Wind energy system optimization method and device based on ecological environment collaborative design

Abstract

The invention provides a wind energy system optimization method and device based on ecological environment collaborative design, and relates to the technical field of ecological environment optimization, and the method comprises the steps: obtaining ecological data of different geographical environment regions; establishing an ecological influence evaluation model based on the ecological data; evaluating the ecological environment of a target ecological region by using the ecological influence evaluation model to obtain an ecological environment evaluation result; according to the ecological environment assessment result and the power generation system and fan operation state data of the target ecological region, establishing a power generation system and fan operation state optimization adjustment model of the target ecological region; optimizing the target ecological region power generation system and fan operation state optimization and adjustment model to obtain an optimized optimization and adjustment model; and optimizing and adjusting the operation states of the power generation system and the fan by using the optimized optimization and adjustment model. Balanced development of energy production and ecological protection can be achieved.

Description

Background Art

[0002] As a clean and renewable energy source, wind energy has the advantages of low environmental pollution and wide resource distribution, and is an important direction for future energy development. However, the construction and operation of large-scale wind energy systems will have an impact on the ecological environment, such as destroying bird habitats, causing noise pollution, and occupying land resources.

[0003] Currently, the existing solutions mainly include optimizing the design of wind energy systems, such as the layout of wind turbines, the optimization design of turbine foundations, and the road path planning, as well as maintaining the stability of the original surface and strengthening the construction of local vegetation in plateau and gobi areas, reducing surface disturbance, fixing mobile sand dunes, and controlling sand dust in plateau desert areas to reduce the disturbance of wind energy systems to the ecological environment. However, there are some problems with the existing solutions. First, the optimization design methods are mainly based on the engineering perspective and lack a comprehensive consideration of ecological environment factors, so they cannot minimize the disturbance to the ecological environment to the greatest extent. Second, the collaborative design methods mainly focus on specific regions, such as plateau gobi and plateau desert, and lack targeted design methods for other regions such as mountains and forests. Third, the existing control strategies mainly focus on improving the operation efficiency and rarely consider ecological environment protection, which may lead to secondary pollution. Summary of the Invention

[0004] To overcome the problems existing in the related technologies, the present invention provides an optimization method and device for a wind energy system based on collaborative design of the ecological environment.

[0005] According to the first aspect of the embodiments of the present invention, there is provided an optimization method for a wind energy system based on collaborative design of the ecological environment, including: Obtaining ecological data of different geographical environment regions; Establishing an ecological impact assessment model based on the ecological data; Evaluating the ecological environment of the target ecological region by using the ecological impact assessment model to obtain an ecological environment assessment result; Establishing an optimization adjustment model for the power generation system and the operation state of the fan in the target ecological region according to the ecological environment assessment result and the power generation system and the fan operation state data in the target ecological region; Optimizing the optimization adjustment model for the power generation system and the operation state of the fan in the target ecological region to obtain an optimized optimization adjustment model; Optimizing and adjusting the power generation system and the operation state of the fan by using the optimized optimization adjustment model.

[0006] In some exemplary embodiments of the present invention, based on the foregoing solution, the different geographical environment regions include plains, mountains, coasts, plateaus, and forests; The ecological data includes air quality fluctuation data, soil quality change data, vegetation coverage change data, and wildlife activity data.

[0007] In some exemplary embodiments of the present invention, based on the foregoing solution, the ecological impact assessment model includes: A first branch model, a second branch model, a third branch model, a fourth branch model, a weight fusion layer, a fully connected layer, and an output layer; Among them, the first branch model, the second branch model, the third branch model, and the fourth branch model have the same structure, and each branch model includes a plurality of sequentially arranged residual blocks, and each residual block includes a first 1×1 convolutional layer, a 3×3 convolutional layer, and a second 1×1 convolutional layer.

[0008] In some exemplary embodiments of the present invention, based on the foregoing solution, the optimization adjustment model of the power generation system and the fan operation state in the target ecological area includes an objective function, and the objective function includes: Among them, Represents maximizing the power generation efficiency, Represents the efficiency of the power generation system, Represents minimizing the ecological environment impact, Represents the impact on the ecological environment, Represents the decision variable.

[0009] In some exemplary embodiments of the present invention, based on the foregoing solution, the optimization adjustment model of the power generation system and the fan operation state in the target ecological area further includes constraint conditions, and the constraint conditions include: Ecological constraint: Technical constraint: Economic constraint: Power generation system stability constraint: ; Among them, Is the ecological environment impact calculated according to the decision variable , Is the acceptable threshold of the ecological environment impact, And Are respectively the minimum power generation and the maximum power generation of the power generation system, And Are respectively the minimum technical limit and the maximum technical limit of the power generation, Is the minimum wind speed requirement of the fan, Is the minimum wind speed threshold of the fan, And Are respectively the operating cost and the maintenance cost, Is the budget limit, is the supply stability index of the power generation system, is the threshold value of supply stability.

[0010] In some exemplary embodiments of the present invention, based on the foregoing solution, the optimization adjustment model of the power generation system and the operating state of the wind turbine in the target ecological area is optimized, and the optimized optimization adjustment model obtained includes: The genetic algorithm is used to optimize the optimization adjustment model of the power generation system and the operating state of the wind turbine in the target ecological area, and the optimized optimization adjustment model is obtained.

[0011] In some exemplary embodiments of the present invention, based on the foregoing solution, after the operating states of the power generation system and the wind turbine are optimized and adjusted by using the optimized optimization adjustment model, the wind energy system optimization method based on collaborative design of the ecological environment further includes: The operation state data of the power generation system and the wind turbine obtained in real time are fed back to the optimized optimization adjustment model to iteratively update the optimized optimization adjustment model.

[0012] According to a second aspect of the embodiments of the present invention, there is provided a device, including: A data acquisition module, configured to acquire ecological data of different geographical environment regions; An evaluation model establishment module, configured to establish an ecological impact evaluation model based on the ecological data; An evaluation module, configured to evaluate the ecological environment of the target ecological area by using the ecological impact evaluation model to obtain an ecological environment evaluation result; An optimization adjustment model establishment module, configured to establish an optimization adjustment model of the power generation system and the operating state of the wind turbine in the target ecological area according to the ecological environment evaluation result and the operating state data of the power generation system and the wind turbine in the target ecological area; A model optimization module, configured to optimize the optimization adjustment model of the power generation system and the operating state of the wind turbine in the target ecological area to obtain an optimized optimization adjustment model; An optimization implementation module, configured to optimize and adjust the operating states of the power generation system and the wind turbine by using the optimized optimization adjustment model.

[0013] According to a third aspect of the embodiments of the present invention, there is provided an electronic device, including: a processor; and a memory, where a computer-readable instruction is stored on the memory, and when the computer-readable instruction is executed by the processor, the wind energy system optimization method based on collaborative design of the ecological environment in the first aspect is implemented.

[0014] According to a fourth aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the wind energy system optimization method based on collaborative design of the ecological environment in the first aspect is implemented.

[0015] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: In the embodiments of the present invention, the degree of impact of the wind power generation system on the ecological environment of the target ecological area is fully considered. Not only can it ensure that while obtaining electricity by using wind energy, the damage to the ecological environment is minimized to achieve a balanced development of energy production and ecological protection, but it also helps to efficiently utilize resources such as land. That is, by fully considering the ecological environment impact, the most suitable location can be selected to build wind energy facilities without damaging the ecological function, improving the utilization efficiency of land resources and avoiding unnecessary resource waste.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings herein are incorporated into the specification and constitute a part of the present invention, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0018] Figure 1 A schematic diagram of the system architecture of an exemplary application environment of a wind energy system optimization method and device based on ecological environment collaborative design to which the embodiments of the present invention can be applied is shown; Figure 2 A schematic flow diagram of a wind energy system optimization method based on ecological environment collaborative design according to some embodiments of the present invention is schematically shown; Figure 3 A schematic structural diagram of an ecological impact assessment model according to some embodiments of the present invention is schematically shown; Figure 4 A schematic diagram of a wind energy system optimization device based on ecological environment collaborative design according to some embodiments of the present invention is schematically shown; Figure 5 A schematic structural diagram of a computer system of an electronic device according to some embodiments of the present invention is schematically shown; Figure 6 A schematic diagram of a computer-readable storage medium according to some embodiments of the present invention is schematically shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0020] The terms used in this invention are for the purpose of describing particular embodiments only and are not intended to limit the invention. The singular forms "a", "the", and "said" used in this invention and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0021] It should be understood that although the terms first, second, third, etc. may be used in this invention to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to a determination".

[0022] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a wind energy system optimization method and device based on collaborative design of the ecological environment to which embodiments of this invention can be applied is shown.

[0023] As Figure 1 shown, the system architecture 100 may include one or more of terminal devices such as a desktop computer 101, a portable computer 102, a smart phone 103, etc., a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the terminal device and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc. The terminal device may be various electronic devices with data processing functions, and a display screen is provided on the electronic device for presenting three-dimensional spatial information of target structural feature points or individual independent pipelines to the user, including but not limited to the above-mentioned desktop computer, portable computer, smart phone, etc. It should be understood that Figure 1 the numbers of terminal devices, networks, and servers in

[0024] The method for optimizing a wind energy system based on collaborative design of the ecological environment provided by the embodiments of the present invention can generally be executed by a terminal device. Correspondingly, the device for optimizing a wind energy system based on collaborative design of the ecological environment is generally set in the terminal device. However, those skilled in the art can easily understand that the method for optimizing a wind energy system based on collaborative design of the ecological environment provided by the embodiments of the present invention can also be executed by the server 105. Correspondingly, the device for optimizing a wind energy system based on collaborative design of the ecological environment can also be set in the server 105. No special limitation is made in this exemplary embodiment.

[0025] In addition, it should be understood that the method for optimizing a wind energy system based on collaborative design of the ecological environment according to the embodiments of the present invention can be configured as a software module. In some implementation scenarios, the optimization solution of the wind energy system based on collaborative design of the present invention can be deployed independently to optimize the power generation systems and the operating states of the wind turbines in different geographical environment regions. In other implementation scenarios, the optimization solution of the wind energy system based on collaborative design of the present invention can be deployed in other software as a functional module of the software. For example, it can be deployed in the analysis software of the power generation system and the operating state of the wind turbine. The present invention does not make any special restrictions on the application mode of the method for optimizing a wind energy system based on collaborative design of the ecological environment.

[0026] Next, the embodiments of the present invention will be described in detail.

[0027] As Figure 2 shown, Figure 2 FIG. is a flowchart of a method for optimizing a wind energy system based on collaborative design of the ecological environment according to an exemplary embodiment of the present invention, including the following steps: S210: Obtain ecological data of different geographical environment regions; S220: Establish an ecological impact assessment model based on the ecological data; S230: Use the ecological impact assessment model to evaluate the ecological environment of the target ecological area to obtain an ecological environment assessment result; S240: Establish an optimization adjustment model for the power generation system and the operating state of the wind turbine in the target ecological area according to the ecological environment assessment result and the data of the power generation system and the operating state of the wind turbine in the target ecological area; S250: Optimize the optimization adjustment model for the power generation system and the operating state of the wind turbine in the target ecological area to obtain an optimized optimization adjustment model; S260: Use the optimized optimization adjustment model to optimize and adjust the power generation system and the operating state of the wind turbine.

[0028] In S210, ecological data of different geographical environment regions is obtained.

[0029] Here, different geographical environment regions include but are not limited to plains, mountains, coasts, plateaus, and forests. On this basis, by deploying advanced ecological monitoring equipment, such as high-precision bird activity monitors, professional noise decibel meters, multi-functional soil composition analyzers, air quality monitors, vegetation coverage monitors, etc., ecological data can be comprehensively collected from multiple dimensions. At the same time, satellite remote sensing technology is used to obtain macroscopic data such as large-area topographical features and vegetation distribution, and combined with sensors installed on-site to obtain real-time microscopic data.

[0030] By obtaining ecological data of different geographical environment regions, a deeper and more comprehensive understanding of the ecological status of the target ecological area can be achieved, providing a reliable basis for subsequent evaluation and optimization. This helps to promptly discover potential ecological problems, such as wildlife habitat destruction, soil erosion, vegetation degradation, etc., and take targeted protection measures.

[0031] Of course, in some embodiments, the ecological data can also be preprocessed for subsequent data use. For example, data cleaning, standardization processing, data dimensionality reduction, etc. are not specifically limited in the present invention.

[0032] Post-processing can also be performed on the data after preprocessing. For example, the preprocessed data is integrated and classified, that is, data of the same type is integrated into a data set, and then the data in each data set is transformed and calculated. For example, data such as PM2.5, PM10, sulfur dioxide, nitrogen oxides, etc. at different monitoring points in a target area are integrated into an air quality data set, and the average change rate, standard deviation, etc. of PM2.5 concentration at different times are compared in this data set to reflect the stability and change trend of air quality.

[0033] In some embodiments, the ecological data also includes soil quality change data. The soil data before and after the construction of the wind energy system can be compared, that is, the change of soil monitoring data over time, and the change amounts of soil fertility indicators (such as organic matter content, nitrogen, phosphorus, and potassium content, etc.), acidity and alkalinity, heavy metal content, etc. are calculated to evaluate the impact of the wind energy system on soil quality.

[0034] In other embodiments, the ecological data also includes vegetation coverage change data. Satellite remote sensing images or field survey data can be used, and indicators such as vegetation indices (such as the normalized difference vegetation index NDVI) are used to quantitatively represent vegetation coverage, so as to calculate the change of vegetation coverage in different periods.

[0035] In addition, the ecological data can also include wildlife activity data, including information such as the species, quantity, and activity range of wild animals. By comparing the activity of wild animals before and after the construction of the wind energy system, the impact on wild animals is evaluated. For example, the occupancy rate of wildlife habitats and the degree of interference with migration routes are calculated.

[0036] S220: Establish an ecological impact assessment model based on the ecological data; Due to the abundance and large quantity of ecological data, it is time-consuming and laborious to rely on manual evaluation. On this basis, the present invention establishes an ecological impact assessment model.

[0037] In some embodiments, the ecological impact assessment model can be generated using existing network models, such as a convolutional neural network model or a recurrent neural network model, as the basic model. However, considering the richness of ecological data, in some embodiments of the present invention, referring to Figure 3 as shown, the ecological impact assessment model includes: a first branch model, a second branch model, a third branch model, a fourth branch model, a weight fusion layer, a fully connected layer, and an output layer; Here, each branch model is used to input a type of data, extract features from the corresponding data it receives, and then input it into the weight fusion layer to allocate corresponding weights and fuse them. The fully connected layer is used to perform regression on the fused features, and finally the output layer outputs the evaluation result.

[0038] On this basis, the first branch model, the second branch model, the third branch model, and the fourth branch model of the present invention have the same structure, and each branch model includes a plurality of sequentially arranged residual blocks, and each residual block includes a first 1×1 convolutional layer, a 3×3 convolutional layer, and a second 1×1 convolutional layer.

[0039] The present invention does not limit the specific number of residual blocks. It should be noted that the input of each residual block and the output result of its second 1×1 convolutional layer are fused to form the output result of the residual block.

[0040] In addition, in the weight fusion layer, the weights of each data in the weight fusion layer can be set first, and the weights can be determined by the analytic hierarchy process (AHP) or the expert scoring method. The experts can be an expert group composed of ecologists, environmental engineers, planning experts, etc.

[0041] For each type of data, determine the quantification method and evaluation criteria. For example, for the change in the types and quantities of wild animals, a benchmark value can be set, and the quantitative score can be determined according to the actual change situation.

[0042] Standardization methods such as range standardization and Z-score standardization can also be used to standardize the quantified indicators so that they can be compared and comprehensively evaluated on the same scale.

[0043] The calculation formula of the weight fusion layer is: Where, is the output of the weight fusion layer, is the weight of the th branch model, is the th feature output of the branch model, N is the total number of branch models.

[0044] Due to the existence of this ecological impact assessment model, during the project planning and implementation phases, ecological factors can be fully considered to evaluate the degree of ecological environmental impact of the wind power generation system on the target ecological area, thereby enabling the formulation of a more scientific and reasonable development plan to minimize the damage to the ecological environment.

[0045] In S230, the ecological environment of the target ecological area is evaluated using the ecological impact assessment model to obtain an ecological environment assessment result.

[0046] The ecological assessment result can be represented in numerical form. For example, a comprehensive assessment index is calculated using the ecological impact assessment model, with a value range between 0 and 100. The higher the value, the greater the degree of ecological environment impact. It can also be represented in a hierarchical form. For example, the ecological impact degree is divided into several levels such as low impact, medium impact, and high impact. Each level corresponds to a certain assessment numerical range, and the degree of ecological environment impact is determined by judging the level to which the comprehensive assessment index or single - index value belongs. It can also be represented in graphical form. For example, each ecological index is used as a different axis of a radar chart, and corresponding points or regions are plotted on the radar chart according to the assessment results. This can visually show the performance of the target ecological area in different ecological aspects and the relative relationship between various indicators. Those skilled in the art can determine according to the actual situation, and the present invention does not make specific limitations.

[0047] In S240, based on the ecological environment assessment result and the power generation system and fan operation status data of the target ecological area, an optimization adjustment model for the power generation system and fan operation status of the target ecological area is established.

[0048] According to the ecological environment assessment result, the key factors and sensitive areas affected by the ecological environment can be determined, and thus this area can be determined as the target ecological area. In addition, the power generation system and fan operation status data of the target ecological area can be the output power of the power generation system in the target ecological area, equipment operation efficiency, maintenance records, etc., as well as the rotation speed of the fan, wind direction tracking situation, operation time, etc. On this basis, the established optimization adjustment model for the power generation system and fan operation status of the target ecological area can adapt to the target area.

[0049] Of course, before establishing the power generation system and the optimization and adjustment model of the operating state of the wind turbines in the target ecological area, the target ecological area can also be optimized and designed. For example, in the plateau gobi area, vegetation restoration and soil improvement technologies can be adopted to maintain the stability of the original surface and strengthen the construction of local vegetation; in the plateau desert area, technologies for fixing mobile sand dunes and controlling sand dust can be adopted to reduce surface disturbance and fix sand dunes.

[0050] In some embodiments of the present invention, the optimization and adjustment of the power generation system and the operating state of the wind turbines in the target ecological area are inseparable from the goal of maximizing power generation efficiency and minimizing the impact on the ecological environment. Therefore, the objective function of the present invention includes: Among them, represents maximizing power generation efficiency, represents the efficiency of the power generation system, represents minimizing the impact on the ecological environment, represents the impact on the ecological environment, represents the decision variable.

[0051] The constraint conditions include: Ecological constraint: Technical constraint: Economic constraint: Power generation system stability constraint: ; Among them, is the ecological environment impact calculated according to the decision variable , is the acceptable threshold of the ecological environment impact, and are the minimum power generation and the maximum power generation of the power generation system respectively, and are the minimum technical limit and the maximum technical limit of the power generation respectively, is the minimum wind speed requirement of the wind turbine, is the minimum wind speed threshold of the wind turbine, and are the operating cost and the maintenance cost respectively, is the budget limit, is the supply stability index of the power generation system, is the threshold of the supply stability.

[0052] In some embodiments, the decision variable includes industrial emissions and resource usage, The calculation process of = ax + bx + c Among them, a 、 b and c respectively represent parameters estimated from historical data, a is the coefficient of industrial emissions, b is the coefficient of resource usage.

[0053] The minimum technical limit refers to the minimum power generation amount at which the power generation equipment can operate stably technically, and the maximum technical limit refers to the maximum power generation amount at which the power generation equipment can operate safely technically. The minimum power generation is obtained from equipment characteristics, technical specifications, and operation experience, and the maximum power generation amount is usually limited by equipment capacity and design parameters. The acceptable threshold of ecological environment impact refers to the maximum impact level that the ecosystem can withstand without causing irreversible damage or loss of function under specific environmental and socio-economic conditions. In the embodiments of the present invention, the acceptable threshold of ecological environment impact includes the concentration of pollutants in the air and the concentration of pollutants in the water in the target ecological area, which can be determined according to empirical values.

[0054] Due to the existence of this optimization adjustment model, it is possible to perform personalized optimization adjustment on the power generation system and the operating state of the fan according to the specific situation of the target ecological area. For example, near wildlife habitats, the operating time and speed of the fan can be adjusted to reduce interference with wildlife; in ecologically fragile areas, soil protection and vegetation restoration measures can be strengthened to reduce the negative impact of the project on the ecological environment.

[0055] In S250, the optimization adjustment model of the power generation system and the operating state of the fan in the target ecological area is optimized to obtain an optimized optimization adjustment model.

[0056] The optimized optimization adjustment model can combine the data of the power generation system and the operating state of the fan to achieve intelligent optimization of the power generation system. By real-time monitoring and analyzing factors such as environmental conditions and fan performance, the operating parameters of the fan are automatically adjusted to improve power generation efficiency. For example, when the wind speed is large, the fan speed is increased, and when the wind speed is small, the fan speed is decreased to reduce energy loss.

[0057] The present invention does not limit the manner capable of optimizing the optimization adjustment model of the power generation system and the operating state of the fan in the target ecological area. For example, in some embodiments, a genetic algorithm or a simulated annealing algorithm can be used to optimize the optimization adjustment model of the power generation system and the operating state of the fan in the target ecological area.

[0058] The process of using a genetic algorithm to optimize the optimization adjustment model of the power generation system and the operating state of the fan in the target ecological area includes: Initializing the population: randomly generating a population containing multiple candidate solutions; Evaluate the population: Calculate the objective function value for each candidate solution, i.e., power generation efficiency, environmental impact, and stability index; Selection: Select candidate solutions with higher fitness according to the objective function values to form the next generation population; Crossover: Perform crossover operations on the selected candidate solutions to generate new candidate solutions; Mutation: Perform mutation operations on the newly generated candidate solutions to increase the diversity of the population; Iteration: Repeat the selection, crossover, and mutation steps until the termination condition is met; Output the result: Output the optimal solution, i.e., the best operating state of the power generation system and the wind turbine.

[0059] Here, the termination condition is reaching the maximum number of iterations or population convergence.

[0060] Fitness function is: where and are respectively the weights of and and are respectively to maximize power generation efficiency and minimize ecological environment impact.

[0061] The optimized optimization adjustment model can combine the operation state data of the power generation system and the wind turbine. By real-time monitoring and analyzing factors such as environmental conditions and wind turbine performance, it can generate optimization instructions for the operation parameters of the wind turbine. These instructions are sent to the power generation system and the wind turbine to automatically adjust the operation parameters of the power generation system and the wind turbine, improving power generation efficiency. For example, when the wind speed is large, reduce the wind turbine speed, and when the wind speed is small, increase the wind turbine speed to reduce energy loss.

[0062] In S260, use the optimized optimization adjustment model to optimize and adjust the operation state of the power generation system and the wind turbine.

[0063] The optimization and adjustment of the operation state of the power generation system and the wind turbine, on the one hand, helps to improve the reliability and stability of the equipment. By reasonably arranging the maintenance plan, timely discovering and repairing equipment failures, the equipment failure rate can be reduced, the service life of the equipment can be extended, and the overall reliability of the power generation system can be improved. On the other hand, it can improve the capture efficiency of wind energy and increase energy output.

[0064] In some exemplary embodiments of the present invention, based on the foregoing solution, after using the optimized optimization adjustment model to optimize and adjust the operation state of the power generation system and the wind turbine, the wind energy system optimization method based on collaborative design of ecological environment further includes: Feed the real-time obtained operation status data of the power generation system and the wind turbines back to the optimized optimization and adjustment model to iteratively update the optimized optimization and adjustment model.

[0065] In this way, the optimized optimization and adjustment model can continuously adapt to the dynamically changing actual situation. Whether it is the change in wind speed, the change in the activity area of wild animals, or the fluctuation of soil quality, etc., it can quickly respond, adjust the operation status of the power generation system and the wind turbines, maintain the optimization effect of the operation status of the power generation system and the wind turbines, ensure operation in the best state at all times, thereby continuously improving the power generation efficiency of the wind energy system, and at the same time minimizing the negative impact on the ecological environment.

[0066] According to the second aspect of the embodiments of the present invention, there is also provided an optimization device 400 for a wind energy system based on collaborative design with the ecological environment. Refer to Figure 4 as shown, including: A data acquisition module 410, configured to acquire ecological data of different geographical environment regions; An evaluation model establishment module 420, configured to establish an ecological impact evaluation model based on the ecological data; An evaluation module 430, configured to evaluate the ecological environment of the target ecological area by using the ecological impact evaluation model to obtain an ecological environment evaluation result; An optimization and adjustment model establishment module 440, configured to establish an optimization and adjustment model for the operation status of the power generation system and the wind turbines in the target ecological area according to the ecological environment evaluation result and the operation status data of the power generation system and the wind turbines in the target ecological area; A model optimization module 450, configured to optimize the optimization and adjustment model for the operation status of the power generation system and the wind turbines in the target ecological area to obtain an optimized optimization and adjustment model; An optimization implementation module 460, configured to optimize and adjust the operation status of the power generation system and the wind turbines by using the optimized optimization and adjustment model.

[0067] In an exemplary embodiment of the present invention, based on the foregoing solution, the optimization device 400 for a wind energy system based on collaborative design with the ecological environment may further include a feedback module, configured to optimize and adjust the operation status of the power generation system and the wind turbines by using the optimized optimization and adjustment model.

[0068] It should be noted that although several modules and sub-modules of the optimization device for a wind energy system based on collaborative design with the ecological environment are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present invention, the features and functions of two or more of the above-described modules or sub-modules can be embodied in one module or unit. Conversely, the features and functions of one module or sub-module described above can be further divided and embodied by multiple modules or sub-modules.

[0069] In addition, in an exemplary embodiment of the present invention, an electronic device capable of implementing the above-mentioned optimization method for a wind energy system based on collaborative design of the ecological environment is also provided.

[0070] Those skilled in the art of the present technology can understand that various aspects of the present invention can be implemented as a system, a method, or a program product. Therefore, various aspects of the present invention can be specifically implemented in the following forms, namely: a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuit", "module", or "system" here.

[0071] The following refers to Figure 5 to describe the electronic device 500 according to such an embodiment of the present invention. Figure 5 The illustrated electronic device 500 is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present invention.

[0072] As Figure 5 shown, the electronic device 500 is presented in the form of a general-purpose computing device. The components of the electronic device 500 may include, but are not limited to: the at least one processing unit 510 mentioned above, the at least one storage unit 520 mentioned above, a bus 530 connecting different system components (including the storage unit 520 and the processing unit 510), and a display unit 540.

[0073] Among them, the storage unit stores program codes, and the program codes can be executed by the processing unit 510, so that the processing unit 510 executes the steps according to various exemplary embodiments of the present invention described in the above-mentioned "exemplary method" part of the present invention. For example, the processing unit 510 can execute S210 as shown in Figure 2 to obtain ecological data of different geographical environment regions; S220, establish an ecological impact assessment model based on the ecological data; S230, use the ecological impact assessment model to evaluate the ecological environment of the target ecological region to obtain an ecological environment assessment result; S240, establish an optimization adjustment model for the power generation system and the fan operation state of the target ecological region according to the ecological environment assessment result and the power generation system and fan operation state data of the target ecological region; S250, optimize the optimization adjustment model for the power generation system and the fan operation state of the target ecological region to obtain an optimized optimization adjustment model; S260, use the optimized optimization adjustment model to optimize and adjust the power generation system and the fan operation state.

[0074] The storage unit 520 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 521 and / or a cache storage unit 522, and may further include a read-only storage unit (ROM) 523.

[0075] The storage unit 520 may also include a program / utility 524 having a set (at least one) of program modules 525. Such program modules 525 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0076] The bus 530 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus structures.

[0077] The electronic device 500 may also communicate with one or more external devices 570 (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 500, and / or may communicate with any device that enables the electronic device 500 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be through the input / output (I / O) interface 550. Also, the electronic device 500 may communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 560. As shown in the figure, the network adapter 560 communicates with other modules of the electronic device 500 through the bus 530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0078] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or can be implemented by the way of software combined with necessary hardware. Therefore, the technical solution according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present invention.

[0079] In an exemplary embodiment of the present invention, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above method of the present invention. In some possible embodiments, various aspects of the present invention may also be implemented in the form of a program product, which includes program code that, when the program product runs on a terminal device, causes the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present invention.

[0080] Referring Figure 6 As shown, a program product 600 for implementing the above method for optimizing a wind energy system based on collaborative design of the ecological environment according to an embodiment of the present invention is described. It may be in the form of a portable compact disc read-only memory unit (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In the present invention, the readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0081] The program product may adopt any combination of one or more readable storage media. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory unit (RAM), a read-only memory unit (ROM), an erasable programmable read-only memory unit (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory unit (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0082] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, executed as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., by using an Internet service provider to connect through the Internet).

[0083] In addition, the above-mentioned drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present invention, rather than for limiting purposes. It is easy to understand that the processes shown in the above-mentioned drawings do not indicate or limit the chronological order of these processes. Additionally, it is also easy to understand that these processes can be executed synchronously or asynchronously, for example, in multiple modules.

[0084] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present invention.

[0085] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include known common general knowledge or conventional technical means in the technical field not disclosed by the present invention. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present invention are pointed out by the claims.

[0086] It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A wind energy system optimization method based on ecological environment collaborative design, characterized in that: include: Obtain ecological data for different geographical areas; establishing an ecological impact assessment model based on the ecological data; Using the ecological impact assessment model to assess the ecological environment of the target ecological area, and obtaining an ecological environment assessment result; Establishing an optimization adjustment model for the power generation system and wind turbine operation status in the target ecological area based on the ecological environment assessment results and the power generation system and wind turbine operation status data in the target ecological area; Optimizing the optimization adjustment model of the power generation system and wind turbine operation status in the target ecological area to obtain an optimized optimization adjustment model; The optimized optimization adjustment model is used to optimize and adjust the operating status of the power generation system and the wind turbine.

2. The wind energy system optimization method based on ecological environment collaborative design according to claim 1 is characterized in that: The different geographical environment areas include plains, mountains, coastal areas, plateaus, and forests; The ecological data includes air quality fluctuation data, soil quality change data, vegetation coverage change data and wild animal activity data.

3. The wind energy system optimization method based on ecological environment collaborative design according to claim 1 is characterized in that: The ecological impact assessment model includes: The first branch model, the second branch model, the third branch model, the fourth branch model, the weight fusion layer, the fully connected layer and the output layer; Among them, the first branch model, the second branch model, the third branch model and the fourth branch model have the same structure and each of the branch models includes a plurality of residual blocks arranged in sequence, and each of the residual blocks includes a first 1×1 convolutional layer, a 3×3 convolutional layer and a second 1×1 convolutional layer.

4. The wind energy system optimization method based on ecological environment collaborative design according to claim 1 is characterized in that: The target ecological area power generation system and wind turbine operation state optimization adjustment model includes an objective function, and the objective function includes: in, represents the maximum power generation efficiency, represents the efficiency of the power generation system, Minimize the impact on the ecological environment. Indicates the impact on the ecological environment, represents the decision variable.

5. The wind energy system optimization method based on ecological environment collaborative design according to claim 4 is characterized in that: The target ecological area power generation system and wind turbine operation state optimization adjustment model also includes constraint conditions, and the constraint conditions include: Ecological constraints: Technical constraints: Economic constraints: Power generation system stability constraints: ; in, According to the decision variables Calculate the ecological and environmental impact, is the acceptable threshold of ecological and environmental impact, and are the minimum and maximum power generation of the power generation system, and are the minimum and maximum technical limits on power generation, is the minimum wind speed requirement of the fan, is the minimum wind speed threshold of the fan, and are operating cost and maintenance cost respectively. It's budget constraints. It is an indicator of the supply stability of the power generation system. is the threshold for supply stability.

6. The wind energy system optimization method based on ecological environment collaborative design according to claim 1 is characterized in that: The target ecological area power generation system and wind turbine operation state optimization adjustment model are optimized, and the optimized optimization adjustment model includes: The target ecological area power generation system and wind turbine operating state optimization adjustment model are optimized using a genetic algorithm to obtain an optimized optimization adjustment model.

7. The wind energy system optimization method based on ecological environment collaborative design according to any one of claims 1 to 6, characterized in that: After optimizing and adjusting the power generation system and the wind turbine operating state using the optimized optimization adjustment model, the wind energy system optimization method based on ecological environment collaborative design also includes: The real-time acquired operating status data of the power generation system and the wind turbine are fed back to the optimized optimization adjustment model to iteratively update the optimized optimization adjustment model.

8. A device for optimizing a wind energy system based on an ecological environment collaborative design according to any one of claims 1 to 7, characterized in that: The device comprises: Data acquisition module, used to obtain ecological data of different geographical areas; An assessment model building module, used to build an ecological impact assessment model based on the ecological data; An assessment module, used to assess the ecological environment of the target ecological area using the ecological impact assessment model to obtain an ecological environment assessment result; An optimization and adjustment model establishment module is used to establish an optimization and adjustment model for the power generation system and wind turbine operating status in the target ecological area according to the ecological environment assessment results and the power generation system and wind turbine operating status data in the target ecological area; A model optimization module is used to optimize the power generation system and wind turbine operation state optimization adjustment model of the target ecological area to obtain an optimized optimization adjustment model; The optimization implementation module is used to optimize and adjust the power generation system and the wind turbine operating state using the optimized optimization adjustment model.

9. An electronic device, characterized in that: include: processor; as well as A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by the processor, implement the wind energy system optimization method based on ecological environment collaborative design as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the wind energy system optimization method based on ecological environment collaborative design as described in any one of claims 1 to 7 is implemented.

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