Hydropower station intelligent safety management and control method and system

Abstract

The invention discloses an intelligent safety management and control method and system for a hydropower station, and the method comprises the steps: obtaining the operation data of the hydropower station, analyzing the operation data, and determining the abnormal parameter data in the operation data; performing anomaly evaluation on the anomaly parameter data of the hydropower station to obtain an anomaly evaluation value of the hydropower station; judging whether the state of the hydropower station is abnormal or not according to the abnormal evaluation value, and determining the safety early warning level of the hydropower station according to the abnormal evaluation value after judging that the state of the hydropower station is abnormal; and setting a safety adjustment coefficient of the hydropower station according to the abnormal evaluation value, and performing safety control adjustment on the operation data of the hydropower station according to the safety adjustment coefficient. According to the invention, the operation condition of the hydropower station can be monitored in real time, abnormal conditions can be found in time, safety early warning can be given out in time, a time window is provided for taking prevention measures, the safety early warning level is quantified and the adjustment strategy of the operation data is determined through the abnormal evaluation value, and safety management and control adjustment can be automatically carried out on the operation data in time. And human errors are reduced.

Description

Technical Field

[0001] The present invention relates to the field of hydropower technology, and in particular to an intelligent safety management and control method and system for a hydropower station. Background Art

[0002] In today's rapidly developing energy sector, hydropower stations, as a clean and renewable energy supply method, play an increasingly important role worldwide. With the advancement of technology and the growth of energy demand, the safe operation of hydropower stations has become a key link in ensuring energy supply, maintaining the ecological environment and ensuring the safety of people's lives and property.

[0003] However, traditional safety management and control methods for hydropower stations face many challenges, such as the lack of comprehensive analysis of data, which affects the accuracy and timeliness of decision-making. When emergencies occur, the emergency response of traditional methods is not fast and flexible enough, and timely management and control adjustments cannot be made, resulting in great threats to the safety of hydropower stations. Therefore, the introduction of intelligent safety management and control methods has become an inevitable trend in the safety management of hydropower stations. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for intelligent safety management of a hydropower station, comprising:

[0005] Obtain the operating data of the hydropower station, analyze the operating data, and determine the abnormal parameter data in the operating data;

[0006] Performing abnormal evaluation on abnormal parameter data of the hydropower station to obtain an abnormal evaluation value of the hydropower station;

[0007] Determine whether the state of the hydropower station is abnormal according to the abnormal evaluation value, and after determining that the state of the hydropower station is abnormal, determine the safety warning level of the hydropower station according to the abnormal evaluation value;

[0008] The safety adjustment coefficient of the hydropower station is set according to the abnormal assessment value, and the operating data of the hydropower station is safely controlled and adjusted according to the safety adjustment coefficient.

[0009] Furthermore, the obtaining of the operating data of the hydropower station and analyzing the operating data to determine abnormal parameter data in the operating data includes:

[0010] Acquire the operation data of the hydropower station, and divide the operation data into several parameter data groups according to parameter types;

[0011] Input each parameter data group into a preset abnormal data screening model to obtain abnormal data corresponding to each parameter data group;

[0012] The number of data corresponding to the abnormal data of each parameter data group is counted, and the parameter data group whose data number exceeds the preset threshold is selected to be determined as the abnormal parameter data in the operation data.

[0013] Further, the abnormal parameter data of the hydropower station is evaluated abnormally to obtain an abnormal evaluation value of the hydropower station, including:

[0014] Acquire abnormal parameter data of the hydropower station, and group the abnormal parameter data according to parameter types to obtain several abnormal parameter data groups;

[0015] Obtaining the normal parameter data group corresponding to each abnormal parameter data group, and calculating the standard deviation of each abnormal parameter data group and the corresponding normal parameter data group;

[0016] Calculate the difference between the standard deviation of each abnormal parameter data group and the corresponding normal parameter data group, and evaluate the difference to obtain the abnormal evaluation value of each abnormal parameter data group;

[0017] The abnormal evaluation value of the hydropower station is determined based on the abnormal evaluation value corresponding to each abnormal parameter data group and the preset weight.

[0018] Further, the abnormal evaluation value of the hydropower station is determined based on the abnormal evaluation value and weight corresponding to each abnormal parameter data group, including:

[0019]

[0020] Among them, L is the abnormal evaluation value of the hydropower station, exp is the natural exponential function, n is the number of abnormal parameter data groups, Mi is the abnormal evaluation value of the i-th abnormal parameter data group, and αi is the preset weight of the i-th abnormal parameter data group.

[0021] Further, judging whether the state of the hydropower station is abnormal according to the abnormal evaluation value includes:

[0022] Compare the abnormal evaluation value with the preset standard evaluation value, and determine whether the state of the hydropower station is abnormal based on the comparison result;

[0023] If the abnormal evaluation value exceeds the preset standard evaluation value, the status of the hydropower station is judged to be abnormal;

[0024] If the abnormal evaluation value does not exceed the preset standard evaluation value, the status of the hydropower station is judged to be normal.

[0025] Further, determining the safety warning level of the hydropower station according to the abnormal evaluation value includes:

[0026] A corresponding relationship between the safety warning level and the abnormal assessment value interval is preset. For each abnormal assessment value interval, a corresponding safety warning level is associated;

[0027] An abnormal assessment value is obtained, and based on a mapping relationship between an abnormal assessment value interval to which the abnormal assessment value belongs and a corresponding relationship between a safety warning level and an abnormal assessment value interval, a safety warning level corresponding to the abnormal assessment value interval is selected.

[0028] Furthermore, the safety adjustment coefficient of the hydropower station is set according to the abnormal evaluation value, and the operation data of the hydropower station is safety controlled and adjusted according to the safety adjustment coefficient, including:

[0029] Preset the standard evaluation value and standard adjustment coefficient, and calculate the difference between the abnormal evaluation value and the standard evaluation value;

[0030] The standard adjustment coefficient is corrected according to the difference, and the corrected standard adjustment coefficient is set as the safety adjustment coefficient of the hydropower station;

[0031] Multiply the safety adjustment coefficient by the operating data of the hydropower station to complete the safety control and adjustment of the operating data of the hydropower station.

[0032] The present invention also provides an intelligent safety management and control system for a hydropower station, comprising:

[0033] An acquisition module is used to acquire the operation data of the hydropower station, analyze the operation data, and determine abnormal parameter data in the operation data;

[0034] An evaluation module, used to perform abnormal evaluation on abnormal parameter data of the hydropower station to obtain an abnormal evaluation value of the hydropower station;

[0035] A judgment module, used to judge whether the state of the hydropower station is abnormal according to the abnormal evaluation value, and after judging that the state of the hydropower station is abnormal, determine the safety warning level of the hydropower station according to the abnormal evaluation value;

[0036] The adjustment module is used to set the safety adjustment coefficient of the hydropower station according to the abnormal evaluation value, and to perform safety management and control on the operation data of the hydropower station according to the safety adjustment coefficient.

[0037] Compared with the prior art, the intelligent safety management and control method and system of a hydropower station according to the embodiment of the present invention has the following beneficial effects:

[0038] The present invention can monitor the operation of the hydropower station in real time, discover abnormal situations in time, and issue safety warnings in time, providing a time window for taking preventive measures. It can also quantify the safety warning level and determine the adjustment strategy of the operation data through abnormal evaluation values, and timely and automatically perform safety management and adjustment of the operation data to reduce human errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the process structure of the intelligent safety management and control method of a hydropower station in an embodiment of the present invention;

[0040] Figure 2 It is a schematic diagram of the composition of the intelligent safety management and control system of a hydropower station in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0042] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0043] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying a relative degree of importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0044] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technical personnel in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0045] like Figure 1As shown, in an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, including: S100: acquiring operating data of a hydropower station, analyzing the operating data, and determining abnormal parameter data in the operating data; S200: performing an abnormality assessment on the abnormal parameter data of the hydropower station to obtain an abnormality assessment value of the hydropower station; S300: judging whether the state of the hydropower station is abnormal according to the abnormal assessment value, and after judging that the state of the hydropower station is abnormal, determining the safety warning level of the hydropower station according to the abnormal assessment value; S400: setting a safety adjustment coefficient of the hydropower station according to the abnormal assessment value, and performing safety management and control adjustment on the operating data of the hydropower station according to the safety adjustment coefficient.

[0046] Furthermore, the present invention can monitor the operation of the hydropower station in real time, discover abnormal situations in time, and issue safety warnings in time, providing a time window for taking preventive measures. It can also quantify the safety warning level and determine the adjustment strategy of the operation data through abnormal evaluation values, and timely and automatically perform safety management and adjustment of the operation data to reduce human errors.

[0047] In an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, wherein the operating data of the hydropower station is obtained, and the operating data is analyzed to determine abnormal parameter data in the operating data, including: obtaining the operating data of the hydropower station, and dividing the operating data into a plurality of parameter data groups according to parameter type; inputting each parameter data group into a preset abnormal data screening model to obtain abnormal data corresponding to each parameter data group; counting the number of data corresponding to the abnormal data of each parameter data group, and selecting the parameter data group whose data number exceeds a preset threshold value to determine it as the abnormal parameter data in the operating data.

[0048] Specifically, the operation data of the hydropower station is collected through sensors, monitoring systems, maintenance records and other channels, and the data from different systems are integrated together to ensure the integrity and consistency of the data. The operation data is divided into different data groups according to the parameter type (such as water level, flow, temperature, etc.); one or more preset abnormal data screening models are selected, and each data group is input into the abnormal data screening model. The model will output the abnormal data of each data group. These abnormal values ​​may be caused by equipment failure, environmental changes or other abnormal conditions; the number of abnormal data in each data group is counted to facilitate the assessment of the severity of the abnormal data; a threshold is set according to historical data and business needs to determine whether the abnormal data exceeds the normal range, and the data groups with the number of abnormal data exceeding the preset threshold are screened out. The parameters corresponding to these data groups are abnormal parameter data. Through the above steps, the hydropower station can realize real-time monitoring and analysis of the operation data, detect abnormal conditions in time, and help ensure the long-term stable operation of the hydropower station.

[0049] In an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, wherein abnormal parameter data of the hydropower station is evaluated abnormally to obtain an abnormal evaluation value of the hydropower station, including: obtaining abnormal parameter data of the hydropower station, and grouping the abnormal parameter data according to parameter type to obtain a plurality of abnormal parameter data groups; obtaining a normal parameter data group corresponding to each abnormal parameter data group, and calculating the standard deviation of each abnormal parameter data group and the corresponding normal parameter data group respectively; calculating the difference between the standard deviation of each abnormal parameter data group and the corresponding normal parameter data group, and evaluating and valuing the difference to obtain an abnormal evaluation value of each abnormal parameter data group; and determining the abnormal evaluation value of the hydropower station based on the abnormal evaluation value corresponding to each abnormal parameter data group and a preset weight.

[0050] Specifically, abnormal parameter data are screened out from the operation data of the hydropower station, and the abnormal parameter data are divided into different data groups according to the parameter type; for each abnormal parameter data group, the corresponding normal parameter data group is found, and these data groups contain parameter values ​​under normal operating conditions; for each abnormal parameter data group and the corresponding normal parameter data group, their standard deviation is calculated, and the standard deviation is a statistic that measures the degree of data dispersion and reflects the degree of deviation of the data from the average value; the difference between the standard deviation of each abnormal parameter data group and the standard deviation of the corresponding normal parameter data group is calculated, and this difference reflects the difference between the degree of dispersion of the abnormal parameter data group and the degree of dispersion under normal operating conditions, and the calculated difference is evaluated to determine the abnormal evaluation value of each abnormal parameter data group, and this evaluation value reflects the degree of abnormality of the abnormal parameter data group; according to business needs and expert opinions, a preset weight is assigned to each abnormal parameter data group, and the weight reflects the importance of different parameters in safety assessment, and the abnormal evaluation value of each abnormal parameter data group is multiplied by the corresponding weight, and then these products are added to obtain the abnormal evaluation value of the hydropower station, which comprehensively considers the influence of all abnormal parameter data groups and can be used to judge the overall safety status of the hydropower station. Through the above steps, the hydropower station can conduct in-depth analysis of abnormal parameter data, evaluate the degree of abnormality, and determine the overall safety status of the hydropower station. This method helps to improve the safety management level of the hydropower station and ensure the stable operation of the hydropower station.

[0051] In an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, wherein the abnormal evaluation value of the hydropower station is determined based on the abnormal evaluation value and weight corresponding to each abnormal parameter data group, including:

[0052]

[0053] Among them, L is the abnormal evaluation value of the hydropower station, exp is the natural exponential function, n is the number of abnormal parameter data groups, Mi is the abnormal evaluation value of the i-th abnormal parameter data group, and αi is the preset weight of the i-th abnormal parameter data group.

[0054] In an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, wherein judging whether the state of the hydropower station is abnormal based on an abnormal evaluation value comprises: comparing the abnormal evaluation value with a preset standard evaluation value, and judging whether the state of the hydropower station is abnormal based on the comparison result; if the abnormal evaluation value exceeds the preset standard evaluation value, judging that the state of the hydropower station is abnormal; if the abnormal evaluation value does not exceed the preset standard evaluation value, judging that the state of the hydropower station is normal.

[0055] Specifically, according to the safety standards and business needs of the hydropower station, a standard evaluation value is set. This value is the benchmark for measuring the safety status of the hydropower station. It is usually determined based on historical data and industry standards. The abnormal evaluation value calculated in real time is compared with the preset standard evaluation value; if the abnormal evaluation value exceeds the preset standard evaluation value, it means that the operating status of the hydropower station exceeds the normal safety threshold, and there may be potential safety risks; according to the comparison result, if the abnormal evaluation value exceeds the preset standard evaluation value, the status of the hydropower station is judged to be abnormal; if the abnormal evaluation value does not exceed the preset standard evaluation value, the status of the hydropower station is judged to be normal, indicating that the operation of the hydropower station is within a safe range. Through the above steps, the hydropower station can evaluate and judge the operating status in real time to ensure the safe operation of the hydropower station. This method helps to improve the safety management level of hydropower stations and reduce the incidence of safety accidents.

[0056] In an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, wherein the safety warning level of the hydropower station is determined according to the abnormal assessment value, including: presetting a safety warning level-abnormal assessment value interval correspondence relationship, wherein the safety warning level-abnormal assessment value interval correspondence relationship is associated with a corresponding safety warning level for each abnormal assessment value interval; obtaining the abnormal assessment value, and based on a mapping relationship between the abnormal assessment value interval to which the abnormal assessment value belongs within the safety warning level-abnormal assessment value interval correspondence relationship, selecting the safety warning level corresponding to the abnormal assessment value interval.

[0057] Specifically, according to the safety requirements and operation experience of the hydropower station, a series of corresponding relationships between safety warning levels and abnormal assessment value intervals are pre-set, and the range of abnormal assessment values ​​is divided into multiple intervals. Each interval corresponds to a specific safety warning level. The safety warning level usually includes "normal", "warning", "attention", "emergency", etc. The higher the level, the greater the potential safety risk; the system calculates the abnormal assessment value of the hydropower station in real time. This is a comprehensive indicator based on the analysis of the operation data of the hydropower station, which reflects the current safety status of the hydropower station. According to the interval to which the abnormal assessment value belongs, the corresponding interval is found in the preset safety warning level-abnormal assessment value interval correspondence relationship. According to the interval found, the safety warning level corresponding to the interval is selected, and the selected safety warning level is applied to the operation status of the hydropower station, and the corresponding safety response measures are initiated. Through the above steps, the hydropower station can quickly determine the current safety warning level according to the abnormal assessment value calculated in real time, and take corresponding safety measures. This method helps to improve the safety management level of the hydropower station and ensure the stable operation of the hydropower station.

[0058] In an embodiment of the present application, a method for intelligent safety management and control of a hydropower station is provided, wherein a safety adjustment coefficient of the hydropower station is set according to an abnormal evaluation value, and operation data of the hydropower station is safety managed and adjusted according to the safety adjustment coefficient, including: presetting a standard evaluation value and a standard adjustment coefficient, and calculating the difference between the abnormal evaluation value and the standard evaluation value; correcting the standard adjustment coefficient according to the difference, and setting the corrected standard adjustment coefficient as the safety adjustment coefficient of the hydropower station; and multiplying the safety adjustment coefficient by the operation data of the hydropower station to complete the safety management and control of the operation data of the hydropower station.

[0059] Specifically, according to the safety standards and business needs of the hydropower station, a standard assessment value is set. This value is the benchmark for measuring the safety status of the hydropower station. It is usually determined based on historical data and industry standards. In order to ensure that the hydropower station operates within a safe range, a standard adjustment coefficient needs to be set. This coefficient is the standard for adjusting the operating data of the hydropower station to ensure that the operating status of the hydropower station remains within the preset safety assessment value range; the system calculates the abnormal assessment value of the hydropower station in real time and compares it with the preset standard assessment value, calculates the difference between the abnormal assessment value and the standard assessment value, and this difference reflects the difference between the current operating status of the hydropower station and the preset safety status. The size and direction of the difference are analyzed to determine whether the standard adjustment coefficient needs to be increased or decreased. The standard adjustment coefficient is corrected according to the difference to make it more consistent with the current operating status of the hydropower station. The corrected standard adjustment coefficient is set as the safety adjustment coefficient of the hydropower station to guide the adjustment of the operating data of the hydropower station; the safety adjustment coefficient is multiplied by the operating data of the hydropower station to complete the safety control and adjustment of the operating data of the hydropower station. Through adjustment, the operating data of the hydropower station is kept within the preset safety assessment value range to ensure the safe operation of the hydropower station. Through the above steps, the hydropower station can conduct safety control and adjustment of the operating data based on the real-time calculated abnormal assessment value and the corrected standard adjustment coefficient to ensure the stable operation of the hydropower station. This method helps to improve the safety management level of the hydropower station and reduce the occurrence rate of safety accidents.

[0060] like Figure 2 As shown, in an embodiment of the present application, a hydropower station intelligent safety management and control system is provided, including: an acquisition module, used to acquire the operating data of the hydropower station, analyze the operating data, and determine the abnormal parameter data in the operating data; an evaluation module, used to perform an abnormal evaluation on the abnormal parameter data of the hydropower station to obtain an abnormal evaluation value of the hydropower station; a judgment module, used to judge whether the state of the hydropower station is abnormal according to the abnormal evaluation value, and after judging that the state of the hydropower station is abnormal, determine the safety warning level of the hydropower station according to the abnormal evaluation value; an adjustment module, used to set the safety adjustment coefficient of the hydropower station according to the abnormal evaluation value, and perform safety management and control adjustment on the operating data of the hydropower station according to the safety adjustment coefficient.

[0061] In summary, the embodiment of the present invention provides a method and system for intelligent safety management and control of a hydropower station, which includes: obtaining the operating data of the hydropower station, analyzing it, and determining the abnormal parameter data therein; performing an abnormal evaluation on the abnormal parameter data of the hydropower station to obtain the abnormal evaluation value of the hydropower station; judging whether the state of the hydropower station is abnormal according to the abnormal evaluation value, and after judging that the state of the hydropower station is abnormal, determining the safety warning level of the hydropower station according to the abnormal evaluation value; setting the safety adjustment coefficient of the hydropower station according to the abnormal evaluation value, and performing safety management and control on the operating data of the hydropower station according to the safety adjustment coefficient. The present invention can monitor the operation of the hydropower station in real time, discover abnormal situations in time, and issue safety warnings in time, provide a time window for taking preventive measures, and quantify the safety warning level and determine the adjustment strategy of the operating data through the abnormal evaluation value, and timely and automatically perform safety management and control on the operating data to reduce human errors.

[0062] Finally, it should be noted that: Obviously, a person skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technology, the present invention is also intended to include these modifications and variations.

[0063] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Technical personnel in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0064] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0065] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings. However, it is easy for a person skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, a person skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for intelligent safety management and control of a hydropower station, characterized in that: include: Obtain the operating data of the hydropower station, analyze the operating data, and determine the abnormal parameter data in the operating data; Performing abnormal evaluation on abnormal parameter data of the hydropower station to obtain an abnormal evaluation value of the hydropower station; Determine whether the state of the hydropower station is abnormal according to the abnormal evaluation value, and after determining that the state of the hydropower station is abnormal, determine the safety warning level of the hydropower station according to the abnormal evaluation value; The safety adjustment coefficient of the hydropower station is set according to the abnormal assessment value, and the operating data of the hydropower station is safely controlled and adjusted according to the safety adjustment coefficient.

2. A method for intelligent safety management and control of a hydropower station according to claim 1, characterized in that: The step of obtaining the operating data of the hydropower station and analyzing the operating data to determine abnormal parameter data in the operating data includes: Acquire the operation data of the hydropower station, and divide the operation data into several parameter data groups according to parameter types; Input each parameter data group into a preset abnormal data screening model to obtain abnormal data corresponding to each parameter data group; The number of data corresponding to the abnormal data of each parameter data group is counted, and the parameter data group whose data number exceeds the preset threshold is selected to be determined as the abnormal parameter data in the operation data.

3. A method for intelligent safety management and control of a hydropower station according to claim condition 2, characterized in that: The abnormal parameter data of the hydropower station is evaluated abnormally to obtain an abnormal evaluation value of the hydropower station, including: Acquire abnormal parameter data of the hydropower station, and group the abnormal parameter data according to parameter types to obtain several abnormal parameter data groups; Obtaining the normal parameter data group corresponding to each abnormal parameter data group, and calculating the standard deviation of each abnormal parameter data group and the corresponding normal parameter data group; Calculate the difference between the standard deviation of each abnormal parameter data group and the corresponding normal parameter data group, and evaluate the difference to obtain the abnormal evaluation value of each abnormal parameter data group; The abnormal evaluation value of the hydropower station is determined based on the abnormal evaluation value corresponding to each abnormal parameter data group and the preset weight.

4. A method for intelligent safety management and control of a hydropower station according to claim condition 3, characterized in that: The method of determining the abnormal evaluation value of the hydropower station based on the abnormal evaluation value and weight corresponding to each abnormal parameter data group includes: Among them, L is the abnormal evaluation value of the hydropower station, exp is the natural exponential function, n is the number of abnormal parameter data groups, Mi is the abnormal evaluation value of the i-th abnormal parameter data group, and αi is the preset weight of the i-th abnormal parameter data group.

5. A method for intelligent safety management and control of a hydropower station according to claim condition 3, characterized in that: The step of judging whether the state of the hydropower station is abnormal according to the abnormal evaluation value includes: Compare the abnormal evaluation value with the preset standard evaluation value, and determine whether the state of the hydropower station is abnormal based on the comparison result; If the abnormal evaluation value exceeds the preset standard evaluation value, the status of the hydropower station is judged to be abnormal; If the abnormal evaluation value does not exceed the preset standard evaluation value, the status of the hydropower station is judged to be normal.

6. A method for intelligent safety management and control of a hydropower station according to claim condition 5, characterized in that: Determining the safety warning level of the hydropower station according to the abnormal evaluation value includes: A corresponding relationship between the safety warning level and the abnormal assessment value interval is preset. For each abnormal assessment value interval, a corresponding safety warning level is associated; An abnormal assessment value is obtained, and based on a mapping relationship between an abnormal assessment value interval to which the abnormal assessment value belongs and a corresponding relationship between a safety warning level and an abnormal assessment value interval, a safety warning level corresponding to the abnormal assessment value interval is selected.

7. A method for intelligent safety management and control of a hydropower station according to claim 6, characterized in that: The safety adjustment coefficient of the hydropower station is set according to the abnormal evaluation value, and the operation data of the hydropower station is safely controlled and adjusted according to the safety adjustment coefficient, including: Preset the standard evaluation value and standard adjustment coefficient, and calculate the difference between the abnormal evaluation value and the standard evaluation value; The standard adjustment coefficient is corrected according to the difference, and the corrected standard adjustment coefficient is set as the safety adjustment coefficient of the hydropower station; Multiply the safety adjustment coefficient by the operating data of the hydropower station to complete the safety control and adjustment of the operating data of the hydropower station.

8. An intelligent safety management and control system for a hydropower station, characterized in that: include: An acquisition module is used to acquire the operation data of the hydropower station, analyze the operation data, and determine abnormal parameter data in the operation data; An evaluation module, used to perform abnormal evaluation on abnormal parameter data of the hydropower station to obtain an abnormal evaluation value of the hydropower station; A judgment module, used to judge whether the state of the hydropower station is abnormal according to the abnormal evaluation value, and after judging that the state of the hydropower station is abnormal, determine the safety warning level of the hydropower station according to the abnormal evaluation value; The adjustment module is used to set the safety adjustment coefficient of the hydropower station according to the abnormal evaluation value, and to perform safety management and control on the operation data of the hydropower station according to the safety adjustment coefficient.

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