Environmental evaluation and early warning system for wind power plant

Abstract

The invention relates to the technical field of wind power plant environment evaluation, and discloses an environment evaluation and early warning system for a wind power plant, which comprises a setting module used for presetting environment evaluation indexes of operation cycles including an evaluated operation cycle and an unevaluated operation cycle; the evaluation module is used for calculating an environment sub-evaluation difference value of the evaluated operation cycle; the early warning module is used for judging whether an early warning instruction is generated or not based on the environment sub-evaluation difference value and the predicted environment sub-evaluation value; the simulation module is used for generating a first management optimization strategy based on the environment sub-evaluation difference value, the predicted environment sub-evaluation value and a preset objective function if the early warning instruction is generated, and performing analogue simulation to obtain a simulated environment sub-evaluation value; the correction module is used for judging whether the first management optimization strategy is corrected or not according to the simulation environment sub-evaluation value, if yes, a second management optimization strategy is obtained, and the negative influence on the environment is reduced to the maximum extent while the resource utilization rate is improved.

Description

Technical Field

[0001] The present application relates to the technical field of wind farm environmental assessment, and in particular to an environmental assessment and early warning system for wind farms. Background Art

[0002] As an indispensable clean energy power generation facility in the power system, wind farms are increasingly important in the power supply structure and are being used more and more widely as the demand for renewable energy grows. However, the construction and operation of wind farms will inevitably have an impact on the environment in the area where the wind farms are located.

[0003] In existing technologies, environmental assessments of wind farms mostly rely on manually collecting environmental data before and after the construction of the wind farm to evaluate the impact of the wind farm on the environment. The assessment accuracy and comprehensiveness are low, and it cannot improve resource utilization while minimizing the negative impact on the environment, and cannot ensure the coordinated development of the economy and the environment. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides an environmental assessment and early warning system for wind farms. By setting environmental assessment indicators for each operating cycle, calculating the environmental sub-assessment difference of the evaluated operating cycle and the predicted environmental sub-assessment value of the unevaluated operating cycle, and combining the preset objective function to generate a first management optimization strategy, generate a simulated environmental sub-assessment value of the first management optimization strategy, and optimize the first management optimization strategy, accurately assess the degree of impact of the wind farm on the environment and optimize the management strategy, so as to improve resource utilization while minimizing the negative impact on the environment.

[0005] In some embodiments of the present application, an environmental assessment and early warning system for a wind farm is provided, comprising: A setting module, configured to divide the operation cycle into a plurality of operation cycles and pre-set the environmental assessment index for each operation cycle, wherein the operation cycle includes an assessed operation cycle and an unevaluated operation cycle; An evaluation module, configured to set environmental sub-assessment thresholds for environmental assessment indicators of each operating cycle and calculate environmental sub-assessment differences for environmental assessment indicators of each evaluated operating cycle; An early warning module is used to generate a predicted environmental sub-assessment value of the environmental assessment indicator based on the predicted associated data of the unevaluated operation cycle, and determine whether to generate an early warning instruction based on the environmental sub-assessment difference and the predicted environmental sub-assessment value; a simulation module configured to generate a first management optimization strategy based on the environmental sub-assessment difference, the predicted environmental sub-assessment value, and a preset objective function when a warning instruction is generated, and simulate the unevaluated operating cycle according to the first management optimization strategy to obtain a simulated environmental sub-assessment value; The correction module is used to determine whether to correct the first management optimization strategy according to the simulation environment sub-evaluation value, and if so, obtain the second management optimization strategy and generate corresponding optimization instructions.

[0006] In some embodiments of the present application, the environmental assessment indicators for each operation cycle are pre-set, including: Determine a number of environmental management demand indicators and a number of operational management demand indicators for the corresponding operational cycle based on the environmental management demand and operational management demand of each operational cycle; Calculate the correlation degree between each environmental management demand indicator and each operation management demand indicator in the same operation cycle, and set the operation management demand indicator with a correlation degree greater than a preset correlation degree threshold as the correlation indicator of the corresponding environmental management demand indicator; Generate a correction coefficient based on the number of related indicators of each environmental management demand indicator and the weight coefficient of the corresponding related indicators; The initial weight coefficient of the corresponding environmental management demand indicator is corrected according to the correction coefficient, and the environmental assessment indicator of the operation cycle is generated based on the corrected weight coefficient and the corresponding environmental management demand indicator.

[0007] In some embodiments of the present application, calculating the environmental sub-assessment difference of the environmental assessment indicator of each evaluated operating cycle includes: Pre-set environmental assessment thresholds for the entire operation cycle of the current wind farm; Based on the basic construction information and operation requirements of the wind farm and combined with the basic environmental information, several historical similarity assessment logs are screened out, and the historical environmental sub-assessment value interval of each operation cycle is determined based on the multiple historical similarity assessment logs; Generate the assessment ratio of the corresponding operation cycle based on the historical environment sub-assessment value interval; Divide the environmental assessment threshold according to the assessment proportion to obtain the environmental sub-assessment threshold for each operation cycle; Obtain historical monitoring data for each evaluated operation cycle, and filter out historical related data corresponding to the evaluated operation cycle based on the degree of correlation between the historical monitoring data and the environmental assessment indicators of the corresponding evaluated operation cycle; Comparing the historical correlation data with the corresponding standard data interval to obtain the historical correlation data difference, and generating the environmental sub-assessment value corresponding to the assessed operation cycle based on multiple historical correlation data differences; The environmental sub-assessment value of each evaluated operating cycle is compared with the corresponding environmental sub-assessment threshold to obtain the environmental sub-assessment difference value of the corresponding evaluated operating cycle.

[0008] In some embodiments of the present application, generating a predicted environmental sub-assessment value of an environmental assessment indicator based on the predicted associated data of an unevaluated operating cycle includes: Determining a correlation factor for each unevaluated operation cycle based on a degree of correlation between environmental assessment indicators in a number of historical similar assessment logs and historical monitoring data for each unevaluated operation cycle, the correlation factor comprising a first correlation factor and a second correlation factor; Acquire multiple historical monitoring data and historical monitoring durations of the first correlation factor in the corresponding evaluated operation cycle, and construct a historical change curve corresponding to the first correlation factor according to the historical monitoring durations; Predicting the change characteristics of the first correlation factor in the preset monitoring period of the corresponding unevaluated operation cycle based on the historical change characteristics of the historical change curve in the historical monitoring period, and determining the predicted correlation data of the first correlation factor in the unevaluated operation cycle based on the predicted change characteristics; Set data collection nodes according to the preset monitoring time and preset time interval; Collect historical monitoring data of the second correlation factor in a corresponding unevaluated operating period in each historical similarity evaluation log according to the data collection node, and construct a predicted change curve graph of the second correlation factor, wherein the predicted change curve graph includes a plurality of first predicted change curves; Obtaining similar features between different first predicted change curves, and generating similarity coefficients between the different first predicted change curves based on the similar features; Setting a credibility coefficient of the corresponding first predicted change curve according to a plurality of similarity coefficients between each first predicted change curve and other first predicted change curves, and considering the first predicted change curve with the largest credibility coefficient as the central curve; Screening out the first predicted change curve whose similarity coefficient with the central curve is greater than a preset similarity coefficient threshold, and combining it with the central curve to perform curve fusion to obtain the second predicted change curve of the second correlation factor in the corresponding unevaluated operation period; Determining predicted correlation data of the second correlation factor in the unevaluated operating cycle according to the second predicted change curve; The predicted correlation data of the first correlation factor and the second correlation factor are compared with the corresponding standard data intervals to obtain predicted correlation data differences, and a predicted environment sub-assessment value corresponding to the unevaluated operating cycle is generated according to the multiple predicted correlation data differences.

[0009] In some embodiments of the present application, determining whether to generate a warning instruction based on the environmental sub-assessment difference and the predicted environmental sub-assessment value includes: Pre-set the environmental sub-assessment difference threshold; When the environmental sub-assessment difference value of an assessed operating cycle is greater than the environmental sub-assessment difference threshold, and the predicted environmental sub-assessment values ​​are all greater than the environmental sub-assessment threshold value of the corresponding unevaluated operating cycle, a first-level warning signal is generated; When the environmental sub-assessment differences of several evaluated operating cycles are all less than the environmental sub-assessment difference threshold, and there is a predicted environmental sub-assessment value that is less than the environmental sub-assessment threshold of the corresponding unevaluated operating cycle, a secondary warning signal is generated; When there is an environmental sub-assessment difference value of an evaluated operating cycle that is greater than the environmental sub-assessment difference value threshold, and there is a predicted environmental sub-assessment value that is less than the environmental sub-assessment threshold value of the corresponding unevaluated operating cycle, a third-level warning signal is generated.

[0010] In some embodiments of the present application, generating a first management optimization strategy based on the environmental sub-assessment difference, the predicted environmental sub-assessment value, and a preset objective function includes: Building an optimization strategy reference library for an unevaluated operation cycle of the current wind farm, wherein the optimization strategy reference library includes a first optimization strategy library, a second optimization strategy library, and a third optimization strategy library; When a first-level warning signal is generated, a first coefficient to be optimized is generated according to a first value of the environmental sub-assessment difference being greater than the environmental sub-assessment difference threshold and a weight coefficient corresponding to the assessed operating cycle; Optimizing a plurality of preset management strategies for unevaluated operating cycles according to a first optimization strategy library, wherein the first optimization strategy library includes a plurality of preset first coefficients to be optimized, and each preset first coefficient to be optimized is associated with a corresponding first preset management optimization sub-strategy group; Comparing the first coefficient to be optimized with a plurality of preset first coefficients to be optimized in the first optimization strategy library, and screening out a plurality of first preset management optimization sub-strategy groups whose preset first coefficients to be optimized are greater than the first coefficient to be optimized; When a secondary warning signal is generated, a second coefficient to be optimized is generated according to a second value in which the predicted environmental sub-assessment value is less than the environmental sub-assessment value and a weight coefficient corresponding to an unevaluated operating cycle; Optimizing the preset management strategies for the plurality of unevaluated operating cycles according to a second optimization strategy library, wherein the second optimization strategy library includes a plurality of preset second coefficients to be optimized, and each preset second coefficient to be optimized is associated with a corresponding second preset management optimization sub-strategy group; Comparing the second coefficient to be optimized with a plurality of preset second coefficients to be optimized in the second optimization strategy library, and screening out a plurality of second preset management optimization sub-strategy groups whose preset second coefficients to be optimized are greater than the second coefficient to be optimized; When a third-level warning signal is generated, a third coefficient to be optimized is generated according to a first value of the environmental sub-assessment difference being greater than the environmental sub-assessment difference threshold, a second value of the predicted environmental sub-assessment value being less than the environmental sub-assessment value, and corresponding weight coefficients; Optimizing the preset management strategies for the plurality of unevaluated operating cycles according to a third optimization strategy library, wherein the third optimization strategy library includes a plurality of preset third coefficients to be optimized, and each preset third coefficient to be optimized is associated with a corresponding third preset management optimization sub-strategy group; Comparing the third coefficient to be optimized with several preset third coefficients to be optimized in the third optimization strategy library, and screening out several third preset management optimization sub-strategy groups whose preset third coefficients to be optimized are greater than the third coefficient to be optimized; The preset objective functions include a resource utilization maximization objective function and an environmental impact minimization objective function; Analyze a plurality of first preset management optimization sub-strategy groups according to a resource utilization maximization objective function and an environmental impact minimization objective function to obtain a first preferred management optimization sub-strategy group, and generate a corresponding first management optimization strategy according to the first preferred management optimization sub-strategy group; Analyze the plurality of second preset management optimization sub-strategy groups according to the resource utilization maximization objective function and the environmental impact minimization objective function to obtain a second preferred management optimization sub-strategy group, and generate a corresponding first management optimization strategy according to the second preferred management optimization sub-strategy group; According to the objective function of maximizing resource utilization and the objective function of minimizing environmental impact, several third preset management optimization sub-strategy groups are analyzed to obtain a third preferred management optimization sub-strategy group, and the corresponding first management optimization strategy is generated according to the third preferred management optimization sub-strategy group.

[0011] In some embodiments of the present application, simulating the unevaluated operating cycle according to the first management optimization strategy to obtain a simulation environment sub-evaluation value includes: Performing simulation optimization on the preset management strategy of the corresponding unevaluated operation cycle according to the first management optimization strategy, and constructing a simulation management model of the corresponding unevaluated operation cycle based on the management strategy after simulation optimization, the static scenario information of the corresponding unevaluated operation cycle, and the dynamic operation information; Acquire simulation-related data in the simulation management model of each unevaluated operation cycle according to the data acquisition node, and map it to the corresponding preset monitoring duration to obtain a simulation change curve graph, wherein the simulation change curve graph includes simulation change curves of a plurality of simulation-related data; When the simulation correlation data is the first correlation factor, obtaining a simulation change feature of a simulation change curve corresponding to the simulation correlation data, comparing the simulation change feature with the predicted change feature, and generating a compensation coefficient corresponding to the simulation correlation data according to the comparison result; When the simulation correlation data is a second correlation factor, comparing a simulation change curve corresponding to the simulation correlation data with a corresponding second predicted change curve, and generating a compensation coefficient corresponding to the simulation correlation data according to the comparison result; generating a variation coefficient of corresponding simulation associated data according to a simulation variation feature of a simulation variation curve of each simulation associated data; Comparing the simulation correlation data at each data collection node in the simulation change curve of each simulation correlation data with the corresponding standard data interval to obtain the simulation correlation data difference; A simulation environment sub-evaluation value corresponding to an unevaluated operation cycle is generated according to simulation associated data differences of a plurality of simulation associated data, corresponding variation coefficients, compensation coefficients, and weight coefficients.

[0012] In some embodiments of the present application, the calculation formula of the simulation environment sub-evaluation value is: ; Among them, H is the simulation environment sub-assessment value, h0 is the environment assessment conversion coefficient, n is the total number of simulation related data, m is the total number of data collection nodes, is the correlation data difference threshold of the i-th simulation correlation data, is the simulation associated data difference at the jth data collection node of the ith simulation associated data, bi is the variation coefficient of the ith simulation associated data, ai is the compensation coefficient of the ith simulation associated data, and qi is the weight coefficient of the ith simulation associated data.

[0013] In some embodiments of the present application, determining whether to modify the first management optimization strategy according to the simulation environment sub-evaluation value includes: Presetting a first preset environmental assessment sum value threshold, a second preset environmental assessment sum value threshold, and a third preset environmental assessment sum value threshold for the remaining unevaluated operating cycles; When a first-level warning instruction is generated, a first simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the first simulation environment evaluation value is less than the first preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the first simulation environment evaluation value is greater than the first preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated; When a second-level warning instruction is generated, a second simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the second simulation environment evaluation value is less than the second preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the second simulation environment evaluation value is greater than the second preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated; When a third-level warning instruction is generated, a third simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the third simulation environment evaluation value is less than the third preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the third simulation environment evaluation value is greater than the third preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated.

[0014] Compared with the prior art, the environmental assessment and early warning system for a wind farm in the embodiment of the present application has the following advantages: By setting environmental assessment indicators for each operating cycle, calculating the environmental sub-assessment difference of the evaluated operating cycle and the predicted environmental sub-assessment value of the unevaluated operating cycle, and combining the preset objective function to generate a first management optimization strategy, generating a simulated environmental sub-assessment value of the first management optimization strategy, and optimizing the first management optimization strategy, the degree of environmental impact of the wind farm is accurately assessed and the management strategy is optimized, so as to improve resource utilization while minimizing the negative impact on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of an environmental assessment and early warning system for a wind farm in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0017] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0018] 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 the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0019] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0020] like Figure 1 As shown, an environmental assessment and early warning system for a wind farm according to an embodiment of the present application includes: A setting module, configured to divide the operation cycle into a plurality of operation cycles and pre-set the environmental assessment index for each operation cycle, wherein the operation cycle includes an assessed operation cycle and an unevaluated operation cycle; An evaluation module, configured to set environmental sub-assessment thresholds for environmental assessment indicators of each operating cycle and calculate environmental sub-assessment differences for environmental assessment indicators of each evaluated operating cycle; An early warning module is used to generate a predicted environmental sub-assessment value of the environmental assessment indicator based on the predicted associated data of the unevaluated operation cycle, and determine whether to generate an early warning instruction based on the environmental sub-assessment difference and the predicted environmental sub-assessment value; a simulation module configured to generate a first management optimization strategy based on the environmental sub-assessment difference, the predicted environmental sub-assessment value, and a preset objective function when a warning instruction is generated, and simulate the unevaluated operating cycle according to the first management optimization strategy to obtain a simulated environmental sub-assessment value; The correction module is used to determine whether to correct the first management optimization strategy according to the simulation environment sub-evaluation value, and if so, obtain the second management optimization strategy and generate corresponding optimization instructions.

[0021] In this embodiment, the operation cycle refers to the multiple stages from planning to decommissioning of a wind farm, including the planning stage, design stage, construction stage, operation stage, and decommissioning stage. The environmental assessment indicators of the corresponding operation cycle are set according to the tasks and environmental management requirements of each operation cycle.

[0022] In this embodiment, the environmental assessment threshold of the overall operating cycle refers to the minimum environmental assessment value of all stages, that is, the minimum environmental assessment value that meets the environmental management requirements. According to the importance of each operating cycle, the environmental assessment threshold is divided into the minimum environmental sub-assessment value of the corresponding operating cycle, that is, the environmental sub-assessment threshold. If the environmental sub-assessment value of the evaluated operating cycle is less than the environmental sub-assessment threshold, it means that the environmental assessment result of the corresponding evaluated cycle does not meet the environmental management requirements.

[0023] In this embodiment, the preset objective functions include a resource utilization maximization objective function and an environmental impact minimization objective function.

[0024] In this embodiment, by performing environmental assessment on the environmental assessment indicators of multiple operating cycles of the wind farm, corresponding environmental sub-assessment values ​​and predicted environmental sub-assessment values ​​are obtained, and combined with the corresponding preset objective function, resource utilization efficiency is improved while meeting environmental management needs, and the coordinated development of the economy and the environment is promoted.

[0025] In some embodiments of the present application, the environmental assessment indicators for each operation cycle are pre-set, including: Determine a number of environmental management demand indicators and a number of operational management demand indicators for the corresponding operational cycle based on the environmental management demand and operational management demand of each operational cycle; Calculate the correlation degree between each environmental management demand indicator and each operation management demand indicator in the same operation cycle, and set the operation management demand indicator with a correlation degree greater than a preset correlation degree threshold as the correlation indicator of the corresponding environmental management demand indicator; Generate a correction coefficient based on the number of related indicators of each environmental management demand indicator and the weight coefficient of the corresponding related indicators; The initial weight coefficient of the corresponding environmental management demand indicator is corrected according to the correction coefficient, and the environmental assessment indicator of the operation cycle is generated based on the corrected weight coefficient and the corresponding environmental management demand indicator.

[0026] In this embodiment, environmental management requirements refer to environmental factors that need to be managed in each operating cycle to achieve the environmental requirements of the entire life cycle of the wind farm. Environmental management requirement indicators include multiple indicators such as ecology, noise, water resources, and soil. Operation management requirements refer to operational factors that need to be managed in each operating cycle to achieve the operation requirements of the wind farm. Related indicators refer to operation management requirements that have a significant impact on environmental management requirement indicators.

[0027] In this embodiment, by determining several environmental management demand indicators and related indicators for each operation cycle, an accurate assessment of the importance of the environmental management demand indicators is achieved, thereby obtaining the environmental assessment indicators for each operation cycle, laying the foundation for subsequent environmental assessments, improving the accuracy of environmental assessments throughout the life cycle of wind farms, and improving resource utilization efficiency while meeting environmental management needs, thereby promoting the coordinated development of the economy and the environment.

[0028] In some embodiments of the present application, calculating the environmental sub-assessment difference of the environmental assessment indicator of each evaluated operating cycle includes: Pre-set environmental assessment thresholds for the entire operation cycle of the current wind farm; Based on the basic construction information and operation requirements of the wind farm and combined with the basic environmental information, several historical similarity assessment logs are screened out, and the historical environmental sub-assessment value interval of each operation cycle is determined based on the multiple historical similarity assessment logs; Generate the assessment ratio of the corresponding operation cycle based on the historical environment sub-assessment value interval; Divide the environmental assessment threshold according to the assessment proportion to obtain the environmental sub-assessment threshold for each operation cycle; Obtain historical monitoring data for each evaluated operation cycle, and filter out historical related data corresponding to the evaluated operation cycle based on the degree of correlation between the historical monitoring data and the environmental assessment indicators of the corresponding evaluated operation cycle; Comparing the historical correlation data with the corresponding standard data interval to obtain the historical correlation data difference, and generating the environmental sub-assessment value corresponding to the assessed operation cycle based on multiple historical correlation data differences; The environmental sub-assessment value of each evaluated operating cycle is compared with the corresponding environmental sub-assessment threshold to obtain the environmental sub-assessment difference value of the corresponding evaluated operating cycle.

[0029] In this embodiment, the basic construction information includes the layout and construction of the wind farm, the number and capacity of wind turbines, the type of wind turbines, etc. The basic environmental information refers to the terrain, climate, wind energy resources, etc. of the current wind farm environment. The operation requirement information includes the grid connection standard, power quality, wind energy resource utilization rate, etc.

[0030] In this embodiment, the historical similarity evaluation log refers to the historical evaluation log of other wind farms that have a high degree of similarity with the basic construction information and operation requirement information of each operation cycle of the current wind farm, and the environmental assessment results of the above historical evaluation logs all meet the environmental management requirements.

[0031] In this embodiment, the historical environmental sub-assessment value interval is constructed based on the historical environmental sub-assessment values ​​corresponding to the historical assessment logs of several wind farms that have a high degree of similarity with the current wind farm. The assessment ratio refers to the ratio of the historical environmental sub-assessment value interval to the environmental assessment threshold interval. The current environmental assessment threshold is divided according to the assessment ratio of each operating cycle to obtain the environmental sub-assessment threshold of each operating cycle, that is, the minimum environmental sub-assessment value that meets the environmental management requirements of each operating cycle. When the environmental sub-assessment value is smaller than the environmental sub-assessment threshold, it means that the corresponding environmental management requirements are not met.

[0032] In this embodiment, when the difference between the multiple historical association data is smaller, the corresponding environment sub-assessment value is larger, and vice versa.

[0033] In this embodiment, by calculating the environmental sub-assessment difference of the environmental assessment indicators of each evaluated operating cycle and combining it with the predicted environmental sub-assessment value of the environmental assessment indicators of each unevaluated operating cycle, a comprehensive assessment of the environmental impact of the current wind farm throughout its life cycle is achieved, the accuracy of the assessment is improved, and it is determined whether to issue an early warning, thereby improving resource utilization efficiency while meeting environmental management needs.

[0034] In some embodiments of the present application, generating a predicted environmental sub-assessment value of an environmental assessment indicator based on the predicted associated data of an unevaluated operating cycle includes: Determining a correlation factor for each unevaluated operation cycle based on a degree of correlation between environmental assessment indicators in a number of historical similar assessment logs and historical monitoring data for each unevaluated operation cycle, the correlation factor comprising a first correlation factor and a second correlation factor; Acquire multiple historical monitoring data and historical monitoring durations of the first correlation factor in the corresponding evaluated operation cycle, and construct a historical change curve corresponding to the first correlation factor according to the historical monitoring durations; Predicting the change characteristics of the first correlation factor in the preset monitoring period of the corresponding unevaluated operation cycle based on the historical change characteristics of the historical change curve in the historical monitoring period, and determining the predicted correlation data of the first correlation factor in the unevaluated operation cycle based on the predicted change characteristics; Set data collection nodes according to the preset monitoring time and preset time interval; Collect historical monitoring data of the second correlation factor in a corresponding unevaluated operating period in each historical similarity evaluation log according to the data collection node, and construct a predicted change curve graph of the second correlation factor, wherein the predicted change curve graph includes a plurality of first predicted change curves; Obtaining similar features between different first predicted change curves, and generating similarity coefficients between the different first predicted change curves based on the similar features; Setting a credibility coefficient of the corresponding first predicted change curve according to a plurality of similarity coefficients between each first predicted change curve and other first predicted change curves, and considering the first predicted change curve with the largest credibility coefficient as the central curve; Screening out the first predicted change curve whose similarity coefficient with the central curve is greater than a preset similarity coefficient threshold, and combining it with the central curve to perform curve fusion to obtain the second predicted change curve of the second correlation factor in the corresponding unevaluated operation period; Determining predicted correlation data of the second correlation factor in the unevaluated operating cycle according to the second predicted change curve; The predicted correlation data of the first correlation factor and the second correlation factor are compared with the corresponding standard data intervals to obtain predicted correlation data differences, and a predicted environment sub-assessment value corresponding to the unevaluated operating cycle is generated according to the multiple predicted correlation data differences.

[0035] In this embodiment, the first correlation factor refers to the parameter monitored in the evaluated operating cycle, the second correlation factor refers to the parameter not monitored in the evaluated operating cycle, the historical change characteristics include the change trend, the change value and the change rate, and the preset monitoring period refers to the monitoring period set in advance for the unevaluated operating cycle.

[0036] In this embodiment, similar features are calculated based on the area between different first prediction change curves, the distance at the data acquisition node, the absolute length residual, or the mean and variance of each first prediction change curve at the data acquisition node. The more similar features there are, that is, the larger the similarity coefficients of different first prediction change curves, and the larger the multiple similarity coefficients between the same first prediction change curve and other first prediction change curves, the larger the corresponding credibility coefficient, that is, the higher the credibility of the corresponding first prediction change curve and the higher the accuracy.

[0037] In this embodiment, curve fusion refers to merging the central curve and the screened first predicted change curve into a representative curve, namely the second predicted change curve, so as to ensure the prediction accuracy of the second correlation factor in the unevaluated operating cycle, lay the foundation for whether to generate early warning instructions subsequently, and improve the accuracy of evaluation prediction.

[0038] In some embodiments of the present application, determining whether to generate a warning instruction based on the environmental sub-assessment difference and the predicted environmental sub-assessment value includes: Pre-set the environmental sub-assessment difference threshold; When the environmental sub-assessment difference value of an assessed operating cycle is greater than the environmental sub-assessment difference threshold, and the predicted environmental sub-assessment values ​​are all greater than the environmental sub-assessment threshold value of the corresponding unevaluated operating cycle, a first-level warning signal is generated; When the environmental sub-assessment differences of several evaluated operating cycles are all less than the environmental sub-assessment difference threshold, and there is a predicted environmental sub-assessment value that is less than the environmental sub-assessment threshold of the corresponding unevaluated operating cycle, a secondary warning signal is generated; When there is an environmental sub-assessment difference value of an evaluated operating cycle that is greater than the environmental sub-assessment difference value threshold, and there is a predicted environmental sub-assessment value that is less than the environmental sub-assessment threshold value of the corresponding unevaluated operating cycle, a third-level warning signal is generated.

[0039] In some embodiments of the present application, generating a first management optimization strategy based on the environmental sub-assessment difference, the predicted environmental sub-assessment value, and a preset objective function includes: Building an optimization strategy reference library for an unevaluated operation cycle of the current wind farm, wherein the optimization strategy reference library includes a first optimization strategy library, a second optimization strategy library, and a third optimization strategy library; When a first-level warning signal is generated, a first coefficient to be optimized is generated according to a first value of the environmental sub-assessment difference being greater than the environmental sub-assessment difference threshold and a weight coefficient corresponding to the assessed operating cycle; Optimizing a plurality of preset management strategies for unevaluated operating cycles according to a first optimization strategy library, wherein the first optimization strategy library includes a plurality of preset first coefficients to be optimized, and each preset first coefficient to be optimized is associated with a corresponding first preset management optimization sub-strategy group; Comparing the first coefficient to be optimized with a plurality of preset first coefficients to be optimized in the first optimization strategy library, and screening out a plurality of first preset management optimization sub-strategy groups whose preset first coefficients to be optimized are greater than the first coefficient to be optimized; When a secondary warning signal is generated, a second coefficient to be optimized is generated according to a second value in which the predicted environmental sub-assessment value is less than the environmental sub-assessment value and a weight coefficient corresponding to an unevaluated operating cycle; Optimizing the preset management strategies for the plurality of unevaluated operating cycles according to a second optimization strategy library, wherein the second optimization strategy library includes a plurality of preset second coefficients to be optimized, and each preset second coefficient to be optimized is associated with a corresponding second preset management optimization sub-strategy group; Comparing the second coefficient to be optimized with a plurality of preset second coefficients to be optimized in the second optimization strategy library, and screening out a plurality of second preset management optimization sub-strategy groups whose preset second coefficients to be optimized are greater than the second coefficient to be optimized; When a third-level warning signal is generated, a third coefficient to be optimized is generated according to a first value of the environmental sub-assessment difference being greater than the environmental sub-assessment difference threshold, a second value of the predicted environmental sub-assessment value being less than the environmental sub-assessment value, and corresponding weight coefficients; Optimizing the preset management strategies for the plurality of unevaluated operating cycles according to a third optimization strategy library, wherein the third optimization strategy library includes a plurality of preset third coefficients to be optimized, and each preset third coefficient to be optimized is associated with a corresponding third preset management optimization sub-strategy group; Comparing the third coefficient to be optimized with several preset third coefficients to be optimized in the third optimization strategy library, and screening out several third preset management optimization sub-strategy groups whose preset third coefficients to be optimized are greater than the third coefficient to be optimized; The preset objective functions include a resource utilization maximization objective function and an environmental impact minimization objective function; Analyze a plurality of first preset management optimization sub-strategy groups according to a resource utilization maximization objective function and an environmental impact minimization objective function to obtain a first preferred management optimization sub-strategy group, and generate a corresponding first management optimization strategy according to the first preferred management optimization sub-strategy group; Analyze the plurality of second preset management optimization sub-strategy groups according to the resource utilization maximization objective function and the environmental impact minimization objective function to obtain a second preferred management optimization sub-strategy group, and generate a corresponding first management optimization strategy according to the second preferred management optimization sub-strategy group; According to the objective function of maximizing resource utilization and the objective function of minimizing environmental impact, several third preset management optimization sub-strategy groups are analyzed to obtain a third preferred management optimization sub-strategy group, and the corresponding first management optimization strategy is generated according to the third preferred management optimization sub-strategy group.

[0040] In this embodiment, the first optimization strategy library, the second optimization strategy library, and the third optimization strategy library are respectively constructed in advance based on corresponding historical management optimization logs.

[0041] In this embodiment, according to the objective function of maximizing resource utilization and the objective function of minimizing environmental impact, the first preset management optimization sub-strategy group with the highest resource utilization and the first preset management optimization sub-strategy group with the lowest environmental impact are respectively screened out from several first preset management optimization sub-strategy groups, until the two screened out first preset management optimization sub-strategy groups are the same first preset management optimization sub-strategy group and are set as the first preferred management optimization sub-strategy group, thereby achieving the technical effect of improving resource utilization efficiency while meeting environmental management requirements.

[0042] In some embodiments of the present application, simulating the unevaluated operating cycle according to the first management optimization strategy to obtain a simulation environment sub-evaluation value includes: Performing simulation optimization on the preset management strategy of the corresponding unevaluated operation cycle according to the first management optimization strategy, and constructing a simulation management model of the corresponding unevaluated operation cycle based on the management strategy after simulation optimization, the static scenario information of the corresponding unevaluated operation cycle, and the dynamic operation information; Acquire simulation-related data in the simulation management model of each unevaluated operation cycle according to the data acquisition node, and map it to the corresponding preset monitoring duration to obtain a simulation change curve graph, wherein the simulation change curve graph includes simulation change curves of a plurality of simulation-related data; When the simulation correlation data is the first correlation factor, obtaining a simulation change feature of a simulation change curve corresponding to the simulation correlation data, comparing the simulation change feature with the predicted change feature, and generating a compensation coefficient corresponding to the simulation correlation data according to the comparison result; When the simulation correlation data is a second correlation factor, comparing a simulation change curve corresponding to the simulation correlation data with a corresponding second predicted change curve, and generating a compensation coefficient corresponding to the simulation correlation data according to the comparison result; generating a variation coefficient of corresponding simulation associated data according to a simulation variation feature of a simulation variation curve of each simulation associated data; Comparing the simulation correlation data at each data collection node in the simulation change curve of each simulation correlation data with the corresponding standard data interval to obtain the simulation correlation data difference; A simulation environment sub-evaluation value corresponding to an unevaluated operation cycle is generated according to simulation associated data differences of a plurality of simulation associated data, corresponding variation coefficients, compensation coefficients, and weight coefficients.

[0043] In this embodiment, the simulation change characteristics include a simulation change trend, a simulation change rate, and a simulation change value. The simulation change trend includes a normal change trend and an abnormal change trend. The normal change trend refers to the simulation-related data changing in a direction close to the corresponding standard data interval. The abnormal change trend refers to the simulation-related data changing in a direction away from the corresponding standard data interval. The simulation change trend, the simulation change rate, and the simulation change value are converted into numerical values ​​of the same dimension and the change coefficient is calculated. When the simulation change trend is a normal change trend, the converted value is 1. When the simulation change trend is an abnormal change trend, the converted value is -1. When the simulation change trend is a normal change trend, the change rate, and the change value are large, the corresponding change coefficient is larger, and vice versa.

[0044] In this embodiment, the more similar the simulation change characteristics are to the predicted change characteristics or the smaller the difference between the simulation change curve and the corresponding second predicted change curve is, the higher the accuracy of the simulation correlation data is, that is, the larger the corresponding compensation coefficient is, and vice versa.

[0045] In this embodiment, by simulating the unevaluated operating cycle according to the first management optimization strategy, a simulation environment sub-evaluation value is obtained, and the application effect of the first management optimization strategy is judged based on the simulation environment sub-evaluation value, and deficiencies are discovered in time and adjusted appropriately to improve the optimization effect and ensure that environmental management needs are met.

[0046] In some embodiments of the present application, the calculation formula of the simulation environment sub-evaluation value is: ; Among them, H is the simulation environment sub-assessment value, h0 is the environment assessment conversion coefficient, n is the total number of simulation related data, m is the total number of data collection nodes, is the correlation data difference threshold of the i-th simulation correlation data, is the simulation associated data difference at the jth data collection node of the ith simulation associated data, bi is the variation coefficient of the ith simulation associated data, ai is the compensation coefficient of the ith simulation associated data, and qi is the weight coefficient of the ith simulation associated data.

[0047] In some embodiments of the present application, determining whether to modify the first management optimization strategy according to the simulation environment sub-evaluation value includes: Presetting a first preset environmental assessment sum value threshold, a second preset environmental assessment sum value threshold, and a third preset environmental assessment sum value threshold for the remaining unevaluated operating cycles; When a first-level warning instruction is generated, a first simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the first simulation environment evaluation value is less than the first preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the first simulation environment evaluation value is greater than the first preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated; When a second-level warning instruction is generated, a second simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the second simulation environment evaluation value is less than the second preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the second simulation environment evaluation value is greater than the second preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated; When a third-level warning instruction is generated, a third simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the third simulation environment evaluation value is less than the third preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the third simulation environment evaluation value is greater than the third preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated.

[0048] In this embodiment, the first preset environmental assessment and value threshold is calculated based on the environmental sub-assessment threshold of the remaining unevaluated operating cycles and the first numerical value of the environmental sub-assessment difference of the evaluated operating cycles being greater than the environmental sub-assessment difference threshold; the second preset environmental assessment and value threshold is calculated based on the environmental sub-assessment threshold of the remaining unevaluated operating cycles and the second numerical value of the predicted environmental sub-assessment value being less than the environmental sub-assessment value; and the third preset environmental assessment and value threshold is calculated based on the first numerical value of the environmental sub-assessment difference of the evaluated operating cycles being greater than the environmental sub-assessment difference threshold, the second numerical value of the predicted environmental sub-assessment value being less than the environmental sub-assessment value, and the environmental sub-assessment threshold of the remaining unevaluated operating cycles.

[0049] In this embodiment, the first simulation environment evaluation sum value, the second simulation environment evaluation sum value, and the third simulation environment evaluation sum value are obtained by adding up a plurality of simulation environment sub-evaluation values.

[0050] In this embodiment, the correction instruction for generating the first management optimization strategy is to adjust the management optimization sub-strategy corresponding to the corresponding unevaluated operating cycle of the minimum simulation environment sub-evaluation value, so as to ensure that the resource utilization rate is improved while minimizing the negative impact on the environment and achieving coordinated development of the economy and the environment.

[0051] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and replacements can be made without departing from the technical principles of the present application. These improvements and replacements should also be regarded as the scope of protection of the present application.

Claims

1. An environmental assessment and early warning system for a wind farm, characterized in that: include: A setting module, configured to divide the operation cycle into a plurality of operation cycles and pre-set the environmental assessment index for each operation cycle, wherein the operation cycle includes an assessed operation cycle and an unevaluated operation cycle; An evaluation module, configured to set environmental sub-assessment thresholds for environmental assessment indicators of each operating cycle and calculate environmental sub-assessment differences for environmental assessment indicators of each evaluated operating cycle; An early warning module is used to generate a predicted environmental sub-assessment value of the environmental assessment indicator based on the predicted associated data of the unevaluated operation cycle, and determine whether to generate an early warning instruction based on the environmental sub-assessment difference and the predicted environmental sub-assessment value; a simulation module configured to generate a first management optimization strategy based on the environmental sub-assessment difference, the predicted environmental sub-assessment value, and a preset objective function when a warning instruction is generated, and simulate the unevaluated operating cycle according to the first management optimization strategy to obtain a simulated environmental sub-assessment value; The correction module is used to determine whether to correct the first management optimization strategy according to the simulation environment sub-evaluation value, and if so, obtain the second management optimization strategy and generate corresponding optimization instructions.

2. The environmental assessment and early warning system for wind farms according to claim 1, characterized in that: Pre-set environmental assessment indicators for each operation cycle, including: Determine a number of environmental management demand indicators and a number of operational management demand indicators for the corresponding operational cycle based on the environmental management demand and operational management demand of each operational cycle; Calculate the correlation degree between each environmental management demand indicator and each operation management demand indicator in the same operation cycle, and set the operation management demand indicator with a correlation degree greater than a preset correlation degree threshold as the correlation indicator of the corresponding environmental management demand indicator; Generate a correction coefficient based on the number of related indicators of each environmental management demand indicator and the weight coefficient of the corresponding related indicators; The initial weight coefficient of the corresponding environmental management demand indicator is corrected according to the correction coefficient, and the environmental assessment indicator of the operation cycle is generated based on the corrected weight coefficient and the corresponding environmental management demand indicator.

3. The environmental assessment and early warning system for wind farms according to claim 2, characterized in that: Calculate the environmental sub-assessment difference of the environmental assessment indicators for each assessed operation cycle, including: Pre-set environmental assessment thresholds for the entire operation cycle of the current wind farm; Based on the basic construction information and operation requirements of the wind farm and combined with the basic environmental information, several historical similarity assessment logs are screened out, and the historical environmental sub-assessment value interval of each operation cycle is determined based on the multiple historical similarity assessment logs; Generate the assessment ratio of the corresponding operation cycle based on the historical environment sub-assessment value interval; Divide the environmental assessment threshold according to the assessment proportion to obtain the environmental sub-assessment threshold for each operation cycle; Obtain historical monitoring data for each evaluated operation cycle, and filter out historical related data corresponding to the evaluated operation cycle based on the degree of correlation between the historical monitoring data and the environmental assessment indicators of the corresponding evaluated operation cycle; Comparing the historical correlation data with the corresponding standard data interval to obtain the historical correlation data difference, and generating the environmental sub-assessment value corresponding to the assessed operation cycle based on the multiple historical correlation data difference values; The environmental sub-assessment value of each evaluated operating cycle is compared with the corresponding environmental sub-assessment threshold to obtain the environmental sub-assessment difference value of the corresponding evaluated operating cycle.

4. The environmental assessment and early warning system for a wind farm according to claim 3, characterized in that: Generate the predicted environmental sub-assessment values ​​of the environmental assessment indicators based on the predicted associated data of the unevaluated operating cycle, including: Determining a correlation factor for each unevaluated operation cycle based on a degree of correlation between environmental assessment indicators in a number of historical similar assessment logs and historical monitoring data for each unevaluated operation cycle, the correlation factor comprising a first correlation factor and a second correlation factor; Acquire multiple historical monitoring data and historical monitoring durations of the first correlation factor in the corresponding evaluated operation cycle, and construct a historical change curve corresponding to the first correlation factor according to the historical monitoring durations; Predicting the change characteristics of the first correlation factor in the preset monitoring period of the corresponding unevaluated operation cycle based on the historical change characteristics of the historical change curve in the historical monitoring period, and determining the predicted correlation data of the first correlation factor in the unevaluated operation cycle based on the predicted change characteristics; Set data collection nodes according to the preset monitoring time and preset time interval; Collect historical monitoring data of the second correlation factor in a corresponding unevaluated operating period in each historical similarity evaluation log according to the data collection node, and construct a predicted change curve graph of the second correlation factor, wherein the predicted change curve graph includes a plurality of first predicted change curves; Obtaining similar features between different first predicted change curves, and generating similarity coefficients between the different first predicted change curves based on the similar features; Setting a credibility coefficient corresponding to each first predicted change curve according to a plurality of similarity coefficients between each first predicted change curve and other first predicted change curves, and considering the first predicted change curve with the largest credibility coefficient as the central curve; Screening out the first predicted change curve whose similarity coefficient with the central curve is greater than a preset similarity coefficient threshold, and combining it with the central curve to perform curve fusion to obtain the second predicted change curve of the second correlation factor in the corresponding unevaluated operation period; Determining predicted correlation data of the second correlation factor in the unevaluated operating cycle according to the second predicted change curve; The predicted correlation data of the first correlation factor and the second correlation factor are compared with the corresponding standard data intervals to obtain predicted correlation data differences, and a predicted environment sub-assessment value corresponding to the unevaluated operating cycle is generated according to the multiple predicted correlation data differences.

5. The environmental assessment and early warning system for wind farms according to claim 4, characterized in that: Determine whether to generate a warning instruction based on the difference between the environmental sub-assessment value and the predicted environmental sub-assessment value, including: Pre-set the environmental sub-assessment difference threshold; When the environmental sub-assessment difference value of an assessed operating cycle is greater than the environmental sub-assessment difference threshold, and the predicted environmental sub-assessment values ​​are all greater than the environmental sub-assessment threshold value of the corresponding unevaluated operating cycle, a first-level warning signal is generated; When the environmental sub-assessment differences of several evaluated operating cycles are all less than the environmental sub-assessment difference threshold, and there is a predicted environmental sub-assessment value that is less than the environmental sub-assessment threshold of the corresponding unevaluated operating cycle, a secondary warning signal is generated; When there is an environmental sub-assessment difference value of an evaluated operating cycle that is greater than the environmental sub-assessment difference value threshold, and there is a predicted environmental sub-assessment value that is less than the environmental sub-assessment threshold value of the corresponding unevaluated operating cycle, a third-level warning signal is generated.

6. The environmental assessment and early warning system for a wind farm according to claim 5, characterized in that: Generating a first management optimization strategy based on the environmental sub-assessment difference, the predicted environmental sub-assessment value, and a preset objective function includes: Building an optimization strategy reference library for an unevaluated operation cycle of the current wind farm, wherein the optimization strategy reference library includes a first optimization strategy library, a second optimization strategy library, and a third optimization strategy library; When a first-level warning signal is generated, a first coefficient to be optimized is generated according to a first value of the environmental sub-assessment difference being greater than the environmental sub-assessment difference threshold and a weight coefficient corresponding to the assessed operating cycle; Optimizing a plurality of preset management strategies for unevaluated operating cycles according to a first optimization strategy library, wherein the first optimization strategy library includes a plurality of preset first coefficients to be optimized, and each preset first coefficient to be optimized is associated with a corresponding first preset management optimization sub-strategy group; Comparing the first coefficient to be optimized with a plurality of preset first coefficients to be optimized in the first optimization strategy library, and screening out a plurality of first preset management optimization sub-strategy groups whose preset first coefficients to be optimized are greater than the first coefficient to be optimized; When a secondary warning signal is generated, a second coefficient to be optimized is generated according to a second value in which the predicted environmental sub-assessment value is less than the environmental sub-assessment value and a weight coefficient corresponding to an unevaluated operating cycle; Optimizing the preset management strategies for the plurality of unevaluated operating cycles according to a second optimization strategy library, wherein the second optimization strategy library includes a plurality of preset second coefficients to be optimized, and each preset second coefficient to be optimized is associated with a corresponding second preset management optimization sub-strategy group; Comparing the second coefficient to be optimized with a plurality of preset second coefficients to be optimized in the second optimization strategy library, and screening out a plurality of second preset management optimization sub-strategy groups whose preset second coefficients to be optimized are greater than the second coefficient to be optimized; When a third-level warning signal is generated, a third coefficient to be optimized is generated according to a first value of the environmental sub-assessment difference being greater than the environmental sub-assessment difference threshold, a second value of the predicted environmental sub-assessment value being less than the environmental sub-assessment value, and corresponding weight coefficients; Optimizing the preset management strategies for the plurality of unevaluated operating cycles according to a third optimization strategy library, wherein the third optimization strategy library includes a plurality of preset third coefficients to be optimized, and each preset third coefficient to be optimized is associated with a corresponding third preset management optimization sub-strategy group; Comparing the third coefficient to be optimized with several preset third coefficients to be optimized in the third optimization strategy library, and screening out several third preset management optimization sub-strategy groups whose preset third coefficients to be optimized are greater than the third coefficient to be optimized; The preset objective functions include a resource utilization maximization objective function and an environmental impact minimization objective function; Analyze a plurality of first preset management optimization sub-strategy groups according to a resource utilization maximization objective function and an environmental impact minimization objective function to obtain a first preferred management optimization sub-strategy group, and generate a corresponding first management optimization strategy according to the first preferred management optimization sub-strategy group; Analyze the plurality of second preset management optimization sub-strategy groups according to the resource utilization maximization objective function and the environmental impact minimization objective function to obtain a second preferred management optimization sub-strategy group, and generate a corresponding first management optimization strategy according to the second preferred management optimization sub-strategy group; According to the objective function of maximizing resource utilization and the objective function of minimizing environmental impact, several third preset management optimization sub-strategy groups are analyzed to obtain a third preferred management optimization sub-strategy group, and the corresponding first management optimization strategy is generated according to the third preferred management optimization sub-strategy group.

7. The environmental assessment and early warning system for a wind farm according to claim 6, characterized in that: The unevaluated operation cycle is simulated according to the first management optimization strategy to obtain the simulation environment sub-evaluation value, including: Performing simulation optimization on the preset management strategy of the corresponding unevaluated operation cycle according to the first management optimization strategy, and constructing a simulation management model of the corresponding unevaluated operation cycle based on the management strategy after simulation optimization, the static scenario information of the corresponding unevaluated operation cycle, and the dynamic operation information; Acquire simulation-related data in the simulation management model of each unevaluated operation cycle according to the data acquisition node, and map it to the corresponding preset monitoring duration to obtain a simulation change curve graph, wherein the simulation change curve graph includes simulation change curves of a plurality of simulation-related data; When the simulation correlation data is the first correlation factor, obtaining a simulation change feature of a simulation change curve corresponding to the simulation correlation data, comparing the simulation change feature with the predicted change feature, and generating a compensation coefficient corresponding to the simulation correlation data according to the comparison result; When the simulation correlation data is a second correlation factor, comparing a simulation change curve corresponding to the simulation correlation data with a corresponding second predicted change curve, and generating a compensation coefficient corresponding to the simulation correlation data according to the comparison result; generating a variation coefficient of corresponding simulation associated data according to a simulation variation feature of a simulation variation curve of each simulation associated data; Comparing the simulation correlation data at each data collection node in the simulation change curve of each simulation correlation data with the corresponding standard data interval to obtain the simulation correlation data difference; A simulation environment sub-evaluation value corresponding to an unevaluated operation cycle is generated according to simulation associated data differences of a plurality of simulation associated data, corresponding variation coefficients, compensation coefficients, and weight coefficients.

8. The environmental assessment and early warning system for a wind farm according to claim 7, characterized in that: The calculation formula of the simulation environment sub-evaluation value is: ； Among them, H is the simulation environment sub-assessment value, h0 is the environment assessment conversion coefficient, n is the total number of simulation related data, m is the total number of data collection nodes, is the correlation data difference threshold of the i-th simulation correlation data, is the simulation associated data difference at the jth data collection node of the ith simulation associated data, bi is the variation coefficient of the ith simulation associated data, ai is the compensation coefficient of the ith simulation associated data, and qi is the weight coefficient of the ith simulation associated data.

9. The environmental assessment and early warning system for a wind farm according to claim 8, characterized in that: Determining whether to modify the first management optimization strategy according to the simulation environment sub-evaluation value includes: Presetting a first preset environmental assessment sum value threshold, a second preset environmental assessment sum value threshold, and a third preset environmental assessment sum value threshold for the remaining unevaluated operating cycles; When a first-level warning instruction is generated, a first simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the first simulation environment evaluation value is less than the first preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the first simulation environment evaluation value is greater than the first preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated; When a second-level warning instruction is generated, a second simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the second simulation environment evaluation value is less than the second preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the second simulation environment evaluation value is greater than the second preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated; When a third-level warning instruction is generated, a third simulation environment evaluation sum value is generated based on a plurality of simulation environment sub-evaluation values ​​of the remaining unevaluated operation cycles; If the third simulation environment evaluation value is less than the third preset environment evaluation value threshold, a correction instruction for the first management optimization strategy is generated; if the third simulation environment evaluation value is greater than the third preset environment evaluation value threshold, no correction instruction for the first management optimization strategy is generated.

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