CN116307700A - Electric power system and risk assessment device and method thereof - Google Patents
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Abstract
The application relates to a power system and a risk assessment device and method thereof, comprising a data acquisition module, an index determination module, a risk assessment module and a risk early warning module, wherein the data acquisition module is used for acquiring the running state data of power equipment of each assessment section, the index determination module is used for correspondingly determining the risk assessment index data of each assessment section according to the running state data of each assessment section, the risk assessment module is used for inputting each risk assessment index data into a distributed intelligent assessment model to obtain a risk assessment deviation result of each assessment section, and sending a risk early warning signal to the risk early warning module under the condition that the risk assessment deviation result exceeds a set risk threshold; the risk early warning module is used for carrying out risk early warning prompt of each assessment section according to the risk early warning signals, and the purpose of improving the reliability of risk assessment can be achieved by splitting a whole power grid into a plurality of distributed regional power grid coverage areas and respectively carrying out risk assessment.
Description
Technical Field
The present disclosure relates to the field of power automation technology, and in particular, to a power system and a risk assessment device and method thereof.
Background
The scale of the power system in China is continuously enlarged, and the importance is also increasing. The power system is also called a power network and consists of a multi-stage voltage power substation and a power transmission and distribution line, and comprises three units of power substation, power transmission and power distribution. The main task of the power grid is to transmit and distribute electric energy, ensure normal electricity utilization of industry and residents, and is important to risk assessment of the power grid in order to ensure safe and stable operation of the power grid.
In the existing risk assessment mode for the power grid, most of the existing risk assessment modes still mainly depend on manual verification and check, early warning is carried out after abnormal data conditions are found, and informing and sending technicians carry out maintenance and fault treatment on the state of power transmission and transformation equipment, but the risk assessment reliability of the power grid is poor due to the mode of relying on manual verification and check.
Disclosure of Invention
Based on this, it is necessary to provide a power system, a risk assessment device and a risk assessment method thereof, and to improve the reliability of risk assessment of the power system, aiming at the technical problem that the risk assessment reliability of the power grid is poor due to the above-mentioned manner of relying on manual verification.
The risk assessment device of the power system comprises a data acquisition module, an index determination module, a risk assessment module and a risk early warning module, wherein the data acquisition module is connected with power equipment of each assessment section in the power system;
the data acquisition module is used for acquiring the operation state data of the power equipment of each evaluation section and sending the operation state data of the power equipment of each evaluation section to the index determination module;
the index determining module is used for correspondingly determining risk assessment index data of each assessment section according to the received running state data of each assessment section and sending each risk assessment index data to the risk assessment module;
the risk assessment module is used for inputting the risk assessment index data into a distributed intelligent assessment model to obtain a risk assessment deviation result of each assessment section, and sending a risk early warning signal to the risk early warning module under the condition that the risk assessment deviation result exceeds a set risk threshold;
the risk early warning module is used for carrying out risk early warning prompt of each evaluation section according to the risk early warning signals.
In one embodiment, the index determination module includes a basic index determination unit;
the basic index determining unit is configured to determine a risk value corresponding to each preset basic risk assessment index according to the operation state data corresponding to each assessment section received from the data acquisition module, where the risk assessment index data of each assessment section includes a risk value of each preset basic risk assessment index.
In one embodiment, the index determining module further includes an associated index determining unit;
the association indicator determining unit is configured to determine association indicators of the preset basic risk assessment indicators set by the basic indicator determining unit, obtain at least one association risk indicator, determine a risk value of each association risk indicator according to a risk value of each preset basic risk assessment indicator, and the risk assessment indicator data of each assessment section further includes the risk value of each association risk indicator.
In one embodiment, the risk assessment module comprises an assessment unit and an early warning output unit;
the evaluation unit is used for inputting the risk value of each preset basic risk evaluation index of each evaluation section and the risk value of each associated risk index into the distributed intelligent evaluation model to obtain a risk evaluation deviation result of each evaluation section;
the early warning output unit is used for judging whether the set risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a risk early warning signal corresponding to the assessment sections to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set risk threshold value.
In one embodiment, the early warning output unit comprises a low risk output unit, a medium risk output unit and a high risk output unit;
the low risk output unit is used for judging whether the set low risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a low risk early warning signal of the corresponding assessment section to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set low risk threshold value;
the risk early warning module is used for judging whether the risk early warning signal exceeds a set risk threshold value based on the risk assessment deviation results of the assessment sections and sending a risk early warning signal corresponding to the assessment sections under the condition that the risk assessment deviation results of the assessment sections exceed the set risk threshold value;
the high risk output unit is used for judging whether the set high risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a high risk early warning signal corresponding to the assessment sections to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set high risk threshold value.
In one embodiment, the risk early-warning module includes a low risk early-warning unit, a medium risk early-warning unit, and a high risk early-warning unit;
the low-risk early warning unit is used for carrying out low-risk early warning prompt of the corresponding assessment section under the condition that the low-risk early warning signal is received;
the medium risk early warning unit is used for carrying out medium risk early warning prompt of the corresponding assessment section under the condition that the medium risk early warning signal is received;
the high-risk early warning unit is used for carrying out high-risk early warning prompt corresponding to the assessment section under the condition that the high-risk early warning signal is received.
In one embodiment, the risk assessment device further includes an anomaly correction module, and the anomaly correction module is connected to the risk assessment module;
the abnormality correction module is used for performing abnormality correction on the operation state data of the power equipment of each evaluation section based on the risk evaluation deviation result of each evaluation section.
In one embodiment, the risk assessment device further includes a storage module, where the storage module is connected to the data acquisition module, the index determination module, and the risk assessment module.
In one embodiment, there is also provided a risk assessment method of an electric power system, the method including:
acquiring operation state data of the power equipment of each evaluation section;
correspondingly determining risk assessment index data of each assessment section according to the running state data of each assessment section;
inputting the risk assessment index data into a distributed intelligent assessment model to obtain a risk assessment deviation result of each assessment section;
and outputting a risk early warning signal to carry out risk early warning prompt of the corresponding assessment section under the condition that the risk assessment deviation result exceeds a set risk threshold value.
In one embodiment, there is also provided a power system including a risk assessment apparatus as described above.
According to the power system and the risk assessment device and method thereof, the risk assessment index data of each assessment section are correspondingly determined by collecting the running state data of the power equipment of each assessment section, and then each risk assessment index data is input into the distributed intelligent assessment model to obtain the risk assessment deviation result of each assessment section, and in case that the risk assessment deviation result exceeds the set risk threshold value, a risk early warning signal is timely sent to carry out risk early warning prompt of each assessment section. The whole power grid is split into a plurality of distributed regional power grid coverage areas, and risk assessment is carried out respectively, so that the aim of improving the reliability of the risk assessment can be achieved.
Drawings
FIG. 1 is a system block diagram of a risk assessment device in one embodiment;
FIG. 2 is a system block diagram of a risk assessment apparatus according to another embodiment;
FIG. 3 is a flow chart of a risk assessment method according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
As described in the background art, in the existing risk assessment method for the power system, most of the existing risk assessment method still mainly depends on manual verification and check, early warning is performed after the abnormal condition of data is found, and a report technician overhauls and processes faults on the state of power transmission and transformation equipment, but the risk assessment reliability of the power grid is poor due to the fact that the existing risk assessment method depends on the manual verification and check.
Based on the above, in one embodiment, a risk assessment device is provided, which is applied to a power system composed of a multi-level voltage power substation and a power transmission and distribution line. As shown in fig. 1, the system comprises a data acquisition module, an index determination module, a risk assessment module and a risk early warning module, wherein the data acquisition module is connected with power equipment of each assessment section in a power system; the data acquisition module is used for acquiring the running state data of the power equipment of each evaluation section and sending the running state data of the power equipment of each evaluation section to the index determination module; the index determining module is used for correspondingly determining risk assessment index data of each assessment section according to the received running state data of each assessment section and sending each risk assessment index data to the risk assessment module; the risk assessment module is used for inputting the risk assessment index data into the distributed intelligent assessment model to obtain risk assessment deviation results of each assessment section, and sending a risk early warning signal to the risk early warning module under the condition that the risk assessment deviation results exceed a set risk threshold; the risk early warning module is used for carrying out risk early warning prompt of each assessment section according to the risk early warning signals.
The power system mentioned in the application may refer to an ac/dc substation system corresponding to various voltage classes, and the corresponding power equipment may include a generator set, an ac line, a converter station, a dc line, and the like. The assessment section is a plurality of regional power grid coverage areas participating in risk assessment and divided from the overall power grid coverage area, and can be understood as splitting the overall power grid into a plurality of distributed regional power grid coverage areas for respective risk assessment, and finally summarizing to obtain a final risk assessment result, thereby achieving the purpose of improving the reliability, availability and expansibility of risk assessment. The power equipment of the section, i.e. all power equipment within the coverage area of the regional power grid, is evaluated.
Specifically, the data acquisition module is configured to acquire the operation state data of the electrical equipment of each evaluation section, and then send the operation state data of the electrical equipment of each evaluation section to the index determination module for subsequent determination of risk evaluation index data. It is understood that the operation state data of the power equipment may include current data, voltage data, temperature data, etc. when the equipment and the line are operated, and may also include state data of equipment such as a control switch, a relay protection device, a circuit breaker, an air switch, etc. For current data, devices such as a current divider, a current transmitter and a current sensor can be used for realizing acquisition, devices such as a voltage transmitter and a voltage sensor can be used for realizing acquisition of voltage data, and devices such as a temperature sensor can be used for realizing acquisition of temperature data. In addition, the state data of each power equipment can be acquired by adopting devices such as a PLC input module, a switching value acquisition board card and the like.
Further, the index determination module may determine risk assessment index data for each assessment section based on the collected operational status data for each assessment section, and the risk assessment index data may be used to determine whether the assessment section is at risk for operation, and the number of levels of risk. The expression form of the risk assessment index is not unique, and can be determined based on the form of the collected operation state data, for example, the risk assessment index corresponding to load data such as voltage and current can be an initial voltage level, an initial current level, a voltage fluctuation ratio, a current fluctuation ratio, a load rate and the like, the risk assessment index corresponding to temperature data can be a temperature belonging interval, a temperature overrun value and the like, and the risk assessment index corresponding to switch state data collected by the switch equipment can be state jump times, state jump periods and the like. It may be understood that the operation state data used for determining the risk assessment index data may be a single data value corresponding to a certain time point, or may be multiple sets of data corresponding to a certain time period.
Furthermore, the distributed intelligent evaluation model is used for performing risk evaluation on risk evaluation index data of the distributed regional power grid coverage, the evaluation target subareas can be set, the acquired risk evaluation index data are compared with the set evaluation results in the risk evaluation process, and the risk evaluation deviation results of all evaluation sections are measured in a distributed calculation mode. The specific principle formula of the distributed intelligent evaluation model is as follows:
wherein P represents a risk assessment deviation result, omicron represents a preset fluctuation range corresponding to a risk assessment index, k represents risk assessment index data,
running fluctuation ratio of running state data corresponding to the risk assessment index, +.>
Distribution section, v, representing evaluation section 1 And v 2 The predetermined matrix coverage area and the measured matrix coverage area of the evaluation section are represented, respectively.
It can be understood that the number and types of risk assessment indicators corresponding to each assessment section are not unique, and can be set according to actual situations, and the types of risk assessment indicators can be risk assessment indicator data determined by single type of running state data or associated risk indicator data determined by multiple types of running state data.
The risk assessment deviation results of the assessment sections can be used for judging whether running risks exist or not, for example, a risk threshold value of the risk assessment deviation results can be set correspondingly, and when the risk assessment deviation results exceed the set risk threshold value, a risk early warning signal is sent to a risk early warning module to carry out risk early warning prompt of the assessment sections. The set risk threshold value can be determined according to the risk evaluation deviation result and the set evaluation result of each evaluation section, and is not limited. In addition, the mode of carrying out risk early warning suggestion is not unique, can be through sending early warning signal to the terminal that the skilled person carried, also can be through mutual subassembly carries out early warning suggestion, adopts early warning lamp, early warning buzzer and carries out forms such as early warning suggestion on data center's display device.
According to the risk assessment device of the power system, the risk assessment index data of each assessment section are correspondingly determined by collecting the running state data of the power equipment of each assessment section, and then each risk assessment index data is input into the distributed intelligent assessment model to obtain the risk assessment deviation result of each assessment section, and in case that the risk assessment deviation result exceeds the set risk threshold value, a risk early warning signal is timely sent out to carry out risk early warning prompt of each assessment section. The whole power grid is split into a plurality of distributed regional power grid coverage areas, and risk assessment is carried out respectively, so that the aim of improving the reliability of the risk assessment can be achieved.
In one embodiment, as shown in fig. 2, the index determination module includes a basic index determination unit; the basic index determining unit is used for determining a risk value corresponding to each preset basic risk assessment index according to the running state data corresponding to each assessment section received from the data acquisition module, wherein the risk assessment index data of each assessment section comprises the risk value of each preset basic risk assessment index.
It may be understood that the preset basic risk assessment index is a risk assessment index obtained by performing preset based on the type of the operation state data, for example, the risk assessment index corresponding to the load data such as voltage, current and the like may be an initial voltage level, an initial current level, a voltage fluctuation ratio, a current fluctuation ratio, a load rate and the like, the risk assessment index corresponding to the temperature data may be a temperature belonging interval, a temperature overrun value and the like, and the risk assessment index corresponding to the switch state data collected by the switch device may be a state transition number, a state transition period and the like.
Specifically, after the data acquisition module acquires the running state data corresponding to each evaluation section, the risk value corresponding to each preset basic risk evaluation index can be determined based on the preset calculation mode of each preset basic risk evaluation index. It can be understood that different basic risk assessment indexes have different calculation modes, for example, the calculation modes of risk assessment indexes such as voltage fluctuation ratio, current fluctuation ratio and the like, can be obtained by calculating the difference between the maximum value and the minimum value of data in a period of acquisition time and then comparing the calculated difference with the preset fluctuation range of voltage data or current data.
In the embodiment, the basic risk assessment index system of the power system is reasonably constructed based on the operation state data, so that the operation risk of the power system can be reflected more comprehensively and reliably.
In one embodiment, as shown in fig. 2, the index determining module further includes an associated index determining unit; the association index determining unit is used for performing association index determination on each preset basic risk assessment index set by the basic index determining unit to obtain at least one association risk index, determining the risk value of each association risk index according to the risk value of each preset basic risk assessment index, and the risk assessment index data of each assessment section further comprises the risk value of each association risk index.
It can be understood that the associated risk indicator is obtained by combining at least two preset basic risk assessment indicators, and the at least two preset basic risk assessment indicators are characterized as associated indicators that cause operation risk, such as state transition times corresponding to switch state data, state transition periods, and other basic risk assessment indicators.
Specifically, the manner of associating each preset basic risk assessment index, that is, the manner of obtaining the associated risk index is not unique, may be that the associated risk index is obtained by performing weighted average calculation on each preset basic risk assessment index, and the risk value of each associated risk index is determined according to the risk value of each preset basic risk assessment index. Of course, the association risk indexes may be obtained by summarizing the preset basic risk assessment indexes through a preset logic relationship. For example, the first associated risk indicator may be obtained by summarizing the state transition times and the state transition periods according to the logic relationship, that is, only when the state transition times and the state transition periods do not exceed the set risk threshold, the first associated risk indicator is judged to not exceed the set risk threshold.
In this embodiment, the associated risk indicator setting is performed based on each preset basic risk assessment indicator, so as to assess whether the power system has an operation risk, so that the assessment result is more comprehensive and reliable.
In one embodiment, as shown in fig. 2, the risk assessment module includes an assessment unit and an early warning output unit; the evaluation unit is used for inputting the risk values of each preset basic risk evaluation index and the risk values of each associated risk index of each evaluation section into the distributed intelligent evaluation model to obtain a risk evaluation deviation result of each evaluation section; the early warning output unit is used for judging whether the risk evaluation deviation result exceeds a set risk threshold value based on the risk evaluation deviation result of each evaluation section, and sending a risk early warning signal corresponding to each evaluation section to the risk early warning module under the condition that the risk evaluation deviation result of each evaluation section exceeds the set risk threshold value.
Specifically, after the risk values of the preset basic risk assessment indexes and the risk values of the associated risk indexes of each assessment section, the risk values of the preset basic risk assessment indexes and the risk values of the associated risk indexes can be input into a distributed intelligent assessment model of the assessment unit to obtain a risk assessment deviation result of each assessment section. And further judging whether the operation risk exists or not through the early warning output unit.
The early warning output unit judges that the obtained running risk can be provided with setting modes with different risk grades. For example, in one embodiment, as shown in FIG. 2, the early warning output unit includes a low risk output unit, a medium risk output unit, and a high risk output unit; the low risk output unit is used for judging whether the set low risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a low risk early warning signal of the corresponding assessment section to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set low risk threshold value; the risk early warning module is used for judging whether the risk early warning signal exceeds a set risk threshold value based on the risk assessment deviation results of the assessment sections and sending a risk early warning signal corresponding to the assessment sections under the condition that the risk assessment deviation results of the assessment sections exceed the set risk threshold value; the high risk output unit is used for judging whether the set high risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending high risk early warning signals of the corresponding assessment sections to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set high risk threshold value.
It can be understood that each evaluation section can pertinently set low, medium and high risk thresholds corresponding to the risk evaluation indexes, and can be widely suitable for the running condition of the power grid frequently and randomly fluctuating under new conditions. The specific value of the risk threshold can be set by each evaluation section according to the actual requirement, so as to further realize risk evaluation of the power grid, and the embodiment is not limited specifically.
Correspondingly, under the condition that the early warning output unit has different risk level setting modes, the mode for carrying out early warning prompt can be correspondingly set. For example, in one embodiment, as shown in fig. 2, the risk early warning module includes a low risk early warning unit, a medium risk early warning unit, and a high risk early warning unit; the low-risk early warning unit is used for carrying out low-risk early warning prompt corresponding to the evaluation section under the condition that the low-risk early warning signal is received; the stroke risk early warning unit is used for carrying out stroke risk early warning prompt of the corresponding evaluation section under the condition of receiving the stroke risk early warning signal; the high-risk early warning unit is used for carrying out high-risk early warning prompt corresponding to the evaluation section under the condition that the high-risk early warning signal is received.
It can be understood that the low-risk early warning prompt, the middle-risk early warning prompt and the high-risk early warning prompt respectively have different expression forms, for example, the low-risk early warning prompt, the middle-risk early warning prompt and the high-risk early warning prompt can correspond to different alarm durations responded by the early warning buzzer, different alarm brightness and flashing frequencies can be displayed by the early warning lamp, and the low-risk early warning prompt, the middle-risk early warning prompt and the high-risk early warning prompt can be displayed on display equipment of a data center through different early warning prompt frames so as to achieve the purpose of distinguishing the early warning prompts.
In one embodiment, the risk assessment device further includes an anomaly correction module, and the anomaly correction module is connected with the risk assessment module; the abnormality correction module is used for performing abnormality correction on the operation state data of the power equipment of each evaluation section based on the risk evaluation deviation result of each evaluation section.
It can be understood that the abnormal correction can be understood as the situation that the abnormal condition appears in the running state data display and the sudden correction processing is needed in the normal running process of the power network. Specifically, the abnormality correction module may mark the abnormal position of the power grid running risk based on the obtained risk assessment deviation results of each assessment section, and further feed back and adjust the running state data of the power equipment corresponding to the abnormal position until the risk assessment deviation results obtained based on the running state data are recovered to be normal, so as to implement abnormality correction.
In this embodiment, the abnormality correction module may correct the operation state data in an abnormal state in time based on risk value settings of data such as the operation state risk of the power transmission and transformation device, the power flow risk of the power transmission and transformation device, the power of the generator set, and the node load, so as to ensure the normal operation of the power system.
In an embodiment, the risk assessment device further includes a storage module, and the storage module is connected to the data acquisition module, the index determination module, and the risk assessment module. Specifically, the storage module can be used for storing data output by each module, so that real-time backtracking of the data is realized, the follow-up controllability of the operation risk of the power system is ensured, and the normal operation of the power system is also facilitated.
In one embodiment, as shown in fig. 3, there is provided a risk assessment method of a power system, including the following S200 to S800:
s200: operational state data of the power equipment of each evaluation section is acquired.
The power system mentioned in the application may refer to an ac/dc substation system corresponding to various voltage classes, and the corresponding power equipment may include a generator set, an ac line, a converter station, a dc line, and the like. The assessment section is a plurality of regional power grid coverage areas participating in risk assessment and divided from the overall power grid coverage area, and can be understood as splitting the overall power grid into a plurality of distributed regional power grid coverage areas for respective risk assessment, and finally summarizing to obtain a final risk assessment result, thereby achieving the purpose of improving the reliability, availability and expansibility of risk assessment. The power equipment of the section, i.e. all power equipment within the coverage area of the regional power grid, is evaluated.
Specifically, the data acquisition module is configured to acquire the operation state data of the electrical equipment of each evaluation section, and then send the operation state data of the electrical equipment of each evaluation section to the index determination module for subsequent determination of risk evaluation index data. It is understood that the operation state data of the power equipment may include current data, voltage data, temperature data, etc. when the equipment and the line are operated, and may also include state data of equipment such as a control switch, a relay protection device, a circuit breaker, an air switch, etc. For current data, devices such as a current divider, a current transmitter and a current sensor can be used for realizing acquisition, devices such as a voltage transmitter and a voltage sensor can be used for realizing acquisition of voltage data, and devices such as a temperature sensor can be used for realizing acquisition of temperature data. In addition, the state data of each power equipment can be acquired by adopting devices such as a PLC input module, a switching value acquisition board card and the like.
S400: and correspondingly determining risk assessment index data of each assessment section according to the running state data of each assessment section.
The index determination module may determine risk assessment index data for each assessment section based on the collected operational status data for each assessment section, the risk assessment index data may be used to determine whether an operational risk exists for the assessment section, and the number of levels of risk. The expression form of the risk assessment index is not unique, and can be determined based on the form of the collected operation state data, for example, the risk assessment index corresponding to load data such as voltage and current can be an initial voltage level, an initial current level, a voltage fluctuation ratio, a current fluctuation ratio, a load rate and the like, the risk assessment index corresponding to temperature data can be a temperature belonging interval, a temperature overrun value and the like, and the risk assessment index corresponding to switch state data collected by the switch equipment can be state jump times, state jump periods and the like. It may be understood that the operation state data used for determining the risk assessment index data may be a single data value corresponding to a certain time point, or may be multiple sets of data corresponding to a certain time period.
S600: and (3) inputting the risk assessment index data into a distributed intelligent assessment model to obtain a risk assessment deviation result of each assessment section.
The distributed intelligent evaluation model is used for performing risk evaluation on risk evaluation index data of a distributed regional power grid coverage area, an evaluation target subarea can be set, the acquired risk evaluation index data is compared with a set evaluation result in a risk evaluation process, and a risk evaluation deviation result of each evaluation section is measured in a distributed calculation mode. The specific principle formula of the distributed intelligent evaluation model is as follows:
wherein P represents a risk assessment deviation result, omicron represents a preset fluctuation range corresponding to a risk assessment index, k represents risk assessment index data,
running fluctuation ratio of running state data corresponding to the risk assessment index, +.>
Distribution section, v, representing evaluation section 1 And v 2 The predetermined matrix coverage area and the measured matrix coverage area of the evaluation section are represented, respectively.
It can be understood that the number and types of risk assessment indicators corresponding to each assessment section are not unique, and can be set according to actual situations, and the types of risk assessment indicators can be risk assessment indicator data determined by single type of running state data or associated risk indicator data determined by multiple types of running state data.
S800: and outputting a risk early warning signal to carry out risk early warning prompt of the corresponding assessment section under the condition that the risk assessment deviation result exceeds the set risk threshold value.
The risk assessment deviation results of the assessment sections can be used for judging whether running risks exist or not, for example, a risk threshold value of the risk assessment deviation results can be set correspondingly, and when the risk assessment deviation results exceed the set risk threshold value, a risk early warning signal is sent to a risk early warning module to carry out risk early warning prompt of the assessment sections. The set risk threshold value can be determined according to the risk evaluation deviation result and the set evaluation result of each evaluation section, and is not limited. In addition, the mode of carrying out risk early warning suggestion is not unique, can be through sending early warning signal to the terminal that the skilled person carried, also can be through mutual subassembly carries out early warning suggestion, adopts early warning lamp, early warning buzzer and carries out forms such as early warning suggestion on data center's display device.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
In one embodiment, a computer device, which may be a server, is provided that includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a risk assessment method for an electrical power system.
In one embodiment, a computer device is provided, including a memory storing a computer program and a processor implementing the steps of the risk assessment method of a power system described above when the computer program is executed by the processor.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the risk assessment method of a power system described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the risk assessment method of a power system described above.
In one embodiment, a power system is provided comprising a risk assessment apparatus as in any of the embodiments above.
Specific limitations in one or more power systems and embodiments of a risk assessment method for a power system provided in the present application may refer to the above limitation of a risk assessment device for a power system, which is not described herein.
It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to comply with the related laws and regulations and standards of the related countries and regions.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. The risk assessment device of the power system is characterized by comprising a data acquisition module, an index determination module, a risk assessment module and a risk early warning module, wherein the data acquisition module is connected with power equipment of each assessment section in the power system;
the data acquisition module is used for acquiring the operation state data of the power equipment of each evaluation section and sending the operation state data of the power equipment of each evaluation section to the index determination module;
the index determining module is used for correspondingly determining risk assessment index data of each assessment section according to the received running state data of each assessment section and sending each risk assessment index data to the risk assessment module;
the risk assessment module is used for inputting the risk assessment index data into a distributed intelligent assessment model to obtain a risk assessment deviation result of each assessment section, and sending a risk early warning signal to the risk early warning module under the condition that the risk assessment deviation result exceeds a set risk threshold;
the risk early warning module is used for carrying out risk early warning prompt of each evaluation section according to the risk early warning signals.
2. The risk assessment device according to claim 1, wherein the index determination module comprises a basic index determination unit;
the basic index determining unit is configured to determine a risk value corresponding to each preset basic risk assessment index according to the operation state data corresponding to each assessment section received from the data acquisition module, where the risk assessment index data of each assessment section includes a risk value of each preset basic risk assessment index.
3. The risk assessment device according to claim 2, wherein the index determination module further comprises an associated index determination unit;
the association indicator determining unit is configured to determine association indicators of the preset basic risk assessment indicators set by the basic indicator determining unit, obtain at least one association risk indicator, determine a risk value of each association risk indicator according to a risk value of each preset basic risk assessment indicator, and the risk assessment indicator data of each assessment section further includes the risk value of each association risk indicator.
4. A risk assessment device according to claim 3, wherein the risk assessment module comprises an assessment unit and an early warning output unit;
the evaluation unit is used for inputting the risk value of each preset basic risk evaluation index of each evaluation section and the risk value of each associated risk index into the distributed intelligent evaluation model to obtain a risk evaluation deviation result of each evaluation section;
the early warning output unit is used for judging whether the set risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a risk early warning signal corresponding to the assessment sections to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set risk threshold value.
5. The risk assessment device of claim 4, wherein the early warning output unit comprises a low risk output unit, a medium risk output unit, and a high risk output unit;
the low risk output unit is used for judging whether the set low risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a low risk early warning signal of the corresponding assessment section to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set low risk threshold value;
the risk early warning module is used for judging whether the risk early warning signal exceeds a set risk threshold value based on the risk assessment deviation results of the assessment sections and sending a risk early warning signal corresponding to the assessment sections under the condition that the risk assessment deviation results of the assessment sections exceed the set risk threshold value;
the high risk output unit is used for judging whether the set high risk threshold value is exceeded based on the risk assessment deviation results of the assessment sections, and sending a high risk early warning signal corresponding to the assessment sections to the risk early warning module under the condition that the risk assessment deviation results of the assessment sections exceed the set high risk threshold value.
6. The risk assessment device of claim 5, wherein the risk early warning module comprises a low risk early warning unit, a medium risk early warning unit, and a high risk early warning unit;
the low-risk early warning unit is used for carrying out low-risk early warning prompt of the corresponding assessment section under the condition that the low-risk early warning signal is received;
the medium risk early warning unit is used for carrying out medium risk early warning prompt of the corresponding assessment section under the condition that the medium risk early warning signal is received;
the high-risk early warning unit is used for carrying out high-risk early warning prompt corresponding to the assessment section under the condition that the high-risk early warning signal is received.
7. The risk assessment device according to any one of claims 1 to 6, further comprising an anomaly correction module, the anomaly correction module being connected to the risk assessment module;
the abnormality correction module is used for performing abnormality correction on the operation state data of the power equipment of each evaluation section based on the risk evaluation deviation result of each evaluation section.
8. The risk assessment device of any one of claims 1 to 6, further comprising a storage module coupled to the data acquisition module, the index determination module, and the risk assessment module.
9. A risk assessment method for an electrical power system, the method comprising:
acquiring operation state data of the power equipment of each evaluation section;
correspondingly determining risk assessment index data of each assessment section according to the running state data of each assessment section;
inputting the risk assessment index data into a distributed intelligent assessment model to obtain a risk assessment deviation result of each assessment section;
and outputting a risk early warning signal to carry out risk early warning prompt of the corresponding assessment section under the condition that the risk assessment deviation result exceeds a set risk threshold value.
10. An electrical power system comprising a risk assessment device according to any one of claims 1-8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117977816A (en) * | 2024-03-29 | 2024-05-03 | 江苏高雷德电力科技有限公司 | Intelligent power supply system for electric power safety |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117977816A (en) * | 2024-03-29 | 2024-05-03 | 江苏高雷德电力科技有限公司 | Intelligent power supply system for electric power safety |
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