Photovoltaic power station emission reduction and carbon sequestration evaluation method and system based on STILT mode

Abstract

The invention discloses a photovoltaic power station emission reduction and carbon sequestration evaluation method and system based on an STILT mode, and relates to the technical field of photovoltaic power station emission reduction and carbon sequestration evaluation, and the method comprises the steps: carrying out the parameterization of the data of a photovoltaic panel, considering the albedo and surface roughness of the panel, and obtaining the parameters of a photovoltaic power station; according to the parameters of the power station, fitting a photovoltaic output model by using a least square method, and representing a photoelectric conversion process; the carbon emission reduction amount is calculated according to the power generation amount of the power station in combination with marginal emission factors, and the vegetation carbon sink below the photovoltaic panel is evaluated by using a WRF-STILT model. According to the method, the main physical process in the photovoltaic power station can be accurately represented, a simple photovoltaic land surface process mode is established, and reference is provided for climate mode analysis; and meanwhile, the carbon emission reduction and carbon sink effects of the photovoltaic power station are evaluated, so that the evaluation is more accurate. According to the method, more accurate concentration contribution source area distribution is obtained through multiple nested simulation, and important support is provided for photovoltaic power station carbon income and expenditure evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of emission reduction and carbon fixation assessment of photovoltaic power stations, and in particular to an emission reduction and carbon fixation assessment method and system for photovoltaic power stations based on a STILT model. Background Art

[0002] Under the background of carbon neutrality, many countries and regions around the world have successively issued favorable policies for photovoltaics. With the development and progress of clean energy technologies such as photovoltaics and the continuous expansion of installed capacity, by the end of 2022, my country's cumulative photovoltaic power generation installed capacity will reach 392.0GW, becoming the world's largest installed capacity area. Compared with traditional fossil fuels, solar photovoltaics reduce the biogeochemical impact driven by greenhouse gas emissions.

[0003] Photovoltaic power generation does not emit pollutants and greenhouse gases during the energy production process, and avoids the consumption of water resources and damage to the land during the development and utilization of fossil energy. It can also significantly reduce coal consumption and correspondingly reduce the damage to the ecological environment caused by coal mining. At the same time, in addition to reducing carbon emissions during the operation phase of the photovoltaic power generation system, the terrestrial ecosystem under the photovoltaic array also has a certain carbon fixation function.

[0004] As a mutual feedback mechanism between the land and climate systems, land surface processes are not only an important part of the weather, climate and environmental systems, but also one of the basic physical and biochemical processes that affect regional weather, atmospheric circulation and climate change. The exchange of matter, energy and momentum between land and air is not only related to solar radiation forcing and atmospheric circulation, but also to the properties of the land surface.

[0005] Among various numerical weather models, the WRF-STILT atmospheric transport model is a transport model based on the Lagrangian principle, which has several advantages such as stable numerical simulation, conservation of matter and high computational efficiency. In the case of few CO2 observation sites, the Lagrangian model has the advantages of strong targeting for evaluating the regional scale CO2 flux centered on the observation site. Therefore, the flux inversion algorithm based on the WRF-STILT atmospheric transport model and CO2 concentration observations has more advantages in estimating regional CO2 fluxes. Summary of the invention

[0006] In view of the problems existing in the accurate evaluation of the emission reduction and carbon fixation benefits of photovoltaic power generation mentioned above, the present invention is proposed.

[0007] Therefore, the problem to be solved by the present invention is that the existing technology often focuses more on the assessment of emission reduction of photovoltaic power generation, and its ecosystem carbon sink effect is insufficiently understood, and the accuracy of the assessment of ecological and environmental effects at the regional scale is insufficient.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] In the first aspect, an embodiment of the present invention provides a method for evaluating emission reduction and carbon fixation in photovoltaic power stations based on the STILT model, which includes parameterizing various data of photovoltaic panels to obtain parameters of the photovoltaic power station; fitting a photovoltaic output model based on the parameters of the photovoltaic power station; obtaining carbon emission reduction based on the power generation of the photovoltaic power station; and evaluating and analyzing the carbon sink of vegetation below the photovoltaic panel based on the WRF-STILT model to obtain an evaluation result.

[0010] As a preferred solution of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model described in the present invention, the parameterization of various data of the photovoltaic panel includes: obtaining the albedo and surface roughness of the photovoltaic panel; the calculation formula of the photovoltaic panel albedo is:

[0011]

[0012]

[0013]

[0014] The calculation formula of the surface roughness is:

[0015]

[0016]

[0017] The calculation formula of wind speed and temperature profile near the surface is:

[0018]

[0019] in, represents the albedo, is the observed time series of solar shortwave radiation, is the observed time series of albedo, E pv is the net shortwave radiation absorbed by the photovoltaic panel, is the radiation energy received by the photovoltaic panel, is the radiant energy reflected by the photovoltaic panel, Z 0h is the surface roughness, z represents the height, d represents the zero plane displacement height, and T represents the temperature at the observation point.

[0020] As a preferred solution of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model described in the present invention, wherein: the photovoltaic output model obtained by fitting includes fitting the photovoltaic output model using the least squares method according to the parameters of the photovoltaic power station, and the calculation formula of the photovoltaic output model is:

[0021] E=E pv ·(e -4.014-2.94V )

[0022] Among them, E is the actual processing data of the photovoltaic power station, E pv is the observed net shortwave radiation absorbed by the PV panels, and V is the wind speed.

[0023] As a preferred solution of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model described in the present invention, the carbon emission reduction benefit of the photovoltaic power station is represented by the potential carbon emission reduction substitution amount, which is calculated in combination with the marginal emission reduction factor. The calculation formula of the carbon emission reduction amount is:

[0024] ER y =BE y =EG pj,y ×EF grid,CM,y

[0025] Among them, ER y is the emission reduction of the operating photovoltaic power generation system in year y, BE y is the baseline emission in year y, EG pj,y is the amount of electricity generated by the photovoltaic power generation system in operation in year y, EF grid,CM,y is the marginal CO of the regional power grid combination in year y 2 Emission factors.

[0026] As a preferred solution of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model described in the present invention, the combined marginal CO 2 The calculation formula for the emission factor is:

[0027] EF grid,CM,y =EF grid,OM,y ×W OM +EF grid,BM,y ×W BM

[0028] Among them, EF grid,OM,y is the marginal emission factor of electricity in year y, EF grid,BM,y is the marginal emission factor of capacity in year y, W OM is the marginal emission factor of electricity, W BM is the capacity marginal emission factor.

[0029] As a preferred solution of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model described in the present invention, wherein: the WRF-STILT model is used to assess and analyze the vegetation carbon sink below the photovoltaic panel, and the assessment result is obtained based on the WRF-STILT atmospheric transmission model and high spatial and temporal resolution CO 2 Flux data, simulating atmospheric CO2 over two typical underlying surfaces 2 concentration, CO based on eddy covariance observations and Bayesian inversion algorithm2 The flux was evaluated while exploring the simulated regional atmospheric CO 2 Concentration composition, meteorological factors on atmospheric CO 2 The influence of concentration, and quantitative CO 2 The footprint of the source region and the isotopic data of CO 2 The applicability of flux inversion is analyzed.

[0030] As a preferred solution of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model described in the present invention, the WRF-STILT model is a transmission model of the Lagrangian random walk theory, which associates the source flux upstream of the observation point with the concentration change of the observation point through the footprint weight; the calculation formula of the WRF-STILT model is:

[0031]

[0032] Among them, m air is the molar weight of air, h is the height of the underlying surface influence layer, ρ is the average density of all particles, N tot is the total number of particles released, Δt p,i,j.k Each particle corresponds to a certain area (x i ,y j ) The time t that the underlying surface influence layer stays m .

[0033] Simulated CO 2 The concentration consists of two parts, including the initial field concentration just entering the simulation area and the local source and sink contribution of the concentration after entering the simulation area. The calculation formula of the local source and sink contribution is:

[0034]

[0035] Among them, ΔCO 2 is the local contribution to the simulated hourly concentration, i is the corresponding hour from 1 to 168 hours, footi is the footprint weight corresponding to the i-th hour in the simulation process, fluxCO 2 is the corresponding source-sink flux.

[0036] In the second aspect, an embodiment of the present invention provides a photovoltaic power station emission reduction and carbon fixation assessment system based on the STILT model, which includes a data processing module, a model fitting module, a calculation module, and an analysis module; the data processing module is used to collect various data of photovoltaic panels, including albedo and surface roughness, and the albedo and surface roughness are parameterized using corresponding formulas; the model fitting module is used to use the acquired data to fit the photovoltaic output model using the least squares method, and the model takes into account the actual processing data of the photovoltaic power station, the observed net shortwave radiation absorbed by the photovoltaic panels, and the wind speed factors; the calculation module includes a carbon emission reduction benefit calculation unit and a marginal emission factor calculation unit element; the carbon emission reduction benefit calculation unit is used to calculate the carbon emission reduction benefit of the photovoltaic power station, convert the photovoltaic carbon emission reduction into potential carbon emission reduction substitution, and calculate it in combination with the marginal emission reduction factor; the marginal emission factor calculation unit is used to calculate the marginal emission factor of electricity and the marginal emission factor of capacity using the combined marginal emission factor calculation method; the analysis module is used to use the WRF-STILT atmospheric transmission model and high-resolution flux data to analyze and process the vegetation carbon sink below the photovoltaic panel, calculate the concentration using the transmission model of the Lagrangian random walk theory, explore the simulated regional atmospheric concentration composition, the influence of meteorological elements on atmospheric concentration, and the quantitative concentration footprint source area.

[0037] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model as described in the first aspect of the present invention is implemented.

[0038] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model as described in the first aspect of the present invention is implemented.

[0039] The beneficial effects of the present invention are as follows: Based on the main physical processes and action mechanisms in photovoltaic power stations, the present invention divides photovoltaic power stations into two layers: photovoltaic canopy and surface, determines the parameters affecting radiation balance in photovoltaic power stations, and is used to represent the shortwave radiation dynamics effect between photovoltaic panels and the surface; and uses the photovoltaic output model to characterize the photoelectric conversion process. This method can accurately represent the main physical processes in photovoltaic power stations, establish a simple photovoltaic land surface process model, and provide a reference for the analysis of the lower boundary conditions of photovoltaic power stations under climate models. The present invention is based on the WRF-STILT model. Under the condition of known observation and simulation sites, multiple nested simulations of meteorological driving fields are performed on areas close to the sites to make the simulated concentration contribution source area more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0041] Figure 1 Schematic diagram of the main physical processes of the photovoltaic power station in Example 1.

[0042] Figure 2 Schematic diagram of the process of the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model in Example 1. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0045] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0046] Example 1

[0047] Reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and this embodiment provides a photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model. The photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model includes: parameterizing various data of the photovoltaic panel to obtain parameters of the photovoltaic power station.

[0048] Furthermore, parameterizing various data of the photovoltaic panel includes: obtaining the albedo and surface roughness of the photovoltaic panel.

[0049] Specifically, shortwave radiation is the main driving force for energy exchange and material transport between photovoltaic panels and the atmosphere, which mainly depends on the albedo of photovoltaic panels. Albedo Represents the net shortwave radiation caused by the photovoltaic panel. The net radiation is the radiation energy received by the photovoltaic panel. and reflected radiant energy The difference in the photovoltaic panel's lower albedo This usually results in an increase in the net absorbed shortwave radiation, while the photovoltaic panel converts the absorbed shortwave radiation into electrical energy E pv , the PV panel albedo uses the solar shortwave radiation above the PV panel and reflected radiant energy to calculate.

[0050] The calculation formula for the albedo of photovoltaic panels is:

[0051]

[0052]

[0053]

[0054] The calculation formula for surface roughness is:

[0055]

[0056] When the atmosphere is in a near-neutral state and ζ≤0.05, the relationship between the wind speed and temperature profile near the surface is expressed by the following formula:

[0057]

[0058] Furthermore, a simplified surface roughness formula is obtained, and the calculation formula is:

[0059]

[0060] in, represents the albedo, is the observed time series of solar shortwave radiation, is the observed time series of albedo, E pv is the net shortwave radiation absorbed by the photovoltaic panel, is the radiation energy received by the photovoltaic panel, is the radiant energy reflected by the photovoltaic panel, Z 0h is the surface roughness, z represents the height, d represents the zero plane displacement height, and T represents the temperature at the observation point.

[0061] According to the parameters of the photovoltaic power station, the photovoltaic output model is fitted.

[0062] Furthermore, the net short-wave solar radiation absorbed by the photovoltaic panels is converted into electrical energy through solar cell modules. Therefore, the effective short-wave radiation actually absorbed by the photovoltaic panels minus the net short-wave radiation required for the photoelectric conversion part is the actual output of the photovoltaic power station, which represents the short-wave radiation required for the photoelectric conversion part in the photovoltaic power station. The photovoltaic output model is introduced into the model.

[0063] Furthermore, fitting the photovoltaic output model includes fitting the photovoltaic output model using the least square method according to the parameters of the photovoltaic power station. The calculation formula of the photovoltaic output model is:

[0064] E=E pv ·(e -4.014-2.94V )

[0065] Among them, E is the actual processing data of the photovoltaic power station, E pv is the observed net shortwave radiation absorbed by the PV panels, and V is the wind speed.

[0066] The carbon emission reduction is obtained by converting the power generation of the photovoltaic power station.

[0067] Furthermore, the carbon emission reduction benefit of the photovoltaic power station is expressed by the potential carbon emission reduction substitution amount, which is calculated in combination with the marginal emission reduction factor. The calculation formula for carbon emission reduction is:

[0068] ER y =BE y =EG pj,y ×EF grid,CM,y

[0069] Among them, ER y is the emission reduction of the operating photovoltaic power generation system in year y, BE y is the baseline emission in year y, EG pj,y is the amount of electricity generated by the photovoltaic power generation system in operation in year y, EF grid,CM,y is the marginal CO of the regional power grid combination in year y 2 Emission factors.

[0070] Furthermore, the combined marginal CO 2 The calculation formula for the emission factor is:

[0071] EF grid,CM,y =EF grid,OM, y×W OM +EF grid,BM,y ×W BM

[0072] Among them, EF grid,OM,y is the marginal emission factor of electricity in year y, EF grid,BM,y is the marginal emission factor of capacity in year y, W OM is the marginal emission factor of electricity, WBM is the capacity marginal emission factor.

[0073] Based on the WRF-STILT model, the carbon sink of vegetation below the photovoltaic panels was evaluated and analyzed, and the evaluation results were obtained.

[0074] Furthermore, the carbon sink of vegetation below the photovoltaic panels was evaluated and analyzed based on the WRF-STILT model. The evaluation results are based on the WRF-STILT atmospheric transport model and high spatial and temporal resolution CO 2 Flux data, simulating atmospheric CO2 over two typical underlying surfaces 2 concentration, CO based on eddy covariance observations and Bayesian inversion algorithm 2 The flux was evaluated while exploring the simulated regional atmospheric CO 2 Concentration composition, meteorological factors on atmospheric CO 2 The influence of concentration, and quantitative CO 2 The footprint of the source region and the isotopic data of CO 2 The applicability of flux inversion is analyzed.

[0075] Furthermore, the WRF-STILT model is a transport model of Lagrangian random walk theory, which associates the source flux upstream of the observation point with the concentration change at the observation point through the footprint weight; the calculation formula of the WRF-STILT model is:

[0076]

[0077] Among them, m air is the molar weight of air, h is the height of the underlying surface influence layer, ρ is the average density of all particles, N tot is the total number of particles released, Δt p,i,j.k Each particle corresponds to a certain area (x i ,y j ) The time t that the underlying surface influence layer stays m ;

[0078] Simulated CO 2 The concentration consists of two parts, including the initial field concentration just entering the simulation area and the local source and sink contribution of the concentration after entering the simulation area. The calculation formula for the local source and sink contribution is:

[0079]

[0080] Among them, ΔCO 2 is the local contribution to the simulated hourly concentration, i is the corresponding hour from 1 to 168 hours, footi is the footprint weight corresponding to the i-th hour in the simulation process, fluxCO 2is the corresponding source-sink flux.

[0081] Furthermore, the present embodiment also provides a multi-source power grid information fusion system based on the Internet of Things, including a data processing module, a model fitting module, a calculation module, and an analysis module.

[0082] Specifically, the data processing module is used to collect various data of the photovoltaic panel, including albedo and surface roughness, and the corresponding formulas are used for parameterization of albedo and surface roughness. The model fitting module is used to use the acquired data to fit the photovoltaic output model using the least squares method. The model is based on the actual processing data of the photovoltaic power station, the observed net shortwave radiation absorbed by the photovoltaic panel and the wind speed. The calculation module includes a carbon emission reduction benefit calculation unit and a marginal emission factor calculation unit. The carbon emission reduction benefit calculation unit is used to calculate the carbon emission reduction benefit of the photovoltaic power station, convert the photovoltaic carbon emission reduction into potential carbon emission reduction substitution, and calculate it in combination with the marginal emission reduction factor. The marginal emission factor calculation unit is used to calculate the marginal emission factor of electricity and the marginal emission factor of capacity using the combined marginal emission factor calculation method. The analysis module is used to analyze and process the vegetation carbon sink below the photovoltaic panel using the WRF-STILT atmospheric transmission model and high-resolution flux data, calculate the concentration using the transmission model of the Lagrangian random walk theory, explore the simulated regional atmospheric concentration composition, the influence of meteorological elements on atmospheric concentration, and the footprint source area of ​​quantitative concentration.

[0083] This embodiment also provides a computer device, which is applicable to a photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model proposed in the above embodiment.

[0084] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. 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 communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0085] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT mode as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0086] Example 2

[0087] Referring to Table 1, which is the second embodiment of the present invention, based on the first embodiment, in order to verify the beneficial effects of the present invention, this embodiment is scientifically demonstrated through economic benefit calculation and simulation experiments.

[0088] Table 1 Basic information of photovoltaic power station

[0089] project parameter Installed capacity 50MW Annual equivalent full load hours 1200h Annual power generation 60GWh Area 100 hectares Module type and efficiency Monocrystalline silicon, 18% Location 35 degrees north latitude

[0090] As shown in Table 1, first, the parameterization is evaluated.

[0091] 1. The albedo of the photovoltaic panel is calculated to be 0.15 and the surface roughness is 0.05m.

[0092] 2. According to the actual power generation data of the power station, the photovoltaic output model is fitted by the least squares method: P = 0.8S-0.05V + error term; where P is the actual photovoltaic output, S is the net shortwave radiation absorbed by the photovoltaic panel, and V is the wind speed.

[0093] Secondly, calculate the carbon emission reduction. According to the grid benchmark emission factor of 0.6tCO 2 / MWh, and a marginal emission factor of 0.8tCO 2 / MWh and capacity marginal emission factor 1.0tCO 2 / MWh, the annual emission reduction of the power station is calculated to be approximately: 60GWh*(0.6-0.50.8-0.51.0)tCO 2 / MWh = 18,000tCO 2 .

[0094] Then, the WRF-STILT model assesses vegetation carbon sinks.

[0095] The simulation results show that compared with bare land, the annual average net CO2 absorption flux of vegetation under the photovoltaic power station increases by 20gC·m-2, and the additional carbon sink of 100 hectares of land under the power station is about 200tC.

[0096] Finally, a comparative analysis is performed with the existing technology, as shown in Table 2:

[0097] Table 2 Comparison table with prior art

[0098] project This method Existing methods Parametric calculation Consider multiple influencing factors Consider only power generation Carbon Emission Reduction <![CDATA[18,000tCO 2 / year]]> <![CDATA[15,000tCO 2 / Year<!-- 7 --> ]]> Carbon sink assessment Quantitative analysis Not considered

[0099] In summary, based on the main physical processes and action mechanisms in photovoltaic power stations, the present invention divides photovoltaic power stations into two layers: photovoltaic canopy and surface, determines the parameters affecting radiation balance in photovoltaic power stations, which are used to represent the shortwave radiation dynamics effect between photovoltaic panels and the surface; and uses the photovoltaic output model to characterize the photoelectric conversion process. This method can accurately represent the main physical processes in photovoltaic power stations, establish a simple photovoltaic land surface process model, and provide a reference for the analysis of the lower boundary conditions of photovoltaic power stations under climate models.

[0100] The present invention is based on the WRF-STILT model. Under the condition of known observation and simulation sites, multiple nested simulations of meteorological driving fields are performed on areas close to the sites, so that the simulated concentration contribution source area is more accurate.

[0101] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating emission reduction and carbon sequestration in photovoltaic power plants based on the STILT model, characterized by: include, Parameterize the various data of the photovoltaic panels to obtain the parameters of the photovoltaic power station; According to the parameters of the photovoltaic power station, the photovoltaic output model is fitted; Carbon emission reduction is obtained by converting the power generation of photovoltaic power stations; Based on the WRF-STILT model, the carbon sink of vegetation below the photovoltaic panels was evaluated and analyzed, and the evaluation results were obtained.

2. The method for evaluating emission reduction and carbon fixation in photovoltaic power plants based on the STILT model according to claim 1, characterized in that: The photovoltaic panel data include the photovoltaic panel's albedo, surface roughness, near-surface wind speed and temperature profile; The parameterization of various data of the photovoltaic panel includes: obtaining the albedo and surface roughness of the photovoltaic panel; The calculation formula of the albedo of the photovoltaic panel is, The calculation formula of the surface roughness is: The calculation formula of the wind speed and temperature profile near the surface is: in, represents the albedo, is the observed time series of solar shortwave radiation, is the observed time series of albedo, E pv is the net shortwave radiation absorbed by the photovoltaic panel, is the radiation energy received by the photovoltaic panel, is the radiant energy reflected by the photovoltaic panel, Z 0h is the surface roughness, z represents the height, d represents the zero plane displacement height, and T represents the temperature at the observation point.

3. The method for evaluating emission reduction and carbon fixation in photovoltaic power plants based on the STILT model according to claim 1, characterized in that: The photovoltaic output model obtained by fitting includes fitting the photovoltaic output model using the least square method according to the parameters of the photovoltaic power station; the calculation formula of the photovoltaic output model is: E=E pv ·(And -4.014-2.94V ) Among them, E is the actual processing data of the photovoltaic power station, E pv is the observed net shortwave radiation absorbed by the PV panels, and V is the wind speed.

4. The method for evaluating emission reduction and carbon fixation in photovoltaic power plants based on the STILT model according to claim 1, characterized in that: The carbon emission reduction benefit of the photovoltaic power station is expressed by the potential carbon emission reduction substitution amount, which is calculated in combination with the marginal emission reduction factor; the calculation formula of the carbon emission reduction amount is: IS y =BE y =EG pj,y ×EF grid,CM,y Among them, ER y is the emission reduction of the operating photovoltaic power generation system in year y, BE y is the baseline emission in year y, EG pj,y is the amount of electricity generated by the photovoltaic power generation system in operation in year y, EF grid,CM,y is the marginal CO2 emission factor of the regional power grid combination in year y.

5. The method for evaluating emission reduction and carbon fixation in photovoltaic power plants based on the STILT model according to claim 4, characterized in that: The calculation formula of the combined marginal CO2 emission factor is: IF grid,CM,y =EF grid,OM,y ×W OM +EF grid,BM,y ×W BM Among them, EF grid,OM,y is the marginal emission factor of electricity in year y, EF grid,BM,y is the marginal emission factor of capacity in year y, W OM is the marginal emission factor of electricity, W BM is the capacity marginal emission factor.

6. The method for evaluating emission reduction and carbon fixation in photovoltaic power plants based on the STILT model according to claim 1, characterized in that: The WRF-STILT model is used to evaluate and analyze the vegetation carbon sink below the photovoltaic panels. The evaluation results are based on the WRF-STILT atmospheric transport model and high spatial and temporal resolution CO2 flux data, simulating the atmospheric CO2 concentration of two typical underlying surfaces, and evaluating the CO2 flux based on eddy covariance observations and the Bayesian inversion algorithm. At the same time, the composition of atmospheric CO2 concentration in the simulated region, the influence of meteorological elements on the atmospheric CO2 concentration, and the footprint source area of ​​the quantitative CO2 concentration are explored, and the applicability of isotope data in future CO2 flux inversion is analyzed.

7. The method for evaluating emission reduction and carbon fixation in photovoltaic power plants based on the STILT model according to claim 6, characterized in that: The WRF-STILT model is a transport model of Lagrangian random walk theory, which associates source flux upstream of the observation point with concentration changes at the observation point through footprint weights; The calculation formula of the WRF-STILT model is: Among them, m air is the molar weight of air, h is the height of the underlying surface influence layer, ρ is the average density of all particles, N tot is the total number of particles released, Δt p,i,j.k Each particle corresponds to a certain area (x i ,y j ) The time t that the underlying surface influence layer stays m ; The simulated CO2 concentration consists of two parts, including the initial field concentration just entering the simulation area and the local source and sink contribution of the concentration after entering the simulation area. The calculation formula of the local source and sink contribution is: Among them, ΔCO2 is the local contribution of the simulated hourly concentration, i is the corresponding hour from 1 to 168 hours, footi is the footprint weight corresponding to the i-th hour in the simulation process, and fluxCO2 is the corresponding source-sink flux.

8. A photovoltaic power station emission reduction and carbon fixation assessment system based on the STILT model, based on the photovoltaic power station emission reduction and carbon fixation assessment method based on the STILT model according to any one of claims 1 to 7, characterized in that: It includes a data processing module, a model fitting module, a calculation module, and an analysis module; The data processing module is used to collect various data of the photovoltaic panel, including albedo and surface roughness, and use corresponding formulas to parameterize the albedo and surface roughness; The model fitting module is used to use the acquired data to fit a photovoltaic output model using the least squares method, and the model is based on the actual processing data of the photovoltaic power station, the observed net shortwave radiation absorbed by the photovoltaic panel and the wind speed; The calculation module includes a carbon emission reduction benefit calculation unit and a marginal emission factor calculation unit; The carbon emission reduction benefit calculation unit is used to calculate the carbon emission reduction benefit of the photovoltaic power station, convert the photovoltaic carbon emission reduction amount into a potential carbon emission reduction substitution amount, and calculate it in combination with the marginal emission reduction factor; The marginal emission factor calculation unit is used to calculate the marginal emission factor of electricity and the marginal emission factor of capacity using a combined marginal emission factor calculation method; The analysis module is used to analyze and process the vegetation carbon sink below the photovoltaic panels using the WRF-STILT atmospheric transport model and high-resolution flux data, calculate the concentration using the transport model of the Lagrangian random walk theory, explore the composition of atmospheric concentration in the simulated region, the impact of meteorological elements on atmospheric concentration, and the footprint source area of ​​the quantitative concentration.

9. 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 for evaluating emission reduction and carbon fixation in a photovoltaic power station based on the STILT model are implemented as described in any one of claims 1 to 7.

10. 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 for evaluating emission reduction and carbon fixation in a photovoltaic power station based on the STILT model according to any one of claims 1 to 7 are implemented.

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