat and cooling provided to slightly exceed or fall short of the load demand.

[0158] Among them, the hydrogen balance constraint can be expressed as:

[0159] ;

[0160] Where: Indicates that the hydrogen storage tank is in the scene Down Hydrogen load at the time; Indicates that the hydrogen storage tank is The amount of hydrogen supplied to the hydrogen load at all times; Indicates in the scene Down The amount of hydrogen purchased at any given moment.

[0161] For the hydrogen storage subsystem in the solar-hydrogen storage integrated energy system, its supply and demand balance is similar to the balance law of the thermal subsystem. In addition to the hydrogen produced within the solar-hydrogen storage integrated energy system, part of the hydrogen may also come from the external hydrogen network.

[0162] Among them, the natural gas balance constraint can be expressed as:

[0163] ;

[0164] Where: Indicates in the scene The amount of natural gas purchased at the next time t; Indicates that the gas boiler is in the scene The amount of natural gas consumed at time t.

[0165] The natural gas consumption in the natural gas subsystem comes from the external natural gas network. In the system, the natural gas consumption equipment can be a gas boiler.

[0166] In specific implementation, the energy network transmission power constraint can be expressed as:

[0167] ;

[0168] Where: and They represent the lower and upper limits of the external power grid transmission power respectively; and They represent the lower limit and upper limit of hydrogen delivered by the external hydrogen network respectively; and They represent the lower and upper limits of natural gas delivered by the external natural gas network, respectively.

[0169] Considering the stability and security of energy supply, the energy exchange between the system and the external network needs to be strictly controlled to ensure that it is carried out within an appropriate range.

[0170] In specific implementation, the device power constraint can be expressed as:

[0171] ;

[0172] Where: and Indicates the lower and upper limits of the hydrogen storage capacity of the hydrogen storage tank. and Respectively represent the hydrogen storage tank in the scene The initial hydrogen storage capacity and the final hydrogen storage capacity; and They represent the lower and upper limits of the heat storage capacity of the heat storage tank, and Respectively represent the heat storage tank in the scene The initial heat storage and the final heat storage; Indicates the device Maximum output power; and The functions of a device are usually limited by its design parameters, including the maximum power constraint.

[0173] It can be seen that this application constructs a two-stage capacity planning model (first-stage planning optimization model and second-stage operation optimization model) from the three dimensions of economy, environmental protection and system stability, which improves the accuracy of capacity planning of the integrated energy system of light and hydrogen storage, and can better take into account the economy, environmental protection and system stability in the planning and operation process.

[0174] To facilitate understanding by those skilled in the art, FIG5 exemplarily provides a logic diagram of a two-stage capacity planning method.

[0175] As can be seen, Figure 5 shows a two-stage capacity planning method that takes into account planning optimization and operation optimization. First, the annual comprehensive cost (ACC), annual carbon emission (ACE) and annual energy deficiency rate (AED) are used as objective functions, and the equipment installation capacity is used as a constraint to construct the first-stage planning optimization model. Second, the annual operation value is used as the objective function, and the power balance, equipment power and energy network transmission power are used as constraints to construct the second-stage operation optimization model.

[0176] In one embodiment, the first-stage planning optimization model is solved using a second-generation non-dominated sorting genetic algorithm, and the second-stage operation optimization model is solved using a mixed integer linear programming. The first-stage planning optimization model passes the solved equipment capacity planning configuration scheme to the second-stage operation optimization model. The second-stage operation optimization model further simulates the actual operation with the equipment capacity as the output boundary, obtains the daily operating conditions of each device, and feeds the operation results back to the first-stage planning optimization model to verify the accuracy of the capacity planning configuration scheme and prompt the first-stage planning optimization model to continue to find the optimal solution. Through continuous iteration, the Pareto solution set of the final generation of capacity planning configuration scheme is obtained.

[0177] In summary, this application constructs a two-stage capacity planning model (first-stage planning optimization model and second-stage operation optimization model) based on the three core dimensions of economy, environmental protection, and system stability, which can optimize the planning and operation of the photovoltaic hydrogen storage integrated energy system. At the same time, the full life cycle carbon emission theory is used to clarify the accounting boundaries and methods of system carbon emissions, ensure the environmental orientation and scientific accuracy of system configuration decisions, effectively balance economic benefits, environmental protection indicators and operational stability, and provide strong decision-making support for the sustainable development of the photovoltaic hydrogen storage integrated energy system.

[0178] To facilitate understanding by those skilled in the art, FIG6 exemplarily provides a logic diagram of another two-stage capacity planning method, in which a two-stage model (a first-stage planning optimization model and a second-stage operation optimization model) is solved by a multi-objective optimization algorithm (NSGA-II) and a mixed integer linear programming method.

[0179] The specific implementation includes the following steps:

[0180] Step 1: Input the original system data, i.e. the energy data of the solar-hydrogen storage integrated energy system.

[0181] Step 2: Generate the initial population for device selection. Under the constraints of the upper and lower limits of device capacity, randomly generate an initial population of size N. At the same time, pass the decision variables of the first stage to the second stage.

[0182] Step 3: Calculate fitness. Considering that individuals (equipment capacity planning solutions) are randomly generated, a penalty number is added to make the fitness of the corresponding individuals tend to infinity, so that they are eliminated in the evolution.

[0183] Step 4: Select a new parent generation through fast non-dominated sorting and roulette. At the same time, the second stage takes the minimum annual operating value as the objective function, calls mathematical optimization technology (CPLEX) to solve the mixed integer linear programming, calculates the annual operating value of the system, and feeds it back to the first stage to generate a new parent generation.

[0184] Step 5: Crossover and mutation to select new offspring.

[0185] Step 6: The offspring and the parent generation are merged to generate a new population and the new fitness is calculated.

[0186] Step 7: Determine whether the number of iterations has reached the maximum. If not, repeat steps 2 to 6.

[0187] Step 8: Output data such as annual economic value, annual carbon emissions, annual energy shortage rate, capacity planning scheme, and annual operating value.

[0188] It can be seen that through the above-mentioned capacity planning method of the integrated solar-hydrogen storage energy system, the capacity can be planned in a more scientific and standardized manner. From multiple dimensions, a two-stage capacity planning model (the first-stage planning optimization model and the second-stage operation optimization model) is constructed, which can better take into account the economy, environmental protection and system stability in the planning and operation process.

[0189] In another embodiment, energy data of the photovoltaic-hydrogen storage integrated energy system is obtained, including: inputting photovoltaic component description data of the photovoltaic-hydrogen storage integrated energy system into a photovoltaic power generation model to obtain the power of the photovoltaic components in the photovoltaic-hydrogen storage integrated energy system; and determining the energy data of the photovoltaic-hydrogen storage integrated energy system based on the power of the photovoltaic components.

[0190] The photovoltaic module description data may include the number of photovoltaic modules, the rated power of the photovoltaic modules, the solar radiation intensity and ambient temperature under standard environmental conditions, the actual solar radiation intensity and actual operating temperature of the photovoltaic modules, etc.

[0191] In specific implementation, the photovoltaic power generation model can be expressed as:

[0192] ;

[0193] ;

[0194] Where: is the power of the photovoltaic module; is the number of PV panels; is the rated power of the PV module; and They represent the solar radiation intensity and ambient temperature under standard ambient conditions. , the ambient temperature is 25℃; is the power temperature coefficient, which reflects the influence of temperature on photovoltaic modules; and are the actual solar radiation intensity and actual operating temperature of the photovoltaic module respectively; is the actual ambient temperature.

[0195] According to the power of the photovoltaic modules, the energy data of the photovoltaic hydrogen storage integrated energy system can be determined. The energy data of the photovoltaic hydrogen storage integrated energy system may include the energy data of key components, such as the energy data of the photovoltaic modules and the hydrogen storage equipment.

[0196] In another embodiment, before inputting the equipment capacity into the second-stage operation optimization model to obtain the power of the equipment in the photo-hydrogen storage integrated energy system after being updated, it also includes: inputting the hydrogen storage equipment description data of the photo-hydrogen storage integrated energy system into the hydrogen storage equipment model to obtain the hydrogen description data of the hydrogen storage equipment in the photo-hydrogen storage integrated energy system; the hydrogen description data includes the hydrogen storage capacity of the hydrogen storage equipment; inputting the equipment capacity into the second-stage operation optimization model to obtain the power of the equipment in the photo-hydrogen storage integrated energy system after being updated, including: inputting the equipment capacity and hydrogen description data into the second-stage operation optimization model to obtain the power of the equipment in the photo-hydrogen storage integrated energy system after being updated.

[0197] Hydrogen storage equipment includes electrolyzers, fuel cells and hydrogen storage tanks. The hydrogen description data may include the power of the electrolyzer in the hydrogen storage equipment, the conversion efficiency of the electrolyzer, the power of the fuel cell in the hydrogen storage equipment, the conversion efficiency of the fuel cell, etc.

[0198] The hydrogen storage equipment model can be expressed as:

[0199] ;

[0200] ;

[0201] ;

[0202] Where: Indicates that the electrolytic cell Hydrogen production at the time; Indicates that the electrolytic cell The electrical power consumed at any given moment; is the conversion efficiency of the electrolyzer; The fuel cell Hydrogen consumption at each time; The fuel cell Output power at the moment; is the conversion efficiency of the fuel cell; , and Respectively represent the hydrogen storage tank The amount of hydrogen stored, injected and consumed at each moment.

[0203] In order to further reduce the abandonment of renewable energy and improve energy efficiency, when the photovoltaic output exceeds the current electricity load demand, the electrolyzer uses the excess electricity to produce hydrogen. On the contrary, when the photovoltaic output is not enough to meet the electricity load demand, the fuel cell is started or the electricity is purchased to fill the power gap. Therefore, the amount of hydrogen injected and hydrogen consumption They can be expressed as:

[0204]

[0205]

[0206] ;

[0207] Where: represents the electrical load demand at time t; represents the electric power delivered by the external power grid at time t; It indicates the amount of hydrogen supplied by the hydrogen storage tank to the hydrogen load at time t; and 0,1 variables.

[0208] In the specific implementation, the hydrogen description data includes the hydrogen storage capacity of the hydrogen storage tank in the hydrogen storage equipment, the hydrogen production of the electrolyzer, the hydrogen consumption of the fuel cell, etc.

[0209] The equipment capacity and hydrogen description data are input into the second-stage operation optimization model to obtain the updated power of the equipment in the light-hydrogen storage integrated energy system. For details, please refer to the above embodiment. The hydrogen description data can be used in the constraint conditions of the second-stage operation optimization model. For example, the hydrogen balance constraint condition in the power balance constraint condition requires the use of hydrogen description data (the amount of hydrogen supplied to the hydrogen load by the hydrogen storage tank). ) to determine whether the hydrogen balance constraint is met; for example, the equipment power constraint requires hydrogen description data (the hydrogen storage capacity of the hydrogen storage tank ) to determine whether the device power constraints are met.

[0210] In another embodiment, as shown in FIG. 7 , a capacity planning method for a photovoltaic hydrogen storage integrated energy system is provided, and the method is described by taking the application of the method to the terminal in FIG. 1 as an example, including the following steps:

[0211] S702, obtaining energy data of the solar hydrogen storage integrated energy system.

[0212] Energy data includes the power of equipment in the photovoltaic, hydrogen and storage integrated energy system and the load demand for the photovoltaic, hydrogen and storage integrated energy system.

[0213] In one of the embodiments, energy data of a photovoltaic hydrogen storage integrated energy system is obtained, including: inputting photovoltaic component description data of the photovoltaic hydrogen storage integrated energy system into a photovoltaic power generation model to obtain the power of the photovoltaic components in the photovoltaic hydrogen storage integrated energy system; and determining the energy data of the photovoltaic hydrogen storage integrated energy system based on the power of the photovoltaic components.

[0214] S704, obtain the equipment cycle carbon emissions and energy cycle carbon emissions of the solar hydrogen storage integrated energy system.

[0215] The equipment cycle carbon emissions include the carbon emissions from the equipment in the production, operation and disposal stages of the photovoltaic hydrogen storage integrated energy system; the energy cycle carbon emissions include the carbon emissions from the mining, operation and disposal stages of the photovoltaic hydrogen storage integrated energy system in the process of consuming external energy.

[0216] S706, input the value description data into the annual economic value calculation model to obtain the annual economic value; input the equipment's power input, equipment cycle carbon emissions and energy cycle carbon emissions into the annual carbon emissions calculation model to obtain the annual carbon emissions; input the load demand into the annual energy shortage rate calculation model to obtain the annual energy shortage rate; under the condition of satisfying the constraints of the first-stage planning optimization model, determine the equipment capacity that minimizes the annual economic value, annual carbon emissions and annual energy shortage rate as the equipment capacity of the solar hydrogen storage integrated energy system.

[0217] Among them, the constraints of the first-stage planning optimization model include equipment installation constraints, equipment capacity constraints, and load demand constraints.

[0218] S708, input the equipment capacity into the annual operation value calculation model to obtain the annual operation value; under the condition that the constraints of the second-stage operation optimization model are met, determine the power of the equipment that makes the annual operation value the lowest, as the updated power of the equipment, and return to step S706.

[0219] The constraints of the second-stage operation optimization model include power balance constraints, energy network transmission power constraints, and equipment power constraints.

[0220] It should be noted that the specific limitations of the above steps can refer to the specific limitations of a capacity planning method for a solar-hydrogen storage integrated energy system mentioned above.

[0221] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0222] Based on the same inventive concept, the embodiment of the present application also provides a capacity planning device for a photovoltaic hydrogen storage integrated energy system for implementing the capacity planning method for the photovoltaic hydrogen storage integrated energy system involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the capacity planning device for one or more photovoltaic hydrogen storage integrated energy systems provided below can refer to the limitations of the capacity planning method for photovoltaic hydrogen storage integrated energy systems above, and will not be repeated here.

[0223] In an exemplary embodiment, as shown in FIG8 , a capacity planning device for a photovoltaic hydrogen storage integrated energy system is provided, comprising:

[0224] The data acquisition module 810 is used to acquire energy data of the photovoltaic, hydrogen and storage integrated energy system; the energy data includes the power of the equipment in the photovoltaic, hydrogen and storage integrated energy system and the load demand for the photovoltaic, hydrogen and storage integrated energy system.

[0225] The capacity planning module 820 is used to input the energy data into the first-stage planning optimization model to obtain the equipment capacity of the solar-hydrogen storage integrated energy system.

[0226] The power update module 830 is used to input the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and return to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system.

[0227] In one embodiment, the energy data also includes value description data of the solar-hydrogen storage integrated energy system; the first-stage planning optimization model includes an annual economic value calculation model, an annual carbon emissions calculation model and an annual energy shortage rate calculation model; the capacity planning module 820 is specifically used to input the value description data into the annual economic value calculation model to obtain the annual economic value; input the power of the equipment into the annual carbon emissions calculation model to obtain the annual carbon emissions; input the load demand into the annual energy shortage rate calculation model to obtain the annual energy shortage rate; under the condition of satisfying the constraints of the first-stage planning optimization model, determine the equipment capacity that makes the annual economic value, the annual carbon emissions and the annual energy shortage rate the lowest, as the equipment capacity of the solar-hydrogen storage integrated energy system; the constraints of the first-stage planning optimization model include the installation constraints of the equipment, the capacity constraints of the equipment and the load demand constraints.

[0228] In one of the embodiments, the capacity planning device of the photovoltaic hydrogen storage integrated energy system also includes a carbon accounting module; the carbon accounting module is specifically used to obtain the equipment cycle carbon emissions and energy cycle carbon emissions of the photovoltaic hydrogen storage integrated energy system; the equipment cycle carbon emissions include the carbon emissions of the equipment in the photovoltaic hydrogen storage integrated energy system in the three links of production, operation and disposal; the energy cycle carbon emissions include the carbon emissions of the three links of mining, operation and disposal in the process of consuming external energy by the photovoltaic hydrogen storage integrated energy system; the capacity planning module 820 is specifically used to input the power input of the equipment, the equipment cycle carbon emissions and the energy cycle carbon emissions into the annual carbon emissions calculation model to obtain the annual carbon emissions.

[0229] In one embodiment, the power update module 830 is specifically used to input the equipment capacity into the annual operating value calculation model to obtain the annual operating value; under the condition that the constraints of the second-stage operation optimization model are met, determine the power of the equipment that makes the annual operating value the lowest, as the power of the equipment after update; the constraints of the second-stage operation optimization model include power balance constraints, energy network transmission power constraints, and equipment power constraints.

[0230] In one of the embodiments, the data acquisition module 810 is specifically used to input the photovoltaic component description data of the photovoltaic hydrogen storage integrated energy system into a photovoltaic power generation model to obtain the power of the photovoltaic components in the photovoltaic hydrogen storage integrated energy system; and determine the energy data of the photovoltaic hydrogen storage integrated energy system based on the power of the photovoltaic components.

[0231] In one of the embodiments, the data acquisition module 810 is specifically used to input the hydrogen storage device description data of the solar-hydrogen storage integrated energy system into the hydrogen storage device model to obtain the hydrogen description data of the hydrogen storage device in the solar-hydrogen storage integrated energy system; the hydrogen description data includes the hydrogen storage capacity of the hydrogen storage device; the power update module 830 is specifically used to input the device capacity and the hydrogen description data into the second-stage operation optimization model to obtain the updated power of the device in the solar-hydrogen storage integrated energy system.

[0232] Each module in the capacity planning device of the above-mentioned solar hydrogen storage integrated energy system can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0233] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG9. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a capacity planning method for a light hydrogen storage integrated energy system is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0234] Those skilled in the art will understand that the structure shown in FIG. 9 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0235] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0236] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0237] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0238] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0239] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0240] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0241] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A capacity planning method for a photovoltaic hydrogen storage integrated energy system, characterized in that: The method comprises: Obtaining energy data of the photovoltaic hydrogen storage integrated energy system; the energy data includes the power of equipment in the photovoltaic hydrogen storage integrated energy system and the load demand for the photovoltaic hydrogen storage integrated energy system; Inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the solar-hydrogen storage integrated energy system; The equipment capacity is input into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and the process returns to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system.

2. The method according to claim 1, characterized in that The energy data also includes value description data of the photovoltaic hydrogen storage integrated energy system; the first-stage planning optimization model includes an annual economic value calculation model, an annual carbon emission calculation model, and an annual energy shortage rate calculation model; the energy data is input into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system, including: Inputting the value description data into the annual economic value calculation model to obtain the annual economic value; Inputting the power of the device into the annual carbon emissions calculation model to obtain annual carbon emissions; Inputting the load demand into the annual energy shortage rate calculation model to obtain the annual energy shortage rate; Under the condition that the constraints of the first-stage planning optimization model are met, the equipment capacity that minimizes the annual economic value, the annual carbon emissions and the annual energy shortage rate is determined as the equipment capacity of the solar-hydrogen storage integrated energy system; the constraints of the first-stage planning optimization model include the installation constraints of the equipment, the capacity constraints of the equipment and the load demand constraints.

3. The method according to claim 2, characterized in that Before inputting the power of the device into the annual carbon emissions calculation model to obtain the annual carbon emissions, the method further includes: Obtain the equipment cycle carbon emissions and energy cycle carbon emissions of the photohydrogen storage integrated energy system; the equipment cycle carbon emissions include the carbon emissions of the equipment in the photohydrogen storage integrated energy system during the three stages of production, operation and disposal; the energy cycle carbon emissions include the carbon emissions of the three stages of mining, operation and disposal during the process of the photohydrogen storage integrated energy system consuming external energy; The step of inputting the power of the device into the annual carbon emission calculation model to obtain the annual carbon emission comprises: The power input of the equipment, the equipment cycle carbon emissions and the energy cycle carbon emissions are input into the annual carbon emissions calculation model to obtain the annual carbon emissions.

4. The method according to claim 1, characterized in that: The step of inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system includes: Inputting the equipment capacity into the annual operation value calculation model to obtain the annual operation value; Under the condition that the constraints of the second-stage operation optimization model are met, the power of the equipment that minimizes the annual operation value is determined as the power of the equipment after updating; the constraints of the second-stage operation optimization model include power balance constraints, energy network transmission power constraints, and equipment power constraints.

5. The method according to claim 1, characterized in that The energy data of the photovoltaic hydrogen storage integrated energy system is obtained, including: Inputting the photovoltaic component description data of the photovoltaic hydrogen storage integrated energy system into the photovoltaic power generation model to obtain the power of the photovoltaic components in the photovoltaic hydrogen storage integrated energy system; The energy data of the photovoltaic hydrogen storage integrated energy system is determined according to the power of the photovoltaic module.

6. The method according to claim 1, characterized in that Before inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, the method further includes: Inputting the hydrogen storage device description data of the light-hydrogen storage integrated energy system into the hydrogen storage device model to obtain the hydrogen description data of the hydrogen storage device in the light-hydrogen storage integrated energy system; the hydrogen description data includes the hydrogen storage capacity of the hydrogen storage device; The step of inputting the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system includes: The equipment capacity and the hydrogen description data are input into the second-stage operation optimization model to obtain the updated power of the equipment in the solar-hydrogen storage integrated energy system.

7. A capacity planning device for a solar-hydrogen storage integrated energy system, characterized in that: The device comprises: A data acquisition module, used to acquire energy data of the photovoltaic hydrogen storage integrated energy system; the energy data includes the power of equipment in the photovoltaic hydrogen storage integrated energy system and the load demand for the photovoltaic hydrogen storage integrated energy system; A capacity planning module, used to input the energy data into the first-stage planning optimization model to obtain the equipment capacity of the solar-hydrogen storage integrated energy system; The power update module is used to input the equipment capacity into the second-stage operation optimization model to obtain the updated power of the equipment in the photovoltaic hydrogen storage integrated energy system, and return to the step of inputting the energy data into the first-stage planning optimization model to obtain the equipment capacity of the photovoltaic hydrogen storage integrated energy system.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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