Risk assessment result generation method and device, storage medium and electronic device

Abstract

The invention discloses a risk assessment result generation method and device, a storage medium and an electronic device, and relates to the technical field of environment risk assessment, and the method comprises the steps: classifying the collected environment data of an offshore wind plant, and obtaining various types of environment risk data; determining a first environmental factor corresponding to first environmental risk data, calculating a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtaining target risk values corresponding to all environmental factors based on the first risk value, the first environmental risk data is obtained from the various environmental risk data; and generating a risk assessment result according to a comparison result of the target risk value and the risk threshold, and by adopting the technical scheme, the technical problem that the accuracy of the risk assessment result of the offshore wind plant is relatively low is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of environmental risk assessment, in particular to a risk assessment result generation method and device, a storage medium and an electronic device. BACKGROUND

[0002] At present, the environmental risk assessment process of offshore wind farms relies on traditional qualitative analysis methods such as expert assessment and fault tree analysis. Although these methods can preliminarily assess environmental risks, they do not comprehensively consider the impact of different environmental factors on offshore wind farms when facing complex and variable marine environments, resulting in inaccurate risk assessment results. Therefore, in related technologies, there is a technical problem of low accuracy of risk assessment results for offshore wind farms.

[0003] In view of the technical problem of low accuracy of risk assessment results for offshore wind farms in related technologies, an effective solution has not yet been proposed. SUMMARY

[0004] The embodiments of the present application provide a risk assessment result generation method and device, a storage medium and an electronic device to at least solve the technical problem of low accuracy of risk assessment results for offshore wind farms in related technologies.

[0005] According to one of the embodiments of the present application, a risk assessment result generation method is provided, including: classifying collected environmental data of offshore wind farms to obtain multiple environmental risk data; determining a first environmental risk data corresponding to a first environmental factor, calculating a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtaining a target risk value corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the multiple environmental risk data; generating a risk assessment result according to a comparison result of the target risk value and a risk threshold.

[0006] In one exemplary embodiment, calculating a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data includes: determining multiple risk subcategories contained in the first risk category, and traversing the multiple risk subcategories; for each traversed first risk subcategory, determining a first risk event corresponding to the first risk subcategory from all risk events corresponding to the first risk category; obtaining first environmental risk data corresponding to the first risk event from the first environmental risk data; calculating a first occurrence probability and a first risk impact degree of the first risk event according to the first environmental risk data, and calculating the first risk value according to the first occurrence probability and the first risk impact degree.

[0007] In an example embodiment, the first occurrence probability and the first risk impact degree of the first risk event are calculated according to the first environmental risk data, including: obtaining, from the first environmental risk data, a first occurrence number of the first risk event and a second occurrence number of all risk events; determining the first occurrence probability according to a ratio of the first occurrence number to the second occurrence number; determining a value interval in which the ratio is located, and determining the first risk impact degree according to an interval level corresponding to the value interval.

[0008] In an example embodiment, the first risk value is calculated according to the first occurrence probability and the first risk impact degree, including: obtaining a first product of the first occurrence probability and the first risk impact degree in a case where the first risk subcategory is traversed; obtaining a plurality of first products after the plurality of risk subcategories are traversed, and determining the first risk value according to a sum of the plurality of first products.

[0009] In an example embodiment, a target risk value corresponding to all environmental factors is obtained based on the first risk value, including: determining a first risk weight corresponding to the first risk value; determining a second risk value corresponding to other environmental factors and a second risk weight corresponding to the second risk value, wherein the other environmental factors represent environmental factors other than the first environmental factor in the all environmental factors; calculating a second product of the first risk value and the first risk weight, and calculating a third product of the second risk value and the second risk weight; and determining the target risk value based on a sum of the second product and the third product.

[0010] In an example embodiment, the risk threshold value includes at least one of a first preset threshold value and a second preset threshold value, the first preset threshold value being smaller than the second preset threshold value, and a risk assessment result is generated according to a comparison result of the target risk value and the risk threshold value, including one of: in a case where the comparison result indicates that the target risk value is smaller than the first preset threshold value, determining a risk level of the offshore wind farm as a first level, and generating the risk assessment result based on the first level and warning information corresponding to the first level; in a case where the comparison result indicates that the target risk value is equal to or greater than the first preset threshold value and the target risk value is greater than the second preset threshold value, determining a risk level of the offshore wind farm as a second level, and generating the risk assessment result based on the second level and warning information corresponding to the second level; and in a case where the comparison result indicates that the target risk value is equal to or greater than the second preset threshold value, determining a risk level of the offshore wind farm as a third level, and generating the risk assessment result based on the third level and warning information corresponding to the third level.

[0011] According to another aspect of the embodiments of the present application, a device for generating a risk assessment result is also provided, comprising: a classification module configured to classify collected environmental data of a marine wind farm to obtain a plurality of environmental risk data; a calculation module configured to determine a first environmental factor corresponding to first environmental risk data, calculate a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtain a target risk value corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data; and a generation module configured to generate a risk assessment result according to a comparison result of the target risk value and a risk threshold.

[0012] According to still another aspect of the embodiments of the present application, a computer readable storage medium having a computer program stored therein is also provided, wherein the computer program is configured to execute the above-mentioned method for generating a risk assessment result when running.

[0013] According to still another aspect of the embodiments of the present application, an electronic device is also provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-mentioned method for generating a risk assessment result through the computer program.

[0014] According to still another aspect of the embodiments of the present application, a computer program product is also provided, comprising a computer program executable by a processor to implement the above-mentioned method for generating a risk assessment result.

[0015] In the embodiments of the present application, the collected environmental data of a marine wind farm is classified to obtain a plurality of environmental risk data, a first environmental factor corresponding to first environmental risk data is determined, a first risk value of the first environmental factor is calculated according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and a target risk value corresponding to all environmental factors is obtained based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data; and a risk assessment result is generated according to a comparison result of the target risk value and a risk threshold. The embodiments of the present application effectively identify different environmental factors by classifying complex and variable marine environmental data, provide a basis for subsequent risk quantification, solve the technical problem of low accuracy of a risk assessment result of a marine wind farm in the related art, and thus improve the accuracy and reliability of risk assessment. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application, together with the description.

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without any creative effort.

[0018] Figure 1 is a hardware environment schematic diagram of a risk assessment result generation method according to an embodiment of the present application;

[0019] Figure 2 is a flow chart of a risk assessment result generation method according to an embodiment of the present application;

[0020] Figure 3 is a structural block diagram of a risk assessment result generation device according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the personnel in the technical field better understand the present application, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort should be within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in other than the order illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an aspect of the embodiments of the present application, a risk assessment result generation method is provided. The method embodiments provided in the embodiments of the present application can be executed in a server device, a computer terminal or a similar computing device of an offshore wind farm. Taking the case of running on a server device, Figure 1 is a hardware structural block diagram of a server device of a risk assessment result generation method according to an embodiment of the present application. As Figure 1 shown, the server device can include one or more Figure 1Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a microprocessor or a processing device such as a programmable logic device (Field Programmable Gate Array, FPGA)) and a memory 104 for storing data. The server device may also include a transmission device 106 and an input / output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above server device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0024] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for generating risk assessment results in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implementing the above-mentioned method. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories may be connected to the server device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0025] The transmission device 106 is used to receive or send data via a network. A specific example of the aforementioned network may include a wireless network provided by a communications provider of the server device. In one embodiment, the transmission device 106 may include a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0026] In this embodiment, a method for generating risk assessment results is provided, which is applied to the above-mentioned server device. Figure 2 : is a flowchart of a method for generating risk assessment results according to an embodiment of the present application, the process comprising the following steps:

[0027] Step S202: classify the collected environmental data of the offshore wind farm to obtain a variety of environmental risk data;

[0028] In this step, the collected environmental data of the offshore wind farm is classified according to environmental factors to obtain multiple environmental risk data, and one environmental risk data corresponds to one environmental factor. It should be noted that the environmental factor in the present application refers to an environmental risk factor that affects the design, construction, operation, etc. of the offshore wind farm, such as wind, wave, current, sea ice, storm surge, etc.

[0029] In step S204, a first environmental risk data corresponding to a first environmental factor is determined, a first risk value of the first environmental factor is calculated according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and a target risk value corresponding to all environmental factors is obtained based on the first risk value, wherein the first environmental risk data is obtained from the multiple environmental risk data.

[0030] Through the above steps, by classifying the environmental data and comprehensively calculating the risk value of the environmental factor, the environmental risk degree of the offshore wind farm can be accurately quantified, multi-level risk assessment is realized, and the comprehensiveness and accuracy of the evaluation result are improved.

[0031] Meanwhile, this step can also update the environmental data in real time, so as to quickly respond to environmental changes, dynamically adjust the risk assessment result, timely reflect the environmental risk changes of the offshore wind farm and update the risk assessment result, and provide dynamic guidance for the operation and management of the offshore wind farm.

[0032] In step S206, a risk assessment result is generated according to the comparison result of the target risk value and the risk threshold.

[0033] It should be noted that based on the preset risk threshold, this step can automatically generate a risk assessment result and trigger different levels of warning information for timely risk warning, so as to quickly develop corresponding risk response strategies, improve the safety of the wind farm, and effectively prevent and reduce the loss caused by potential environmental risks.

[0034] Through the above steps, the collected environmental data of the offshore wind farm is classified to obtain multiple environmental risk data; a first environmental risk data corresponding to a first environmental factor is determined, a first risk value of the first environmental factor is calculated according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and a target risk value corresponding to all environmental factors is obtained based on the first risk value, wherein the first environmental risk data is obtained from the multiple environmental risk data; and a risk assessment result is generated according to the comparison result of the target risk value and the risk threshold. The present application classifies the complex and changeable marine environmental data, effectively identifies different environmental factors, provides a basis for subsequent risk quantification, solves the technical problem of low accuracy of the risk assessment result of the offshore wind farm in the related art, and further improves the accuracy and reliability of the risk assessment.

[0035] In an example embodiment, the process of calculating the first risk value of the first environmental factor according to the first risk category corresponding to the first environmental factor and the first environmental risk data comprises: determining a plurality of risk subcategories contained in the first risk category, traversing the plurality of risk subcategories; for each traversed first risk subcategory, determining a first risk event corresponding to the first risk subcategory from all risk events corresponding to the first risk category; obtaining first environmental risk data corresponding to the first risk event from the first environmental risk data; calculating a first occurrence probability and a first risk impact degree of the first risk event according to the first environmental risk data, and calculating the first risk value according to the first occurrence probability and the first risk impact degree. This embodiment improves the comprehensiveness and pertinence of risk identification by subdividing risk subcategories and deeply mining the characteristics of various risk events. By quantifying the occurrence probability and impact degree of a risk event, objective evaluation of the risk is achieved.

[0036] Optionally, the first risk impact degree can be standardized, and the value after standardization is [0, 1].

[0037] Optionally, in other embodiments, a risk event database can also be constructed to collect historical risk event information, thereby improving the accuracy of risk prediction.

[0038] In an example embodiment, the scheme of calculating the first occurrence probability and the first risk impact degree of the first risk event according to the first environmental risk data can comprise: obtaining the first occurrence number of the first risk event and the second occurrence number of all risk events from the first environmental risk data; determining the first occurrence probability according to the ratio of the first occurrence number to the second occurrence number; determining the value interval in which the ratio is located, and determining the first risk impact degree according to the interval level corresponding to the value interval. This embodiment enhances the empirical basis of risk assessment by statistically analyzing the historical records of risk events and scientifically calculating the possibility and impact range of the risk. By setting different value intervals, the different severity of risk events is distinguished, and fine management of risk levels is achieved. This embodiment can dynamically adjust the risk assessment strategy according to the actual occurrence of the risk event, thereby improving the flexibility and timeliness of the assessment.

[0039] Optionally, in other embodiments, external risk factors such as economy and policy can also be introduced to comprehensively consider the overall impact of risk events and enrich the dimensions of risk assessment.

[0040] In an exemplary embodiment, the specific steps for calculating the first risk value based on the first probability of occurrence and the first risk impact include: upon traversing to the first risk subcategory, obtaining a first product of the first probability of occurrence and the first risk impact; after traversing the multiple risk subcategories, obtaining multiple first products, and determining the first risk value based on the sum of the multiple first products. This embodiment uses a cumulative product approach to combine the probability of occurrence and impact of risk subcategories to form a holistic assessment of the risk of a specific environmental factor. The quantitative indicators of different risk subcategories are integrated through mathematical operations, ensuring the systematic and complete nature of the risk assessment.

[0041] Similarly, in the process of traversing the multiple risk subcategories and obtaining multiple first products, the calculation method of the first product of each risk subcategory is consistent and will not be repeated here.

[0042] Optionally, in other embodiments, the risk assessment model may be further optimized by adjusting the multiplication coefficient and taking into account the interaction between different risk subcategories.

[0043] In an exemplary embodiment, obtaining the target risk value corresponding to all environmental factors based on the first risk value may include: determining a first risk weight corresponding to the first risk value; determining a second risk value corresponding to other environmental factors, and a second risk weight corresponding to the second risk value, wherein the other environmental factors represent environmental factors other than the first environmental factor among all environmental factors; calculating a second product of the first risk value and the first risk weight, and calculating a third product of the second risk value and the second risk weight; and determining the target risk value based on the sum of the second product and the third product. This embodiment, by assigning corresponding risk weights to different environmental factors, reflects the differences in the risk contributions of each factor and improves the scientificity and rationality of risk assessment. Determining risk weights through the hierarchical analysis method ensures the objectivity and fairness of weight allocation. This embodiment can comprehensively consider the combined impact of various environmental factors and accurately assess the overall risk level faced by offshore wind farms.

[0044] Optionally, the first risk weight corresponding to the first risk value or the second risk weight corresponding to the second risk value may be determined by the following formula:

[0045]

[0046] Among them, λ k is the expert weight, P i,k and I i,k They represent the probability of occurrence and impact of the i-th risk event in the k-th expert’s rating. i,kCorresponding to the first occurrence probability described above, I i,k Corresponding to the first risk impact degree described above. It can be seen that the first risk weight is calculated based on the first occurrence probability, the first risk impact degree and the expert weight. The second risk weight is similar.

[0047] Optionally, in other embodiments, the risk weight can also be updated periodically to reflect changes in environmental conditions and maintain the continuous effectiveness of risk assessment.

[0048] In an exemplary embodiment, the risk threshold includes at least one of the following: a first preset threshold and a second preset threshold, the first preset threshold being smaller than the second preset threshold, and the implementation scheme for generating a risk assessment result according to the comparison result of the target risk value and the risk threshold includes one of the following:

[0049] Scheme 1, in the case where the comparison result is used to indicate that the target risk value is less than the first preset threshold, determining that the risk level of the offshore wind farm is a first level, and generating the risk assessment result based on the first level and the warning information corresponding to the first level.

[0050] Scheme 2, in the case where the comparison result is used to indicate that the target risk value is equal to or greater than the first preset threshold, and the target risk value is greater than the second preset threshold, determining that the risk level of the offshore wind farm is a second level, and generating the risk assessment result based on the second level and the warning information corresponding to the second level.

[0051] Scheme 3, in the case where the comparison result is used to indicate that the target risk value is equal to or greater than the second preset threshold, determining that the risk level of the offshore wind farm is a third level, and generating the risk assessment result based on the third level and the warning information corresponding to the third level.

[0052] In summary, the present embodiment establishes a mapping relationship between the risk assessment result and the risk level by presetting the risk threshold, simplifying the process of risk classification. By setting different levels of warning information, the measures to be taken for different risk levels are clearly defined, enhancing the pertinence and effectiveness of risk response. The present embodiment can quickly respond according to the risk assessment result, timely start the corresponding warning mechanism, and effectively reduce the operation risk of the offshore wind farm.

[0053] Optionally, in other embodiments, the risk threshold can also be dynamically adjusted to adapt to changes in the operating environment of the offshore wind farm, improving the adaptability and stability of the risk warning system.

[0054] For better understanding of the process of the above risk assessment result generation method, the implementation method flow of the above risk assessment result generation is described in combination with optional embodiments below, but not used to limit the technical solutions of the embodiments of the present application.

[0055] A risk assessment result generation method is provided in the present embodiment, which includes the following steps:

[0056] Step S301: The environmental risks of the offshore wind farm are decomposed according to the hierarchical structure by using the risk breakdown structure (RBS), and the following hierarchy is obtained:

[0057] The first layer includes the overall environmental risk.

[0058] The second layer includes five environmental risk factors: wind, wave, current, sea ice, and storm surge.

[0059] The data matrix M corresponding to the environmental risk data of these risk factors is, for example:

[0060] M = [M 风 , M 浪 , M 流 , M 海冰 , M 风暴潮 ].

[0061] Wherein, the historical monitoring data and the field monitoring data of the environmental risk data of each risk factor.

[0062] The third layer includes specific risk categories of each environmental factor. For example, the risk categories of wind can be divided into wind speed exceeding the standard and wind direction change anomaly. The risk categories of sea ice can be divided into sea ice thickness exceeding the standard and floating ice anomaly.

[0063] The fourth layer includes specific risk events corresponding to each risk category and their impact degree.

[0064] Step S302: For x risk events of the same environmental factor, the occurrence probability P i and the impact degree I i of the i-th risk event are calculated, and the risk value R x corresponding to the same environmental factor is obtained: x is a positive integer.

[0065] Step S303: The comprehensive weight W i of the risk value R x is calculated by determining the expert scoring method based on the analytic hierarchy process:

[0066]

[0067] Wherein, λ kis the expert weight, P i,k and I i,k respectively represent the occurrence probability and the impact degree of the ith risk event in the kth expert score.

[0068] Step S304: Calculate the comprehensive risk total value R total , which represents the overall environmental risk of the entire wind farm:

[0069]

[0070] Step S305: Divide the risk level by the preset risk threshold (including the first preset threshold R low , the second preset threshold R high ).

[0071] R total <R low : low risk.

[0072] R low ≤ R total <R high : medium risk.

[0073] R total ≥ R high : high risk.

[0074] Step S306: The risk assessment model can dynamically update the environmental risk as the real-time input of the forecast data. By using the latest wind, wave, current and other data, P i and I i are continuously adjusted, and the latest comprehensive risk value R total is obtained by calculation, providing support for real-time decision-making of the wind farm.

[0075] The above method first classifies the environmental data of the offshore wind farm, and identifies the environmental risk factors such as wind, wave, current, sea ice, storm surge, etc. Then, by using the risk decomposition structure method, each environmental factor is subdivided into multiple risk subcategories, and the occurrence probability and impact degree of each risk event are calculated to form a risk value. Then, by accumulating the products, the comprehensive risk value of a specific environmental factor is obtained. At the same time, the risk weights of different environmental factors are determined by using the analytic hierarchy process, and the overall risk value of the offshore wind farm is calculated. Finally, according to the preset risk threshold, the overall risk value is compared with it to determine the risk level, and the corresponding risk assessment result is generated, realizing the real-time monitoring and early warning of the environmental risk of the offshore wind farm. In the entire use process, the technical scheme of the present application can dynamically respond to environmental changes and update the risk assessment result in real time, providing strong technical support for the safe operation of the offshore wind farm.

[0076] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software on a general hardware platform as necessary, and of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the form of a part that contributes to the prior art. The computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk) and includes a plurality of instructions for causing a server device (which can be a mobile phone, a computer, a server, or a network device) to execute the method of each embodiment of the present application.

[0077] Figure 3 is a structural block diagram of a risk assessment result generation device according to an embodiment of the present application; as shown in Figure 3 , comprising:

[0078] The classification module 32 is configured to classify the collected environmental data of the offshore wind farm to obtain a plurality of environmental risk data.

[0079] The calculation module 34 is configured to determine a first environmental factor corresponding to first environmental risk data, calculate a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtain a target risk value corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data.

[0080] The generation module 36 is configured to generate a risk assessment result according to a comparison result of the target risk value and a risk threshold.

[0081] Through the above device, the collected environmental data of the offshore wind farm is classified to obtain a plurality of environmental risk data; a first environmental factor corresponding to first environmental risk data is determined, a first risk value of the first environmental factor is calculated according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and a target risk value corresponding to all environmental factors is obtained based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data; a risk assessment result is generated according to a comparison result of the target risk value and a risk threshold. The present embodiment effectively identifies different environmental factors by classifying complex and variable marine environmental data, provides a basis for subsequent risk quantification, solves the technical problem of low accuracy of the risk assessment result of the offshore wind farm in the related art, and further improves the accuracy and reliability of risk assessment.

[0082] In an example embodiment, the computing module is further configured to: determine a plurality of risk sub-categories included in the first risk category, and traverse the plurality of risk sub-categories; for each traversed first risk sub-category, determine a first risk event corresponding to the first risk sub-category from all risk events corresponding to the first risk category; obtain first environmental risk data corresponding to the first risk event from the first environmental risk data; calculate a first occurrence probability and a first risk impact degree of the first risk event according to the first environmental risk data, and calculate the first risk value according to the first occurrence probability and the first risk impact degree.

[0083] In an example embodiment, the computing module is further configured to: obtain a first occurrence number of the first risk event and a second occurrence number of all risk events from the first environmental risk data; determine the first occurrence probability according to a ratio of the first occurrence number to the second occurrence number; determine a value interval in which the ratio is located, and determine the first risk impact degree according to an interval level corresponding to the value interval.

[0084] In an example embodiment, the computing module is further configured to: in a case where the first risk sub-category is traversed, obtain a first product of the first occurrence probability and the first risk impact degree; after traversing the plurality of risk sub-categories, obtain a plurality of first products, and determine the first risk value according to a sum of the plurality of first products.

[0085] In an example embodiment, the computing module is further configured to: determine a first risk weight corresponding to the first risk value; determine a second risk value corresponding to other environmental factors and a second risk weight corresponding to the second risk value, wherein the other environmental factors represent environmental factors other than the first environmental factor in the all environmental factors; calculate a second product of the first risk value and the first risk weight, and calculate a third product of the second risk value and the second risk weight; and determine the target risk value based on a sum of the second product and the third product.

[0086] In an example embodiment, the risk threshold value includes at least one of: a first preset threshold value and a second preset threshold value, the first preset threshold value being smaller than the second preset threshold value, and the generating module is further configured to implement one of:

[0087] Scheme 1, in a case where the comparison result is used to indicate that the target risk value is smaller than the first preset threshold value, determining that the risk level of the offshore wind farm is a first level, and generating the risk assessment result based on the first level and pre-warning information corresponding to the first level.

[0088] In a case where the comparison result is used to indicate that the target risk value is equal to or greater than the first preset threshold value and the target risk value is greater than a second preset threshold value, the method further includes: determining a second level for the risk level of the offshore wind farm; and generating the risk assessment result based on the second level and early warning information corresponding to the second level.

[0089] In a case where the comparison result is used to indicate that the target risk value is equal to or greater than the second preset threshold value, the method further includes: determining a third level for the risk level of the offshore wind farm; and generating the risk assessment result based on the third level and early warning information corresponding to the third level.

[0090] Embodiments of the present application also provide a storage medium including a stored program, wherein the program performs any of the above methods when executed.

[0091] Optionally, in the present embodiment, the storage medium can be configured to store program code for performing the following steps:

[0092] S1, classifying the collected environmental data of the offshore wind farm to obtain a plurality of environmental risk data;

[0093] S2, determining a first environmental factor corresponding to first environmental risk data, calculating a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtaining a target risk value corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data;

[0094] S3, generating a risk assessment result according to a comparison result of the target risk value and a risk threshold value.

[0095] Embodiments of the present application also provide an electronic device including a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program to perform the steps in any of the above method embodiments.

[0096] Optionally, the electronic device can further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0097] Optionally, in the present embodiment, the processor can be configured to execute the following steps through the computer program:

[0098] S1, classifying the collected environmental data of the offshore wind farm to obtain a plurality of environmental risk data;

[0099] S2, determine a first environmental factor corresponding to the first environmental risk data, calculate a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtain a target risk value corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data;

[0100] S3, generate a risk assessment result according to a comparison result of the target risk value and a risk threshold.

[0101] Optionally, in the embodiment, the storage medium can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0102] Optionally, the embodiment of the present application further provides a computer program product, and the computer program product includes a computer program.

[0103] Optionally, the embodiment of the present application further provides another computer program product, which includes a non-volatile computer readable storage medium storing a computer program.

[0104] Optionally, the embodiment of the present application further provides a computer program, which includes computer instructions stored in a computer readable storage medium.

[0105] Optionally, specific examples in the embodiment can refer to examples described in the above embodiments and optional implementation manners, and the embodiment will not be described here.

[0106] It is apparent that those skilled in the art can, without departing from the spirit of the present application, make various changes and modifications of the modules or steps of the present application described above, which can be implemented by general computing devices, and can be centralized on a single computing device or distributed on a network composed of multiple computing devices, and optionally, can be implemented by program codes executable by computing devices, so that they can be stored in storage devices and executed by computing devices, and in some cases, the steps shown or described can be executed in different order, or can be made into individual integrated circuit modules, or multiple modules or steps can be made into a single integrated circuit module. Thus, the present application is not limited to any particular combination of hardware and software.

[0107] The above description is only the preferred embodiments of the present application, and it should be pointed out that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method for generating risk assessment results, characterized in that: include: Classify the collected environmental data of offshore wind farms to obtain various environmental risk data; determining a first environmental factor corresponding to first environmental risk data, calculating a first risk value for the first environmental factor based on a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtaining target risk values ​​corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data; A risk assessment result is generated based on a comparison result between the target risk value and the risk threshold.

2. The method for generating risk assessment results according to claim 1, characterized in that: Calculating a first risk value of the first environmental factor according to a first risk category corresponding to the first environmental factor and the first environmental risk data includes: Determine a plurality of risk subcategories included in the first risk category, and traverse the plurality of risk subcategories; for each first risk subcategory traversed, determine a first risk event corresponding to the first risk subcategory from all risk events corresponding to the first risk category; Acquire first environmental risk data corresponding to the first risk event from the first environmental risk data; A first occurrence probability and a first risk impact of the first risk event are calculated based on the first environmental risk data, and the first risk value is calculated based on the first occurrence probability and the first risk impact.

3. The method for generating risk assessment results according to claim 2, characterized in that: Calculating a first occurrence probability and a first risk impact of the first risk event according to the first environmental risk data includes: Obtaining a first occurrence number of the first risk event and a second occurrence number of all risk events from the first environmental risk data; determining the first occurrence probability according to a ratio of the first occurrence number to the second occurrence number; Determine a value interval for the ratio, and determine the first risk impact according to an interval level corresponding to the value interval.

4. The method for generating risk assessment results according to claim 2, characterized in that: Calculating the first risk value according to the first occurrence probability and the first risk impact includes: In case of traversing to the first risk subcategory, obtaining a first product of the first occurrence probability and the first risk impact; After traversing the plurality of risk subcategories, a plurality of first products are obtained, and the first risk value is determined according to a sum of the plurality of first products.

5. The method for generating risk assessment results according to claim 4, characterized in that: Based on the first risk value, the target risk values ​​corresponding to all environmental factors are obtained, including: determining a first risk weight corresponding to the first risk value; Determining a second risk value corresponding to other environmental factors and a second risk weight corresponding to the second risk value, wherein the other environmental factors represent environmental factors among all the environmental factors except the first environmental factor; Calculating a second product of the first risk value and the first risk weight, and calculating a third product of the second risk value and the second risk weight; The target risk value is determined based on a sum of the second product and the third product.

6. The method for generating risk assessment results according to claim 1, wherein: The risk threshold includes at least one of the following: a first preset threshold and a second preset threshold, wherein the first preset threshold is less than the second preset threshold, and the risk assessment result is generated based on the comparison result between the target risk value and the risk threshold, including one of the following: If the comparison result indicates that the target risk value is less than the first preset threshold, determining that the risk level of the offshore wind farm is a first level, and generating the risk assessment result based on the first level and the warning information corresponding to the first level; If the comparison result indicates that the target risk value is equal to or greater than the first preset threshold, and the target risk value is greater than a second preset threshold, determining that the risk level of the offshore wind farm is a second level, and generating the risk assessment result based on the second level and the warning information corresponding to the second level; When the comparison result indicates that the target risk value is equal to or greater than the second preset threshold, the risk level of the offshore wind farm is determined to be the third level, and the risk assessment result is generated based on the third level and the warning information corresponding to the third level.

7. A device for generating risk assessment results, characterized in that: include: The classification module is used to classify the collected environmental data of offshore wind farms to obtain various environmental risk data; a calculation module, configured to determine a first environmental factor corresponding to first environmental risk data, calculate a first risk value for the first environmental factor based on a first risk category corresponding to the first environmental factor and the first environmental risk data, and obtain target risk values ​​corresponding to all environmental factors based on the first risk value, wherein the first environmental risk data is obtained from the plurality of environmental risk data; A generating module is used to generate a risk assessment result based on the comparison result of the target risk value and the risk threshold.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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