Method and system for dynamically evaluating influence of photovoltaic power station on ecological environment

Abstract

The invention provides a method and a system for dynamically evaluating the influence of a photovoltaic power station on an ecological environment, and the method comprises the steps: constructing a multi-element real-time monitoring system of the photovoltaic power station, and continuously collecting various ecological environment data inside and outside the power station; transmitting the collected data to a rear end in real time for data processing, and constructing a multi-element environment feature database; analyzing long-term monitored data in a database, and determining evolution laws of various environmental parameters in the power station, influence change laws of the power station on various ecological environmental factors and various ecological influence weights; and determining an AHP weight based on the various ecological influence weights, constructing various ecological evolution prediction models and operation and maintenance decision prediction models of the power station based on the AHP weight, and determining an operation and maintenance strategy and an ecological restoration scheme of the power station by using the prediction models. According to the method, by fusing multi-source real-time monitoring and multi-dimensional data analysis, the influence of the photovoltaic power station on the ecological environment is dynamically evaluated, and the accuracy and comprehensiveness of evaluation are improved.

Description

Technical Field

[0001] This application relates to the field of ecological environment monitoring technology for new energy power plants, and in particular to a dynamic assessment method and system for the impact of photovoltaic power plants on the ecological environment. Background Technology

[0002] Currently, the number and scale of photovoltaic power plants in operation are gradually increasing. During construction and after operation, photovoltaic power plants can impact the ecological environment of the site. Therefore, in order to achieve goals such as environmental protection and ecological restoration, it is necessary to assess the impact of photovoltaic power plants on the surrounding ecological environment.

[0003] However, the assessment schemes for the impact of photovoltaic power plants on the ecological environment in related technologies have yielded relatively one-sided assessment results, with limited and inaccurate assessment data. Furthermore, the assessment results obtained from these technologies cannot be applied to subsequent power plant operation and maintenance and ecological restoration projects. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, the first objective of this application is to propose a dynamic assessment method for the impact of photovoltaic power plants on the ecological environment. This method improves the accuracy and comprehensiveness of the assessment by integrating multi-source real-time monitoring and multi-dimensional data analysis to dynamically assess the impact of photovoltaic power plants on the ecological environment.

[0006] The second objective of this application is to propose a dynamic assessment system for the ecological and environmental impacts of photovoltaic power plants.

[0007] The third objective of this application is to propose an electronic device.

[0008] The fourth objective of this application is to provide a non-transitory computer-readable storage medium.

[0009] To achieve the above objectives, the first aspect of this application is to propose a dynamic assessment method for the ecological and environmental impact of photovoltaic power plants, comprising the following steps:

[0010] A multi-element real-time monitoring system covering photovoltaic power plants at different times and in different areas is constructed. Based on the multi-element real-time monitoring system, various ecological and environmental data inside and outside the photovoltaic power plant are continuously collected. Among them, the various environmental data include micro-region ecological data, and the micro-region includes the area corresponding to the rain collection line in the photovoltaic module.

[0011] The collected ecological and environmental data are transmitted to the backend in real time for data processing to construct a multi-element environmental characteristic database.

[0012] The analysis of various long-term monitored ecological and environmental data in the multi-element environmental characteristic database determines the evolution patterns of various environmental parameters within the photovoltaic power station, the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts.

[0013] Based on the various ecological impact weights, the weights of the Analytic Hierarchy Process (AHP) are determined, and based on the AHP weights, various ecological evolution prediction models and operation and maintenance decision prediction models for photovoltaic power plants are constructed. The prediction models are then used to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants.

[0014] Optionally, the collection of various ecological and environmental data inside and outside the photovoltaic power station includes: monitoring plant physiological parameters of vegetation communities in different areas inside and outside the photovoltaic power station, and obtaining key test parameters of the vegetation communities through testing, wherein the different areas include the areas corresponding to the rainwater catchment line; determining the evolution patterns of various environmental parameters within the photovoltaic power station and the changing patterns of the impact of the photovoltaic power station on various ecological and environmental factors, including: based on the plant physiological parameters and the key test parameters, determining the changing patterns of the stress resistance of plants in different areas and the changing patterns of the impact of the photovoltaic power station on plant growth within the site.

[0015] Optionally, the multiple ecological evolution prediction models include a plant growth evolution prediction model. The step of using the prediction model to determine the operation and maintenance strategy and ecological restoration plan of the photovoltaic power station includes: using the plant growth evolution prediction model to determine a plant screening matrix suitable for different areas of the photovoltaic power station; selecting adaptable plants for different areas of the photovoltaic power station through the plant screening matrix; and optimizing the photovoltaic system layout based on the adaptable plants corresponding to different areas.

[0016] Optionally, the collection of various ecological and environmental data inside and outside the photovoltaic power station includes: collecting soil samples from different areas inside the photovoltaic power station and control points outside the station; analyzing the microbial parameters of the soil samples using high-throughput sequencing and determining the soil composition parameters of the soil samples; determining the evolution patterns of various environmental parameters within the photovoltaic power station and the changing patterns of the photovoltaic power station's influence on various ecological and environmental factors, including: determining a regression model of microbial α-diversity index and soil composition content based on the microbial parameters and the soil composition parameters; and determining the changing patterns of the influence of photovoltaic equipment shading on rhizosphere microbiota and the changing patterns of the influence of the photovoltaic power station on the soil composition parameters based on the regression model.

[0017] Optionally, the multiple ecological evolution prediction models include a microbial community and soil environment evolution prediction model. The step of using the prediction model to determine the operation and maintenance strategy and ecological restoration plan for the photovoltaic power station includes: using the microbial community and soil environment evolution prediction model to determine differentiated fertilization plans and ecological restoration plans for different areas within the photovoltaic power station site.

[0018] Optionally, the collection of various ecological and environmental data inside and outside the photovoltaic power station includes: collecting wind and sand particle flux parameters in different areas inside and outside the photovoltaic power station through a wind and sand flow array system; determining the evolution law of various environmental parameters inside the photovoltaic power station, including: performing momentum analysis on the wind and sand particle flux parameters to calculate the probability distribution of the impact height and position of wind and sand particles; generating a wind and sand convergence heat map based on the probability distribution; and using a prediction model to determine the operation and maintenance strategy and ecological restoration plan of the photovoltaic power station, including: adjusting the sand barrier layout strategy based on the wind and sand convergence heat map; constructing a wind and sand operation and maintenance prediction model based on the wind and sand convergence heat map, and determining the cleaning strategy of photovoltaic modules and the layout strategy of photovoltaic module supports through the wind and sand operation and maintenance prediction model.

[0019] Optionally, the collection of various ecological and environmental data inside and outside the photovoltaic power station includes: collecting various meteorological element data inside the photovoltaic power station and calculating various flux parameters based on the various meteorological element data; determining the influence and change patterns of the photovoltaic power station on various ecological and environmental factors includes: determining the influence patterns of the photovoltaic power station on meteorological parameters in different areas within the site based on the various meteorological element data and the various flux parameters.

[0020] To achieve the above objectives, the second aspect of this application also proposes a dynamic assessment system for the ecological and environmental impacts of photovoltaic power plants, comprising the following modules:

[0021] The monitoring module is used to construct a multi-element real-time monitoring system covering photovoltaic power plants in different time periods and different areas. Based on the multi-element real-time monitoring system, it continuously collects various ecological and environmental data inside and outside the photovoltaic power plant. Among them, the various environmental data include micro-region ecological data, and the micro-region includes the area corresponding to the rainwater collection line in the photovoltaic module.

[0022] The transmission module is used to transmit the collected various ecological and environmental data to the backend for data processing in real time and to construct a multi-element environmental feature database.

[0023] The analysis module is used to analyze various ecological and environmental data monitored over a long period of time in the multi-element environmental characteristic database, and to determine the evolution patterns of various environmental parameters within the photovoltaic power station, the change patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts.

[0024] The decision-making module is used to determine the weights of the Analytic Hierarchy Process (AHP) based on the various ecological impact weights, and to construct various ecological evolution prediction models and operation and maintenance decision prediction models for photovoltaic power plants based on the AHP weights. The prediction models are then used to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants.

[0025] To achieve the above objectives, a third aspect of this application also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a dynamic assessment method for the ecological and environmental impact of a photovoltaic power plant as described in any of the first aspects above.

[0026] To achieve the above objectives, the fourth aspect of this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the dynamic assessment method for the ecological and environmental impact of the photovoltaic power station described in any one of the first aspects.

[0027] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects: This application first constructs a full-chain monitoring system covering space, time, and elements, enabling real-time monitoring of various environmental elements of photovoltaic power plants in different time periods and regions. Then, through a closed-loop system from monitoring to transmission to analysis to decision-making, the monitoring data is analyzed and processed, realizing a dynamic assessment of the impact of photovoltaic power plants on the ecological environment. The assessment results can be applied to practical projects such as the operation and maintenance of photovoltaic power plants and ecological restoration. This application reveals the micro-regional ecological differentiation law, quantifies the ecological corridor effect of the rainwater collection lines between photovoltaic panels, and also establishes a data chain for desertification control projects, converting the momentum of wind and sand particles into mechanical design parameters for sand barriers. Based on long-term monitoring, it determines the AHP weights and constructs a predictive operation and maintenance model, which can dynamically adjust the cleaning cycle and support angle. Thus, by integrating multi-source real-time monitoring and multi-dimensional data analysis, this application dynamically assesses the impact of photovoltaic power plants on the ecological environment, improving the accuracy and comprehensiveness of the assessment, and providing a foundation for subsequent ecological restoration, equipment operation and maintenance, and desertification control projects of photovoltaic power plants.

[0028] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0029] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0030] Figure 1 This is a flowchart illustrating a dynamic assessment method for the ecological and environmental impact of a photovoltaic power plant, as proposed in an embodiment of this application.

[0031] Figure 2 This is a schematic diagram of a rain collection line in a photovoltaic string according to an embodiment of this application;

[0032] Figure 3This is a flowchart illustrating a sand barrier layout optimization algorithm proposed in an embodiment of this application;

[0033] Figure 4 This is a schematic diagram of the structure of a dynamic assessment system for the ecological and environmental impact of a photovoltaic power station, as proposed in an embodiment of this application. Detailed Implementation

[0034] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0035] It should be noted that the environmental impact assessment of photovoltaic power plants in the relevant embodiments has the following problems: (1) Data fragmentation: meteorological, soil, vegetation and other data are collected independently and lack spatiotemporal correlation; (2) Monitoring blind spots: ecological differences in micro-areas such as gaps between photovoltaic panels (rain catchment lines) and under the panels are ignored; (3) Static analysis: it relies on short-term sampling and cannot reflect long-term dynamic evolution patterns; (4) Decision disconnect: monitoring results are difficult to directly guide engineering practices such as sand barrier layout and plant selection.

[0036] Therefore, this application proposes a dynamic assessment method for the impact of photovoltaic power plants on the ecological environment, aiming to construct a full-chain monitoring and assessment system covering "space-time-elements" to solve the above problems.

[0037] The following description, with reference to the accompanying drawings, illustrates a method and system for dynamically assessing the ecological and environmental impacts of photovoltaic power plants, as proposed in an embodiment of this application.

[0038] Figure 1 This is a flowchart illustrating a dynamic assessment method for the ecological and environmental impact of a photovoltaic power plant, as proposed in an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0039] Step S101: Construct a multi-element real-time monitoring system covering photovoltaic power stations in different time periods and regions. Based on the multi-element real-time monitoring system, continuously collect various ecological and environmental data inside and outside the photovoltaic power station. Among them, various environmental data include micro-regional ecological data, and micro-regions include the areas corresponding to the rainwater collection lines in the photovoltaic modules.

[0040] Specifically, this application first constructs a comprehensive real-time monitoring system covering different time periods and stages of a photovoltaic power station. As an example, the comprehensive real-time monitoring system constructed in this application includes, but is not limited to, devices such as: meteorological gradient towers, open-circuit eddy covariance systems, wind and sand flow arrays, soil composition sensors, vegetation physiological parameter acquisition terminals, and rhizosphere microbial sampling modules. This enables long-term monitoring of various ecological and environmental data, including meteorological parameters, soil environmental parameters, wind and sand environmental parameters, microbial community parameters, and vegetation community parameters, both inside and outside the photovoltaic power station area.

[0041] In order to reveal the ecological differentiation patterns of micro-regions, this application also monitors multiple micro-regions within the photovoltaic power station (such as the area corresponding to the rainwater harvesting line in the photovoltaic module) during data monitoring to collect micro-region ecological data.

[0042] Step S102 involves transmitting the collected various ecological and environmental data to the backend for real-time data processing to construct a multi-element environmental characteristic database.

[0043] Specifically, based on the "monitoring-transmission-analysis-decision" closed-loop system of this application, the monitoring system constructed in this application can also transmit various collected ecological and environmental data to the backend for data processing in real time. This enables the automatic collection, transmission, and processing of meteorological, soil, gas, wind and sand, microbial, and vegetation data, establishing a real-time monitoring technology process for all elements of the environmental characteristics of photovoltaic power plants, encompassing "environmental monitoring—real-time transmission—data processing."

[0044] As one possible implementation, when transmitting data, edge computing and cloud synchronization can be achieved through an Internet of Things (IoT) gateway, supporting 5G / LoRa heterogeneous network transmission.

[0045] Furthermore, the collected ecological and environmental data are processed in the backend, and a multi-element environmental characteristic database is constructed using the processed data.

[0046] As one possible implementation, this embodiment first collects data on multiple ecological and environmental elements, such as meteorology, soil, gas, wind and sand, microorganisms, and vegetation, in different areas, including the photovoltaic module area, the intervals between photovoltaic modules, and the control area outside the photovoltaic power station, combining the monitoring system established in step S101 with various methods such as on-site surveys. The collected data is then transmitted to a backend server for processing, including data preprocessing, normalization, and standardization. The processed data is then used to construct a multi-element environmental characteristic database containing data resources, hardware, software, and applications.

[0047] Step S103: Analyze various ecological and environmental data monitored over a long period of time in the multi-element environmental characteristic database to determine the evolution patterns of various environmental parameters within the photovoltaic power station, the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts.

[0048] Specifically, this application involves long-term, continuous sampling of various ecological and environmental data both inside and outside the photovoltaic power station, using the methods described above. All collected data is stored in a multi-element environmental characteristic database. Furthermore, the data in the database can be analyzed to generate long-term dynamic evolution patterns of various ecological and environmental elements, as well as the impact weights of the photovoltaic power station on these elements.

[0049] As an example, the data stored in the database is analyzed based on the multi-factor hierarchical analysis method to reveal the evolution law of light resources, the change law of various environmental impact factors, the causal relationship of environmental changes, and the weight of the ecological impact of photovoltaic power plants.

[0050] Step S104: Determine the weights of the Analytic Hierarchy Process (AHP) based on multiple ecological impact weights, and construct multiple ecological evolution prediction models and operation and maintenance decision prediction models for photovoltaic power plants based on the AHP weights. Use the prediction models to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants.

[0051] Specifically, by utilizing the evolution patterns of various environmental parameters within the photovoltaic power station, the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts analyzed in step S103, basic underlying architecture data support is provided for the establishment of various new energy ecological evolution prediction models, the fault diagnosis and adjustment of operation and maintenance strategies for photovoltaic equipment, and ecological restoration measures.

[0052] One possible implementation is to use the determined ecological impact weights as weights in the Analytic Hierarchy Process (AHP), or to construct a judgment matrix based on the determined ecological impact weights, and then calculate the AHP weights by solving for the eigenvector corresponding to the largest eigenvalue of the judgment matrix. Then, combining the determined AHP weights with long-term variation patterns, a predictive operation and maintenance model is constructed using the AHP algorithm to guide the operation and maintenance of the power plant. For example, the predictive operation and maintenance model constructed in this application dynamically adjusts the cleaning cycle of photovoltaic modules and the bracket angle based on long-term AHP weights. In this application, the ecological impact weights can be the weights representing the varying impact patterns of different ecological and environmental factors on each photovoltaic power plant.

[0053] The following section details the specific implementation process of this application in analyzing and generating the long-term dynamic evolution patterns of various environmental factors, as well as using predictive models to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants, among other practical engineering practices.

[0054] In one embodiment of this application, various ecological environment data are collected inside and outside the photovoltaic power station, including: monitoring plant physiological parameters of vegetation communities in different areas inside and outside the photovoltaic power station, and obtaining key test parameters of the vegetation communities through testing, wherein different areas include the areas corresponding to the rainwater catchment line; determining the evolution patterns of various environmental parameters within the photovoltaic power station and the changing patterns of the photovoltaic power station's impact on various ecological environment factors, including: determining the changing patterns of plant stress resistance performance in different areas and the changing patterns of the photovoltaic power station's impact on plant growth within the site based on plant physiological parameters and key test parameters. Multiple ecological evolution prediction models include a plant growth evolution prediction model, which is used to determine the operation and maintenance strategy and ecological restoration plan for the photovoltaic power station, including: using the plant growth evolution prediction model to determine plant selection matrices suitable for different areas of the photovoltaic power station; selecting adaptable plants for different areas of the photovoltaic power station using the plant selection matrix, and optimizing the photovoltaic system layout based on the adaptable plants corresponding to different areas.

[0055] Specifically, this embodiment monitors vegetation growth at different locations within the photovoltaic power station, especially the gaps between components after the photovoltaic panels are installed (i.e., Figure 2 The areas shown include the rainwater collection line, the shaded area under the panels, the area between the photovoltaic arrays, and the control area outside the field. Quantitative measurements of plant physiological parameters such as vegetation cover, height, density, biomass, species composition, survival rate, growth rate, plant height, canopy width, water content, and photosynthetic parameters were conducted. Furthermore, key parameters such as the transcriptional expression levels of key plant genes, key enzyme activities, and amino acid content were obtained through corresponding testing protocols.

[0056] Furthermore, the study analyzes the changing patterns of plant stress resistance (including but not limited to: cold resistance, drought resistance, salt and alkali resistance, disease resistance, trampling resistance, and lodging resistance) in different regions, and then reveals the impact of photovoltaic power stations on vegetation growth in the area based on these patterns. Based on the established patterns, a plant growth evolution prediction model is constructed to generate a regional adaptive plant screening matrix, identifying the optimal species. This provides technical support for the screening of adaptive plants in different regions of photovoltaic power stations and also guides the optimization of photovoltaic system layout in subsequent photovoltaic-ecological high-efficiency synergistic systems.

[0057] In one embodiment of this application, various ecological and environmental data are collected both inside and outside the photovoltaic power station, including: collecting soil samples from different areas inside the photovoltaic power station and control points outside the station; analyzing the microbial parameters of the soil samples using high-throughput sequencing and determining the soil composition parameters; determining the evolution patterns of various environmental parameters within the photovoltaic power station and the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, including: determining a regression model of microbial α-diversity index and soil composition content based on microbial parameters and soil composition parameters; and determining the changing patterns of the impact of photovoltaic equipment shading on rhizosphere microbiota and the changing patterns of the impact of the photovoltaic power station on soil composition parameters based on the regression model. Multiple ecological evolution prediction models include a microbial community and soil environment evolution prediction model. These prediction models are used to determine the operation and maintenance strategies and ecological restoration schemes for the photovoltaic power station, including: using the microbial community and soil environment evolution prediction model to determine differentiated fertilization schemes and ecological restoration schemes for different areas within the photovoltaic power station site.

[0058] Specifically, this embodiment collects soil samples monthly or quarterly from within the station (under the plate, in the catchment area, and between the arrays) and from control points outside the station. High-throughput sequencing methods (such as 16S / ITS rRNA genes) are used to analyze microbial parameters such as the species and abundance of microorganisms in the soil (including the rhizosphere) both inside and outside the station, and vegetation community indicators are investigated simultaneously. At the same time, soil composition parameters (including but not limited to: soil bulk density, moisture, nitrogen, phosphorus, potassium, pH, electrical conductivity, and organic matter content) are collected using a soil composition analyzer.

[0059] Then, a regression model was established between the alpha diversity index of microorganisms and the soil nitrogen, phosphorus, and potassium content to reveal the mechanism by which photovoltaic shading affects rhizosphere microbiota and to reveal the changing patterns of soil composition parameters such as soil moisture, nutrients, bulk density, and pH caused by photovoltaic power plants. Based on the established patterns, a predictive model for the evolution of microbial communities and the soil environment was constructed to provide technical support for differentiated fertilization and ecological restoration in different areas of the site.

[0060] In one embodiment of this application, various ecological environment data inside and outside the photovoltaic power station are collected, including: collecting wind and sand particle flux parameters in different areas inside and outside the photovoltaic power station through a wind and sand flow array system; determining the evolution law of various environmental parameters inside the photovoltaic power station, including: performing momentum analysis on the wind and sand particle flux parameters to calculate the probability distribution of the impact height and position of wind and sand particles; generating a wind and sand convergence heat map based on the probability distribution; and using a prediction model to determine the operation and maintenance strategy and ecological restoration plan of the photovoltaic power station, including: adjusting the sand barrier layout strategy based on the wind and sand convergence heat map; constructing a wind and sand operation and maintenance prediction model based on the wind and sand convergence heat map, and determining the cleaning strategy of photovoltaic modules and the layout strategy of photovoltaic module supports through the wind and sand operation and maintenance prediction model.

[0061] Specifically, the process of optimizing sand barrier placement based on monitored wind and sand parameters in this embodiment is as follows: Figure 3 As shown in the figure. This embodiment uses monitoring data from a wind-sand flow array system to obtain sand particle flux parameters at different locations (including but not limited to: the leading edge of the plate, the vortex zone behind the plate, the boundary of the field area, and the surrounding sand source areas). These parameters are vectors (including direction and velocity) and describe the amount of sand particles passing through a unit area per unit time. Then, momentum analysis is performed on the collected data to obtain the impact height distribution probability, momentum-wind speed coupling coefficient, and wind-sand convergence points. Based on the wind-sand convergence hotspots, a heat map of sand barrier layout is generated, and a spacing adjustment strategy is dynamically output to guide the direction, spacing, and key areas for the photovoltaic sand control sand barrier layout. Furthermore, the wind-sand operation and maintenance prediction model described above can be constructed using the wind-sand convergence heat map. This model determines the cleaning strategy (including cleaning cycle) and the layout strategy (including support angle) of the photovoltaic modules.

[0062] In one embodiment of this application, various ecological and environmental data inside and outside the photovoltaic power station are collected, including: collecting various meteorological element data inside the photovoltaic power station and calculating various flux parameters based on the various meteorological element data; determining the influence and change patterns of the photovoltaic power station on various ecological and environmental factors, including: determining the influence patterns of the photovoltaic power station on meteorological parameters in different areas within the site based on the various meteorological element data and various flux parameters.

[0063] Specifically, this embodiment uses an open-circuit eddy covariance system and a meteorological gradient integrated observation system to acquire various meteorological element data, such as three-dimensional wind speed and direction, ultrasonic temperature, CO2 and H2O concentrations, air temperature, relative humidity, dew point, air pressure, precipitation, and irradiance. Then, the acquired meteorological data is used to calculate key parameters such as sensible heat flux, latent heat flux, and water vapor flux. For example, sensible heat flux is calculated using monitored vertical wind speed and temperature, and latent heat flux and water vapor flux are calculated using monitored vertical wind speed and specific humidity.

[0064] Furthermore, based on the different meteorological data and flux parameters of various areas within the photovoltaic power station, the influence of the photovoltaic power station on the changes of parameters such as irradiance, temperature and humidity, and CO2 flux at different locations of the photovoltaic power station over time is analyzed.

[0065] In summary, the dynamic assessment method for the ecological and environmental impact of photovoltaic power plants in this application first constructs a full-chain monitoring system covering space, time, and elements, enabling real-time monitoring of various environmental elements of photovoltaic power plants in different time periods and regions. Then, through a closed-loop system from monitoring to transmission to analysis to decision-making, the monitoring data is analyzed and processed, realizing a dynamic assessment of the ecological and environmental impact of photovoltaic power plants. The assessment results can be applied to practical projects such as photovoltaic power plant operation and maintenance and ecological restoration. This method reveals the micro-regional ecological differentiation patterns, quantifies the ecological corridor effect of rainwater harvesting lines between photovoltaic panels, establishes a data chain for desertification control projects, converts wind and sand particle momentum into sand barrier mechanical design parameters, and constructs a predictive operation and maintenance model based on long-term monitoring to determine AHP weights, enabling dynamic adjustment of cleaning cycles and support angles. Therefore, this method, by integrating multi-source real-time monitoring and multi-dimensional data analysis, dynamically assesses the ecological and environmental impact of photovoltaic power plants, improving the accuracy and comprehensiveness of the assessment, and providing a foundation for subsequent ecological restoration, equipment operation and maintenance, and desertification control projects of photovoltaic power plants.

[0066] To achieve the above embodiments, this application also proposes a dynamic assessment system for the ecological and environmental impact of photovoltaic power plants. Figure 4 This is a schematic diagram of the structure of a dynamic assessment system for the ecological and environmental impact of a photovoltaic power station, as proposed in an embodiment of this application. Figure 4 As shown, the system includes:

[0067] The monitoring module 100 is used to construct a multi-element real-time monitoring system covering photovoltaic power plants in different time periods and different areas. Based on the multi-element real-time monitoring system, it continuously collects various ecological and environmental data inside and outside the photovoltaic power plant. Among them, various environmental data include micro-region ecological data, and micro-regions include the areas corresponding to the rainwater collection lines in the photovoltaic modules.

[0068] The transmission module 200 is used to transmit various collected ecological and environmental data to the backend for data processing in real time and to build a multi-element environmental characteristic database.

[0069] Analysis module 300 is used to analyze various ecological and environmental data monitored over a long period of time in a multi-element environmental characteristic database, and to determine the evolution patterns of various environmental parameters within the photovoltaic power station, the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts.

[0070] The decision module 400 is used to determine the weights of the Analytic Hierarchy Process (AHP) based on various ecological impact weights, and to construct various ecological evolution prediction models and operation and maintenance decision prediction models for photovoltaic power plants based on the AHP weights. The prediction models are then used to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants.

[0071] It should be noted that the explanation of the aforementioned embodiment of the dynamic assessment method for the impact of photovoltaic power plants on the ecological environment also applies to the system of this embodiment, and will not be repeated here.

[0072] In summary, the dynamic assessment system for the ecological and environmental impact of photovoltaic power plants in this application embodiment, by integrating multi-source real-time monitoring and multi-dimensional data analysis, dynamically assesses the impact of photovoltaic power plants on the ecological environment, improves the accuracy and comprehensiveness of the assessment, and provides a basis for subsequent ecological restoration, equipment operation and maintenance, and desertification control projects of photovoltaic power plants.

[0073] To implement the above embodiments, this application also proposes an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute the dynamic assessment method for the ecological and environmental impact of a photovoltaic power station as described in any of the first aspects above.

[0074] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the dynamic assessment method for the ecological and environmental impact of a photovoltaic power station as described in any one of the first aspects of the embodiments above.

[0075] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0076] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0077] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0078] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0079] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0080] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0081] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0082] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A dynamic assessment method for the ecological and environmental impact of photovoltaic power plants, characterized in that, Includes the following steps: A multi-element real-time monitoring system covering photovoltaic power plants at different times and in different regions is constructed. Based on the multi-element real-time monitoring system, various ecological and environmental data inside and outside the photovoltaic power plant are continuously collected. Among them, the various environmental data include micro-region ecological data, and the micro-region includes the area corresponding to the rain collection line in the photovoltaic module. The collected ecological and environmental data are transmitted to the backend in real time for data processing to construct a multi-element environmental characteristic database. The analysis of various long-term monitored ecological and environmental data in the multi-element environmental characteristic database determines the evolution patterns of various environmental parameters within the photovoltaic power station, the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts. Based on the various ecological impact weights, the weights of the Analytic Hierarchy Process (AHP) are determined, and based on the AHP weights, various ecological evolution prediction models and operation and maintenance decision prediction models for photovoltaic power plants are constructed. The prediction models are then used to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants.

2. The method according to claim 1, characterized in that, The collection of various ecological and environmental data both inside and outside the photovoltaic power station includes: The plant physiological parameters of vegetation communities in different areas inside and outside the photovoltaic power station are monitored, and key test parameters of the vegetation communities are obtained through testing. The different areas include the areas corresponding to the rainwater harvesting line. Determine the evolution patterns of various environmental parameters within the photovoltaic power station and the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, including: Based on the plant physiological parameters and the key test parameters, the variation patterns of plant stress resistance in different regions and the variation patterns of the impact of photovoltaic power stations on plant growth in the area were determined.

3. The method according to claim 2, characterized in that, The various ecological evolution prediction models include a plant growth evolution prediction model. The method of using these prediction models to determine the operation and maintenance strategies and ecological restoration plans for photovoltaic power plants includes: Using the plant growth and evolution prediction model, plant screening matrices suitable for different areas of photovoltaic power plants were determined. The plant selection matrix is ​​used to select suitable plants for different areas of the photovoltaic power station, and the photovoltaic system layout is optimized based on the suitable plants for different areas.

4. The method according to claim 1, characterized in that, The collection of various ecological and environmental data both inside and outside the photovoltaic power station includes: Soil samples were collected from different areas inside the photovoltaic power station and from external control points. The microbial parameters of the soil samples were analyzed by high-throughput sequencing, and the soil composition parameters of the soil samples were determined. Determine the evolution patterns of various environmental parameters within the photovoltaic power station and the changing patterns of the photovoltaic power station's impact on various ecological and environmental factors, including: Based on the microbial parameters and the soil component parameters, a regression model for the relationship between the microbial α diversity index and soil component content was determined. Based on the regression model, the influence of photovoltaic equipment shading on rhizosphere microbiota and the influence of photovoltaic power stations on soil composition parameters were determined.

5. The method according to claim 4, characterized in that, The various ecological evolution prediction models include microbial community and soil environment evolution prediction models. The use of these prediction models to determine the operation and maintenance strategies and ecological restoration plans for photovoltaic power plants includes: Using the aforementioned microbial community and soil environment evolution prediction model, differentiated fertilization schemes and ecological restoration schemes were determined for different areas within the photovoltaic power station site.

6. The method according to claim 1, characterized in that, The collection of various ecological and environmental data both inside and outside the photovoltaic power station includes: A wind and sand particle flux parameter was collected in different areas inside and outside the photovoltaic power station using a wind and sand flow array system. Determine the evolution patterns of various environmental parameters within the photovoltaic power station, including: Momentum analysis was performed on the flux parameters of the sand particles to calculate the probability distribution of the impact height and position of the sand particles. A wind and sand convergence heat map is generated based on the probability distribution; The method of using predictive models to determine the operation and maintenance strategy and ecological restoration plan for photovoltaic power plants includes: Based on the aforementioned wind and sand convergence heat map, the sand barrier deployment strategy is adjusted. Based on the aforementioned wind and sand heat map, a wind and sand operation and maintenance prediction model is constructed. The cleaning strategy for photovoltaic modules and the arrangement strategy for photovoltaic module supports are determined through the wind and sand operation and maintenance prediction model.

7. The method according to claim 1, characterized in that, The collection of various ecological and environmental data both inside and outside the photovoltaic power station includes: Collect various meteorological element data within the photovoltaic power station, and calculate various flux parameters based on the aforementioned meteorological element data; Determine the changing patterns of the impact of the photovoltaic power station on various ecological and environmental factors, including: Based on the aforementioned meteorological data and flux parameters, the influence of photovoltaic power plants on meteorological parameters in different areas within the site is determined.

8. A dynamic assessment system for the ecological and environmental impact of photovoltaic power plants, characterized in that, Includes the following modules: The monitoring module is used to construct a multi-element real-time monitoring system covering photovoltaic power plants in different time periods and different areas. Based on the multi-element real-time monitoring system, it continuously collects various ecological and environmental data inside and outside the photovoltaic power plant. Among them, the various environmental data include micro-region ecological data, and the micro-region includes the area corresponding to the rainwater collection line in the photovoltaic module. The transmission module is used to transmit the collected various ecological and environmental data to the backend for data processing in real time and to construct a multi-element environmental feature database. The analysis module is used to analyze various ecological and environmental data monitored over a long period of time in the multi-element environmental characteristic database, and to determine the evolution patterns of various environmental parameters within the photovoltaic power station, the change patterns of the photovoltaic power station's impact on various ecological and environmental factors, and the weights of various ecological impacts. The decision-making module is used to determine the weights of the Analytic Hierarchy Process (AHP) based on the various ecological impact weights, and to construct various ecological evolution prediction models and operation and maintenance decision prediction models for photovoltaic power plants based on the AHP weights. The prediction models are then used to determine the operation and maintenance strategies and ecological restoration schemes for photovoltaic power plants.

9. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the dynamic assessment method for the ecological and environmental impact of the photovoltaic power plant as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the dynamic assessment method for the ecological and environmental impact of photovoltaic power plants as described in any one of claims 1-7.

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