Photovoltaic energy flow logistics monitoring method, system and device for grassland in arid region

Abstract

The invention belongs to the technical field of photovoltaic park microhabitat ground element monitoring equipment, and discloses an arid area grassland photovoltaic energy flow logistics monitoring method, system and device. The method comprises the following steps: acquiring energy transmission and biological meteorological data above, below and among photovoltaic array panels in a photovoltaic park in real time, and acquiring carbon-water flux information and vegetation phenology data of the photovoltaic park; acquiring data such as energy transmission, biological meteorology, carbon-water flux and surface vegetation phenology outside the photovoltaic park; the differences of energy transmission, logistics circulation, microclimate and the like inside and outside the photovoltaic park and above, below and among photovoltaic array panels in the photovoltaic park are monitored in real time, and the influence of the photovoltaic park on the local microenvironment is quantified. According to the invention, full-time monitoring is carried out through the phenological camera, and succession characteristics of adaptability and plasticity of the photovoltaic park and the ground surface vegetation to the disturbed microhabitat are accurately perceived. According to the method, the ecological suitability of the photovoltaic park in the arid region can be quantitatively evaluated, and high-quality development of ecological construction of the photovoltaic industry is promoted.

Description

Technical Field

[0001] The invention belongs to the technical field of photovoltaic park microhabitat ground element monitoring equipment, and discloses a method, system and device for monitoring photovoltaic energy flow and logistics in grasslands in arid areas. Background Art

[0002] With the construction and operation of photovoltaic parks in deserts, Gobi and desert grasslands, their impact on the local microecological environment needs urgent attention. It is of practical significance to conduct quantitative assessments of the impact of large-scale photovoltaic park construction and operation on the original ecological environment to guide the sustainable development of solar energy resources in arid areas and promote the high-quality development of ecological construction in arid areas.

[0003] Existing technology 1: Evaluation of the adaptability of major crops under different precipitation years in four major ecological zones based on the APSIM model (Agricultural Science 2022, 55(10): 1917-1937, 2022.10.004 Liu Xiaxia, Li Yang, Wang Jing, Huang Mingxia, Bai Rui, Song Yang, Hu Qi, Zhang Jiaying, Chen Renwei), the public study selected typical sites in four ecological zones, and applied the verified APSIM model to quantify the potential yield, rain-fed yield and yield difference of six crops, so as to calculate the crop yield reduction rate under different precipitation years, evaluate its adaptability and analyze the sensitivity of crops to water based on the crop water production function.

[0004] Existing Technology 2: Evaluation of Ecological Adaptability of Warm-Season Herbaceous Plants on Highway Slopes (Journal of Northeastern University (Natural Science Edition), Vol. 39, No. 1, January 2018, Liang Li, Ji Guibin, Zhao Ying) In order to optimize and screen vegetation suitable for highway slopes, the Guanghe Expressway slope construction was taken as the research object, and a study on the selection of warm-season vegetation species on highway slopes was carried out. A sowing experiment was conducted on 8 local warm-season herbaceous plants, and the ecological adaptability of plant species was evaluated using the hierarchical analysis method.

[0005] Prior art three: Evaluation of ecological adaptability of 57 cool-season grass turf varieties in Beijing (Grassland Science, Vol. 27, No. 8, 2010.08) was published at the experimental base. Through quantitative determination of lawn characteristic indicators of different varieties of tall fescue (Festuca arundinacea), red fescue (F. aubra), hard fescue (F. ovina var. durivscula), meadow bluegrass (Poapratensis) and perennial ryegrass (Lolium perenne), the ecological adaptability of each lawn grass variety was comprehensively evaluated.

[0006] Prior art 4: Evaluation of flue-cured tobacco ecological adaptability based on GIS and fuzzy set theory (Chinese Tobacco Science, 2016-06, 37(3), Zhang Jiuquan, Liang Hongbo, Dong Jianxin, Wu Yuanhua), publicly uses GIS and fuzzy set modeling technology to collect and test soil and tobacco leaf samples in tobacco-growing areas, collect and organize climate and topographic data, analyze the correlation between tobacco leaf quality and ecological conditions, determine evaluation factors, and conduct ecological suitability evaluation. The results show that altitude, sunshine hours and soil type can be used as key factors for evaluating the ecological suitability of flue-cured tobacco.

[0007] Through the above analysis, the problems and defects of the existing technology are as follows: the existing technology has a single monitoring device and function in the monitoring of near-surface energy transmission, material circulation and other elements in the micro-habitats of desert, Gobi and desert photovoltaic parks. For the monitoring of photovoltaic energy flow and logistics in grasslands in arid areas, it is urgent to improve its multi-data interactivity and system perception and diagnosis, and comprehensively improve the monitoring accuracy. Summary of the invention

[0008] In order to overcome the problems existing in the related art, the embodiments disclosed in the present invention provide a method, system and device for monitoring photovoltaic energy flow and logistics in grasslands in arid areas.

[0009] The technical solution is as follows: A method for monitoring photovoltaic energy flow and logistics in grasslands in arid areas, the method comprising:

[0010] S1, real-time acquisition of energy transmission and biometeorological data on, under and between photovoltaic array panels in the photovoltaic park, carbon and water flux information in the photovoltaic park, and phenological characteristic data of surface vegetation under and between photovoltaic array panels;

[0011] S2, obtain data on energy transmission, biometeorology, carbon and water fluxes, and phenological characteristics of surface vegetation outside the photovoltaic park;

[0012] S3, all the above acquired data information is transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through the wireless transmission antenna, so as to monitor the difference between the data information inside the photovoltaic park and outside the photovoltaic park in real time, and quantify the disturbance effect of the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal;

[0013] S4, in the photovoltaic park, through full-time monitoring by phenological cameras, perceive the succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to disturbed microhabitats;

[0014] S5, quantitatively assess the ecological suitability of photovoltaic parks in arid areas.

[0015] In step S1, in the photovoltaic park, energy transmission sensors installed on, under, and between photovoltaic array panels are used to obtain near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels upward, and soil temperature and humidity data information; biometeorological sensors installed on, under, and between photovoltaic array panels are used to obtain air temperature and humidity, wind speed and direction, precipitation, and surface evapotranspiration data information; carbon and water flux change information in the photovoltaic park is obtained through carbon and water flux sensors and three-dimensional ultrasonic anemometers; surface vegetation growth information is obtained through phenological cameras; all the above data information is obtained and transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through wireless transmission antennas;

[0016] In step S2, outside the photovoltaic park, the near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels upward, and soil temperature and humidity data information are obtained respectively through the energy transmission sensors deployed; the air temperature and humidity, wind speed and direction, precipitation, and surface evapotranspiration data information are obtained respectively through the biometeorological sensors deployed; the carbon and water flux information outside the photovoltaic park is obtained through the carbon and water flux sensor and the three-dimensional ultrasonic anemometer;

[0017] In step S3, all the above data information (steps S1 and S2) are transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through the wireless transmission antenna. Among them, step S3 mainly compares the data inside and outside the photovoltaic park to determine the impact of the photovoltaic park on the local microhabitat and its extent;

[0018] The step S3 specifically includes: the energy flow remote monitoring terminal receives the monitoring information in the photovoltaic park in step S1 for comparison, and quantifies the difference values ​​of energy transmission and biometeorology on, under, and between panels of the photovoltaic array; at the same time, the energy flow remote monitoring terminal receives the monitoring information outside the photovoltaic park in step S2, and compares it with the difference values ​​of energy transmission and biometeorology on, under, and between panels of the photovoltaic array, and at the same time, compares the acquired plant growth characteristics and carbon and water flux change information inside and outside the photovoltaic park, and quantifies the impact of the disturbance on the local microenvironment in the photovoltaic park through the energy flow remote monitoring terminal, the biometeorology includes air temperature, and the carbon and water flux includes precipitation and evapotranspiration; the quantification of the impact of the photovoltaic park on the disturbance on the local microenvironment includes obtaining the impact information on the disturbance in the local microenvironment in the photovoltaic park by quantitatively analyzing the energy transmission path and the relationship between energy transmission, air temperature, precipitation, and evapotranspiration.

[0019] Furthermore, the energy transfer pathways and relationships in energy transfer are quantitatively analyzed, including:

[0020] The energy relationship between the photovoltaic array panels outside the photovoltaic park and the photovoltaic park is:

[0021] Rχ,outer ≈R χ,between

[0022] χ∈(net,down,up,par,soil)

[0023] Where: R χ,outer is the radiation outside the photovoltaic park, R χ,between is the radiation in the photovoltaic park, χ includes net radiation net, downward shortwave radiation down, upward longwave radiation up, photosynthetically active radiation par and soil heat flux soil;

[0024] Among them, the energy transmission paths and relationships between photovoltaic array panels outside the photovoltaic park and the photovoltaic park are as follows:

[0025] R net =R down -R up -R soil

[0026] R par =λ×R down

[0027] Where: R net is the net radiation in the energy transfer path, R down is the downward short-wave radiation in the energy transmission path, R up is the upward long-wave radiation in the energy transmission path, R soil is the soil heat flux between photovoltaic array panels in the energy transmission path, R par is the photosynthetically active radiation in the energy transmission pathway, and λ is the downward short-wave radiation R in the energy transmission pathway. down Photosynthetically active radiation R in energy transfer pathway par The ratio of

[0028] The energy transmission paths and their relationships between the photovoltaic array panels and under the panels in the photovoltaic park are as follows:

[0029] R net-bellow +R net-over

[0030] =(R down-bellow +R down-over )-(R up-bellow +R up-over )-R soil

[0031] R par-bellow =λ bellow ×R down-bellow

[0032] R par-over =λ over ×Rdown-over

[0033] Where: R net-bellow is the net radiation under the photovoltaic array panel, R net-over is the net radiation on the photovoltaic array panel, R down-bellow is the downward shortwave radiation from the photovoltaic array panel, R down-over is the downward short-wave radiation on the photovoltaic array panel, R up-bellow is the upward long-wave radiation from the photovoltaic array panel, R up-over is the upward long-wave radiation on the photovoltaic array panel, R soil is the soil heat flux under the photovoltaic array panel, R par-bellow is the photosynthetically active radiation under the photovoltaic array panel, λ bellow is the ratio of photosynthetically active radiation under the photovoltaic array panel to the shortwave radiation under the panel, P par-over is the photosynthetically active radiation on the photovoltaic array panel, λ over It is the ratio of photosynthetically active radiation under the photovoltaic array panel to the shortwave radiation under the panel;

[0034] Quantitative analysis of temperature relationships includes:

[0035] The relationship between the air temperature outside the photovoltaic park and between the photovoltaic array panels in the photovoltaic park is as follows:

[0036] T up-outer ≈T up-between

[0037] T down-outer ≈T down-between

[0038] T up-outer =λ outer ×T down-outer

[0039] T up-between =λ between ×T down-between

[0040] Where: T up-outer is the upper air temperature outside the photovoltaic park, T up-between is the upper air temperature between photovoltaic array panels in the photovoltaic park, T down-outer is the lower layer temperature outside the photovoltaic park, T down-between is the lower air temperature between photovoltaic array panels in the photovoltaic park, λ outer is the ratio of the upper and lower air temperatures outside the photovoltaic park, λ between is the ratio of the upper and lower air temperatures between the photovoltaic array panels in the photovoltaic park;

[0041] Quantitative analysis of precipitation relationships includes:

[0042] The relationship between the precipitation inside and outside the photovoltaic park and the front eaves, under the panels, and between the rear eaves and panels of the photovoltaic array in the photovoltaic park is as follows:

[0043] P outer ≈P between

[0044]

[0045] Where: P outer is the precipitation outside the photovoltaic park, P between is the precipitation between photovoltaic array panels in the photovoltaic park, P bellow is the precipitation under the photovoltaic array in the photovoltaic park, including: the front eaves of the photovoltaic array P before , PV array panel P under Between the photovoltaic array panels behind , the above precipitation is per unit area;

[0046] Quantitative analysis of evapotranspiration relationships includes:

[0047] The relationship between the evaporation and heat release of the photovoltaic arrays in front of the photovoltaic array, under the photovoltaic array, behind the photovoltaic array and between the photovoltaic arrays in the photovoltaic array is as follows:

[0048] ET outer ≈ET between ≈ET before ≈ET under ≈ET behind

[0049] Where: ET outer ET is the surface evapotranspiration outside the photovoltaic park. between ET is the surface evapotranspiration between photovoltaic array panels in the photovoltaic park. before ET is the evapotranspiration from the front eaves of the photovoltaic array in the photovoltaic park. under ET is the surface evapotranspiration under the photovoltaic array panels in the photovoltaic park. behind It is the surface evaporation behind the photovoltaic array in the photovoltaic park.

[0050] Furthermore, by installing energy transmission sensors on, under, and between photovoltaic array panels, we can obtain data on near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels, and soil temperature and humidity, including:

[0051] S201, by calculating the initial incident sunlight energy A and estimating the initial incident reflection interference frequency Obtain the changing band h0 of the initial incident solar radiation wave; where, The value range is shortwave band;

[0052] S202, obtaining the first sunlight incident energy A1 and the first incident reflection interference frequency by calculating the change band h0 of the initial incident solar radiation wave and measuring the initial radiation energy transmission decay E0

[0053] S203, by calculating the first sunlight incident energy A1 and the first incident reflection interference frequency Obtaining the change band h1 of the first incident solar radiation wave and the first radiation energy transmission decay E1;

[0054] S204, obtaining the second sunlight incident energy A2 and the second incident reflection interference frequency by calculating the change band h1 of the first incident solar radiation wave and the first radiation energy transmission decay E1

[0055] S205, determining whether the difference ΔA between the second incident sunlight energy A2 and the initial incident sunlight energy A satisfies ΔA<0.3A and whether the second incident reflection interference frequency and the first incident reflection interference frequency The difference value Is it satisfied? If both conditions are met, the calculation ends; otherwise, the second incident reflection interference frequency is used The second incident sunlight energy A2 replaces the first incident reflected interference frequency and the first sunlight incident energy A1, repeat steps S203 and S204 until, after i cycles, ΔA satisfies ΔA<0.3A. satisfy At this time h i , A i and The closest real number, the calculation ends.

[0056] In step S201, the initial incident sunlight energy A and the estimated initial incident reflection interference frequency are calculated. include:

[0057] In the photovoltaic module radiation energy conversion module in the photovoltaic array, the changing band constant a of the incident solar radiation wave is expressed as:

[0058]

[0059] Where c is the speed of light in vacuum, k is the angular frequency of incident solar radiation, and ω is the incident angle of sunlight. is the incident reflection interference frequency at the incident solar radiation angle e, k p k is the angular frequency of radiation energy conversion of the photovoltaic module radiation energy conversion module in the volt array, p The expression is:

[0060]

[0061] Where, e is the incident solar radiation angle, m is e is the incident energy of sunlight at the incident solar radiation wave angle e, ε0 is the initial incident energy deviation of sunlight;

[0062] When the solar radiation wave passes through the photovoltaic module radiation energy conversion module in the photovoltaic array with a thickness of l, the radiation energy transmission decay amount E and the first variation band h a They are:

[0063] E =40log 10 (e -bl )=-17.38bl

[0064]

[0065] In the formula, h p is the band interval of solar radiation waves propagating in the radiation energy conversion module of the photovoltaic module, h0 is the band interval of solar radiation waves propagating in free space, a0 is the band interval constant of solar radiation waves in free space, and b is the surface area of ​​the photovoltaic module in the photovoltaic array;

[0066] In step S202, the calculated initial incident solar radiation waveband h0 and the measured initial radiation energy transmission decay are used to calculate the initial incident solar radiation waveband h0 and the measured initial radiation energy transmission decay. E 0, obtain the first incident sunlight energy A1 and the first incident reflection interference frequency include:

[0067] In the photovoltaic module radiation energy conversion module in the photovoltaic array, the expression of the radiation energy transmission decay constant b of the incident solar radiation wave is:

[0068]

[0069] In the formula, k p1 is the first radiation energy conversion angular frequency of the radiation energy conversion module of the photovoltaic component in the voltaic array, k p1 The expression is as follows:

[0070]

[0071] When the solar radiation wave passes through the thickness The PV array's radiant energy conversion module has a decay in the initial radiant energy transmission. E 0 and the second changing band h b They are:

[0072]

[0073] In the formula, h p1 is the variation band of the first radiation energy conversion of the radiation energy conversion module of the photovoltaic component in the photovoltaic array, and l1 is the first thickness of the radiation energy conversion module of the photovoltaic component in the photovoltaic array.

[0074] In step S4, in the photovoltaic park, the adaptability and plasticity of the surface vegetation in the photovoltaic park to the disturbed microhabitat are monitored by the phenological camera throughout the whole period, and the succession characteristics, including growth adaptability and ecological adaptability, are sensed. The monitoring indicators of growth adaptability are plant height and coverage; the observation indicators of ecological adaptability are diversity index and dominance index;

[0075] The calculation formula for the adaptability of surface vegetation in photovoltaic parks to disturbed habitats is:

[0076]

[0077] Where: SI is the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat, n is the number of factors, W i The weight of factor i, μ i is the degree of membership of factor i, x is the height, coverage, diversity index and dominance index;

[0078] Diversity index formula:

[0079]

[0080] Where: D is the diversity index of the observation area, m is the number of species, is the joint probability of randomly selecting two individuals;

[0081] Dominance index formula:

[0082]

[0083] Where: C is the dominance index of the observation area, is the ratio of the number of individuals in the i-th group to the total number;

[0084] Based on the calculation of the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat, the vegetation species that are adapted to the disturbed habitat in the photovoltaic park are selected, including:

[0085] (1) The Q data value declared by the pre-selected growing plant is converted into the Y data value;

[0086] (2) Based on the implementation of the Y data value, select plants with adaptability and plasticity to disturbed habitats.

[0087] In step (1), the Q data value declared by the pre-selected growing plant is converted into the Y data value, including:

[0088] When there is N V The pre-selected growing plants participate in the election as competitors, and the competition process of plants with adaptability and plasticity to the disturbed habitat; each pre-selected growing plant participating in the competition declares a Q data value as a fittest survival regulation method, and it does not exceed the energy transmission and biometeorological excess values ​​in the growth environment; after the fittest survival regulation method declaration stage is over, the Y data value is allocated according to the proportion of the Q data value submitted by each growing plant. The energy transmission and biometeorological growth guarantee conditions are deducted from the Q data value energy transmission and biometeorological data value of the growing plant. When competitor i (i∈{1,2,…,N V}) has Q data value And declare q i Q data values ​​participate in the selection of plants with adaptability and plasticity to disturbed habitats, among which Then, in the plant selection of adaptability and plasticity to disturbed habitats, the data value of competitor i under the conditions of suitable energy transmission and biometeorological growth guarantee is:

[0089]

[0090] Among them, Q1 is the total number of Y data values ​​implemented by the system in the process of plant selection for adaptability and plasticity to disturbed habitats, and Y i The data values ​​of competitor i in plant election for adaptability and plasticity to disturbed habitats under conditions of suitable energy transfer and biometeorological growth assurance;

[0091] The final survival of the fittest regulation methods based on game balance include:

[0092] (A) Constructing and defining the plant competition game of adaptability and plasticity to disturbed habitats V ;

[0093] The growing plants join the task by announcing the Q data value as a survival of the fittest regulation method to maximize utility, where the utility of the growing plants is affected by the survival of the fittest regulation method of competitors, expressed as a non-cooperative verification game M V = {N V ,Q,F i}, is the set of competitor's survival of the fittest regulation modes, F i is the utility function of competitor i;

[0094] (B) Quantify the utility of growing plants participating in the game:

[0095]

[0096] In the formula, is the value function of the Q data value for competitor i; represents the expected rewards that competitors receive as plants for their adaptability and plasticity to disturbed habitats; represents the additional rewards gained by becoming a plant that is adaptable and plastic to disturbed habitats; represents the cost of deducting the Q data value;

[0097] (C) Solve the optimal survival of the fittest regulation mode of growing plants when solving the game equilibrium;

[0098] Plant competition game between adaptability and plasticity to disturbed habitats V The Nash equilibrium is represented as a set of fittest survival control methods For all i∈{1,…,N V},satisfy Plant competition game between adaptability and plasticity to disturbed habitats V There is a unique Nash equilibrium Q * ,satisfy:

[0099]

[0100] In the formula, Competitive game of plant adaptability and plasticity to disturbed habitats V The subset of the survival of the fittest regulation set in the Nash equilibrium of , Q1 is the survival of the fittest regulation set of the first competitor, Q2 is the survival of the fittest regulation set of the second competitor;

[0101] In step (2), according to the implementation of the Y data value, plants with adaptability and plasticity to the disturbed habitat are selected, including:

[0102] (a) Set the minimum unit of Y data value to cluster, and the data to a string of length g Y For the kth Y data value obtained from growing plant i, a cluster of numbers In the collection Z i middle, represents the set of all Y data values ​​obtained by growing plant i in the previous game process;

[0103] (b) Function Will Maps to binary numbers 0 or 1: Define and calculate the length g t Another string of binary digits C w :

[0104]

[0105] In the formula, The binary function of the kth Y data value obtained for growing plant i in the wth cluster;

[0106] (c) The length is g t The binary number C w is hashed into a length of g t The new binary number C w* =H(C w ), and hold w* The same Y data value binary number The competitors become plants with adaptability and plasticity to disturbed habitats in the process;

[0107] The final survival of the fittest regulation methods based on game balance include:

[0108] (1) Construct and define the plant competition game M of adaptability and plasticity to disturbed habitats V ;

[0109] The growing plants join the task by announcing a certain number of Q data values ​​as a survival of the fittest regulation method to maximize utility, where the utility of the growing plants is affected by the survival of the fittest regulation methods of other competitors, expressed as a non-cooperative verification game M V = {N V ,Q,F i},in is the set of competitor's survival of the fittest regulation modes, F i is the utility function of competitor i;

[0110] (2) quantify the utility of growing plants participating in the game;

[0111]

[0112] in, is the value function of the Q data value for competitor i; F i The first term in represents the expected reward that competitors receive as plants that are adaptable and plastic to the disturbed habitat; F i The second term in F represents the additional reward for being a plant that is adaptable and plastic to disturbed habitats; i The third term in represents the cost of deducting the Q data value;

[0113] (3) Find the optimal survival-of-the-fittest regulation mode for growing plants when solving the game equilibrium;

[0114] Plant competition game between adaptability and plasticity to disturbed habitats V The Nash equilibrium is represented as a set of fittest survival control methods For all i∈{1,…,N V},satisfy Plant competition game between adaptability and plasticity to disturbed habitats V There is a unique Nash equilibrium Q * ,satisfy:

[0115]

[0116] Another object of the present invention is to provide a photovoltaic energy flow and logistics monitoring system for grasslands in arid areas, the system implementing the photovoltaic energy flow and logistics monitoring method for grasslands in arid areas, the system comprising:

[0117] The data information acquisition module in the photovoltaic park is used to obtain the energy transmission and biometeorological data on, under and between photovoltaic array panels in the photovoltaic park in real time, obtain the carbon and water flux information in the photovoltaic park, and the phenological characteristic data of the surface vegetation under and between photovoltaic array panels;

[0118] The data information acquisition module outside the photovoltaic park is used to obtain energy transmission, biometeorology, carbon and water flux, and surface vegetation phenological characteristics data outside the photovoltaic park;

[0119] The module for analyzing the impact of disturbances in the photovoltaic park on the local microenvironment is used to transmit all acquired data information to the data collector through signals, and send it to the energy flow remote monitoring terminal through the wireless transmission antenna, so as to monitor the difference between the data information inside the photovoltaic park and outside the photovoltaic park in real time, and quantify the impact of disturbances in the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal;

[0120] The succession characteristic analysis module is used to perceive the succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to the disturbed microhabitat through full-time monitoring by phenological cameras;

[0121] The ecological suitability quantitative assessment module is used to quantitatively assess the ecological suitability of photovoltaic parks in arid areas.

[0122] Another object of the present invention is to provide a photovoltaic energy flow and logistics monitoring device for grasslands in arid areas, which is implemented by a photovoltaic energy flow and logistics monitoring system for grasslands in arid areas, and the device comprises:

[0123] A fence is installed between the grassland inside the photovoltaic park and the grassland outside the photovoltaic park; a photovoltaic array is installed on the grassland inside the photovoltaic park, and grassland photovoltaic energy flow and logistics monitoring structures for quantitatively monitoring and evaluating the disturbance of the photovoltaic park to the local microhabitat are installed on the grassland inside the photovoltaic park and the grassland outside the photovoltaic park. The grassland photovoltaic energy flow and logistics monitoring structures are located between the photovoltaic array photovoltaic components.

[0124] The grassland photovoltaic energy flow and logistics monitoring structure comprises: a biometeorological vortex correlation monitoring system installed on the grassland in the photovoltaic park or on the grassland ground outside the photovoltaic park; the biometeorological vortex correlation monitoring system comprises a main bracket;

[0125] A plurality of sub-supports are installed on the main support, and biological / meteorological and water vapor flux sensors are mounted at different positions of the sub-supports for conducting microhabitat observations inside and outside the photovoltaic park and at different positions of the photovoltaic array in the photovoltaic park.

[0126] Combined with all the above technical solutions, the beneficial effects of the present invention are as follows: for the microhabitat disturbance caused by the construction and operation of large-scale photovoltaic parks in arid areas and its derived adaptive succession, this method obtains the energy transmission and biometeorological data on, under and between photovoltaic array panels in photovoltaic parks in real time, obtains carbon and water flux information, and vegetation phenology data in photovoltaic parks; obtains data such as energy transmission, biometeorology, carbon and water flux, and surface vegetation phenology outside photovoltaic parks; real-time monitoring of the differences in energy transmission, logistics circulation, and micrometeorology between photovoltaic array panels, under and between panels inside and outside photovoltaic parks, as well as photovoltaic parks, to quantify the impact of photovoltaic parks on the local microenvironment. The present invention uses phenological cameras to monitor all the time, and accurately perceives the succession characteristics of the adaptability and plasticity of photovoltaic parks and surface vegetation to disturbed microhabitats. The present invention can quantitatively evaluate the ecological suitability of photovoltaic parks in arid areas and promote the high-quality development of photovoltaic industry ecological construction.

[0127] Specifically, the present invention carries out monitoring of near-surface energy transmission, material circulation and other elements for the micro-habitats of desert, Gobi and desert-type photovoltaic parks. Two sets of monitoring systems are designed, which are deployed inside and outside the photovoltaic park respectively, to monitor whether the micro-environment of the photovoltaic park changes after operation and quantify the degree of change. The monitoring system set up in the photovoltaic park can monitor the energy transmission, temperature and humidity between the upper and lower parts of the photovoltaic components and the panels in real time. The monitoring of the local micro-habitat elements of the photovoltaic park can quantitatively identify the changes in the near-surface solar shortwave radiation, total radiation, net radiation, photosynthetically active radiation, soil temperature and humidity, air temperature and humidity, and carbon and water flux caused by the photovoltaic park. Through the full-time monitoring of the phenological camera, the growth characteristics of surface vegetation in the photovoltaic park are obtained.

[0128] The monitoring system and the monitoring method can be used to obtain the succession characteristics of the adaptability and plasticity of the surface vegetation in the photovoltaic park to the disturbed habitat. The monitoring system can further promote the theory and application of the "photovoltaic grass production" and "grass-light complementarity" models in arid areas. Moreover, the monitoring accuracy of the present invention is greatly improved. Further promote the theory and application of the "photovoltaic grass production" and "grass-light complementarity" models in arid areas. Moreover, the monitoring accuracy of the present invention is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0129] The accompanying drawings herein are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description, serve to explain the principles of the present disclosure;

[0130] Figure 1 is a flow chart of a method for monitoring photovoltaic energy flow and logistics in arid grasslands provided by an embodiment of the present invention;

[0131] Figure 2 Schematic diagram of a photovoltaic energy flow and logistics monitoring device for grassland in arid areas provided by an embodiment of the present invention;

[0132] In the figure: 1. Fence; 2. Grassland inside the photovoltaic park; 3. Grassland outside the photovoltaic park; 4. Burial depth; 5. Photovoltaic array; 501. Photovoltaic module; 502. Column; 503. Pile foundation; 6. Biometeorological eddy covariance monitoring system; 601. Data collector; 602. Air temperature and humidity sensor; 603. Wind speed and direction sensor; 604. Rain gauge; 605. Net radiation sensor; 606. Total radiation sensor; 607. Photosynthetically active radiation sensor; 608. Long-wave radiation sensor; 609. Soil sensor; 6091. Soil heat flux plate; 6092. Soil temperature sensor; 6093. Soil moisture sensor; 610. Surface evaporation sensor; 611. Carbon and water flux sensor; 612. Three-dimensional ultrasonic anemometer; 613. Phenological camera; 614. Lightning rod; 615. Wireless transmission antenna; 616. Main bracket. DETAILED DESCRIPTION

[0133] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific implementation disclosed below.

[0134] Embodiment 1, as Figure 1 As shown, the photovoltaic energy flow and logistics monitoring method for grassland in arid areas provided by the embodiment of the present invention includes:

[0135] S1, real-time acquisition of energy transmission and biometeorological data on, under and between photovoltaic array panels in the photovoltaic park, carbon and water flux information in the photovoltaic park, and phenological characteristic data of surface vegetation under and between photovoltaic array panels;

[0136] S2, obtain data on energy transmission, biometeorology, carbon and water fluxes, and phenological characteristics of surface vegetation outside the photovoltaic park;

[0137] S3, all the above acquired data information is transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through the wireless transmission antenna, so as to monitor the difference between the data information inside the photovoltaic park and outside the photovoltaic park in real time, and quantify the disturbance effect of the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal;

[0138] S4, in the photovoltaic park, through full-time monitoring by phenological cameras, perceive the succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to disturbed microhabitats;

[0139] S5, quantitatively assess the ecological suitability of photovoltaic parks in arid areas.

[0140] Exemplarily, the step S1 specifically includes: in the photovoltaic park, the near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels upward, and soil temperature and humidity data information are respectively obtained through energy transmission sensors arranged on, under, and between photovoltaic array panels, and the air temperature and humidity, wind speed and direction, rain gauge, and surface evaporation data information are respectively obtained through biometeorological sensors arranged on, under, and between photovoltaic array panels; and the carbon and water flux information in the photovoltaic park is obtained through a carbon and water flux sensor 611 and a three-dimensional ultrasonic anemometer 612; all the above-mentioned data information is transmitted to the data collector 601 through a signal, and all the above-mentioned data information is sent to the energy flow remote monitoring terminal through a wireless transmission antenna 615;

[0141] Exemplarily, step S2 specifically includes: outside the photovoltaic park, respectively obtaining near-surface net radiation, short-wave radiation, photosynthetically active radiation, upward long-wave radiation from the ground or photovoltaic panels, and soil temperature and humidity data information through the deployed energy transmission sensors, and respectively obtaining air temperature and humidity, wind speed and direction, rain gauge, and surface evaporation data information through the deployed biometeorological sensors; and obtaining carbon and water flux information outside the photovoltaic park through the carbon and water flux sensor 611 and the three-dimensional ultrasonic anemometer 612;

[0142] Exemplarily, in step S3, all the data information obtained above (steps S1 and S2) are transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through the wireless transmission antenna. Among them, step S3 mainly compares the data inside and outside the photovoltaic park to determine the impact of the photovoltaic park on the local microhabitat and its extent;

[0143] Exemplarily, the step S3 specifically includes: the energy flow remote monitoring terminal receives the monitoring information in the photovoltaic park in step S1 for comparison, and obtains the energy transmission and biometeorological difference values ​​on, under, and between the photovoltaic array panels; at the same time, the energy flow remote monitoring terminal receives the monitoring information outside the photovoltaic park in step S2, and compares it with the energy transmission and biometeorological difference values ​​on, under, and between the photovoltaic array panels, and at the same time, compares the obtained plant growth characteristics and carbon and water flux change information inside and outside the photovoltaic park, and quantifies the impact of the disturbance in the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal, the biometeorology includes air temperature, and the carbon and water flux includes precipitation and evapotranspiration; the quantification of the impact of the photovoltaic park on the disturbance in the local microenvironment includes obtaining the impact information on the disturbance in the local microenvironment in the photovoltaic park by quantitatively analyzing the energy transmission pathway and the relationship between energy transmission, temperature relationship, precipitation relationship, and evapotranspiration relationship.

[0144] Exemplarily, quantitative analysis of energy transfer pathways and relationships in energy transfer includes:

[0145] The energy relationship between the photovoltaic array panels outside the photovoltaic park and the photovoltaic park is:

[0146] R χ,outer ≈R χ,between

[0147] χ∈(net,down,up,par,soil)

[0148] Where: R χ,outer is the radiation outside the photovoltaic park, R χ,between is the radiation in the photovoltaic park, χ includes net radiation net, downward shortwave radiation down, upward longwave radiation up, photosynthetically active radiation par and soil heat flux soil;

[0149] Among them, the energy transmission paths and relationships between photovoltaic array panels outside the photovoltaic park and the photovoltaic park are as follows:

[0150] R net =R down -R up -R soil

[0151] R par =λ×R down

[0152] Where: R net is the net radiation in the energy transfer path, R down is the downward short-wave radiation in the energy transmission path, R up is the upward long-wave radiation in the energy transmission path, R soil is the soil heat flux between photovoltaic array panels in the energy transmission path, Rpar is the photosynthetically active radiation in the energy transmission pathway, and λ is the downward short-wave radiation R in the energy transmission pathway. down Photosynthetically active radiation R in energy transfer pathway par The ratio of

[0153] The energy transmission paths and their relationships between the photovoltaic array panels and under the panels in the photovoltaic park are as follows:

[0154] R net-bellow +R net-over

[0155] =(R down-bellow +R down-over )-(R up-bellow +R up-over )-R soil

[0156] R par-bellow =λ bellow ×R down-bellow

[0157] R par-over =λ over ×R down-over

[0158] Where: R net-bellow is the net radiation under the photovoltaic array panel, R net-over is the net radiation on the photovoltaic array panel, R down-bellow is the downward shortwave radiation from the photovoltaic array panel, R down-over is the downward short-wave radiation on the photovoltaic array panel, R up-bellow is the upward long-wave radiation from the photovoltaic array panel, R up-over is the upward long-wave radiation on the photovoltaic array panel, R soil is the soil heat flux under the photovoltaic array panel, R par-bellow is the photosynthetically active radiation under the photovoltaic array panel, λ bellow is the ratio of photosynthetically active radiation under the photovoltaic array panel to the shortwave radiation under the panel, R par-over is the photosynthetically active radiation on the photovoltaic array panel, λ over It is the ratio of photosynthetically active radiation under the photovoltaic array panel to the shortwave radiation under the panel;

[0159] Quantitative analysis of temperature relationships includes:

[0160] The relationship between the air temperature outside the photovoltaic park and between the photovoltaic array panels in the photovoltaic park is as follows:

[0161] T up-outer ≈T up-between

[0162] T down-outer ≈T down-between

[0163] T up-outer =λ outer ×T down-outer

[0164] T up-between =λ between ×T down-between

[0165] Where: T up-outer is the upper air temperature outside the photovoltaic park, T up-between is the upper air temperature between photovoltaic array panels in the photovoltaic park, T down-outer is the lower layer temperature outside the photovoltaic park, T down-between is the lower air temperature between photovoltaic array panels in the photovoltaic park, λ outer is the ratio of the upper and lower air temperatures outside the photovoltaic park, λ between is the ratio of the upper and lower air temperatures between the photovoltaic array panels in the photovoltaic park;

[0166] Quantitative analysis of precipitation relationships includes:

[0167] The relationship between the precipitation inside and outside the photovoltaic park and the front eaves, under the panels, and between the rear eaves and panels of the photovoltaic array in the photovoltaic park is as follows:

[0168] P outer ≈P between

[0169]

[0170] Where: P outer is the precipitation outside the photovoltaic park, P between is the precipitation between photovoltaic array panels in the photovoltaic park, P bellow is the precipitation under the photovoltaic array in the photovoltaic park, including P before Photovoltaic array front eaves, P under Photovoltaic array panel and P behind Between photovoltaic array panels, the above precipitation amounts are per unit area;

[0171] Quantitative analysis of evapotranspiration relationships includes:

[0172] The relationship between the evaporation and heat release of the photovoltaic arrays in front of the photovoltaic array, under the photovoltaic array, behind the photovoltaic array and between the photovoltaic arrays in the photovoltaic array is as follows:

[0173] ET outer ≈ET between ≈ET before ≈ET under ≈ET behind

[0174] Where: ET outer FT is the surface evapotranspiration outside the photovoltaic park,between ET is the surface evapotranspiration between photovoltaic array panels in the photovoltaic park. before ET is the evapotranspiration from the front eaves of the photovoltaic array in the photovoltaic park. under ET is the surface evapotranspiration under the photovoltaic array panels in the photovoltaic park. behind It is the surface evaporation behind the photovoltaic array in the photovoltaic park.

[0175] For example, energy transmission sensors installed on, under, and between photovoltaic array panels are used to obtain near-surface net radiation, short-wave radiation, photosynthetically active radiation, upward long-wave radiation from the ground or photovoltaic panels, and soil temperature and humidity data, including:

[0176] S201, by calculating the initial incident sunlight energy A and estimating the initial incident reflection interference frequency Obtain the changing band h0 of the initial incident solar radiation wave; where, The value range is shortwave band;

[0177] S202, obtaining the first sunlight incident energy A1 and the first incident reflection interference frequency by calculating the change band h0 of the initial incident solar radiation wave and measuring the initial radiation energy transmission decay E0

[0178] S203, by calculating the first sunlight incident energy A1 and the first incident reflection interference frequency Obtaining the change band h1 of the first incident solar radiation wave and the first radiation energy transmission decay E1;

[0179] S204, obtaining the second sunlight incident energy A2 and the second incident reflection interference frequency by calculating the change band h1 of the first incident solar radiation wave and the first radiation energy transmission decay E1

[0180] S205, determining whether the difference ΔA between the second incident sunlight energy A2 and the initial incident sunlight energy A satisfies ΔA<0.3A and whether the second incident reflection interference frequency and the first incident reflection interference frequency The difference value Is it satisfied? If both conditions are met, the calculation ends; otherwise, the second incident reflection interference frequency is used The second incident sunlight energy A2 replaces the first incident reflected interference frequency and the first sunlight incident energy A1, repeat steps S203 and S204 until, after i cycles, ΔA satisfies ΔA<0.3A. satisfy At this time h i , A iand The closest real number, the calculation ends.

[0181] In step S201, the initial incident sunlight energy A and the estimated initial incident reflection interference frequency are calculated. include:

[0182] In the photovoltaic module radiation energy conversion module in the photovoltaic array, the changing band constant a of the incident solar radiation wave is expressed as:

[0183]

[0184] Where c is the speed of light in vacuum, k is the angular frequency of incident solar radiation, and ω is the incident angle of sunlight. is the incident reflection interference frequency at the incident solar radiation angle e, k p k is the angular frequency of radiation energy conversion of the photovoltaic module radiation energy conversion module in the volt array, p The expression is:

[0185]

[0186] Where, e is the incident solar radiation angle, m is e is the incident energy of sunlight at the incident solar radiation wave angle e, ε0 is the initial incident energy deviation of sunlight;

[0187] When the solar radiation wave passes through the photovoltaic module radiation energy conversion module in the photovoltaic array with a thickness of l, the radiation energy transmission decay amount E and the first variation band h a They are:

[0188] E =40log 10 (e -bl )=-17.38bl

[0189]

[0190] In the formula, h p is the band interval of solar radiation waves propagating in the radiation energy conversion module of the photovoltaic module, h0 is the band interval of solar radiation waves propagating in free space, a0 is the band interval constant of solar radiation waves in free space, and b is the surface area of ​​the photovoltaic module in the photovoltaic array;

[0191] The radiation energy transmission decay and change band of solar radiation wave and the incident energy A of sunlight e , initial incident reflection interference frequency The thickness l of the PV module radiation energy conversion module in the PV array is related to the angular frequency k of the incident solar radiation wave;

[0192] In step S202, the calculated initial incident solar radiation waveband h0 and the measured initial radiation energy transmission decay are used to calculate the initial incident solar radiation waveband h0 and the measured initial radiation energy transmission decay. E 0, obtain the first incident sunlight energy A1 and the first incident reflection interference frequency include:

[0193] In the photovoltaic module radiation energy conversion module in the photovoltaic array, the expression of the radiation energy transmission decay constant b of the incident solar radiation wave is:

[0194]

[0195] In the formula, k p1 is the first radiation energy conversion angular frequency of the radiation energy conversion module of the photovoltaic component in the voltaic array, k p1 The expression is as follows:

[0196]

[0197] When the solar radiation wave passes through the thickness The PV array's radiant energy conversion module has a decay in the initial radiant energy transmission. E 0 and the second changing band h b They are:

[0198]

[0199]

[0200] In the formula, h p1 is the variation band of the first radiation energy conversion of the radiation energy conversion module of the photovoltaic component in the photovoltaic array, and l1 is the first thickness of the radiation energy conversion module of the photovoltaic component in the photovoltaic array.

[0201] Exemplarily, in step S3, obtaining the energy transmission difference values ​​above, below, and between photovoltaic array panels includes obtaining the soil temperature and humidity energy transmission difference values ​​above, below, and between photovoltaic array panels, which can be obtained by directly comparing the data monitored by the soil heat flux panel 6091, the soil temperature sensor 6092, and the soil moisture sensor 6093.

[0202] Exemplarily, the difference values ​​of near-surface net radiation, short-wave radiation, photosynthetically active radiation, and upward long-wave radiation energy transmission from the ground or photovoltaic panels between photovoltaic array panels can be obtained by direct comparison with actual monitored values.

[0203] Exemplarily, in step S4, in the photovoltaic park, the adaptability and plasticity of the surface vegetation in the photovoltaic park to the disturbed microhabitat are monitored by the phenological camera throughout the whole period, including: the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat includes growth adaptability and ecological adaptability, wherein the monitoring indicators of growth adaptability include: plant height and coverage; the observation indicators of ecological adaptability include: diversity index and dominance index; the calculation formula of the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat is as follows:

[0204]

[0205] Where: SI is the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat, n is the number of factors, W i The weight of factor i, μ i is the degree of membership of factor i, and x is the height, coverage, diversity index and dominance index; since the value range of weight and degree of membership is 0.0-1.0, the obtained suitability index is in the range of 0.0-1.0, 0 means completely unsuitable, and 1 means 100% suitable;

[0206] The diversity index formula is:

[0207]

[0208] Where: D is the diversity index of the observation area, m is the number of species, the lowest value of Simpson's diversity index is 0, the highest value is 1, the lowest value is 0, all individuals belong to one species, the highest value is 1, which means that each individual belongs to a different species. If the proportion of the number of individuals of species i to the total number of individuals in the community is 1, then the joint probability of randomly selecting two individuals of species i is

[0209] The formula for the dominance index is:

[0210] Where: C is the dominance index of the observation area, is the ratio of the number of individuals in the i-th group to the total number; according to the above formula, the more the number of individuals (or biomass) in the community is concentrated on a few groups, the greater the dominance of the community; the more dispersed, the smaller the dominance of the community; the closer to the tropics, the more complex the community, the more species, and the smaller the dominance of the community; using this index to describe the composition of the community is helpful for understanding the ecology of the community;

[0211] Furthermore, we screened vegetation species that can adapt to the disturbed habitats of photovoltaic parks to provide theoretical support for accelerating ecological restoration and recovery after the operation of photovoltaic parks;

[0212] As another example, in step S4, in the plant growth succession characteristics of the adaptability and plasticity of the surface vegetation in the photovoltaic park to the disturbed habitat, the energy transmission and biometeorological suitability value Y and the growth credibility Q are described by two numerical values ​​respectively, the Y data value is used to serve the suitable energy transmission and biometeorological growth guarantee conditions, and the Q data value is used for growth credibility weight evaluation; the Y data value will only be implemented when the system generates a new living space; at the same time, the exchange process between real species and Y data values ​​is allowed between growing plants; the requester needs to pay the Y data value to the photovoltaic park suitable growth assessment system as an incentive for them to accept the published tasks; after completing the task, the photovoltaic park suitable growth assessment system will obtain additional Q data values ​​from the system according to the quality of the results, suitable energy transmission and biometeorological growth guarantee conditions or penalties; each growing plant that wants to become a plant with adaptability and plasticity to the disturbed habitat can participate in the verification competition; during the competition, the growing plant consumes a certain number of Q data values ​​and obtains a certain number of Y data values; the role of each participant changes dynamically according to its own status and needs.

[0213] For example, the plant growth succession characteristics of the adaptability and plasticity of surface vegetation in photovoltaic parks to disturbed habitats are ultimately obtained, realizing the theory and application of photovoltaic grass production and grass-light complementary model in arid areas.

[0214] It can be understood that the characteristics of plant growth succession are usually as follows: with the changes in the natural geographical environment, the plant kingdom itself moves and develops in constant contradictions; the dominant type in a certain period is replaced by another more evolved type of plant in the process of development. At this time, the plant kingdom undergoes a qualitative change and enters a new stage of development.

[0215] Among them, the plant growth succession characteristics that ultimately obtain the adaptability and plasticity of the surface vegetation in the photovoltaic park to the disturbed habitat include: obtaining the growth characteristics of different growth stages of plants through phenological cameras, screening surface vegetation species suitable for disturbed habitat changes, and ultimately obtaining plants that are adaptable and plastic to the disturbed habitat in the photovoltaic park;

[0216] Exemplarily, the step of selecting vegetation species suitable for disturbed habitats includes:

[0217] When there are N pre-selected plants in the photovoltaic park suitable growth assessment system, the pre-selected plants adopt a certain survival of the fittest regulation method to participate in the competition process in order to become plants with adaptability and plasticity to the disturbed habitat, and allocate a part of suitable energy transmission and biometeorological growth guarantee conditions according to the survival of the fittest regulation method of the pre-selected plants; the exchange process of Q data value and Y data value involves a public survival interval game; at the same time, according to the game results, a unique and unpredictable plant with adaptability and plasticity to the disturbed habitat is selected to generate the next living space, including:

[0218] (1) The pre-selected growing plants declare a certain number of Q data values ​​to be exchanged for Y data values;

[0219] When there is N V The pre-selected growing plants participate in the election as competitors, and the competition process of plants with adaptability and plasticity to the disturbed habitat; each pre-selected growing plant participating in the competition declares a Q data value as a fittest survival regulation method, and it does not exceed the energy transmission and biometeorological excess values ​​in the growth environment; after the fittest survival regulation method declaration stage is over, the Y data value is allocated according to the proportion of the Q data value submitted by each growing plant. The energy transmission and biometeorological growth guarantee conditions are deducted from the Q data value energy transmission and biometeorological data value of the growing plant. When competitor i (i∈{1,2,…,N V}) has Q data value And declare q i Q data values ​​participate in the selection of plants with adaptability and plasticity to disturbed habitats, among which Then, in the plant selection of adaptability and plasticity to disturbed habitats, the data value of competitor i under the conditions of suitable energy transmission and biometeorological growth guarantee is:

[0220]

[0221] Among them, Q1 is the total number of Y data values ​​implemented by the system in the process of plant selection for adaptability and plasticity to disturbed habitats, and Y i The data values ​​of competitor i in plant election for adaptability and plasticity to disturbed habitats under conditions of suitable energy transfer and biometeorological growth assurance;

[0222] (2) Select plants with adaptability and plasticity to disturbed habitats based on the implementation of Y data values.

[0223] (a) Set the minimum unit of Y data value to cluster, and the data to a string of length g Y The k-th Y data value obtained for growing plant i is stored as a string of binary numbers In the collection Zi middle, represents the set of all Y data values ​​obtained by growing plant i in the previous game process;

[0224] (b) Function Will Maps to binary numbers 0 or 1: Define and calculate the length g t Another string of binary digits C w :

[0225]

[0226] In the formula, The binary function of the kth Y data value obtained for growing plant i in the wth cluster;

[0227] (c)g t The binary number of length C w is hashed into a length of g t The new binary number C w* =H(C w ), and hold w* The same Y data value binary number The competitors become plants with adaptability and plasticity to disturbed habitats in the process;

[0228] The system provides the Y data value of additional suitable energy transmission and biometeorological growth guarantee conditions to the plants that ultimately have adaptability and plasticity to the disturbed habitat, which is recorded as Q2; the suitable energy transmission and biometeorological growth guarantee conditions consist of two parts: Q1 and Q2, where Q1 is used for the first competitor of suitable energy transmission and biometeorological growth guarantee conditions, and Q2 is used for the second competitor (second plant) of suitable energy transmission and biometeorological growth guarantee conditions that ultimately have adaptability and plasticity to the disturbed habitat; the pre-selected growth plants that cannot become plants with adaptability and plasticity to the disturbed habitat will also obtain some growth environment conditions, thereby promoting the pre-selected growth plants to actively participate in the competition among plants with adaptability and plasticity to the disturbed habitat.

[0229] Exemplarily, based on the appropriate energy transmission and biometeorological growth guarantee condition benefits of the players in the quantitative competition process, the final survival of the fittest regulation method is established according to the game balance, including:

[0230] (A) Constructing and defining the plant competition game of adaptability and plasticity to disturbed habitats V ;

[0231] The growing plants join the task by announcing a certain number of Q data values ​​as a survival of the fittest regulation method to maximize utility, where the utility of the growing plants is affected by the survival of the fittest regulation methods of other competitors, expressed as a non-cooperative verification game M V = {N V ,Q,F i},in is the set of competitor's survival of the fittest regulation modes, F i is the utility function of competitor i;

[0232] (B) Quantify the utility of growing plants participating in the game;

[0233]

[0234] in, is the value function of the Q data value for competitor i; F i The first term in represents the expected reward that competitors receive as plants that are adaptable and plastic to the disturbed habitat; F i The second term in F represents the additional reward for being a plant that is adaptable and plastic to disturbed habitats; i The third term in represents the cost of deducting the Q data value;

[0235] (C) Solve the optimal survival of the fittest regulation mode of growing plants when solving the game equilibrium;

[0236] Plant competition game between adaptability and plasticity to disturbed habitats V The Nash equilibrium is represented as a set of fittest survival control methods For all i∈{1,…,N V},satisfy Plant competition game between adaptability and plasticity to disturbed habitats V There is a unique Nash equilibrium Q * ,satisfy:

[0237]

[0238] In the formula, Competitive game of plant adaptability and plasticity to disturbed habitats V The subset of the survival of the fittest regulation set in the Nash equilibrium of , Q1 is the survival of the fittest regulation set of the first competitor, Q2 is the survival of the fittest regulation set of the second competitor;

[0239] It can be understood that through the above embodiments, the present invention obtains information on whether there is a difference in energy transmission inside and outside the photovoltaic park, and the quantified value; and specifically obtains information on whether there is a difference in energy transmission above, under, and between photovoltaic modules in the photovoltaic park;

[0240] At the same time, the present invention obtains information on whether there are differences in the micro (meteorological) environment inside and outside the photovoltaic park, and the quantitative value; specifically, it obtains information on whether there are differences in the micro meteorological environment above, under, and between photovoltaic modules in the photovoltaic park; and the present invention obtains data information on the response of grassland vegetation to the photovoltaic park and the microenvironment at different locations within the area, so as to obtain the plant growth succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to the disturbed habitat, and to realize the theory and application of photovoltaic grass production and grass-light complementary mode in arid areas, providing technical support, and the monitoring accuracy is only very high.

[0241] Embodiment 2, the photovoltaic energy flow and logistics monitoring system for grasslands in arid areas provided by the embodiment of the present invention comprises:

[0242] The data information acquisition module in the photovoltaic park is used to obtain the energy transmission and biometeorological data on, under and between photovoltaic array panels in the photovoltaic park in real time, obtain the carbon and water flux information in the photovoltaic park, and the phenological characteristic data of the surface vegetation under and between photovoltaic array panels;

[0243] The data information acquisition module outside the photovoltaic park is used to obtain energy transmission, biometeorology, carbon and water flux, and surface vegetation phenological characteristics data outside the photovoltaic park;

[0244] The module for analyzing the impact of disturbances in the photovoltaic park on the local microenvironment is used to transmit all acquired data information to the data collector through signals, and send it to the energy flow remote monitoring terminal through the wireless transmission antenna, so as to monitor the difference between the data information inside the photovoltaic park and outside the photovoltaic park in real time, and quantify the impact of disturbances in the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal;

[0245] The succession characteristic analysis module is used to perceive the succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to the disturbed microhabitat through full-time monitoring by phenological cameras;

[0246] The ecological suitability quantitative assessment module is used to quantitatively assess the ecological suitability of photovoltaic parks in arid areas.

[0247] Embodiment 3, as Figure 2 As shown, the photovoltaic energy flow and logistics monitoring device for grasslands in arid areas provided by an embodiment of the present invention comprises: a fence 1, wherein the fence 1 is installed between the grassland 2 inside the photovoltaic park and the grassland 3 outside the photovoltaic park; the grassland 2 inside the photovoltaic park is installed with a photovoltaic array 5, and both the grassland 2 inside the photovoltaic park and the grassland 3 outside the photovoltaic park are installed with grassland photovoltaic energy flow and logistics monitoring structures for quantitatively monitoring and evaluating the disturbance of the photovoltaic park to the local microhabitat, and the grassland photovoltaic energy flow and logistics monitoring structure is located between the photovoltaic array 5 and the photovoltaic components 501.

[0248] The grassland photovoltaic energy flow monitoring structure includes: a biometeorological vortex correlation monitoring system 6 installed on the ground of a grassland 2 in a photovoltaic park or a grassland 3 outside a photovoltaic park; the biometeorological vortex correlation monitoring system 6 includes a main bracket 616;

[0249] A plurality of sub-supports are installed on the main support 616, and biological / meteorological and water vapor flux sensors are mounted at different positions of the sub-supports for conducting microhabitat observations inside and outside the photovoltaic park and at different positions of the photovoltaic array in the photovoltaic park.

[0250] The biometeorological eddy correlation monitoring system 6 also includes:

[0251] The data collector 601 is located in the data acquisition chassis, which is located at the bottom of the main bracket 616 1m above the ground and is fixed to the main bracket 616 by fixing screws; the data collector 601 is connected to the wireless transmission antenna 615 outside the data acquisition chassis; the data collector 601 is connected to the energy transmission sensor or biological / meteorological sensor through signals.

[0252] The energy transmission sensor includes a net radiation sensor 605, a total radiation sensor 606, a photosynthetically active radiation sensor 607, a long-wave radiation sensor 608 and a soil sensor 609, which respectively monitor near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels upward, and soil temperature and humidity. The net radiation sensor 605, the total radiation sensor 606, the photosynthetically active radiation sensor 607, and the long-wave radiation sensor 608 are all installed on a sub-bracket; the soil sensor 609 includes a soil heat flux plate 6091, a soil temperature sensor 6092, and a soil moisture sensor 6093, which are all buried below the ground.

[0253] The biological / meteorological sensor includes an air temperature and humidity sensor 602, a wind speed and direction sensor 603, a rain gauge 604 and a surface evaporation sensor 610 for respectively monitoring air temperature and humidity, wind speed and direction, precipitation, and surface evaporation. The air temperature and humidity sensor 602 and the wind speed and direction sensor 603 are both installed on a sub-bracket, and the rain gauge 604 and the surface evaporation sensor 610 are respectively installed on the front eaves, under the panels, rear eaves and between the panels of the photovoltaic components 501 in the photovoltaic park and as accessories of the monitoring device outside the photovoltaic park.

[0254] The biometeorological eddy correlation monitoring system 6 also includes: a phenological camera 613, which is located in the middle of the main bracket 616, 3 meters from the ground, and can rotate 360° horizontally and flip 90° vertically up and down, to maximize the flexibility of adjusting the angle.

[0255] The biometeorological eddy correlation monitoring system 6 also includes: a carbon and water flux sensor 611 and a three-dimensional ultrasonic anemometer 612, both of which are installed on the auxiliary bracket and connected to the data collector 601 respectively;

[0256] The biometeorological eddy correlation monitoring system 6 also includes: a lightning rod 614 located on the top of the main support 616.

[0257] Working principle: In the grassland 2 (grassland photovoltaic ecosystem) in the photovoltaic park, energy transmission sensors and biological / meteorological sensors are designed for the upper and lower parts of the photovoltaic modules 501 of the photovoltaic array 5 and between the photovoltaic modules 501 to monitor the microhabitats at different locations in the photovoltaic park. The photovoltaic modules 501 are fixed to the grassland 2 (grassland photovoltaic ecosystem) in the photovoltaic park through columns 502 and pile foundations 503; the grassland photovoltaic energy flow and logistics monitoring device 1 includes 2 sets of bio-meteorological eddy correlation monitoring systems, which are respectively located between the panels of the photovoltaic array 5 in the photovoltaic park 2 and in the adjacent area outside the fence 3 of the photovoltaic park;

[0258] The photovoltaic array 5 includes a photovoltaic module 501 that converts solar energy into electrical energy or sends it to a battery for storage, or drives a load to work. The electrical energy generated by the photovoltaic array 5 is directly transmitted to the power grid in the form of direct current, or the generated direct current is converted into alternating current through an inverter and transmitted to the power grid; grid-connected power generation of the photovoltaic array 5 is achieved. The power of each sensor and electrical equipment in the monitoring device provided by the present invention is supplied by the mains.

[0259] Exemplarily, the main bracket 616 is the physical carrier of the monitoring system, and various sensors are installed on multiple sub-brackets to realize the monitoring of the micro-habitats of the grassland 2 in the photovoltaic park and the grassland 3 outside the photovoltaic park.

[0260] Exemplarily, the data collector 601 is located in the data acquisition chassis, which is located at the bottom of the main bracket 616, 1m above the ground, and is fixed to the main bracket 616 by fixing screws; the data collector 601 collects sensor data and has pre-processing capabilities; the data collector 601 is connected to the wireless transmission antenna 615 outside the data acquisition chassis to transmit data in real time by wireless means. The energy transmission sensor is installed on the sub-bracket, which is connected to the main bracket 616.

[0261] Exemplarily, the energy transfer sensor includes a net radiation sensor 605, a total radiation sensor 606, a photosynthetically active radiation sensor 607, a long-wave radiation sensor 608 and a soil sensor 609 (including a soil heat flux plate 6091, a soil temperature sensor 6092, and a soil moisture sensor 6093), which respectively monitor near-surface net radiation, short-wave radiation, photosynthetically active radiation, upward long-wave radiation from the ground or photovoltaic panels, soil temperature and humidity, etc.

[0262] The soil heat flux plate 6091, the soil temperature sensor 6092, and the soil moisture sensor 6093 are buried below the ground at a depth of 4, the depth of 4 is set to 1 m, and the average burial depth interval is 0.2 m;

[0263] Exemplarily, the biological / meteorological sensor includes an air temperature and humidity sensor 602, a wind speed and direction sensor 603, a rain gauge 604 and a ground evaporation sensor 610, which respectively monitor air temperature and humidity, wind speed and direction, precipitation, and ground evaporation.

[0264] For example, the grassland photovoltaic energy flow monitoring structure of grassland 2 in the photovoltaic park is located on the upper part of the photovoltaic module 501, between the lower panel 202 of the photovoltaic module 501 and the photovoltaic module 501, and the phenological camera 613 is located in the middle of the main bracket 616, 3m above the ground, and can rotate 360° horizontally and flip up and down 90° vertically. The phenological camera is used to carry out full-time, high-precision monitoring to quantify the adaptive succession characteristics of surface vegetation in the photovoltaic park to the disturbed habitat.

[0265] The present invention can monitor the biometeorology, water vapor flux and vegetation phenology inside and outside the photovoltaic park in real time, quantitatively explore the impact of the photovoltaic park on the local microhabitat and the adaptability of its surface vegetation, and thus objectively evaluate the suitability of the photovoltaic park.

[0266] Exemplarily, the biometeorological eddy covariance monitoring system 6 also includes a surface evaporation sensor 610 ; a carbon and water flux sensor 611 ; a three-dimensional ultrasonic anemometer 612 ; and a lightning rod 614 located on top of the main support 616 .

[0267] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for monitoring photovoltaic energy flow in grasslands in arid areas, characterized in that: The method includes: S1, real-time acquisition of energy transmission and biometeorological data on, under and between photovoltaic array panels in the photovoltaic park, carbon and water flux information in the photovoltaic park, and phenological characteristic data of surface vegetation under and between photovoltaic array panels; S2, obtain data on energy transmission, biometeorology, carbon and water fluxes, and phenological characteristics of surface vegetation outside the photovoltaic park; S3, all the above acquired data information is transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through the wireless transmission antenna, so as to monitor the difference between the data information inside the photovoltaic park and outside the photovoltaic park in real time, and quantify the disturbance effect of the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal; S4, in the photovoltaic park, through full-time monitoring by phenological cameras, perceive the succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to disturbed microhabitats; S5, quantitatively assess the ecological suitability of photovoltaic parks in arid areas.

2. The photovoltaic energy flow monitoring method for grasslands in arid areas according to claim 1 is characterized in that: In step S1, in the photovoltaic park, the energy transmission sensors installed on, under and between the photovoltaic array panels are used to obtain the near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels upward, and soil temperature and humidity data information; the biometeorological sensors installed on, under and between the photovoltaic array panels are used to obtain the air temperature and humidity, wind speed and direction, precipitation, and surface evapotranspiration data information; the carbon and water flux change information in the photovoltaic park is obtained through the carbon and water flux sensor and the three-dimensional ultrasonic anemometer; the surface vegetation growth information is obtained through the phenological camera; all the above data information is obtained and transmitted to the data collector through signals, and sent to the energy flow remote monitoring terminal through the wireless transmission antenna; In step S2, outside the photovoltaic park, the near-surface net radiation, short-wave radiation, photosynthetically active radiation, upward long-wave radiation from the ground or photovoltaic panels, and soil temperature and humidity data information are obtained respectively through the energy transmission sensors deployed; the air temperature and humidity, wind speed and direction, precipitation, and surface evapotranspiration data information are obtained respectively through the biometeorological sensors deployed; the carbon and water flux information outside the photovoltaic park is obtained through the carbon and water flux sensor and the three-dimensional ultrasonic anemometer.

3. The photovoltaic energy flow monitoring method for grasslands in arid areas according to claim 1 is characterized in that: In step S3, the energy flow remote monitoring terminal receives the monitoring information in the photovoltaic park in step S1 for comparison, and quantifies the difference in energy transmission and biometeorological values ​​on, under, and between photovoltaic array panels; At the same time, the energy flow remote monitoring terminal receives the monitoring information outside the photovoltaic park in step S2, compares it with the difference values ​​of energy transmission and biometeorology on, under and between panels of the photovoltaic array, compares the acquired plant growth characteristics inside and outside the photovoltaic park, and the change information of carbon and water flux, and quantifies the impact of the disturbance on the local microenvironment in the photovoltaic park through the energy flow remote monitoring terminal; The biometeorology includes air temperature; the carbon and water flux includes precipitation and evapotranspiration; the quantitative impact of the photovoltaic park on the disturbed local microenvironment includes obtaining the impact information of the photovoltaic park on the disturbed local microenvironment by quantitatively analyzing the energy transmission pathway and the relationship between energy transmission, temperature relationship, precipitation relationship, and evapotranspiration relationship.

4. The photovoltaic energy flow monitoring method for grasslands in arid areas according to claim 3 is characterized in that: Quantitative analysis of energy transfer pathways and relationships in energy transfer, including: The energy relationship between the photovoltaic array panels outside the photovoltaic park and the photovoltaic park is: R χ,outer ≈R χ,between χ∈(net,down,up,par,soil) Where: R χ,outer is the radiation outside the photovoltaic park, R χ,between is the radiation in the photovoltaic park, χ includes net radiation net, downward shortwave radiation down, upward longwave radiation up, photosynthetically active radiation par and soil heat flux soil; Among them, the energy transmission paths and relationships between photovoltaic array panels outside the photovoltaic park and the photovoltaic park are as follows: R net =R down -R up -R soil R par =λ×R down Where: R net is the net radiation in the energy transfer path, R down is the downward short-wave radiation in the energy transmission path, R up is the upward long-wave radiation in the energy transmission path, R soil is the soil heat flux between photovoltaic array panels in the energy transmission path, R par is the photosynthetically active radiation in the energy transmission pathway, and λ is the downward short-wave radiation R in the energy transmission pathway. down Photosynthetically active radiation R in energy transfer pathway par The ratio of The energy transmission paths and their relationships between the photovoltaic array panels and under the panels in the photovoltaic park are as follows: R net-bellow +R net-over =(R down-bellow +R dow n -over )-(R up-bellow +R up-over )-R soil R par-bellow =λ bellow ×R down-bellow R par-over =λ over ×R down-over Where: R net-bellow is the net radiation under the photovoltaic array panel, R net-over is the net radiation on the photovoltaic array panel, R down-bellow is the downward shortwave radiation from the photovoltaic array panel, R down-over is the downward short-wave radiation on the photovoltaic array panel, R up-bellow is the upward long-wave radiation from the photovoltaic array panel, R up-over is the upward long-wave radiation on the photovoltaic array panel, R soil is the soil heat flux under the photovoltaic array panel, R par-bellow is the photosynthetically active radiation under the photovoltaic array panel, λ bellow is the ratio of photosynthetically active radiation under the photovoltaic array panel to the shortwave radiation under the panel, R par-over is the photosynthetically active radiation on the photovoltaic array panel, λ over It is the ratio of photosynthetically active radiation under the photovoltaic array panel to the shortwave radiation under the panel; Quantitative analysis of temperature relationships, including: The relationship between the air temperature outside the photovoltaic park and between the photovoltaic array panels in the photovoltaic park is as follows: T up-outer ≈T up-between T down-outer ≈T down-between T up-outer =λ outer ×T down-outer T up-berween =λ between ×T down-berween Where: T up-outer is the upper air temperature outside the photovoltaic park, T up-between is the upper air temperature between photovoltaic array panels in the photovoltaic park, T down-outer is the lower layer temperature outside the photovoltaic park, T down-between is the lower air temperature between photovoltaic array panels in the photovoltaic park, λ outer is the ratio of the upper and lower air temperatures outside the photovoltaic park, λ between is the ratio of the upper and lower air temperatures between the photovoltaic array panels in the photovoltaic park; Quantitative analysis of precipitation relationships, including: The relationship between the precipitation inside and outside the photovoltaic park and the front eaves, under the panels, and between the rear eaves and panels of the photovoltaic array in the photovoltaic park is as follows: P outer ≈P between Where: P outer is the precipitation outside the photovoltaic park, P between is the precipitation between photovoltaic array panels in the photovoltaic park, P bellow is the precipitation under the photovoltaic array in the photovoltaic park, including: the front eaves of the photovoltaic array P before , PV array panel under P under Between the photovoltaic array panels behind ; Quantitative analysis of evapotranspiration relationships, including: The relationship between the evaporation and heat release of the photovoltaic arrays in front of the photovoltaic array, under the photovoltaic array, behind the photovoltaic array and between the photovoltaic arrays in the photovoltaic array is as follows: AND outer ≈AND between ≈AND before ≈AND under ≈AND behind Where: ET outer FT is the surface evapotranspiration outside the photovoltaic park, between ET is the surface evapotranspiration between photovoltaic array panels in the photovoltaic park. before ET is the evapotranspiration from the front eaves of the photovoltaic array in the photovoltaic park. under ET is the evapotranspiration under the photovoltaic array panels in the photovoltaic park. behind It is the surface evaporation behind the photovoltaic array in the photovoltaic park.

5. The photovoltaic energy flow monitoring method for grasslands in arid areas according to claim 2 is characterized in that: Energy transmission sensors installed on, under, and between photovoltaic array panels are used to obtain near-surface net radiation, short-wave radiation, photosynthetically active radiation, long-wave radiation from the ground or photovoltaic panels, and soil temperature and humidity data, including: S201, by calculating the initial incident sunlight energy A and estimating the initial incident reflection interference frequency Obtain the changing band h0 of the initial incident solar radiation wave; where, The value range is shortwave band; S202, obtaining the first sunlight incident energy A1 and the first incident reflection interference frequency by calculating the change band h0 of the initial incident solar radiation wave and measuring the initial radiation energy transmission decay E0 S203, by calculating the first sunlight incident energy A1 and the first incident reflection interference frequency Obtaining the change band h1 of the first incident solar radiation wave and the first radiation energy transmission decay E1; S204, obtaining the second sunlight incident energy A2 and the second incident reflection interference frequency by calculating the change band h1 of the first incident solar radiation wave and the first radiation energy transmission decay E1 S205, determining whether the difference ΔA between the second incident sunlight energy A2 and the initial incident sunlight energy A satisfies ΔA<0.3A and whether the second incident reflection interference frequency and the first incident reflection interference frequency The difference value Is it satisfied? If both conditions are met, the calculation ends; otherwise, the second incident reflection interference frequency is used The second incident sunlight energy A2 replaces the first incident reflected interference frequency and the first sunlight incident energy A1, repeat steps S203 and S204 until, after i cycles, ΔA satisfies ΔA<0.3A. satisfy At this time h i , A i and The closest real number, the calculation ends.

6. The photovoltaic energy flow monitoring method for grasslands in arid areas according to claim 5 is characterized in that: In step S201, the initial incident sunlight energy A and the estimated initial incident reflection interference frequency are calculated. include: In the photovoltaic module radiation energy conversion module in the photovoltaic array, the changing band constant a of the incident solar radiation wave is expressed as: Where c is the speed of light in a vacuum, k is the angular frequency of incident solar radiation, and ω is the incident angle of sunlight. is the incident reflection interference frequency at the incident solar radiation angle e, k p k is the angular frequency of radiation energy conversion of the photovoltaic module radiation energy conversion module in the volt array, p The expression is: Where, e is the incident solar radiation angle, m is e is the incident energy of sunlight at the incident solar radiation wave angle e, ε0 is the initial incident energy deviation of sunlight; When the solar radiation wave passes through the photovoltaic module radiation energy conversion module in the photovoltaic array with a thickness of l, the radiation energy transmission decay amount E and the first variation band h a They are: E =40log 10 (e -bl )=-17.38bl In the formula, h p is the band interval of solar radiation waves propagating in the radiation energy conversion module of the photovoltaic module, h0 is the band interval of solar radiation waves propagating in free space, a0 is the band interval constant of solar radiation waves in free space, and b is the surface area of ​​the photovoltaic module in the photovoltaic array; In step S202, the first incident solar radiation energy A1 and the first incident reflection interference frequency are obtained by calculating the change band h0 of the initial incident solar radiation wave and measuring the initial radiation energy transmission decay E0. include: In the photovoltaic module radiation energy conversion module in the photovoltaic array, the expression of the radiation energy transmission decay constant b of the incident solar radiation wave is: In the formula, k p1 is the first radiation energy conversion angular frequency of the radiation energy conversion module of the photovoltaic component in the voltaic array, k p1 The expression is as follows: When the solar radiation wave passes through the thickness The PV array's radiant energy conversion module has a decay in the initial radiant energy transmission. E 0 and the second changing band h b They are: In the formula, h p1 is the variation band of the first radiation energy conversion of the radiation energy conversion module of the photovoltaic component in the photovoltaic array, and l1 is the first thickness of the radiation energy conversion module of the photovoltaic component in the photovoltaic array.

7. The method for monitoring photovoltaic energy flow in grasslands in arid areas according to claim 1, characterized in that: In step S4, in the photovoltaic park, the adaptability and plasticity of the surface vegetation in the photovoltaic park to the disturbed microhabitat are monitored by the phenological camera throughout the whole period, and the succession characteristics, including growth adaptability and ecological adaptability, are sensed. The monitoring indicators of growth adaptability are plant height and coverage; the observation indicators of ecological adaptability are diversity index and dominance index; The calculation formula for the adaptability of surface vegetation in photovoltaic parks to disturbed habitats is: Where: SI is the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat, n is the number of factors, W i The weight of factor i, μ i is the degree of membership of factor i, x is the height, coverage, diversity index and dominance index; Diversity index formula: Where: D is the diversity index of the observation area, m is the number of species, is the joint probability of randomly selecting two individuals; Dominance index formula: Where: C is the dominance index of the observation area, is the ratio of the number of individuals in the i-th group to the total number; Based on the calculation of the adaptability of the surface vegetation in the photovoltaic park to the disturbed habitat, the vegetation species that are adapted to the disturbed habitat in the photovoltaic park are selected, including: (1) The Q data value declared by the pre-selected growing plant is converted into the Y data value; (2) Based on the implementation of the Y data value, select plants with adaptability and plasticity to disturbed habitats.

8. The photovoltaic energy flow monitoring method for grasslands in arid areas according to claim 7 is characterized in that: In step (1), the Q data value declared by the pre-selected growing plant is converted into the Y data value, including: When there is N V The pre-selected growing plants participate in the election as competitors, and the competition process of plants with adaptability and plasticity to the disturbed habitat; each pre-selected growing plant participating in the competition declares a Q data value as a fittest survival regulation method, and it does not exceed the energy transmission and biometeorological excess values ​​in the growth environment; after the fittest survival regulation method declaration stage is over, the Y data value is allocated according to the proportion of the Q data value submitted by each growing plant. The energy transmission and biometeorological growth guarantee conditions are deducted from the Q data value energy transmission and biometeorological data value of the growing plant. When competitor i (i∈{1,2,…,N V }) has Q data value And declare q i Q data values ​​participate in the selection of plants with adaptability and plasticity to disturbed habitats, among which Then, in the plant selection of adaptability and plasticity to disturbed habitats, the data value of competitor i under the conditions of suitable energy transmission and biometeorological growth guarantee is: Among them, Q1 is the total number of Y data values ​​implemented by the system in the process of plant selection for adaptability and plasticity to disturbed habitats, and Y i The data values ​​of competitor i in plant election for adaptability and plasticity to disturbed habitats under conditions of suitable energy transfer and biometeorological growth assurance; The final survival of the fittest regulation methods based on game balance include: (A) Constructing and defining the plant competition game of adaptability and plasticity to disturbed habitats V ; The growing plants join the task by announcing the Q data value as a survival of the fittest regulation method to maximize utility, where the utility of the growing plants is affected by the survival of the fittest regulation method of competitors, expressed as a non-cooperative verification game M V = {N V ,Q,F i }, is the set of competitor's survival of the fittest regulation modes, F i is the utility function of competitor i; (B) Quantify the utility of growing plants participating in the game: In the formula, is the value function of the Q data value for competitor i; represents the expected reward received by the first competitor as a plant for its adaptability and plasticity to the disturbed habitat; indicates that the second competitor becomes an additional reward for plants with adaptability and plasticity to the disturbed habitat; represents the cost of deducting the Q data value; (C) Solve the optimal survival of the fittest regulation mode of growing plants when solving the game equilibrium; Plant competition game between adaptability and plasticity to disturbed habitats V The Nash equilibrium is represented as a set of fittest survival control methods For all i∈{1,…,N V },satisfy Plant competition game between adaptability and plasticity to disturbed habitats V There is a unique Nash equilibrium Q * ,satisfy: In the formula, Competitive game of plant adaptability and plasticity to disturbed habitats V The subset of the survival of the fittest regulation set in the Nash equilibrium of , Q1 is the survival of the fittest regulation set of the first competitor, Q2 is the survival of the fittest regulation set of the second competitor; In step (2), according to the implementation of the Y data value, plants with adaptability and plasticity to the disturbed habitat are selected, including: (a) Set the minimum unit of Y data value to cluster, and the data to a string of length g Y For the kth Y data value obtained from growing plant i, a cluster of numbers In the collection Z i middle, represents the set of all Y data values ​​obtained by growing plant i in the previous game process; (b) Function Will Maps to binary numbers 0 or 1: Define and calculate the length g t Another string of binary digits C w : In the formula, The binary function of the kth Y data value obtained for growing plant i in the wth cluster; (c) The length is g t The binary number C w is hashed into a length of g t The new binary number Holding The same Y data value binary number The competitors become plants with adaptability and plasticity to disturbed habitats in the process; The final survival of the fittest regulation methods based on game balance include: (1) Construct and define the plant competition game M of adaptability and plasticity to disturbed habitats V ; The growing plants join the task by announcing a certain number of Q data values ​​as a survival of the fittest regulation method to maximize utility, where the utility of the growing plants is affected by the survival of the fittest regulation methods of other competitors, expressed as a non-cooperative verification game M V = {N V ,Q,F i },in is the set of competitor's survival of the fittest regulation modes, F i is the utility function of competitor i; (2) quantify the utility of growing plants participating in the game; in, is the value function of the Q data value for competitor i; F i The first term in represents the expected reward that competitors receive as plants that are adaptable and plastic to the disturbed habitat; F i The second term in F represents the additional reward for being a plant that is adaptable and plastic to disturbed habitats; i The third term in represents the cost of deducting the Q data value; (3) Find the optimal survival-of-the-fittest regulation mode for growing plants when solving the game equilibrium; Plant competition game between adaptability and plasticity to disturbed habitats V The Nash equilibrium is represented as a set of fittest survival control methods For all i∈{1,…,N V },satisfy Plant competition game between adaptability and plasticity to disturbed habitats V There is a unique Nash equilibrium Q * ,satisfy:

9. A photovoltaic energy flow monitoring system for grasslands in arid areas, characterized in that: The system implements the method for monitoring photovoltaic energy flow in grasslands in arid areas as claimed in any one of claims 1 to 8, and the system comprises: The data information acquisition module in the photovoltaic park is used to obtain the energy transmission and biometeorological data on, under and between photovoltaic array panels in the photovoltaic park in real time, obtain the carbon and water flux information in the photovoltaic park, and the phenological characteristic data of the surface vegetation under and between photovoltaic array panels; The data information acquisition module outside the photovoltaic park is used to obtain energy transmission, biometeorology, carbon and water flux, and surface vegetation phenological characteristics data outside the photovoltaic park; The module for analyzing the impact of disturbances in the photovoltaic park on the local microenvironment is used to transmit all acquired data information to the data collector through signals, and send it to the energy flow remote monitoring terminal through the wireless transmission antenna, so as to monitor the difference between the data information inside the photovoltaic park and outside the photovoltaic park in real time, and quantify the impact of disturbances in the photovoltaic park on the local microenvironment through the energy flow remote monitoring terminal; The succession characteristic analysis module is used to perceive the succession characteristics of the adaptability and plasticity of surface vegetation in the photovoltaic park to the disturbed microhabitat through full-time monitoring by phenological cameras; The ecological suitability quantitative assessment module is used to quantitatively assess the ecological suitability of photovoltaic parks in arid areas.

10. A photovoltaic energy flow monitoring device for grasslands in arid areas, characterized in that: The device is implemented by the arid grassland photovoltaic energy flow and logistics monitoring system according to claim 9, and the device comprises: A fence (1) is installed between a grassland (2) inside a photovoltaic park and a grassland (3) outside the photovoltaic park; a photovoltaic array (5) is installed on the grassland (2) inside the photovoltaic park; grassland photovoltaic energy flow and logistics monitoring structures for quantitatively monitoring and evaluating the disturbance of the photovoltaic park to the local microhabitat are installed on the grassland (2) inside the photovoltaic park and the grassland (3) outside the photovoltaic park; the grassland photovoltaic energy flow and logistics monitoring structures are located between the photovoltaic array (5) and the photovoltaic components (501); The grassland photovoltaic energy flow and material flow monitoring structure comprises: a biometeorological eddy correlation monitoring system (6) installed on the ground of a grassland (2) in a photovoltaic park or a grassland (3) outside a photovoltaic park; the biometeorological eddy correlation monitoring system (6) comprises a main support (616); A plurality of sub-supports are installed on the main support (616), and biological / meteorological and water vapor flux sensors are mounted at different positions of the sub-supports for conducting microhabitat observations inside and outside the photovoltaic park and at different positions of the photovoltaic array in the photovoltaic park.

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