CN117592693A - Power grid dispatching method, system, device, computer equipment and storage medium - Google Patents

Power grid dispatching method, system, device, computer equipment and storage medium Download PDF

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CN117592693A
CN117592693A CN202311480757.0A CN202311480757A CN117592693A CN 117592693 A CN117592693 A CN 117592693A CN 202311480757 A CN202311480757 A CN 202311480757A CN 117592693 A CN117592693 A CN 117592693A
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instruction
instruction sequence
scheduling
data
power grid
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吴奇珂
区伟健
程培军
徐策
钟卓颖
钱韦廷
胡佳
黄浩崴
庄跃
黎翔
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Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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Abstract

The present application relates to a power grid dispatching method, system, apparatus, computer device, storage medium and computer program product. The method comprises the following steps: receiving an encrypted scheduling instruction sequence; decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data; carrying out authenticity verification and rationality verification on the scheduling instruction sequence in the scheduling instruction sequence data; and under the condition that the scheduling instruction sequence passes the authenticity verification and the rationality verification, executing the power grid scheduling operation according to the scheduling instruction in the scheduling instruction sequence. In the scheme, before the scheduling instruction sequence is executed, the authenticity verification and the rationality verification are carried out on the scheduling instruction sequence, and the scheduling instruction sequence is allowed to be executed only under the condition that the authenticity verification and the rationality verification pass, so that the reliability of a power grid scheduling system can be improved by adopting the method.

Description

Power grid dispatching method, system, device, computer equipment and storage medium
Technical Field
The present disclosure relates to the field of power grid dispatching technologies, and in particular, to a power grid dispatching method, system, apparatus, computer device, storage medium, and computer program product.
Background
With the development of power grid dispatching technology, in order to ensure safe and stable operation of a power grid, external reliable power supply is ensured, various power production works are ensured to be orderly carried out, and the power grid needs to be managed through power dispatching. The work content of the power dispatching comprises data information fed back by various information acquisition devices or information provided by monitoring personnel, and the current operation condition of the power grid is judged by combining actual operation parameters of the power grid such as voltage, current, frequency, load and the like.
In the prior art, in order to effectively manage the operation process of the power grid, a worker is usually required to observe the operation condition of the power grid at any time, and manage the power grid by sending a scheduling instruction so as to command on-site personnel or an automatic control system to adjust the operation condition of the power grid, thereby preventing power grid safety accidents such as damage to power grid equipment and overload of a power transmission line.
However, the current power grid dispatching method lacks effective safety error prevention means, external malicious attacks are easy to receive, for example, fake dispatching instructions are received, the power grid dispatching system can influence the stable operation of the power grid due to executing the fake dispatching instructions, and the reliability of the power grid dispatching system is low.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a power grid dispatching method, system, apparatus, computer device, computer readable storage medium, and computer program product that can improve the reliability of a power grid dispatching system.
In a first aspect, the present application provides a power grid scheduling method. The method comprises the following steps:
receiving an encrypted scheduling instruction sequence;
decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data;
carrying out authenticity verification and rationality verification on the scheduling instruction sequence in the scheduling instruction sequence data;
and under the condition that the scheduling instruction sequence passes the authenticity verification and the rationality verification, executing the power grid scheduling operation according to the scheduling instruction in the scheduling instruction sequence.
In one embodiment, the scheduling instruction sequence in the scheduling instruction sequence data carries first biological characteristic information of an instruction editing user;
the verifying of the authenticity of the scheduling instruction in the scheduling instruction sequence data comprises the following steps:
analyzing the scheduling instruction sequence data and determining an instruction editing user with the scheduling instruction sequence data sending authority;
Acquiring characteristic indication data output by a circulating data source at the editing moment of a scheduling instruction;
extracting second biological characteristic information of the instruction editing user matched with the characteristic indicating data;
and performing similarity matching on the first biological characteristic information and the second biological characteristic information to obtain an authenticity verification result.
In one embodiment, the extracting the second biometric information of the instruction editing user that matches the feature indication data includes:
determining a type extraction identifier matched with the feature indication data according to a mapping relation between the preset feature indication data and the type extraction identifier, wherein the type extraction identifier is used for representing the type of the biological feature information to be extracted;
and extracting the second biological characteristic information corresponding to the type extraction identification.
In one embodiment, verifying the rationality of the dispatch instruction sequence in the dispatch instruction sequence data includes:
acquiring power grid state information corresponding to the editing moment of the scheduling instruction sequence;
taking the scheduling instruction sequence data and the power grid state information as inputs, and calling a trained instruction rationality verification model to obtain a rationality verification result;
The trained instruction rationality check is obtained by training based on historical scheduling instruction sequence data and power grid state information corresponding to scheduling instruction editing time.
In one embodiment, the instruction rationality check model, when invoked, performs the steps of:
and verifying the command ordering rationality of the scheduling command sequence data according to the scheduling command sequence data and the power grid state information to obtain a command ordering rationality verification result.
In a second aspect, the present application further provides a power grid dispatching system. The system comprises: the instruction sending end and the instruction receiving end are in communication connection;
the instruction sending end is used for editing a dispatching instruction sequence, acquiring feature indication data corresponding to the current moment of a circulating data source, determining a type extraction identifier matched with the feature indication data according to the feature indication data and the preset mapping relation between the feature indication data and the type extraction identifier, extracting first biological feature information of an instruction editing user corresponding to the type extraction identifier, adding the biological feature information into the dispatching instruction sequence, performing encryption processing to obtain the encrypted dispatching instruction sequence, and sending the encrypted dispatching instruction sequence to the instruction receiving end;
The instruction receiving end is configured to respond to the encrypted scheduling instruction sequence, and call the power grid scheduling method according to any one of the foregoing embodiments to perform power grid scheduling.
In a third aspect, the present application further provides a power grid dispatching device. The device comprises:
the instruction acquisition module is used for receiving the encrypted scheduling instruction sequence;
the instruction decryption module is used for decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data;
the instruction verification module is used for verifying authenticity and rationality of the scheduling instruction sequence in the scheduling instruction sequence data;
and the instruction execution module is used for executing power grid dispatching operation according to the dispatching instructions in the dispatching instruction sequence under the condition that the dispatching instruction sequence passes the authenticity verification and the rationality verification.
In a fourth aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of the method as described above when the processor executes the computer program.
In a fifth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the method as described above.
In a sixth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of the method as described above.
The power grid dispatching method, the system, the device, the computer equipment, the storage medium and the computer program product are used for receiving the encrypted dispatching instruction sequence, decrypting the encrypted dispatching instruction sequence to obtain dispatching instruction sequence data, further carrying out authenticity verification and rationality verification on the dispatching instruction sequence in the dispatching instruction sequence data, and under the condition that the dispatching instruction sequence passes the authenticity verification and the rationality verification, indicating that the dispatching instruction sequence is edited by a user with instruction editing authority, and the dispatching instruction sequence is reasonable and matched with the power grid running state, and executing power grid dispatching operation corresponding to the dispatching instruction sequence. Therefore, the possibility that the power grid dispatching system is attacked by the outside can be reduced, and the safety risk caused by the fact that the power grid dispatching system executes fake dispatching instructions or unreasonable dispatching instructions is reduced, so that the reliability of the power grid dispatching system is improved.
Drawings
FIG. 1 is an application environment diagram of a power grid scheduling method in one embodiment;
FIG. 2 is a flow chart of a power grid dispatching method in one embodiment;
FIG. 3 is a flow diagram of scheduling instruction authenticity verification in one embodiment;
FIG. 4 is a flow chart illustrating the verification of the authenticity of a dispatch instruction in another embodiment;
FIG. 5 is a flow diagram of validation of dispatch instructions in one embodiment;
FIG. 6 is a block diagram of a grid dispatching system in one embodiment;
FIG. 7 is a block diagram of a power grid dispatching apparatus in one embodiment;
fig. 8 is an internal structural diagram of a computer device in one 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.
The power grid dispatching method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the transmitting end 102 communicates with the receiving end 104 through a network. The sender data store system may send data that needs to be processed by the sender 102, and the receiver data store system may receive data that needs to be processed by the receiver 104. The data storage systems may be integrated on the transmitting end 102 and the receiving end 104, respectively, or may be placed on a cloud or other network server. The receiving end 104 receives the encrypted scheduling instruction sequence, decrypts the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data, further performs authenticity verification and rationality verification on the scheduling instruction sequence in the scheduling instruction sequence data, and executes power grid scheduling operation corresponding to the scheduling instruction sequence under the condition that the scheduling instruction sequence passes the authenticity verification and the rationality verification. The transmitting end 102 and the receiving end 104 may be implemented by a server or a server cluster formed by a plurality of servers, or may be implemented by one or more terminals or devices with data processing capability.
In one embodiment, as shown in fig. 2, a power grid scheduling method is provided, and the method is applied to the receiving end 104 in fig. 1 for illustration, and includes the following steps:
s200, receiving an encrypted scheduling instruction sequence.
In a grid dispatching system, the sequence of dispatching instructions comprises a series of operating commands for controlling and managing the operation of the power network, for example, generator dispatching instructions involving the starting and stopping of generators, load management instructions for managing the load of the grid and distributing the power resources, line switching instructions for opening or closing the transmission line, etc.
Dispatch instruction transmission and dispatch instruction execution are typically two distinct ports, such as by a grid dispatch center encrypting the dispatch instruction sequence and transmitting the encrypted dispatch instruction sequence to the instruction execution side to reduce security risks such as interception of the dispatch instruction sequence during transmission and unauthorized access and modification of the dispatch instruction sequence. For example, when the grid dispatching center needs to send a dispatching command sequence to a remote power station, the grid dispatching center may generate a dispatching command sequence containing operation commands, for example, increase the output power of a certain generator. Before the scheduling instruction sequence is sent out, the scheduling instruction sequence can be sent into an encryption module, the encryption module is used for encrypting the scheduling instruction sequence by using a safe encryption algorithm, an encrypted scheduling instruction sequence is obtained, the encrypted scheduling instruction sequence can be transmitted to an execution end of a target power station through the Internet or a special communication line, and the execution end of the target power station receives the encrypted scheduling instruction sequence. There are various encryption methods and protocols that can be used to secure the sequence of scheduling instructions, such as, but not limited to, symmetric encryption algorithms and asymmetric encryption algorithms, and the choice of encryption algorithm may depend on the specific needs of the grid scheduling system.
S400, decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data.
After receiving the encrypted scheduling instruction sequence, the scheduling instruction execution end needs to decrypt the encrypted scheduling instruction sequence, so as to obtain scheduling instruction sequence data. The scheduling instruction sequence data not only comprises the content of the scheduling instruction sequence, but also comprises a time stamp of the sending time of the scheduling instruction, information of a scheduling instruction editor, information of a scheduling instruction receiver, priority of the execution of the scheduling instruction and the like, and the data can improve the correctness and the safety of the scheduling instruction.
The instruction execution end needs to acquire a correct decryption key, for example, through a secure key exchange protocol or a pre-shared key, and after the instruction execution end receives the encrypted scheduling instruction sequence, the instruction execution end uses the decryption key to decrypt the encrypted scheduling instruction sequence to obtain the original scheduling instruction sequence data. And the secret key is used for decrypting the scheduling instruction sequence, so that confidentiality and security of the scheduling instruction sequence are improved.
And S600, carrying out authenticity verification and rationality verification on the scheduling instruction sequence in the scheduling instruction sequence data.
After the instruction execution end obtains the scheduled execution sequence data, the instruction execution end also needs to perform authenticity verification and rationality verification on the scheduled instruction sequence before executing the scheduled instruction sequence in the scheduled instruction sequence. The authenticity verification is a key step for guaranteeing the data security and reliability of the power grid dispatching system, for example, the source of a dispatching instruction sequence needs to be confirmed so as to ensure that the dispatching instruction sequence is sent by an authorized instruction editing user, whether the dispatching instruction sequence is tampered in the transmission process is checked, and the integrity of the dispatching instruction sequence is verified by using a digital signature or a hash value; the rationality verification is a key step for guaranteeing the safety and stability of the power grid dispatching system, for example, checking whether the dispatching instruction sequence is consistent with the current working requirement of the power grid dispatching system or verifying whether the dispatching instruction sequence can cause potential risks, such as short circuit, overload and the like, so as to reduce the possibility that the dispatching instruction sequence brings adverse effects to the power grid dispatching system.
For example, when a certain power station in the power grid dispatching system receives a dispatching command sequence from a power grid dispatching center, the output power of a certain generator is required to be improved, and before the power station executes the dispatching command sequence, the authenticity of the dispatching command sequence is verified. In performing the authenticity verification, the source of the dispatch instruction sequence may be verified a priori, for example using a digital certificate or identity token to ensure that the dispatch instruction sequence is from an authorized utility company or grid dispatching center, or by obtaining biometric information of the instruction editing user from information carried by the dispatch instruction sequence, to verify whether the instruction editing user is an authorized instruction editing user. In addition, the transmission channel of the scheduling instruction sequence can be verified, so that the scheduling instruction sequence is ensured to be transmitted through an encrypted and protected communication channel, and the scheduling instruction sequence is prevented from being tampered maliciously in the transmission process; the scheduling instruction sequence can be compared with the historical scheduling instruction sequence to ensure that the sending mode and the content format of the scheduling instruction sequence are consistent with the historical scheduling instruction sequence.
In addition to the authenticity verification, the power plant also requires a rationality verification of the sequence of scheduling instructions. For example, the power station needs to acquire the current working state of the power system, such as the running state of the generator, the load condition of the line, the available capacity of the transformer substation, and the like, and then evaluate whether the scheduling command sequence forms a risk for the safety state of the power system, such as whether the output power of the generator is increased to cause overload or unstable voltage of the power system, and whether other measures need to be taken to reduce the safety risk, such as starting other generators or adjusting the voltage of the generators. In addition, it can be checked whether the sequence of scheduling instructions would violate the requirements of the power system operation, such as whether environmental regulations or power market regulations would be violated; the time of execution of the sequence of scheduling instructions may also be evaluated, as well as checking whether devices and human resources in the power system are available to execute the corresponding sequence of scheduling instructions.
S800, under the condition that the dispatching instruction sequence passes the authenticity verification and the rationality verification, executing the power grid dispatching operation according to the dispatching instruction in the dispatching instruction sequence.
Under the condition that the scheduling instruction sequence passes the authenticity verification and the rationality verification, the instruction execution end considers that the received scheduling instruction sequence is from a legal source, is not tampered and is reasonable to operate, and meets the requirement of the power system.
If any verification flow of the authenticity verification and the rationality verification of the dispatching instruction sequence fails, the instruction execution end will not execute the corresponding power grid dispatching operation. If the scheduling instruction sequence does not pass the authenticity verification, the source of the scheduling instruction sequence is illegal; if the scheduling instruction sequence fails the rationality verification, it means that the scheduling instruction sequence does not conform to the current requirement of the power system, and even the security risk is brought to the power system. In addition, if the scheduling instruction sequence fails the authenticity verification, the instruction execution end can send a notification to the related party or the power grid dispatching center to report the authenticity verification condition of the scheduling instruction sequence, and the power grid dispatching center can check the original scheduling instruction sequence according to the verification condition, verify the identity of the instruction editor, check the source of the scheduling instruction sequence and the like; if the dispatching instruction sequence fails the rationality verification, the instruction execution terminal can send a notification to the related party or the power grid dispatching center to report the rationality verification condition of the dispatching instruction sequence, and can also request the power grid dispatching center to recheck the dispatching instruction sequence or propose instruction modification suggestions and the like.
In the power grid dispatching method, the encrypted dispatching instruction sequence is received, decryption processing is carried out on the encrypted dispatching instruction sequence to obtain dispatching instruction sequence data, authenticity verification and rationality verification are carried out on the dispatching instruction sequence in the dispatching instruction sequence data, and under the condition that the dispatching instruction sequence passes through the authenticity verification and the rationality verification, the dispatching instruction sequence is edited by a user with instruction editing authority, and is reasonable and matched with the power grid running state, and then power grid dispatching operation corresponding to the dispatching instruction sequence is executed. Therefore, the possibility that the power grid dispatching system is attacked by the outside can be reduced, and the safety risk caused by the fact that the power grid dispatching system executes fake dispatching instructions or unreasonable dispatching instructions is reduced, so that the reliability of the power grid dispatching system is improved.
In one embodiment, as shown in fig. 3, the scheduling instruction sequence in the scheduling instruction sequence data carries the first biometric information of the instruction editing user, and S600 includes:
s610, analyzing the dispatching instruction sequence data and determining an instruction editing user with dispatching instruction sequence data sending authority.
In the power grid dispatching system, the instruction execution end can analyze and obtain an instruction editing user with the authority of sending the dispatching instruction sequence according to the dispatching instruction sequence data. Illustratively, an instruction editing user library is maintained in the power dispatching system to record and manage the rights of the instruction editing user. Through the instruction editing user library, a system administrator or related staff can query which instruction editing users have what instruction editing rights. For example, the scheduling instruction sequence data may include a scheduling instruction type, which the instruction execution end uses to query which instruction editing users have associated scheduling instruction sequence data transmission rights.
The instruction execution end analyzes the scheduling instruction to determine the type of the scheduling instruction, namely, an engine power adjustment instruction, and then queries an instruction editing user library, such as an input instruction type or related keywords, and the query result displays an instruction editing user with the transmission authority of the scheduling instruction of the type. By the method, the instruction execution end can determine the instruction editing user with the sending authority of the scheduling instruction of the specific type, so that the authenticity of the subsequent scheduling instruction sequence can be verified.
S630, obtaining characteristic indication data output by the circulating data source at the editing moment of the scheduling instruction.
The feature indication data may be used to characterize the kind of biometric information to be extracted. For example, a mapping relationship between the feature value indicating data and the type of the biometric information to be extracted may be pre-established, for example, the feature indicating data may be a limited random number, the biometric information to be extracted may be fingerprint information and face information, and the pre-established mapping relationship may be that when the feature indicating data is an odd number, the corresponding biometric information is fingerprint information; when the feature indication data is even, the corresponding biometric information is face information.
The circulating data source is a data source generated or refreshed according to a certain period, for example, data generated according to time, events or other conditions, and the circulating data source can be an external data source such as weather forecast, astronomical station information or a designated water level place, or can be a preset internal data source capable of circularly outputting different elements in the same data set in sequence. By way of example, the cyclic data source may be weather data, the weather data source providing weather data updated hourly or daily, and the mapping table at this time may be: the "sunny day" corresponds to the "fingerprint information", "cloudy day" corresponds to the "voiceprint information", "rainy day" corresponds to the "face information", and the like. The source of the recurring data may be a data port capable of recurring output of some fixed data content, and the fed back data content may be used as a biometric information type selected from a number of biometric information types for authenticity verification. Therefore, after the instruction execution end receives the scheduling instruction sequence, the instruction execution end needs to acquire the feature indication data output by the circulating data source at the instruction editing time so as to extract the correct biological feature type later, and the scheduling instruction sequence data can comprise a time stamp at the instruction editing time, so that the feature extraction data output by the circulating data source at the instruction editing time can be positioned through the time stamp.
In addition, the feature extraction data may directly indicate not only the kind of the biological feature to be extracted but also the kind of the biological feature to be extracted. For example, the mapping relation between the feature extraction data and the type extraction identifier and the mapping relation between the pre-constructed type extraction identifier and the biological feature type are pre-constructed, and the mapping from the feature extraction data to the biological feature type needs to be performed twice, so that the safety and the reliability of the authenticity verification process are further improved. The feature extraction data comprise a "sunny day" and the corresponding type extraction identifier is a "fingerprint extraction identifier", and further, fingerprint information of the instruction editing user can be extracted from a biological feature information base of the instruction editing user by using the "fingerprint extraction identifier".
S650, extracting the second biological characteristic information of the instruction editing user matched with the characteristic indicating data.
The dispatch instruction sequence in the dispatch instruction sequence data carries first biological characteristic information of the instruction editing user, wherein the first biological characteristic information is the biological characteristic information of the instruction editing user added by the instruction sending end when the dispatch instruction is edited, and the first biological characteristic information can be sent together with the dispatch instruction sequence in a digital watermark mode. The second biological characteristic information is the biological characteristic information of the user edited by the extracted instruction according to the characteristic indication data output by the circulating data source when the instruction execution end verifies the authenticity of the scheduling instruction in the scheduling instruction sequence.
For example, a feature information base is provided in the power grid dispatching system, and a plurality of different types of biometric information of the command editing user are stored in the feature information base, and the biometric information of the different command editing users is different. The instruction execution end determines the instruction editing user with the dispatching instruction sequence data sending authority by analyzing the dispatching instruction sequence data, and only extracts the biological characteristic information matched with the characteristic indication data of the instruction editing user from the characteristic information base to be recorded as second biological characteristic information for subsequent dispatching instruction authenticity verification. The instruction execution end has the authority to access the characteristic information base, the type of the biological characteristic to be extracted can be clarified through the characteristic indication data, the query language or other database query tools matched with the characteristic information base are used for submitting the query to the characteristic information base to search the biological characteristic information type matched with the characteristic indication data, and the required biological characteristic information type can be extracted from the characteristic information base after the query is successful. The steps can be automatically completed, or can be completed by combining automation and manual operation, so that the safety and the accuracy of the process of extracting the second biological characteristic information are ensured.
And S670, performing similarity matching on the first biological characteristic information and the second biological characteristic information to obtain an authenticity verification result.
After the first biometric information and the second biometric information are obtained, similarity matching needs to be carried out on the first biometric information and the second biometric information so as to determine whether the first biometric information and the second biometric information are the same instruction for editing the biometric information of the user. Illustratively, corresponding features, such as feature points, lines, colors, shapes, etc., are first extracted from the first biometric information and the second biometric information, depending on the type of biometric feature. After extracting the features, a predetermined comparison algorithm may be invoked to compare features of the first biometric information and the second biometric information, such as pattern matching, similarity metrics, or other algorithms, to evaluate similarity between the two. The similarity score of the two can be obtained through a comparison algorithm and is used for measuring the similarity degree of the first biological characteristic information and the second biological characteristic information. Comparing the similarity score with a predefined similarity threshold, and if the similarity score is higher than the threshold, considering that the similarity score and the threshold are matched; otherwise, the two are considered to be not matched. The authenticity verification result can be obtained according to the similarity result, and if the similarity matching result indicates that the matching is successful, the authenticity verification result is indicated to pass; if the similarity matching fails, the authenticity verification result is indicated to fail.
S690: and verifying the rationality of the scheduling instruction in the scheduling instruction sequence data.
After the authenticity of the scheduling instruction in the scheduling instruction sequence is verified, the reasonability verification of the scheduling instruction sequence is also needed to further improve the safety and reliability of the power system. For example, rationality verification may include verifying whether each dispatch instruction value in a dispatch instruction sequence is within a reasonable range, such as whether voltage-current values are within an allowable range, reducing potential security risks; and the method can also comprise the step of carrying out security verification on each scheduling instruction in the scheduling instruction sequence, wherein if the power grid is unstable due to the fact that the generator is turned off when the scheduling instruction is executed, the instruction execution end can judge that the scheduling instruction fails to pass the rationality verification. In addition, the rationality verification can also evaluate the rationality of the dispatching instruction sequence, and whether the dispatching instruction sequence is suitable for the current working state of the power system, for example, the dispatching instruction of opening the power line can be performed under the condition that the voltage level of the transformer substation is proper, if the dispatching instruction sequence requires that the voltage is regulated to be unsuitable for opening the power line, the power line is opened, and the instruction execution terminal can judge that the dispatching instruction sequence is unreasonable. The rationality verification may also perform a compliance determination on the scheduling instruction sequence to verify whether the scheduling instruction sequence meets the power industry specifications.
In this embodiment, by analyzing the scheduling instruction sequence data, determining an instruction editing user having the transmission authority of the scheduling instruction sequence data, and acquiring feature indication data output by the cyclic data source at the time of the scheduling instruction editing, second biometric information of the instruction editing user matched with the feature indication data is extracted, and then similarity matching is performed on the first biometric information and the second biometric information, so as to obtain an authenticity verification result. According to the authenticity verification method, the types of the biological characteristics are random, so that the reliability of the authenticity verification process can be improved, and the risk that the power grid dispatching system is attacked by external fake instructions or fake biological characteristic information is reduced. In addition, after the authenticity verification is carried out on the dispatching instruction in the dispatching instruction sequence, the rationality verification is carried out on the dispatching instruction sequence, so that the reliability of the power grid dispatching system is further improved.
In one embodiment, as shown in fig. 4, S650 includes:
s652, according to the mapping relation between the preset feature indication data and the type extraction identification, the type extraction identification matched with the feature indication data is determined, and the type extraction identification is used for representing the type of the biological feature information to be extracted.
The type extraction identifier is used for representing the type of the to-be-extracted biological feature information, and may be an information extraction identifier or an information extraction tag, through which the type of the to-be-extracted biological feature can be determined, for example, the type extraction identifier is a "fingerprint identifier", and the type extraction identifier can be used for extracting fingerprint information of a corresponding instruction editing user from the feature information base.
Taking a circulating data source as a weather data source as an example, updating feature indication data output once per hour, wherein the feature indication data can comprise three weather data of sunny days, rainy days and cloudy days, and the mapping relation between the preset feature indication data and type extraction identifiers is stored in the system, such as fingerprint identifiers corresponding to sunny days, face identifiers corresponding to rainy days and voiceprint identifiers corresponding to cloudy days. The weather data can be directly obtained from a weather station, and can also be externally connected with a weather sensor or other equipment capable of monitoring weather so as to obtain the weather data in real time. The scheduling instruction sequence received by the instruction receiving end comprises time stamp data corresponding to the instruction editing time, the feature indication data output by the weather data source at the instruction editing time can be determined according to the time stamp data, for example, the feature indication data is 'sunny', and the corresponding type extraction type can be determined to be 'fingerprint identification' according to the mapping relation between the preset feature indication data and the type extraction identification.
S654, extracting second biometric information corresponding to the type extraction identifier.
After the type extraction identifier is obtained, second biometric information matched with the type extraction identifier can be extracted from the biometric information base, or corresponding biometric information can be obtained from an external data source, for example, an identity card photo of the instruction editing user is obtained, and facial information of the instruction editing user is extracted from the biometric information. Taking the example of extracting the second biological characteristic information corresponding to the type extraction identifier from the biological characteristic information base, the instruction execution end has the authority to access the biological characteristic information base, submits the query to the biological characteristic information base by using a query language or a database query tool according to the type extraction identifier, and filters the query result based on the type extraction identifier to search the biological characteristic information of the specified type, wherein the query result is the second biological characteristic information matched with the type extraction identifier. In addition, the query result can be appropriately processed, such as image processing, voice analysis or other data processing steps, so as to meet the authenticity verification requirement.
In this embodiment, according to the feature indication data and the mapping relationship between the feature indication data and the type extraction identifier, the type extraction identifier may be determined, and the corresponding second biometric information may be extracted using the type extraction identifier to provide for subsequent authenticity verification. Because the feature indication data has certain randomness, the mapping relation between the feature indication data and the type extraction identification can be preset, and an external attacker cannot know the meaning of the feature indication data easily, even if the meaning of the feature indication data is known, the mapping relation between the feature indication data and the type extraction identification cannot be known, so that the reliability of the power grid dispatching system is improved. In addition, the mapping relation between the feature indication data and the type extraction identification can be set according to the requirements, so that the flexibility of the power grid dispatching system is improved.
In one embodiment, as shown in fig. 5, the trained command plausibility check is obtained based on the historical scheduling command sequence data and the grid state information corresponding to the scheduling command editing time, and S690 includes:
s692, acquiring power grid state information corresponding to the editing time of the scheduling instruction sequence.
The grid status information, including voltage level, current frequency, power factor, equipment status, and load conditions in the power system, may be used to evaluate the power system's operation.
The sensor or other measuring device of the transformer substation is in communication connection with the instruction execution end, and the sensor or measuring device can measure parameters such as voltage, current, frequency, power factor and the like, and the instruction execution end can periodically request to acquire the parameters, or can set the device to send the parameters to the instruction execution end at regular time. When the instruction execution end needs to acquire the power grid state information corresponding to the editing moment of the scheduling instruction sequence, a data acquisition request can be sent to the corresponding measuring equipment, and the data acquisition request can carry a time stamp corresponding to the editing moment of the scheduling instruction sequence; the time stamp can also be used for directly inquiring in a power grid state information base so as to acquire the power grid state information corresponding to the editing moment of the scheduling instruction sequence.
S694, the trained instruction rationality verification model is called by taking the dispatching instruction sequence data and the power grid state information as inputs, and a rationality verification result is obtained.
The trained command rationality verification model can be obtained by training based on historical scheduling command sequence data and power grid state information corresponding to the scheduling command editing time, for example, the past power grid scheduling command sequence data, corresponding power grid state information and response of a power system are used as training data, the command rationality verification model is trained, the training data comprises normal conditions and abnormal conditions, and the training goal of the command rationality verification model is to learn the relation between the scheduling command sequence data and the power grid state information. The instruction rationality verification model may be a neural network model, such as a convolutional neural network, a time-series neural network, and the like, to analyze the instruction sequence and the power grid state information.
Before the dispatching instruction sequence data and the power grid state information are input into the trained instruction rationality check model, the power grid state information and the dispatching instruction sequence data can be subjected to data normalization processing, sequence filling, segmented coding and other operations, so that the dispatching instruction sequence is converted into characteristics suitable for model input. The trained instruction rationality check model is used for evaluating rationality of the scheduling instruction sequence, and can also be used for predicting a response result of the power system to the scheduling instruction sequence.
For example, the instruction rationality check model is trained using a historical dataset that may include historical grid state information, corresponding scheduling instruction sequences, and power system responses, resulting in a trained instruction rationality check model. The trained instruction rationality verification model can accept the scheduling instruction sequence data and the power grid state information as input and output a rationality verification result, and the rationality verification result can be probability score to represent the rationality degree of the scheduling instruction sequence data, and can be reasonable or unreasonable.
In addition, the power grid dispatching system can continuously monitor the performance of the model, update the training data periodically or irregularly, and carry out improvement on the instruction rationality check model so as to adapt to the change of the power grid state information and the power grid dispatching requirement.
In this embodiment, by acquiring the power grid state information corresponding to the editing moment of the scheduling instruction sequence, and taking the scheduling instruction sequence data and the power grid state information as inputs, invoking the trained instruction rationality verification model, a rationality verification result can be obtained, the rationality verification result can help power grid scheduling personnel make decisions about whether to execute the scheduling instruction sequence, and a rationality threshold can also be set, and an automation system automatically determines whether to execute the scheduling instruction sequence, thereby improving the safety and reliability of the power grid scheduling system.
In one embodiment, the instruction rationality check model, when invoked, performs the steps of:
and verifying the command ordering rationality of the scheduling command sequence data according to the scheduling command sequence data and the power grid state information to obtain a command ordering rationality verification result.
The instruction rationality checking model can judge whether each scheduling instruction in the scheduling instruction sequence data is reasonable or not, and can judge the instruction ordering rationality of the scheduling instruction sequence data to verify, so that an instruction ordering rationality verification result is obtained.
For example, in the training stage of the instruction rationality check model, historical power grid state information, a corresponding scheduling instruction sequence and a sequencing label related to the sequencing of the scheduling instruction sequence need to be used, and the sequencing label can represent rationality sequencing of the instruction sequence, including normal sequencing and abnormal sequencing, so that the trained instruction rationality check model is obtained. Preprocessing the scheduling instruction data and the power grid state information, such as performing data normalization processing, sequence filling, segment coding on the scheduling instruction sequence, and the like, so that the scheduling instruction sequence is converted into characteristics suitable for model input. And taking the dispatching instruction sequence data and the power grid state information as inputs, calling the trained instruction rationality verification model, and outputting an instruction sequencing rationality verification result. For example, the scheduling command sequence includes two scheduling commands, namely "start high-power generator" and "start low-power generator" in order, and the grid state information includes the grid load information and the voltage. The scheduling instruction sequence data and the power grid state information are input into a trained instruction rationality verification model, and the voltage instability and the frequency fluctuation of a power system are possibly caused by directly starting a high-power generator, so that the stability of the power system is negatively influenced, and therefore, the instruction ordering rationality verification result output by the trained instruction rationality verification model can be 'unreasonable'. In addition, the trained command rationality verification model can also give out suggestions related to scheduling command sequences according to the input power grid state information. For example, the grid status information indicates that the power system cannot meet the load demand, and additional power generators need to be started, and the advice on the scheduling command sequence given by the trained command rationality check model may be "start low-power generator first" and "start high-power generator later" to maintain the stability of the power system.
In this embodiment, when the trained instruction rationality verification model is invoked, the instruction ordering rationality of the instruction sequence data can be verified according to the scheduling instruction sequence data and the power grid state information, so as to obtain an instruction ordering rationality verification result, reduce the negative influence of the unreasonably ordered scheduling instruction sequence on the power system, and further improve the reliability of the power grid scheduling system.
In order to make a clearer description of the power grid dispatching method provided in the present application, a specific embodiment and fig. 5 are described below, where the specific embodiment includes the following steps:
s200, receiving an encrypted scheduling instruction sequence.
S400, decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data.
S610, analyzing the dispatching instruction sequence data and determining an instruction editing user with dispatching instruction sequence data sending authority.
S630, obtaining characteristic indication data output by the circulating data source at the editing moment of the scheduling instruction.
S652, according to the mapping relation between the preset feature indication data and the type extraction identification, the type extraction identification matched with the feature indication data is determined, and the type extraction identification is used for representing the type of the biological feature information to be extracted.
S654, extracting second biometric information corresponding to the type extraction identifier.
And S670, performing similarity matching on the first biological characteristic information and the second biological characteristic information to obtain an authenticity verification result.
S692, acquiring power grid state information corresponding to the editing time of the scheduling instruction sequence.
S694, taking the dispatching instruction sequence data and the power grid state information as input, and calling a trained instruction rationality verification model to obtain a rationality verification result.
S800, under the condition that the dispatching instruction sequence passes the authenticity verification and the rationality verification, executing the power grid dispatching operation according to the dispatching instruction in the dispatching instruction sequence.
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, as shown in fig. 6, there is provided a power grid dispatching system 300 comprising: the instruction sending end 320 and the instruction receiving end 340 are in communication connection;
the instruction sending end 320 is configured to edit the scheduling instruction sequence, obtain feature indication data corresponding to the current time of the cyclic data source, determine a type extraction identifier matched with the feature indication data according to the feature indication data and a mapping relationship between the preset feature indication data and the type extraction identifier, extract first biological feature information of an instruction editing user corresponding to the type extraction identifier, add the biological feature information to the scheduling instruction sequence, perform encryption processing, obtain an encrypted scheduling instruction sequence, and send the encrypted scheduling instruction sequence to the instruction receiving end 340.
The instruction receiving end 340 is configured to respond to the encrypted scheduling instruction sequence, and call the power grid scheduling method in any one of the power grid scheduling method embodiments to perform power grid scheduling.
The instruction sending end 320 is mainly configured to embed the first biometric information of the instruction editing user into the scheduling instruction sequence, and encrypt and send the first biometric information to the instruction receiving end 340. The feature indication data may be used to characterize the kind of biometric information to be extracted. For example, a mapping relationship between the feature value indicating data and the type of the biometric information to be extracted may be pre-established, for example, the feature indicating data may be a limited random number, the biometric information to be extracted may be fingerprint information and face information, and the pre-established mapping relationship may be that when the feature indicating data is an odd number, the corresponding biometric information is fingerprint information; when the feature indication data is even, the corresponding biometric information is face information.
The circulating data source is a data source generated or refreshed according to a certain period, for example, data generated according to time, events or other conditions, and the circulating data source can be an external data source such as weather forecast, astronomical station information or a designated water level place, or can be a preset internal data source capable of circularly outputting different elements in the same data set in sequence. By way of example, the cyclic data source may be weather data, the weather data source providing weather data updated hourly or daily, and the mapping table at this time may be: the "sunny day" corresponds to the "fingerprint information", "cloudy day" corresponds to the "voiceprint information", "rainy day" corresponds to the "face information", and the like. The source of the recurring data may be a data port capable of recurring output of some fixed data content, and the fed back data content may be used as a biometric information type selected from a number of biometric information types for authenticity verification.
In addition, the feature extraction data may directly indicate not only the kind of the biological feature to be extracted but also the kind of the biological feature to be extracted. For example, the mapping relation between the feature extraction data and the type extraction identifier and the mapping relation between the pre-constructed type extraction identifier and the biological feature type are pre-constructed, and the mapping from the feature extraction data to the biological feature type needs to be performed twice, so that the safety and the reliability of the authenticity verification process are further improved. The feature extraction data comprise a "sunny day" and the corresponding type extraction identifier is a "fingerprint extraction identifier", and further, fingerprint information of the instruction editing user can be extracted from a biological feature information base of the instruction editing user by using the "fingerprint extraction identifier".
In an exemplary embodiment, the power grid dispatching system is provided with a feature information base, and the feature information base stores a plurality of different types of biometric information of the command editing user, wherein the biometric information of the different command editing users is different. Since the instruction execution end has determined the instruction editing user with the sending authority of the dispatching instruction sequence data by analyzing the dispatching instruction sequence data, only the biological characteristic information matched with the characteristic indication data of the instruction editing user is extracted from the characteristic information base and is recorded as the first biological characteristic information for the instruction receiving end 340 to verify the authenticity of the dispatching instruction. Illustratively, the instruction sending end 320 has the authority to access the feature information base, the type of the biological feature to be extracted can be clarified through the feature indication data, and the query is submitted to the feature information base to search the type of the biological feature information matched with the feature indication data by using a query language matched with the feature information base or other database query tools, so that the required type of the biological feature information can be extracted from the feature information base after the query is successful. The steps can be automatically completed, or can be completed by combining automation and manual operation, so that the safety and the accuracy of the process of extracting the first biological characteristic information are ensured.
After extracting the first biometric information of the instruction editing user corresponding to the type extraction identifier, the instruction transmitting end 320 adds the biometric information to the scheduling instruction sequence and performs encryption processing to obtain an encrypted scheduling instruction sequence, and then transmits the encrypted scheduling instruction sequence to the instruction receiving end 340. Then, the instruction receiving end 340 may call the power grid dispatching method in any of the embodiments of the power grid dispatching method to perform power grid dispatching, and execute the corresponding power grid dispatching operation to determine the smooth running of the power grid, and the specific power grid dispatching process is not described herein.
The power grid dispatching system allows the instruction sending end 320 to add the first biological characteristic information of the instruction editing user to the dispatching instruction sequence, encrypts and sends the first biological characteristic information to the instruction receiving end 340, and when the authenticity verification and the rationality verification of the dispatching instruction sequence by the instruction receiving end 340 are passed, the corresponding power grid dispatching operation is executed, so that the correctness and the rationality of the dispatching instruction sequence are improved, and the safe and stable operation of the power grid is ensured.
Based on the same inventive concept, the embodiment of the application also provides a power grid dispatching device for realizing the power grid dispatching method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the power grid dispatching device or devices provided below may be referred to the limitation of the power grid dispatching method hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 7, there is provided a power grid dispatching apparatus 700, comprising: instruction fetch module 720, instruction decrypt module 740, instruction validate module 760, and instruction execute module 780, wherein:
an instruction acquisition module 720 for receiving an encrypted scheduling instruction sequence;
the instruction decryption module 740 is configured to decrypt the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data;
the instruction verification module 760 is configured to perform authenticity verification and rationality verification on the scheduled instruction sequence in the scheduled instruction sequence data;
the instruction execution module 780 is configured to execute a power grid dispatching operation according to a dispatching instruction in the dispatching instruction sequence if the dispatching instruction sequence passes the authenticity verification and the rationality verification.
In one embodiment, the scheduling instruction sequence in the scheduling instruction sequence data carries the first biological feature information of the instruction editing user, and the instruction verification module 760 is further configured to analyze the scheduling instruction sequence data and determine the instruction editing user having the transmission authority of the scheduling instruction sequence data; acquiring characteristic indication data output by a circulating data source at the editing moment of a scheduling instruction; extracting second biological characteristic information of the instruction editing user matched with the characteristic indicating data; and performing similarity matching on the first biological characteristic information and the second biological characteristic information to obtain an authenticity verification result.
In one embodiment, the instruction verification module 760 is further configured to determine, according to a mapping relationship between the preset feature indication data and the type extraction identifier, the type extraction identifier that matches the feature indication data, where the type extraction identifier is used to characterize a type of biometric information to be extracted; second biometric information corresponding to the type extraction identification is extracted.
In one embodiment, the instruction verification module 760 is further configured to obtain the grid state information corresponding to the scheduled instruction sequence editing time; taking scheduling instruction sequence data and power grid state information as input, and calling a trained instruction rationality verification model to obtain a rationality verification result; the trained command rationality check is obtained based on the historical scheduling command sequence data and the power grid state information corresponding to the scheduling command editing time.
In one embodiment, when the instruction verification module 760 invokes the order rationality check model, the order rationality check model performs the following steps: and verifying the command ordering rationality of the scheduling command sequence data according to the scheduling command sequence data and the power grid state information to obtain a command ordering rationality verification result.
The various modules in the power grid dispatching device can be fully or partially implemented by software, hardware and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 8. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. 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 used for storing data such as feature indication data, type extraction identification, first biological feature information, second biological feature information and the like. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a power grid dispatching method.
It will be appreciated by those skilled in the art that the structure shown in fig. 8 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the embodiments of the grid scheduling method described above when the computer program is executed.
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 grid scheduling method embodiments described above.
In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the grid scheduling method embodiments described above.
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. A method for grid dispatching, the method comprising:
receiving an encrypted scheduling instruction sequence;
decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data;
carrying out authenticity verification and rationality verification on the scheduling instruction sequence in the scheduling instruction sequence data;
and under the condition that the scheduling instruction sequence passes the authenticity verification and the rationality verification, executing the power grid scheduling operation according to the scheduling instruction in the scheduling instruction sequence.
2. The method of claim 1, wherein the scheduling instruction sequence in the scheduling instruction sequence data carries first biometric information of an instruction editing user;
the verifying of the authenticity of the scheduling instruction in the scheduling instruction sequence data comprises the following steps:
analyzing the scheduling instruction sequence data and determining an instruction editing user with the scheduling instruction sequence data sending authority;
acquiring characteristic indication data output by a circulating data source at the editing moment of a scheduling instruction;
extracting second biological characteristic information of the instruction editing user matched with the characteristic indicating data;
and performing similarity matching on the first biological characteristic information and the second biological characteristic information to obtain an authenticity verification result.
3. The method of claim 2, wherein the extracting the instruction to edit the second biometric information of the user that matches the feature indication data comprises:
determining a type extraction identifier matched with the feature indication data according to a mapping relation between the preset feature indication data and the type extraction identifier, wherein the type extraction identifier is used for representing the type of the biological feature information to be extracted;
And extracting the second biological characteristic information corresponding to the type extraction identification.
4. The method of claim 1, wherein validating the sequence of scheduled instructions in the sequence of scheduled instructions data comprises:
acquiring power grid state information corresponding to the editing moment of the scheduling instruction sequence;
taking the scheduling instruction sequence data and the power grid state information as inputs, and calling a trained instruction rationality verification model to obtain a rationality verification result;
the trained instruction rationality check is obtained by training based on historical scheduling instruction sequence data and power grid state information corresponding to scheduling instruction editing time.
5. The method of claim 4, wherein the instruction plausibility check model, when invoked, performs the steps of:
and verifying the command ordering rationality of the scheduling command sequence data according to the scheduling command sequence data and the power grid state information to obtain a command ordering rationality verification result.
6. A power grid dispatching system, the system comprising: the instruction sending end and the instruction receiving end are in communication connection;
the instruction sending end is used for editing a dispatching instruction sequence, acquiring feature indication data corresponding to the current moment of a circulating data source, determining a type extraction identifier matched with the feature indication data according to the feature indication data and the preset mapping relation between the feature indication data and the type extraction identifier, extracting first biological feature information of an instruction editing user corresponding to the type extraction identifier, adding the biological feature information into the dispatching instruction sequence, performing encryption processing to obtain the encrypted dispatching instruction sequence, and sending the encrypted dispatching instruction sequence to the instruction receiving end;
The instruction receiving end is configured to respond to the encrypted scheduling instruction sequence, and call the power grid scheduling method according to any one of claims 1 to 5 to perform power grid scheduling.
7. A power grid dispatching apparatus, the apparatus comprising:
the instruction acquisition module is used for receiving the encrypted scheduling instruction sequence;
the instruction decryption module is used for decrypting the encrypted scheduling instruction sequence to obtain scheduling instruction sequence data;
the instruction verification module is used for verifying authenticity and rationality of the scheduling instruction sequence in the scheduling instruction sequence data;
and the instruction execution module is used for executing power grid dispatching operation according to the dispatching instructions in the dispatching instruction sequence under the condition that the dispatching instruction sequence passes the authenticity verification and the rationality verification.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 5.
CN202311480757.0A 2023-11-08 2023-11-08 Power grid dispatching method, system, device, computer equipment and storage medium Pending CN117592693A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118129760A (en) * 2024-04-30 2024-06-04 中国电建集团华东勘测设计研究院有限公司 Track route recording device applied to water environment monitoring

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118129760A (en) * 2024-04-30 2024-06-04 中国电建集团华东勘测设计研究院有限公司 Track route recording device applied to water environment monitoring

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