Method and device for simulating digital attack and defense environment of new energy power station

Abstract

The present invention discloses a method and device for simulating a digital attack and defense environment of a new energy power station, which relates to the technical field of salinity gradient energy power stations. Introducing digital simulation methods can achieve comprehensive monitoring and analysis of ocean dynamics and climate conditions, providing rich data support for managers. These data not only help identify the changing trends of power generation efficiency but also provide a scientific basis for the decision-making process. Managers can make more reasonable decisions based on the analysis results of the data, and the early warning mechanism can respond in a timely manner to environmental changes and the decline in equipment performance. Through the monitoring and identification of potential risks, the system can quickly take measures when facing a decline in power generation efficiency, equipment failures, or extreme climate changes. By analyzing the power generation efficiency and demand in different regions, managers can reasonably allocate equipment and personnel to avoid unnecessary operating costs. Effective resource allocation not only improves work efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of salinity gradient energy power stations, and particularly relates to a method and device for simulating a digital attack and defense environment of a new energy power station. Background Art

[0002] Under the background of global energy transformation and sustainable development, the development and utilization of new energy have received increasing attention. In particular, ocean energy, as a clean and renewable energy form, has received extensive attention due to its rich resources and small environmental impact. Salinity gradient energy, as an important form of ocean energy, generates electricity by utilizing the energy difference between different salinities of seawater and has good development potential. Therefore, a method and device for simulating a digital attack and defense environment of a new energy power station are needed.

[0003] The prior art, such as a method for correcting salinity profile data of an MVP system based on temperature gradient profile analysis disclosed in a patent application of invention with publication number CN117216473A, includes the steps of: preprocessing the MVP profile data, performing response time correction on the preprocessed MVP profile data by using a sensor response time optimal correction algorithm, finding the best thermal lag correction coefficient of each layer's thermal inertia correction algorithm by using an enumeration optimization algorithm in each thermocline and non-thermocline layer, calculating the corrected temperature data by using the best thermal lag correction coefficient, and calculating the salinity by using the conductivity data, pressure data, and the corrected temperature data. This method for correcting salinity profile data of the MVP system significantly reduces the salinity difference between the up and down measurement profiles of the MVP, and the salinity spikes are basically eliminated. In particular, obvious improvement is obtained at the thermocline layer. The average absolute salinity difference between the up and down profiles is reduced from 0.04 psu to 0.014 psu, and the overall salinity error is reduced by 65%.

[0004] Regarding the above solution, the applicant of the present invention found that the above technology has at least the following technical problems: 1. In the traditional method, the acquisition of ocean dynamic parameters and climate conditions often relies on manual collection and regular monitoring, resulting in lagging data updates. This lag may lead to untimely judgment of the power generation efficiency in the salinity gradient energy power station, affecting the overall efficiency and energy output of the system. At the same time, without a real-time analysis system, the prior art may rely on static models or historical data in the evaluation of power generation efficiency. Such a method may not accurately reflect the current actual situation, resulting in misleading evaluations, thus affecting the optimization and scheduling of the system.

[0005] 2. In traditional monitoring systems, if the power generation efficiency in a certain area decreases, there is often a lack of timely warning mechanisms, resulting in the accumulation of problems and no solutions that can be quickly adjusted and optimized. This slowness can lead to potential energy losses and premature equipment damage. It is difficult to evaluate the impact of climate conditions on power generation efficiency in real time, resulting in the inability to dynamically adjust power generation plans. For example, seasonal climate changes or sudden weather events are not considered in a timely manner, leading to a decrease in power generation efficiency or unstable system operation. At the same time, existing technologies lack comprehensive consideration of dynamic change factors and cannot form a systematic closed-loop optimization control, which may lead to a decrease in energy utilization efficiency and an increase in operating costs. Traditional technologies also have difficulty in comprehensively analyzing complex ocean dynamics and climate conditions, restricting in-depth understanding of the operating status of energy stations and optimal decision-making. Summary of the Invention

[0006] Aiming at the above-mentioned technical deficiencies, the purpose of the present invention is to provide a method and device for simulating the digital attack and defense environment of new energy stations.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a method for simulating the digital attack and defense environment of a new energy station. Step 1: Acquisition of ocean dynamics parameters: Acquire the ocean dynamics parameters corresponding to each area in the target salinity gradient energy station at the current moment, and then analyze to obtain the ocean dynamics evaluation coefficients corresponding to each area in the target salinity gradient energy station, and judge whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted.

[0008] Step 2: Warning of judgment results: When the power generation efficiency of a certain area in the target salinity gradient energy station needs to be adjusted, then perform warning response processing on the power generation efficiency corresponding to this area in the target salinity gradient energy station.

[0009] Step 3: Acquisition of climate condition evaluation coefficients: After performing warning response processing on the power generation efficiency corresponding to each area in the target salinity gradient energy station, acquire the climate condition data corresponding to each area in the target salinity gradient energy station, and then analyze to obtain the power generation efficiency evaluation coefficients corresponding to each area in the target salinity gradient energy station, and adjust the warning response parameters corresponding to each area in the target salinity gradient energy station.

[0010] Preferably, the ocean dynamics parameters include the water salinity intensity, water temperature, and water flow velocity corresponding to each ocean gradient.

[0011] Preferably, the judgment of whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted is specifically as follows: Q1: Obtain the standard ocean dynamics evaluation coefficient interval corresponding to the target salinity gradient energy station from the database.

[0012] Q2. Compare the ocean dynamics assessment coefficient corresponding to a certain area in the target salinity gradient energy station with the standard ocean dynamics assessment coefficient range. If the ocean dynamics assessment coefficient corresponding to a certain area in the target salinity gradient energy station is within the standard ocean dynamics assessment coefficient, it is determined that the power generation efficiency of the area in the target salinity gradient energy station does not need to be adjusted. Conversely, if the ocean dynamics assessment coefficient corresponding to a certain area in the target salinity gradient energy station is not within the standard ocean dynamics assessment coefficient, it is determined that the power generation efficiency of the area in the target salinity gradient energy station needs to be adjusted. In this way, it is determined whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted.

[0013] Preferably, the standard ocean dynamics assessment coefficient interval corresponding to the target salinity gradient energy station is obtained, and the specific acquisition process is as follows: E1. Through the Meteorological and Oceanographic Bureau, ocean observation stations and satellite remote sensing, historical and real-time ocean dynamic parameter data are collected to obtain the power generation efficiency data of the target salinity gradient energy station under different ocean conditions, and the power generation efficiency of each area is recorded in combination with the corresponding ocean dynamic parameters.

[0014] E2. Clean and organize the collected data, remove outliers and missing values, standardize the data, ensure the comparability of data from different data sources, use statistical analysis methods to determine the relationship between ocean dynamic parameters and power generation efficiency, and identify the key ocean dynamic parameters that affect power generation efficiency.

[0015] E3. Based on the key ocean dynamic parameters that affect power generation efficiency, study power generation cases under different ocean conditions, extract successful and unsuccessful conditions, and use correlation analysis to determine which ocean dynamic parameters have the greatest impact on power generation efficiency. In this way, focus on the most important parameters and analyze the degree of influence of changes in each parameter on power generation efficiency to determine which parameter standard ranges require higher attention, thereby establishing the standard ocean dynamic assessment coefficient range for the target salinity gradient energy site.

[0016] E4. Determine the upper and lower limits of the standard ocean dynamics assessment coefficient to form an interval, set the reasonable range of water salinity intensity, water temperature and water flow velocity corresponding to each ocean gradient, and obtain the relationship between the typical ocean dynamics assessment coefficient and power generation efficiency through multiple experiments or simulations, so as to better formulate standards, use new real-time data to verify the standard ocean dynamics assessment coefficient interval, confirm its validity and accuracy, and determine the standard ocean dynamics assessment coefficient interval corresponding to the target salinity gradient energy station based on the verification results.

[0017] Preferably, the early warning response processing for the power generation efficiency corresponding to this area in the target salinity gradient energy power station is carried out as follows: W1. When the power generation efficiency of each area in the target salinity gradient energy power station needs to be adjusted, if the marine dynamics evaluation coefficient corresponding to this area in the target salinity gradient energy power station is less than the minimum value within the standard marine dynamics evaluation coefficient range, an "inefficient early warning" is triggered. If the marine dynamics evaluation coefficient corresponding to this area is less than 10% of the minimum value within the standard marine dynamics evaluation coefficient range, it is marked as a slight inefficient early warning and an "inefficient early warning" is triggered once. If the marine dynamics evaluation coefficient corresponding to this area is less than 20% of the minimum value within the standard marine dynamics evaluation coefficient range, it is marked as a medium inefficient early warning and an "inefficient early warning" is triggered twice. If the marine dynamics evaluation coefficient corresponding to this area is less than 30% or more of the minimum value within the standard marine dynamics evaluation coefficient range, it is marked as a severe inefficient early warning and an "inefficient early warning" is triggered three times.

[0018] W2. If the marine dynamics evaluation coefficient corresponding to this area in the target salinity gradient energy power station is greater than the maximum value within the standard marine dynamics evaluation coefficient range, a "high-efficiency early warning" is triggered. If the marine dynamics evaluation coefficient corresponding to this area is greater than 10% of the maximum value within the standard marine dynamics evaluation coefficient range, it is marked as a slight high-efficiency early warning and a "high-efficiency early warning" is triggered once. If the marine dynamics evaluation coefficient corresponding to this area is greater than 20% of the maximum value within the standard marine dynamics evaluation coefficient range, it is marked as a medium high-efficiency early warning and a "high-efficiency early warning" is triggered twice. If the marine dynamics evaluation coefficient corresponding to this area is greater than 30% or more of the maximum value within the standard marine dynamics evaluation coefficient range, it is marked as a severe high-efficiency early warning and a "high-efficiency early warning" is triggered three times.

[0019] Preferably, the early warning response parameters corresponding to each area in the target salinity gradient energy power station are adjusted as follows: S1. If an "inefficient early warning" is triggered for a certain area, the power generation efficiency evaluation coefficient corresponding to this area is compared with the power generation efficiency evaluation coefficient range corresponding to each generator set operation mode in the inefficient early warning in the database. If the power generation efficiency evaluation coefficient corresponding to this area is within the power generation efficiency evaluation coefficient range corresponding to a certain generator set operation mode in the inefficient early warning in the database, the early warning response parameters corresponding to this generator set operation mode in the inefficient early warning in the database are used as the early warning response parameters corresponding to this area.

[0020] S2. If "efficient warning" is triggered in a certain area, compare the power generation efficiency evaluation coefficient corresponding to this area with the intervals of power generation efficiency evaluation coefficients corresponding to the operating modes of each generator set in the efficient warning in the database. If the power generation efficiency evaluation coefficient corresponding to this area is within the interval of the power generation efficiency evaluation coefficient corresponding to the operating mode of a certain generator set in the efficient warning in the database, then use the warning response parameters corresponding to the operating mode of this generator set in the efficient warning in the database as the warning response parameters corresponding to this area.

[0021] In the second aspect, the present invention provides a device for simulating a digital attack and defense environment of a new energy power station, including: an ocean dynamics parameter acquisition module: used to acquire the ocean dynamics parameters corresponding to each area in the target salinity gradient energy power station at the current moment, and then analyze to obtain the ocean dynamics evaluation coefficients corresponding to each area in the target salinity gradient energy power station, and judge whether the power generation efficiency of each area in the target salinity gradient energy power station needs to be adjusted.

[0022] A judgment result warning module: used to perform warning response processing on the power generation efficiency corresponding to a certain area in the target salinity gradient energy power station when the power generation efficiency of a certain area in the target salinity gradient energy power station needs to be adjusted.

[0023] A climate condition evaluation coefficient acquisition module: used to obtain the climate condition data corresponding to each area in the target salinity gradient energy power station after performing warning response processing on the power generation efficiency corresponding to each area in the target salinity gradient energy power station, and then analyze to obtain the power generation efficiency evaluation coefficients corresponding to each area in the target salinity gradient energy power station, and adjust the warning response parameters corresponding to each area in the target salinity gradient energy power station.

[0024] The beneficial effects of the present invention are as follows: 1. In the embodiment of the present invention, introducing the digital simulation method can realize the comprehensive monitoring and analysis of ocean dynamics and climate conditions, providing rich data support for managers. These data not only help to identify the changing trends of power generation efficiency, but also provide a scientific basis for the decision-making process. Managers can make more reasonable decisions based on the data analysis results, thereby improving the management level and decision-making efficiency. By acquiring and analyzing ocean dynamics parameters in real time, such as salinity, temperature, and flow velocity, as well as climate condition data, this method can quickly identify areas with low power generation efficiency under specific conditions. By dynamically adjusting power generation strategies, such as operating modes and loads, the working state of the generator sets can be optimized to ensure their operation under optimal conditions, thereby maximizing the energy utilization efficiency. This efficient adjustment can significantly increase the overall power generation and reduce energy waste.

[0025] 2. In the embodiments of the present invention, the early warning mechanism can respond in a timely manner to environmental changes and the degradation of equipment performance. Through the monitoring and identification of potential risks, the system can quickly take measures such as adjusting the power generation strategy and allocating resources when facing a decline in power generation efficiency, equipment failure, or extreme climate change. This rapid response ability not only reduces potential power generation losses but also enhances the stability and reliability of the system in a changing environment, improves the overall resilience of the new energy power station, and significantly reduces the likelihood of accidents through the early warning of potential risks and the implementation of response measures. The real-time monitoring and feedback mechanism enables operators to react quickly when problems occur, reduces the risk of equipment failure, and enhances the emergency response ability. This improvement in safety not only protects the safety of equipment and personnel but also helps to maintain the normal operation of the new energy power station.

[0026] 3. In the embodiments of the present invention, during the process of dynamically adjusting the power generation strategy, human, material, and financial resources can be more effectively allocated. By analyzing the power generation efficiency and demand in different regions, managers can reasonably allocate equipment and personnel, avoiding unnecessary operating costs. Effective resource allocation not only improves work efficiency but also ensures the rational use of various resources, reduces unnecessary waste, and enables the new energy power station to significantly reduce operating costs and improve economic benefits through optimizing the power generation strategy and increasing power generation efficiency. Efficient resource utilization and power production will enhance the market competitiveness of the new energy power station, enabling it to occupy a more favorable position in the highly competitive energy market, thereby attracting more investment and support. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0028] Figure 1 It is a flowchart of the implementation steps of the method of the present invention.

[0029] Figure 2 It is a schematic diagram of the connection of system modules of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0031] As shown in the embodiments of the present invention Figure 1 A method for simulating a digital attack and defense environment of a new energy power station includes: Step 1: Obtaining ocean dynamic parameters: Obtain the ocean dynamic parameters corresponding to each area in the target salinity gradient energy power station at the current moment, and then analyze to obtain the ocean dynamic evaluation coefficients corresponding to each area in the target salinity gradient energy power station, and determine whether the power generation efficiency of each area in the target salinity gradient energy power station needs to be adjusted.

[0032] In a specific embodiment, the ocean dynamic parameters include the water salinity intensity, water temperature, and water flow velocity corresponding to each ocean gradient.

[0033] It should be noted that satellite remote sensing and aerial remote sensing technologies are used to obtain large-scale ocean data, and through remote sensing images and data processing, relevant ocean dynamic parameters are extracted, including: the water salinity intensity, water temperature, and water flow velocity corresponding to each ocean gradient.

[0034] In another specific embodiment, the process of analyzing and obtaining the ocean dynamic evaluation coefficients corresponding to each area in the target salinity gradient energy power station is as follows: Denote the water salinity intensity, water temperature, and water flow velocity corresponding to each ocean gradient in each area as and where h represents the number corresponding to each area, h = 1, 2......n, g represents the number corresponding to each ocean gradient, g = 1, 2......u, n is any integer greater than 2, and u is any integer greater than 2. Substitute into the calculation formula to obtain the ocean dynamic evaluation coefficient α h corresponding to each area in the target salinity gradient energy power station, where A′, B′, and C′ are the standard water salinity intensity, standard water temperature, and standard water flow velocity corresponding to the set ocean gradient respectively, and θ1, θ2, and θ3 are the weight factors corresponding to the water salinity intensity, water temperature, and water flow velocity of the set ocean gradient respectively.

[0035] It should be noted that θ1, θ2, and θ3 are all greater than 0 and less than 1.

[0036] It should also be noted that through the summary of a large amount of research data and experimental data. According to the standard water salinity intensity, standard water temperature, and standard water flow velocity corresponding to the ocean gradient set by professional institutions and research institutions. At the same time, based on the professional knowledge and research basis of domain experts, and through discussions and confirmations with industry organizations or professional institutions. The weight factors corresponding to the water salinity intensity, water temperature, and water flow velocity of the ocean gradient are set by experts according to their own experience and knowledge.

[0037] Once again, it should be noted that the standard water salinity intensity, standard water temperature, and standard water flow velocity are respectively the water salinity intensity threshold, water temperature threshold, and water flow velocity threshold. For example, the standard water salinity intensity is 35, the standard water temperature is 25, and the standard water flow velocity is 1.

[0038] In the embodiments of the present invention, introducing the digital simulation method can achieve comprehensive monitoring and analysis of ocean dynamics and climate conditions, providing rich data support for managers. These data not only help identify the changing trends of power generation efficiency but also provide a scientific basis for the decision-making process. Based on the analysis results of the data, managers can make more reasonable decisions, thereby improving the management level and decision-making efficiency. By obtaining and analyzing ocean dynamics parameters in real time, such as salinity, temperature, and flow velocity, as well as climate condition data, this method can quickly identify areas with low power generation efficiency under specific conditions. By dynamically adjusting power generation strategies, such as operating modes and loads, the working state of the power generation unit can be optimized to ensure its operation under optimal conditions, thereby maximizing the energy utilization efficiency. This efficient regulation can significantly increase the overall power generation and reduce energy waste.

[0039] In another specific embodiment, the process of determining whether the power generation efficiency of each region in the target salinity gradient energy station needs to be adjusted is as follows: Q1. Obtain the standard ocean dynamics evaluation coefficient interval corresponding to the target salinity gradient energy station from the database.

[0040] Q2. Compare the ocean dynamics evaluation coefficient corresponding to a certain region in the target salinity gradient energy station with the standard ocean dynamics evaluation coefficient interval. If the ocean dynamics evaluation coefficient corresponding to a certain region in the target salinity gradient energy station is within the standard ocean dynamics evaluation coefficient, it is determined that the power generation efficiency of this region in the target salinity gradient energy station does not need to be adjusted. On the contrary, if the ocean dynamics evaluation coefficient corresponding to a certain region in the target salinity gradient energy station is not within the standard ocean dynamics evaluation coefficient, it is determined that the power generation efficiency of this region in the target salinity gradient energy station needs to be adjusted. In this way, it is determined whether the power generation efficiency of each region in the target salinity gradient energy station needs to be adjusted.

[0041] In another specific embodiment, the process of obtaining the standard ocean dynamics evaluation coefficient interval corresponding to the target salinity gradient energy station is as follows: E1. Collect historical and real-time ocean dynamics parameter data through the meteorological oceanic administration, ocean observation stations, and satellite remote sensing, obtain the power generation efficiency data of the target salinity gradient energy station under different ocean conditions, and record the data combining the power generation efficiency of each region with the corresponding ocean dynamics parameters.

[0042] E2. Clean and organize the collected data, remove outliers and missing values, standardize the data to ensure the comparability of data from different data sources, use statistical analysis methods to determine the relationship between ocean dynamic parameters and power generation efficiency, and identify the key ocean dynamic parameters that affect power generation efficiency.

[0043] E3. According to the key ocean dynamic parameters that affect power generation efficiency, study power generation cases under different ocean conditions, extract successful and unsuccessful conditions, use correlation analysis to determine which ocean dynamic parameters have the greatest impact on power generation efficiency, so as to focus on the most important parameters, analyze the degree of influence of changes in each parameter on power generation efficiency, and determine which parameter standard ranges require more attention, thereby establishing the standard ocean dynamic evaluation coefficient interval for the target salinity gradient energy station.

[0044] E4. Determine the upper and lower limits of the standard ocean dynamic evaluation coefficient to form an interval, set the reasonable ranges of water salinity intensity, water temperature, and water flow velocity corresponding to each ocean gradient, and obtain the relationship map between typical ocean dynamic evaluation coefficients and power generation efficiency through multiple experiments or simulations to better formulate standards. Use new real-time data to verify the standard ocean dynamic evaluation coefficient interval, confirm its effectiveness and accuracy, and determine the standard ocean dynamic evaluation coefficient interval corresponding to the target salinity gradient energy station according to the verification results.

[0045] It should be noted that after determining the standard ocean dynamic evaluation coefficient interval corresponding to the target salinity gradient energy station according to the verification results, input the standard ocean dynamic evaluation coefficient interval corresponding to the target salinity gradient energy station into the value database for storage.

[0046] Step 2. Early warning of judgment results: When the power generation efficiency in a certain area of the target salinity gradient energy station needs to be adjusted, then carry out early warning response processing on the power generation efficiency corresponding to this area in the target salinity gradient energy station.

[0047] In a specific embodiment, the early warning response processing for the power generation efficiency corresponding to this area in the target salinity gradient energy station is as follows: W1. When the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted, if the marine dynamics evaluation coefficient corresponding to this area in the target salinity gradient energy station is less than the minimum value within the standard marine dynamics evaluation coefficient range, an "inefficient early warning" is triggered. If the marine dynamics evaluation coefficient corresponding to this area is less than 10% of the minimum value within the standard marine dynamics evaluation coefficient range, it is marked as a slight inefficient early warning and an "inefficient early warning" is triggered once. If the marine dynamics evaluation coefficient corresponding to this area is less than 20% of the minimum value within the standard marine dynamics evaluation coefficient range, it is marked as a medium inefficient early warning and an "inefficient early warning" is triggered twice. If the marine dynamics evaluation coefficient corresponding to this area is less than 30% or more of the minimum value within the standard marine dynamics evaluation coefficient range, it is marked as a severe inefficient early warning and an "inefficient early warning" is triggered three times.

[0048] W2. If the marine dynamics evaluation coefficient corresponding to this area in the target salinity gradient energy station is greater than the maximum value within the standard marine dynamics evaluation coefficient range, a "high-efficiency early warning" is triggered. If the marine dynamics evaluation coefficient corresponding to this area is greater than 10% of the maximum value within the standard marine dynamics evaluation coefficient range, it is marked as a slight high-efficiency early warning and a "high-efficiency early warning" is triggered once. If the marine dynamics evaluation coefficient corresponding to this area is greater than 20% of the maximum value within the standard marine dynamics evaluation coefficient range, it is marked as a medium high-efficiency early warning and a "high-efficiency early warning" is triggered twice. If the marine dynamics evaluation coefficient corresponding to this area is greater than 30% or more of the maximum value within the standard marine dynamics evaluation coefficient range, it is marked as a severe high-efficiency early warning and a "high-efficiency early warning" is triggered three times.

[0049] Step 3. Obtaining the climate condition evaluation coefficient: After the early warning response processing for the power generation efficiency corresponding to each area in the target salinity gradient energy station, the climate condition data corresponding to each area in the target salinity gradient energy station is obtained, and then the power generation efficiency evaluation coefficient corresponding to each area in the target salinity gradient energy station is analyzed, and the early warning response parameters corresponding to each area in the target salinity gradient energy station are adjusted.

[0050] In the embodiments of the present invention, the early warning mechanism can respond in a timely manner to changes in the environment and the degradation of equipment performance. Through the monitoring and identification of potential risks, the system can quickly take measures such as adjusting the power generation strategy and allocating resources when facing a decline in power generation efficiency, equipment failures, or extreme climate changes. This rapid response ability not only reduces potential power generation losses but also enhances the stability and reliability of the system in a changing environment, improves the overall resilience of the new energy power station, and can significantly reduce the likelihood of accidents through the early warning of potential risks and the implementation of response measures. The real-time monitoring and feedback mechanism enables operators to react quickly when problems occur, reduces the risk of equipment failures, and enhances the emergency response ability. This improvement in safety not only protects the safety of equipment and personnel but also helps to maintain the normal operation of the new energy power station.

[0051] In a specific embodiment, the climate condition data includes instantaneous wind speed, average tidal height difference, and average wave height.

[0052] It should be noted that meteorological stations are deployed in each area of the target salinity gradient energy power station, equipped with anemometers to monitor the wind speed and direction in the air in real time. These devices can usually provide instantaneous wind speed data. Tide level measuring instruments are used to monitor the change of water level in real time. These data can provide information on the height difference of tides. Wave measuring instruments are deployed to monitor the height and period of waves in real time. Wave buoys usually provide information such as the significant wave height (H_s), etc.

[0053] In another specific embodiment, the obtained power generation efficiency evaluation coefficients corresponding to each area in the target salinity gradient energy power station are analyzed as follows: Denote the instantaneous wind speed, average tidal height difference, and average wave height corresponding to each area as D h 、F h and K h , where h represents the corresponding number of each area, h = 1, 2......n, and n is any integer greater than 2. Substitute it into the calculation formula to obtain the power generation efficiency evaluation coefficient φ h corresponding to each area in the target salinity gradient energy power station. Among them, D′, F′, and K′ are the standard instantaneous wind speed, standard average tidal height difference, and standard average wave height corresponding to the set area respectively, and σ1, σ2, and σ3 are the weight factors corresponding to the instantaneous wind speed, average tidal height difference, and average wave height of the set area respectively.

[0054] It should be noted that σ1, σ2, and σ3 are all greater than 0 and less than 1.

[0055] It should also be noted that through the summary of a large amount of research data and experimental data, according to the standard instantaneous wind speed, standard average tidal level difference, and standard average wave height corresponding to the regions set by professional institutions and research institutions. At the same time, based on the professional knowledge and research basis of domain experts, and through discussions and confirmations with industry organizations or professional institutions, experts set the weight factors corresponding to the regional instantaneous wind speed, average tidal level difference, and average wave height according to their own experience and knowledge.

[0056] Once again, it should be noted that the standard instantaneous wind speed, standard average tidal level difference, and standard average wave height are the instantaneous wind speed threshold, average tidal level difference threshold, and average wave height threshold respectively. For example, the standard instantaneous wind speed is 10, the standard average tidal level difference is 2, and the standard average wave height is 1.

[0057] In another specific embodiment, the adjustment of the early warning response parameters corresponding to each region in the target salinity gradient energy station is as follows: S1. If "inefficient early warning" is triggered in a certain region, then compare the power generation efficiency evaluation coefficient corresponding to this region with the power generation efficiency evaluation coefficient intervals corresponding to the operating modes of each generator set in the inefficient early warning in the database. If the power generation efficiency evaluation coefficient corresponding to this region is within the power generation efficiency evaluation coefficient interval corresponding to a certain generator set operating mode in the inefficient early warning in the database, then use the early warning response parameters corresponding to this generator set operating mode in the inefficient early warning in the database as the early warning response parameters corresponding to this region.

[0058] S2. If "efficient early warning" is triggered in a certain region, then compare the power generation efficiency evaluation coefficient corresponding to this region with the power generation efficiency evaluation coefficient intervals corresponding to the operating modes of each generator set in the efficient early warning in the database. If the power generation efficiency evaluation coefficient corresponding to this region is within the power generation efficiency evaluation coefficient interval corresponding to a certain generator set operating mode in the efficient early warning in the database, then use the early warning response parameters corresponding to this generator set operating mode in the efficient early warning in the database as the early warning response parameters corresponding to this region.

[0059] In the embodiment of the present invention, in the process of dynamically adjusting the power generation strategy, human, material, and financial resources can be more effectively allocated. By analyzing the power generation efficiency and demand in different regions, managers can reasonably allocate equipment and personnel to avoid unnecessary operating costs. Effective resource allocation not only improves work efficiency but also ensures the rational use of various resources, reduces unnecessary waste. By optimizing the power generation strategy and improving power generation efficiency, the new energy station can significantly reduce operating costs and improve economic benefits. Efficient resource utilization and power production will enhance the market competitiveness of the new energy station, enabling it to occupy a more favorable position in the fierce energy market, thereby attracting more investment and support.

[0060] As shown in the embodiments of the present invention Figure 2 A device for simulating a digital attack and defense environment of a new energy power station includes: an ocean dynamics parameter acquisition module: used to acquire the ocean dynamics parameters corresponding to each area in the target salinity gradient energy power station at the current moment, and then analyze to obtain the ocean dynamics evaluation coefficients corresponding to each area in the target salinity gradient energy power station, and judge whether the power generation efficiency of each area in the target salinity gradient energy power station needs to be adjusted.

[0061] A judgment result warning module: used to perform a warning response process on the power generation efficiency corresponding to a certain area in the target salinity gradient energy power station when the power generation efficiency of a certain area in the target salinity gradient energy power station needs to be adjusted.

[0062] A climate condition evaluation coefficient acquisition module: used to acquire the climate condition data corresponding to each area in the target salinity gradient energy power station after performing a warning response process on the power generation efficiency corresponding to each area in the target salinity gradient energy power station, and then analyze to obtain the power generation efficiency evaluation coefficients corresponding to each area in the target salinity gradient energy power station, and adjust the warning response parameters corresponding to each area in the target salinity gradient energy power station.

[0063] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of the present technology can make various modifications or supplements or use similar methods to replace the specific embodiments described, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A method for simulating a digital attack and defense environment of a new energy station, characterized in that: include: Step 1: Acquisition of ocean dynamic parameters: Acquire the ocean dynamic parameters corresponding to each area in the target salinity gradient energy station at the current moment, and then analyze and obtain the ocean dynamic evaluation coefficient corresponding to each area in the target salinity gradient energy station, and determine whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted; The analysis obtains the ocean dynamics assessment coefficients corresponding to each area in the target salinity gradient energy station. The specific analysis process is as follows: The water salinity intensity, water temperature and water flow velocity corresponding to each ocean gradient in each region are respectively recorded as and Among them, h represents the number corresponding to each area, h = 1, 2...n, g represents the number corresponding to each ocean gradient, g = 1, 2...u, n is any integer greater than 2, u is any integer greater than 2, substitute into the calculation formula: The ocean dynamics assessment coefficient α corresponding to each area in the target salinity gradient energy station is obtained h , where A′, B′, and C′ are the standard water salinity intensity, standard water temperature, and standard water flow velocity corresponding to the set ocean gradient, respectively; θ1, θ2, and θ3 are the weight factors corresponding to the set ocean gradient water salinity intensity, water temperature, and water flow velocity, respectively; Step 2: Early warning of the judgment result: when the power generation efficiency of a certain area in the target salinity gradient energy station needs to be adjusted, an early warning response process is then performed on the power generation efficiency corresponding to the area in the target salinity gradient energy station; Step 3: Acquisition of climate condition assessment coefficients: After the power generation efficiency corresponding to each area in the target salinity gradient energy station is processed for early warning response, the climate condition data corresponding to each area in the target salinity gradient energy station is obtained, and then the power generation efficiency assessment coefficient corresponding to each area in the target salinity gradient energy station is analyzed and the early warning response parameters corresponding to each area in the target salinity gradient energy station are adjusted; The analysis obtains the power generation efficiency evaluation coefficient corresponding to each area in the target salinity gradient energy station. The specific analysis process is as follows: The instantaneous wind speed, average tidal height difference and average wave height corresponding to each area are denoted as D h 、F h and K h , where h represents the number corresponding to each area, h = 1, 2...n, n is any integer greater than 2, substitute into the calculation formula The power generation efficiency evaluation coefficient φ corresponding to each area in the target salinity gradient energy station is obtained h , where D′, F′, and K′ are the standard instantaneous wind speed, standard average tidal height difference, and standard average wave height corresponding to the set area, respectively; σ1, σ2, and σ3 are the weight factors corresponding to the instantaneous wind speed, the average tidal height difference, and the average wave height of the set area, respectively.

2. A method for simulating a digital attack and defense environment of a new energy station as claimed in claim 1, characterized in that: The specific judgment process of judging whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted is as follows: Q1. Obtain the standard ocean dynamics assessment coefficient interval corresponding to the target salinity gradient energy station from the database; Q2. Compare the ocean dynamics assessment coefficient corresponding to a certain area in the target salinity gradient energy station with the standard ocean dynamics assessment coefficient range. If the ocean dynamics assessment coefficient corresponding to a certain area in the target salinity gradient energy station is within the standard ocean dynamics assessment coefficient, it is determined that the power generation efficiency of the area in the target salinity gradient energy station does not need to be adjusted. Conversely, if the ocean dynamics assessment coefficient corresponding to a certain area in the target salinity gradient energy station is not within the standard ocean dynamics assessment coefficient, it is determined that the power generation efficiency of the area in the target salinity gradient energy station needs to be adjusted. In this way, it is determined whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted.

3. A method for simulating a digital attack and defense environment of a new energy station as claimed in claim 2, characterized in that: The specific acquisition process of obtaining the standard ocean dynamics assessment coefficient interval corresponding to the target salinity gradient energy station is as follows: E1. Collect historical and real-time ocean dynamic parameter data through the Meteorological and Oceanographic Bureau, ocean observation stations and satellite remote sensing, obtain the power generation efficiency data of the target salinity gradient energy station under different ocean conditions, and record the data combining the power generation efficiency of each area with the corresponding ocean dynamic parameters; E2. Clean and organize the collected data, remove outliers and missing values, standardize the data, ensure the comparability of data from different data sources, use statistical analysis methods to determine the relationship between ocean dynamic parameters and power generation efficiency, and identify the key ocean dynamic parameters that affect power generation efficiency; E3. Based on the key ocean dynamic parameters that affect power generation efficiency, study power generation cases under different ocean conditions, extract successful and unsuccessful conditions, and use correlation analysis to determine which ocean dynamic parameters have the greatest impact on power generation efficiency, so as to focus on the most important parameters and analyze the impact of changes in each parameter on power generation efficiency to determine which parameter standard ranges require higher attention, thereby establishing standard ocean dynamic assessment coefficient ranges for target salinity gradient energy sites; E4. Determine the upper and lower limits of the standard ocean dynamics assessment coefficient to form an interval, set the reasonable range of water salinity intensity, water temperature and water flow velocity corresponding to each ocean gradient, and obtain the relationship between the typical ocean dynamics assessment coefficient and power generation efficiency through multiple experiments or simulations, so as to better formulate standards, use new real-time data to verify the standard ocean dynamics assessment coefficient interval, confirm its validity and accuracy, and determine the standard ocean dynamics assessment coefficient interval corresponding to the target salinity gradient energy station based on the verification results.

4. A method for simulating a digital attack and defense environment of a new energy station as claimed in claim 3, characterized in that: The specific analysis process of the early warning response process for the power generation efficiency corresponding to the area in the target salinity gradient energy station is as follows: W1. When the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted, if the ocean dynamics assessment coefficient corresponding to the area in the target salinity gradient energy station is less than the minimum value in the standard ocean dynamics assessment coefficient range, the "inefficiency warning" is triggered; if the ocean dynamics assessment coefficient corresponding to the area is less than 10% of the minimum value in the standard ocean dynamics assessment coefficient range, it is marked as a slight inefficiency warning and triggers a "inefficiency warning"; if the ocean dynamics assessment coefficient corresponding to the area is less than 20% of the minimum value in the standard ocean dynamics assessment coefficient range, it is marked as a moderate inefficiency warning and triggers a second "inefficiency warning"; if the ocean dynamics assessment coefficient corresponding to the area is less than 30% or more of the minimum value in the standard ocean dynamics assessment coefficient range, it is marked as a serious inefficiency warning and triggers three "inefficiency warnings"; W2. If the ocean dynamics assessment coefficient corresponding to the area in the target salinity gradient energy station is greater than the maximum value in the standard ocean dynamics assessment coefficient range, a "high-efficiency warning" is triggered; if the ocean dynamics assessment coefficient corresponding to the area is greater than 10% of the maximum value in the standard ocean dynamics assessment coefficient range, it is marked as a slight high-efficiency warning and triggers one "high-efficiency warning"; if the ocean dynamics assessment coefficient corresponding to the area is greater than 20% of the maximum value in the standard ocean dynamics assessment coefficient range, it is marked as a moderate high-efficiency warning and triggers a second "high-efficiency warning"; if the ocean dynamics assessment coefficient corresponding to the area is greater than 30% or more of the maximum value in the standard ocean dynamics assessment coefficient range, it is marked as a severe high-efficiency warning and triggers three "high-efficiency warnings".

5. A method for simulating a digital attack and defense environment of a new energy station as claimed in claim 4, characterized in that: The warning response parameters corresponding to each area in the target salinity gradient energy station are adjusted, and the specific analysis process is as follows: S1. If an area triggers "inefficiency warning", the power generation efficiency evaluation coefficient corresponding to the area is compared with the power generation efficiency evaluation coefficient interval corresponding to the operation mode of each generator set in the inefficiency warning in the database. If the power generation efficiency evaluation coefficient corresponding to the area is within the power generation efficiency evaluation coefficient interval corresponding to the operation mode of a generator set in the inefficiency warning in the database, the warning response parameter corresponding to the operation mode of the generator set in the inefficiency warning in the database is used as the warning response parameter corresponding to the area; S2. If a certain area triggers "high-efficiency warning", the power generation efficiency evaluation coefficient corresponding to the area is compared with the power generation efficiency evaluation coefficient interval corresponding to the operating mode of each generator set in the high-efficiency warning in the database. If the power generation efficiency evaluation coefficient corresponding to the area is within the power generation efficiency evaluation coefficient interval corresponding to the operating mode of a certain generator set in the high-efficiency warning in the database, the warning response parameters corresponding to the operating mode of the generator set in the high-efficiency warning in the database are used as the warning response parameters corresponding to the area.

6. A device for simulating the digital attack and defense environment of a new energy station for executing the method for simulating the digital attack and defense environment of a new energy station as described in any one of claims 1 to 5, characterized in that: include: Ocean dynamics parameter acquisition module: used to obtain the ocean dynamics parameters corresponding to each area in the target salinity gradient energy station at the current moment, and then analyze and obtain the ocean dynamics evaluation coefficient corresponding to each area in the target salinity gradient energy station, and determine whether the power generation efficiency of each area in the target salinity gradient energy station needs to be adjusted; Judgment result warning module: when the power generation efficiency of a certain area in the target salinity gradient energy station needs to be adjusted, the power generation efficiency corresponding to the area in the target salinity gradient energy station is warned and responded to; Climate condition assessment coefficient acquisition module: used to obtain the climate condition data corresponding to each area in the target salinity gradient energy station after the power generation efficiency corresponding to each area in the target salinity gradient energy station is processed for early warning response, and then analyze and obtain the power generation efficiency assessment coefficient corresponding to each area in the target salinity gradient energy station, and adjust the early warning response parameters corresponding to each area in the target salinity gradient energy station.

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