Offshore wind power operation safety prediction system based on data analysis

Abstract

The invention belongs to the field of offshore wind power operation, relates to a data analysis technology, and aims to solve the problem that comprehensive analysis cannot be carried out by combining requirements of different operation procedures on a construction environment and environment prediction data in the prior art, in particular to an offshore wind power operation safety prediction system based on data analysis. The meteorological monitoring module is in communication connection with an operation analysis module and a prediction analysis module, and the operation analysis module and the prediction analysis module are both in communication connection with an operation planning module; generating a monitoring period, dividing the monitoring period into a plurality of monitoring time periods, and obtaining a meteorological coefficient of the monitoring area at the end time of the monitoring time periods; according to the invention, the meteorological risk of the offshore wind power operation area can be monitored and analyzed, multiple meteorological parameters are obtained at the end time of each monitoring time period in a periodic monitoring mode, comprehensive calculation is carried out to obtain the meteorological coefficient, and the meteorological risk degree of the monitoring area is fed back according to the meteorological coefficient.

Description

Technical Field

[0001] The present invention belongs to the field of offshore wind power operations and relates to data analysis technology, in particular to an offshore wind power operation safety prediction system based on data analysis. Background Art

[0002] The construction of offshore wind farms is a high-risk operation type. The offshore operating environment is complex. During the construction process, the operating area is limited and the facilities are relatively highly concentrated. There are a large number of complex and uncertain factors in the operation, which makes the construction of offshore wind farms very risky.

[0003] The offshore wind power operation safety prediction system in the existing technology can only evaluate the construction safety of wind power operations based on environmental monitoring data, but cannot conduct a comprehensive analysis of the requirements of different operation processes for the construction environment and environmental prediction data, resulting in unreasonable planning of the operation process and the failure to ensure the completion progress of the overall construction period.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an offshore wind power operation safety prediction system based on data analysis, which is used to solve the problem that the existing technology cannot combine the requirements of different operation processes on the construction environment with the environmental prediction data for comprehensive analysis;

[0006] The technical problem to be solved by the present invention is: how to provide an offshore wind power operation safety prediction system based on data analysis that can conduct a comprehensive analysis of the requirements of different operation processes for the construction environment and environmental prediction data.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A data analysis-based offshore wind power operation safety prediction system includes a meteorological monitoring module, wherein the meteorological monitoring module is communicatively connected to an operation analysis module and a prediction analysis module, wherein both the operation analysis module and the prediction analysis module are communicatively connected to an operation planning module;

[0009] The meteorological monitoring module is used to monitor and analyze the meteorological risks in the offshore wind power operation area: mark the offshore wind power operation area as a monitoring area, generate a monitoring cycle and divide the monitoring cycle into several monitoring periods, and obtain the meteorological coefficient QX of the monitoring area at the end of the monitoring period; send the meteorological coefficient QX of the monitoring area in the monitoring period to the operation analysis module and the prediction analysis module;

[0010] The operation analysis module is used to evaluate and analyze the feasibility of offshore wind power operations: all operation processes that meet the operation implementation conditions in the monitoring area are marked as evaluation processes, each evaluation process corresponds to an evaluation threshold, and the evaluation process is marked as a neglected process or a qualified process according to the evaluation threshold; all qualified processes are sent to the operation planning module;

[0011] The prediction and analysis module is used to predict and analyze the operational safety risks in the offshore wind power operation area: mark the most recent L1 monitoring periods as analysis periods, obtain the analysis line of the analysis period, mark all completed historical monitoring cycles as analysis periods, retrieve the complete analysis line charts of all analysis cycles and mark them as reference lines, compare and analyze the analysis lines with the reference lines to obtain the prediction analysis values ​​of the prediction matching periods, and send the prediction analysis values ​​of the prediction matching periods to the operation planning module;

[0012] The operation planning module is used to plan and analyze offshore wind power operations.

[0013] Furthermore, the process of obtaining the meteorological coefficient QX of the monitoring area includes: obtaining wind pole data FJ, wave pole data LJ and fog pole data WJ and performing numerical calculations to obtain the meteorological coefficient QX of the monitoring area during the monitoring period;

[0014] The wind pole data FJ is the maximum value of the sea breeze level in the monitoring area during the monitoring period, the wave pole data LJ is the maximum value of the wave height in the monitoring area during the monitoring period, and the fog pole data WJ is the maximum value of the ocean salt fog concentration in the monitoring area during the monitoring period.

[0015] Furthermore, the specific process of marking an evaluation process as a neglected process or a compliant process includes: comparing the evaluation threshold of each evaluation process with the meteorological coefficient QX of the monitoring area during the monitoring period in turn: if the meteorological coefficient QX is less than the evaluation threshold, it is determined that the meteorological conditions of the evaluation process meet the requirements, and the corresponding evaluation process is marked as a compliant process; if the meteorological coefficient QX is greater than or equal to the evaluation threshold, it is determined that the meteorological conditions of the evaluation process do not meet the requirements, and the corresponding evaluation process is marked as a neglected process.

[0016] Furthermore, the process of obtaining the analysis line of the analysis period includes: counting the meteorological coefficient QX of the analysis period and marking it as the analysis coefficient, then establishing a rectangular coordinate system with time as the X-axis and the analysis coefficient as the Y-axis, marking L1 analysis points in the rectangular coordinate system with the end time of the analysis period as the horizontal coordinate and the meteorological coefficient QX at the end time of the analysis period as the vertical coordinate, and connecting the analysis points from left to right in sequence to obtain the analysis line.

[0017] Furthermore, the specific process of comparing and analyzing the analysis line with the reference line includes: translating the analysis line to the rectangular coordinate system of the reference line and making the left endpoint of the analysis line on the Y axis, making straight lines perpendicular to the X axis at the two endpoints of the analysis line and marking them as dividing lines, and translating the analysis line horizontally from left to right until the horizontal coordinate value of the right endpoint of the analysis line is the same as that of the right endpoint of the reference line; marking the sum of the area values ​​of all closed areas enclosed by the two dividing lines, the analysis line and the reference line during the horizontal translation as a matching value.

[0018] Furthermore, the specific marking process of the prediction matching cycle and the prediction analysis value includes: marking the smallest matching value in the lateral shift process as the identification value of the analysis cycle; marking the analysis cycle with the smallest identification value in all analysis cycles as the prediction matching cycle, marking the horizontal coordinate value of the right end point of the analysis line corresponding to the identification value in the prediction matching cycle as the matching time point of the prediction matching cycle, and marking the meteorological coefficient QX of the most recent monitoring period after the matching time point of the prediction matching cycle as the prediction analysis value of the prediction matching cycle.

[0019] Furthermore, the specific process of planning and analyzing offshore wind power operations in the operation planning module includes: comparing the predicted analysis value with the meteorological coefficient QX of the current monitoring period: if the predicted analysis value is greater than the meteorological coefficient QX of the current monitoring period, then all eligible processes are sorted in descending order according to the evaluation threshold value to obtain a priority execution sequence; if the predicted analysis value is less than or equal to the meteorological coefficient QX of the current monitoring period, then all eligible processes are sorted in descending order according to the urgency of the construction period to obtain a priority execution sequence; and the priority execution sequence is sent to the mobile phone terminal of the manager.

[0020] The present invention has the following beneficial effects:

[0021] 1. The meteorological monitoring module can monitor and analyze the meteorological risks in the offshore wind power operation area. By periodically monitoring, multiple meteorological parameters are obtained at the end of each monitoring period and the meteorological coefficient is obtained by comprehensive calculation. The meteorological risk level of the monitoring area is fed back according to the meteorological coefficient, providing data support for the feasibility assessment process of the operation;

[0022] 2. The operation analysis module can be used to evaluate and analyze the feasibility of offshore wind power operations. According to the comparison results of the evaluation thresholds corresponding to all evaluation processes when ensuring the safety of operations and the meteorological coefficients of the monitoring area, the evaluation processes are marked differently, and the operation processes with safety risks under the current meteorological risk level are eliminated to ensure the safety of offshore wind power operations;

[0023] 3. The forecast analysis module can be used to forecast and analyze the operational safety risks in offshore wind power operation areas, screen the forecast matching period by comparing historical meteorological data, and extract the forecast analysis value corresponding to the forecast matching period. The forecast analysis value can be used to provide data support for operation planning analysis and improve the accuracy of forecast results.

[0024] 4. The operation planning module can be used to plan and analyze offshore wind power operations. A priority execution sequence can be generated based on the comparison results between the predicted analysis value and the meteorological coefficient of the current monitoring period. When the predicted trend of the meteorological coefficient changes, the execution priority of the evaluation process can be changed to improve the overall efficiency of the operation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0027] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] Embodiment 1: Figure 1 As shown, a data analysis-based offshore wind power operation safety prediction system includes a meteorological monitoring module, the meteorological monitoring module is communicatively connected to an operation analysis module and a prediction analysis module, and both the operation analysis module and the prediction analysis module are communicatively connected to an operation planning module.

[0030] The meteorological monitoring module is used to monitor and analyze the meteorological risks in the offshore wind power operation area: mark the offshore wind power operation area as the monitoring area, generate a monitoring cycle and divide the monitoring cycle into several monitoring periods, and obtain the wind pole data FJ, wave pole data LJ and fog pole data WJ of the monitoring area at the end of the monitoring period; the wind pole data FJ is the maximum value of the sea breeze level value in the monitoring area during the monitoring period, the wave pole data LJ is the maximum value of the sea wave height in the monitoring area during the monitoring period, and the fog pole data WJ is the maximum value of the ocean salt spray concentration value in the monitoring area during the monitoring period; The meteorological coefficient QX of the monitoring area during the monitoring period is obtained by the formula QX=k1*FJ+k2*LJ+k3*WJ, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the meteorological coefficient QX of the monitoring area during the monitoring period is sent to the operation analysis module and the prediction analysis module; a number of meteorological parameters are obtained at the end of each monitoring period in a periodic monitoring manner and the meteorological coefficient is obtained by comprehensive calculation; the meteorological risk degree of the monitoring area is fed back according to the meteorological coefficient to provide data support for the operation feasibility assessment process.

[0031] The operation analysis module is used to evaluate and analyze the feasibility of offshore wind power operations: all operation processes that meet the operation implementation conditions in the monitoring area are marked as evaluation processes, and each evaluation process corresponds to an evaluation threshold. The evaluation threshold is the maximum critical value of the meteorological coefficient QX at which the evaluation process can be safely implemented. The evaluation threshold of each evaluation process is compared with the meteorological coefficient QX of the monitoring area during the monitoring period in turn: if the meteorological coefficient QX is less than the evaluation threshold, it is determined that the meteorological conditions of the evaluation process meet the requirements, and the corresponding evaluation process is marked as a compliant process; if the meteorological coefficient QX is greater than or equal to the evaluation threshold, it is determined that the meteorological conditions of the evaluation process do not meet the requirements, and the corresponding evaluation process is marked as a neglected process; all compliant processes are sent to the operation planning module; according to the comparison results of the evaluation thresholds corresponding to all evaluation processes when ensuring the safety of the operation and the meteorological coefficients of the monitoring area, the evaluation processes are differentiated and marked, and the operation processes with safety risks under the current meteorological risk level are eliminated to ensure the safety of offshore wind power operations.

[0032] The prediction and analysis module is used to predict and analyze the operational safety risks in offshore wind power operation areas: mark the most recent L1 monitoring periods as analysis periods, count the meteorological coefficient QX of the analysis period and mark it as the analysis coefficient, then establish a rectangular coordinate system with time as the X-axis and the analysis coefficient as the Y-axis, mark L1 analysis points in the rectangular coordinate system with the end time of the analysis period as the horizontal coordinate and the meteorological coefficient QX at the end time of the analysis period as the vertical coordinate, L1 is a numerical constant, and the specific value of L1 is set by the management personnel; connect the analysis points from left to right in sequence to obtain an analysis line, mark all completed historical monitoring cycles as analysis cycles, retrieve the complete analysis line chart of all analysis cycles and mark them as reference lines, translate the analysis line to the rectangular coordinate system of the reference line and make the left end point of the analysis line on the Y-axis, make straight lines perpendicular to the X-axis at both end points of the analysis line and mark them as dividing lines, and translate the analysis line parallel to the left from right. , until the horizontal coordinate value of the right end point of the analysis line is the same as that of the right end point of the reference line; during the horizontal shift, the sum of the area values ​​of all closed areas surrounded by the two dividing lines, the analysis line and the reference line is marked as the matching value, and the smallest matching value during the horizontal shift is marked as the identification value of the analysis period; the analysis period with the smallest identification value in all analysis periods is marked as the predicted matching period, the horizontal coordinate value of the right end point of the analysis line corresponding to the identification value in the predicted matching period is marked as the matching time point of the predicted matching period, and the meteorological coefficient QX of the nearest monitoring period after the matching time point of the predicted matching period is marked as the predicted analysis value of the predicted matching period; the predicted analysis value of the predicted matching period is sent to the job planning module; the predicted matching period is screened by comparing historical meteorological data, and the predicted analysis value corresponding to the predicted matching period is extracted, and data support is provided for job planning analysis according to the predicted analysis value to improve the accuracy of the prediction result.

[0033] The operation planning module is used to plan and analyze offshore wind power operations: compare the predicted analysis value with the meteorological coefficient QX of the current monitoring period: if the predicted analysis value is greater than the meteorological coefficient QX of the current monitoring period, all eligible processes are sorted in descending order according to the evaluation threshold value to obtain a priority execution sequence; if the predicted analysis value is less than or equal to the meteorological coefficient QX of the current monitoring period, all eligible processes are sorted in descending order according to the urgency of the construction period to obtain a priority execution sequence; the priority execution sequence is sent to the mobile phone terminal of the manager; the priority execution sequence is generated based on the comparison result of the predicted analysis value and the meteorological coefficient of the current monitoring period, and the execution priority of the evaluation process is changed when the predicted trend of the meteorological coefficient changes, so as to improve the overall efficiency of the operation process completion.

[0034] Embodiment 2: Figure 2As shown, a method for predicting safety of offshore wind power operations based on data analysis includes the following steps:

[0035] Step 1: Monitor and analyze the meteorological risks in the offshore wind power operation area: mark the offshore wind power operation area as the monitoring area, generate a monitoring cycle and divide the monitoring cycle into several monitoring periods, and obtain the meteorological data QX of the monitoring area at the end of the monitoring period;

[0036] Step 2: Evaluate and analyze the feasibility of offshore wind power operations: mark all operation processes that meet the operation implementation conditions in the monitoring area as evaluation processes, and mark the evaluation processes as qualified processes or ignored processes according to the evaluation threshold of the evaluation processes;

[0037] Step 3: Conduct a forecast analysis on the operational safety risks in the offshore wind power operation area and obtain the forecast analysis value;

[0038] Step 4: Plan and analyze the offshore wind power operations based on the predicted analysis values ​​and obtain a priority execution sequence, which is then sent to the manager's mobile phone terminal.

[0039] A data analysis-based offshore wind power operation safety prediction system, when working, marks the offshore wind power operation area as a monitoring area, generates a monitoring cycle and divides the monitoring cycle into several monitoring time periods, obtains meteorological data QX of the monitoring area at the end of the monitoring time period; marks all operation procedures that meet the operation implementation conditions in the monitoring area as evaluation procedures, and marks the evaluation procedures as compliant procedures or ignored procedures according to the evaluation threshold of the evaluation procedures; predicts and analyzes the operation safety risks in the offshore wind power operation area and obtains the prediction analysis value; plans and analyzes the offshore wind power operation according to the prediction analysis value and obtains a priority execution sequence, and sends the priority execution sequence to the mobile phone terminal of the manager.

[0040] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0041] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; such as: formula QX = k1*FJ+k2*LJ+k3*WJ; technicians in this field collect multiple groups of sample data and set corresponding meteorological coefficients for each group of sample data; substitute the set meteorological coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of k1, k2 and k3 as 3.85, 2.67 and 2.02 respectively;

[0042] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding meteorological coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the meteorological coefficient is proportional to the value of the wind pole data.

[0043] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0044] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A safety prediction system for offshore wind power operations based on data analysis, characterized in that: It includes a meteorological monitoring module, the meteorological monitoring module is communicatively connected to an operation analysis module and a prediction analysis module, and the operation analysis module and the prediction analysis module are both communicatively connected to an operation planning module; The meteorological monitoring module is used to monitor and analyze the meteorological risks in the offshore wind power operation area: mark the offshore wind power operation area as a monitoring area, generate a monitoring cycle and divide the monitoring cycle into several monitoring periods, and obtain the meteorological coefficient QX of the monitoring area at the end of the monitoring period; send the meteorological coefficient QX of the monitoring area in the monitoring period to the operation analysis module and the prediction analysis module; The operation analysis module is used to evaluate and analyze the feasibility of offshore wind power operations: all operation processes that meet the operation implementation conditions in the monitoring area are marked as evaluation processes, each evaluation process corresponds to an evaluation threshold, and the evaluation process is marked as a neglected process or a qualified process according to the evaluation threshold; all qualified processes are sent to the operation planning module; The prediction and analysis module is used to predict and analyze the operational safety risks in the offshore wind power operation area: mark the most recent L1 monitoring periods as analysis periods, obtain the analysis line of the analysis period, mark all completed historical monitoring cycles as analysis periods, retrieve the complete analysis line charts of all analysis cycles and mark them as reference lines, compare and analyze the analysis lines with the reference lines to obtain the prediction analysis values ​​of the prediction matching periods, and send the prediction analysis values ​​of the prediction matching periods to the operation planning module; The operation planning module is used to plan and analyze offshore wind power operations.

2. The offshore wind power operation safety prediction system based on data analysis according to claim 1 is characterized in that: The process of obtaining the meteorological coefficient QX of the monitoring area includes: obtaining wind pole data FJ, wave pole data LJ and fog pole data WJ and performing numerical calculations to obtain the meteorological coefficient QX of the monitoring area during the monitoring period; The wind pole data FJ is the maximum value of the sea breeze level in the monitoring area during the monitoring period, the wave pole data LJ is the maximum value of the wave height in the monitoring area during the monitoring period, and the fog pole data WJ is the maximum value of the ocean salt fog concentration in the monitoring area during the monitoring period.

3. The offshore wind power operation safety prediction system based on data analysis according to claim 2 is characterized in that: The specific process of marking an evaluation process as a neglected process or a compliant process includes: comparing the evaluation threshold of each evaluation process with the meteorological coefficient QX of the monitoring area during the monitoring period in turn: if the meteorological coefficient QX is less than the evaluation threshold, it is determined that the meteorological conditions of the evaluation process meet the requirements, and the corresponding evaluation process is marked as a compliant process; if the meteorological coefficient QX is greater than or equal to the evaluation threshold, it is determined that the meteorological conditions of the evaluation process do not meet the requirements, and the corresponding evaluation process is marked as a neglected process.

4. The offshore wind power operation safety prediction system based on data analysis according to claim 3 is characterized in that: The process of obtaining the analysis line of the analysis period includes: counting the meteorological coefficient QX of the analysis period and marking it as the analysis coefficient, then establishing a rectangular coordinate system with time as the X-axis and the analysis coefficient as the Y-axis, marking L1 analysis points in the rectangular coordinate system with the end time of the analysis period as the horizontal coordinate and the meteorological coefficient QX at the end time of the analysis period as the vertical coordinate, and connecting the analysis points from left to right in sequence to obtain the analysis line.

5. The offshore wind power operation safety prediction system based on data analysis according to claim 4 is characterized in that: The specific process of comparing and analyzing the analysis polyline with the reference polyline includes: translating the analysis polyline to the rectangular coordinate system of the reference polyline and making the left end point of the analysis polyline on the Y axis, making straight lines perpendicular to the X axis at both end points of the analysis polyline and marking them as dividing lines, and translating the analysis polyline horizontally from left to right until the horizontal coordinate value of the right end point of the analysis polyline is the same as that of the right end point of the reference polyline; marking the sum of the area values ​​of all closed areas enclosed by the two dividing lines, the analysis polyline and the reference polyline during the horizontal translation as the matching value.

6. The offshore wind power operation safety prediction system based on data analysis according to claim 5, characterized in that: The specific marking process of the prediction matching cycle and the prediction analysis value includes: marking the smallest matching value in the horizontal shift process as the identification value of the analysis cycle; marking the analysis cycle with the smallest identification value in all analysis cycles as the prediction matching cycle, marking the horizontal coordinate value of the right end point of the analysis line corresponding to the identification value in the prediction matching cycle as the matching time point of the prediction matching cycle, and marking the meteorological coefficient QX of the nearest monitoring period after the matching time point of the prediction matching cycle as the prediction analysis value of the prediction matching cycle.

7. The offshore wind power operation safety prediction system based on data analysis according to claim 6, characterized in that: The specific process of planning and analyzing offshore wind power operations in the operation planning module includes: comparing the predicted analysis value with the meteorological coefficient QX of the current monitoring period: if the predicted analysis value is greater than the meteorological coefficient QX of the current monitoring period, then all eligible processes are sorted in descending order according to the evaluation threshold value to obtain a priority execution sequence; if the predicted analysis value is less than or equal to the meteorological coefficient QX of the current monitoring period, then all eligible processes are sorted in descending order according to the urgency of the construction period to obtain a priority execution sequence; the priority execution sequence is sent to the mobile phone terminal of the manager.

Images