CN111369088A - Block chain control system and control method for power grid dispatching system - Google Patents
Block chain control system and control method for power grid dispatching system Download PDFInfo
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Abstract
The invention relates to a block chain control system and a control method for a power grid dispatching system, wherein a block chain comprises an updating block, a storage block, a backup block and a sharing block, and the system comprises a storage module, an updating module, a sharing module and a backup module; the invention can realize the purpose that historical information can be inquired and the power grid data of the power system can be backed up by controlling the updating block, the storage block, the backup block and the sharing block to respectively record the updating information, the storage information, the backup information and the sharing information of the power grid data of the power system.
Description
Technical Field
The invention relates to the technical field of power system automation, in particular to a block chain control system and a block chain control method for a power grid dispatching system.
Background
The development of the power grid dispatching system can be summarized into two stages: in the empirical dispatching stage and the analytic dispatching stage, along with the development of technology and the rapid expansion of the power grid scale, the days when dispatchers of power grid companies carry out regional power grid dispatching and accident emergency treatment by virtue of experience and strain capacity are gradually going far away, and the analytic dispatching system gradually occupies the market leading position. With the development and the deepening of the power system, in order to ensure the safe and high-quality operation of the power grid, the power regulation and control system can simultaneously operate a plurality of application systems, and the power grid dispatching system needs to store and share data with other systems.
In the prior art, in order to realize data exchange and sharing between a power grid dispatching system and other systems, a power grid dispatching control data model is established according to the guidance of Common Information Model (CIM) extension, and a data exchange scheme including a data exchange frame, overall data exchange design and data subscription is formed by combining with the IEC 61970 standard.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to solve the problem of data interaction between a power grid dispatching system and other application systems in the prior art by using a block chain technology.
The purpose of the invention is realized by adopting the following technical scheme:
the invention provides a block chain control system facing a power grid dispatching system, which is improved in that a block chain comprises an updating block, a storage block, a backup block and a sharing block, and the system comprises a storage module, an updating module, a sharing module and a backup module;
the updating module is used for acquiring power grid updating data of the power system, recording updating information of the updating block and sending the power grid updating data of the power system to the storage block;
the storage module is used for acquiring and storing the power grid updating data provided by the updating block, recording the storage information of the storage block and sending the power grid updating data stored in the storage block to the backup block; the shared block is also used for sending data required by the user to the shared block according to the user request;
the backup module is used for backing up the data stored in the storage block and recording the backup information of the backup block;
and the sharing module is used for calling data required by the user from the storage block according to the user request, sending the data to the user and recording the sharing information of the sharing block.
Preferably, the update module includes:
the identity authentication module is used for performing identity authentication on the acquired power grid updating data of the power system by using a preset data linked list;
the updating nonlinear hash coding module is used for acquiring a first hash value of the power grid updating data of the power system by taking the characteristic data of the power grid updating data of the power system as the input of a pre-established neural network model if the identity authentication is passed, or else, acquiring the power grid updating data of the power system again;
the data updating module is used for acquiring the Hamming distance between the first Hash value and the Hash value in the updating block Hash table, recording updating information corresponding to the Hash value in the updating block Hash table if the Hamming distance is smaller than a preset threshold value, and sending the power grid updating data of the power system and the first Hash value thereof to the storage block, or adding the first Hash value to the updating block Hash table and recording the updating information corresponding to the first Hash value;
the characteristic data comprises a collecting node timestamp, a collecting node information abstract and a collecting node identity; the preset data linked list comprises the number of collection nodes of the power grid data of the power system, a collection node timestamp, a collection node information abstract and a collection node identity.
Preferably, the storage module includes:
the power grid dispatching rule verification module is used for verifying whether the power grid parameters of the power grid updating data of the power system provided by the obtained updating block conform to preset power grid dispatching rules or not;
the storage nonlinear hash coding module is used for acquiring a second hash value of the power grid updating data of the power system provided by the acquired updating block by taking the acquired characteristic data of the power grid updating data of the power system provided by the updating block as the input of a pre-established neural network model if the storage nonlinear hash coding module passes the verification of the power grid scheduling rule verification module, or else, acquiring the power grid updating data of the power system provided by the updating block again;
the storage data verification module is used for verifying whether the second hash value is the same as the first hash value of the power grid updating data of the power system provided by the obtained updating block, if so, the storage data module is switched to, and otherwise, the power grid updating data of the power system provided by the updating block is obtained again;
the storage data module is used for acquiring the hamming distance between the second hash value and the hash value in the storage block hash table, recording storage information corresponding to the hash value in the storage block hash table if the hamming distance is smaller than a preset threshold value, sending the data stored in the storage block and the second hash value thereof to the backup block, sending the power grid data and the hash value thereof required by a user to the shared block, and otherwise, adding the second hash value to the storage block hash table and recording the storage information corresponding to the second hash value;
and the storage information comprises the acquired power grid updating data of the power system provided by the updating block.
Preferably, the backup module comprises:
the backup nonlinear hash coding module is used for taking the acquired characteristic data of the data stored in the storage block as the input of a pre-established neural network model and acquiring a third hash value of the data stored in the acquired storage block;
the backup data verification module is used for verifying whether the third hash value is the same as the second hash value of the acquired data stored in the storage block, if so, the backup data module is switched to, and otherwise, the data stored in the storage block is acquired again;
the backup data module is used for acquiring the Hamming distance between the third Hash value and the Hash value in the backup block Hash table, if the Hamming distance is smaller than a preset threshold value, recording backup information corresponding to the Hash value in the backup block Hash table, otherwise, adding the third Hash value into the backup block Hash table, and recording the backup information corresponding to the third Hash value;
and the backup information comprises the data stored in the acquired storage blocks.
Preferably, the sharing module includes:
the shared nonlinear hash coding module is used for taking the acquired characteristic data of the power grid data required by the user and provided by the storage block as the input of a pre-established neural network model and acquiring a fourth hash value of the power grid data required by the user and provided by the acquired storage block;
the shared data verification module is used for verifying whether the fourth hash value is the same as the acquired third hash value of the power grid data required by the user and provided by the storage block, if so, the shared data module is switched to, and otherwise, the power grid data required by the user and provided by the storage block is acquired again;
the shared data module is used for acquiring the Hamming distance between the fourth Hash value and the Hash value in the Hash table of the shared data module, if the Hamming distance is smaller than a preset threshold value, recording shared information corresponding to the Hash value in the Hash table of the shared data module, otherwise, adding the fourth Hash value into the Hash table of the shared block, and recording the shared information corresponding to the fourth Hash value;
and the shared interface module is used for calling the power grid data required by the user from the storage block and sending the power grid data to the user.
Preferably, the obtaining process of the pre-established neural network model includes:
obtaining a hash value of characteristic data of the historical power grid data by using a hash algorithm;
and training the initial neural network model by taking the characteristic data of the historical power grid data as input layer training sample data of the initial neural network model and taking the hash value of the characteristic data of the historical power grid data as output layer training sample data of the initial neural network model, and acquiring the pre-established neural network model.
The invention provides a block chain control method for a power grid dispatching system, which is improved in that the method comprises the following steps:
the updating module acquires power grid updating data of the power system, records updating information of an updating block and sends the power grid updating data of the power system to a storage block;
the storage module acquires and stores power grid updating data provided by the updating block, records storage information of the storage block, sends the data stored in the storage block to the backup block, and sends data required by a user to the sharing block;
the backup module backs up the data stored in the storage block and records backup information of the backup block;
the sharing module calls data required by the user from the storage block according to the user request, sends the data required by the user and provided by the storage block to the user, and records sharing information of the sharing block.
Compared with the closest prior art, the invention has the following beneficial effects:
according to the block chain control system and the control method for the power grid dispatching system, provided by the invention, historical information of interaction between the power system and the power grid dispatching system is recorded by controlling the updating block, the sharing block, the storage block and the backup block, so that the problem that the historical information cannot be inquired, the data is updated or the sharing is abnormal in the prior art is solved; the problem of data loss in the prior art is solved by backing up the power grid data of the power system through the backup blocks.
Drawings
FIG. 1 is a block chain system structure diagram of the grid dispatching system;
fig. 2 is a control flow chart of the blockchain system of the grid dispatching system.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a block chain system facing a power grid dispatching system, as shown in fig. 1, a block chain comprises an updating block, a storage block, a backup block and a sharing block, and the system comprises a storage module, an updating module, a sharing module and a backup module;
the updating module is used for acquiring power grid updating data of the power system, recording updating information of the updating block and sending the power grid updating data of the power system to the storage block;
the storage module is used for acquiring and storing the power grid updating data provided by the updating block, recording the storage information of the storage block and sending the power grid updating data stored in the storage block to the backup block; the shared block is also used for sending data required by the user to the shared block according to the user request;
the backup module is used for backing up the data stored in the storage block and recording the backup information of the backup block;
and the sharing module is used for calling data required by the user from the storage block according to the user request, sending the data to the user and recording the sharing information of the sharing block.
In an embodiment of the application, the update module includes:
the identity authentication module is used for performing identity authentication on the acquired power grid updating data of the power system by using a preset data linked list;
the updating nonlinear hash coding module is used for acquiring a first hash value of the power grid updating data of the power system by taking the characteristic data of the power grid updating data of the power system as the input of a pre-established neural network model if the identity authentication is passed, or else, acquiring the power grid updating data of the power system again;
the data updating module is used for acquiring the Hamming distance between the first Hash value and the Hash value in the updating block Hash table, recording updating information corresponding to the Hash value in the updating block Hash table if the Hamming distance is smaller than a preset threshold value, and sending the power grid updating data of the power system and the first Hash value thereof to the storage block, or adding the first Hash value to the updating block Hash table and recording the updating information corresponding to the first Hash value;
the characteristic data comprises a collecting node timestamp, a collecting node information abstract and a collecting node identity; the preset data linked list comprises the number of collection nodes of the power grid data of the power system, a collection node timestamp, a collection node information abstract and a collection node identity.
The specific process of utilizing the preset data linked list to carry out identity verification on the acquired power grid updating data of the power system is to compare the number of the acquisition nodes, the time stamp of the acquisition nodes, the summary of the acquisition node information and the identity of the acquisition nodes of the power grid data of the power system in the preset data linked list with the number of the acquisition nodes, the time stamp of the acquisition nodes, the summary of the acquisition node information and the identity of the acquisition nodes of the power grid updating data of the power system one by one.
The memory module includes:
the power grid dispatching rule verification module is used for verifying whether the power grid parameters of the power grid updating data of the power system provided by the obtained updating block conform to preset power grid dispatching rules or not;
the storage nonlinear hash coding module is used for acquiring a second hash value of the power grid updating data of the power system provided by the acquired updating block by taking the acquired characteristic data of the power grid updating data of the power system provided by the updating block as the input of a pre-established neural network model if the storage nonlinear hash coding module passes the verification of the power grid scheduling rule verification module, or else, acquiring the power grid updating data of the power system provided by the updating block again;
the storage data verification module is used for verifying whether the second hash value is the same as the first hash value of the power grid updating data of the power system provided by the obtained updating block, if so, the storage data module is switched to, and otherwise, the power grid updating data of the power system provided by the updating block is obtained again;
the storage data module is used for acquiring the hamming distance between the second hash value and the hash value in the storage block hash table, recording storage information corresponding to the hash value in the storage block hash table if the hamming distance is smaller than a preset threshold value, sending the data stored in the storage block and the second hash value thereof to the backup block, sending the power grid data and the hash value thereof required by a user to the shared block, and otherwise, adding the second hash value to the storage block hash table and recording the storage information corresponding to the second hash value;
and the storage information comprises the acquired power grid updating data of the power system provided by the updating block.
The backup module comprises:
the backup nonlinear hash coding module is used for taking the acquired characteristic data of the data stored in the storage block as the input of a pre-established neural network model and acquiring a third hash value of the data stored in the acquired storage block;
the backup data verification module is used for verifying whether the third hash value is the same as the second hash value of the acquired data stored in the storage block, if so, the backup data module is switched to, and otherwise, the data stored in the storage block is acquired again;
the backup data module is used for acquiring the Hamming distance between the third Hash value and the Hash value in the backup block Hash table, if the Hamming distance is smaller than a preset threshold value, recording backup information corresponding to the Hash value in the backup block Hash table, otherwise, adding the third Hash value into the backup block Hash table, and recording the backup information corresponding to the third Hash value;
and the backup information comprises the data stored in the acquired storage blocks.
The sharing module comprises:
the shared nonlinear hash coding module is used for taking the acquired characteristic data of the power grid data required by the user and provided by the storage block as the input of a pre-established neural network model and acquiring a fourth hash value of the power grid data required by the user and provided by the acquired storage block;
the shared data verification module is used for verifying whether the fourth hash value is the same as the acquired third hash value of the power grid data required by the user and provided by the storage block, if so, the shared data module is switched to, and otherwise, the power grid data required by the user and provided by the storage block is acquired again;
the shared data module is used for acquiring the Hamming distance between the fourth Hash value and the Hash value in the Hash table of the shared data module, if the Hamming distance is smaller than a preset threshold value, recording shared information corresponding to the Hash value in the Hash table of the shared data module, otherwise, adding the fourth Hash value into the Hash table of the shared block, and recording the shared information corresponding to the fourth Hash value;
and the shared interface module is used for calling the power grid data required by the user from the storage block and sending the power grid data to the user.
The pre-established neural network model obtaining process comprises the following steps:
obtaining a hash value of characteristic data of the historical power grid data by using a hash algorithm;
and training the initial neural network model by taking the characteristic data of the historical power grid data as input layer training sample data of the initial neural network model and taking the hash value of the characteristic data of the historical power grid data as output layer training sample data of the initial neural network model, and acquiring the pre-established neural network model.
The input layer of the initial neural network model includes 4096 nodes, and the hidden layers include a first hidden layer and a second hidden layer.
The neural network model expands the hidden layer to two layers, on one hand, enough nonlinear relations in the samples are obtained through two layers of nonlinear transformation, and then the binary hash codes with stronger expression capability and independence are learned, and on the other hand, the problems that parameters are greatly increased, the calculated amount is too large, overfitting is easy to happen and the like due to too many layers are avoided.
The invention provides a block chain control method for a power grid dispatching system, as shown in fig. 2, the method comprises the following steps:
s1, an updating module acquires power grid updating data of an electric power system, records updating information of an updating block and sends the power grid updating data of the electric power system to a storage block;
s2, the storage module acquires and stores power grid updating data provided by the updating block, records storage information of the storage block, sends the data stored in the storage block to the backup block, and also sends data required by a user to the sharing block;
s3, the backup module backs up the data stored in the storage block and records backup information of the backup block;
and S4, the sharing module calls data required by the user from the storage block according to the user request, sends the data required by the user and provided by the storage block to the user, and records the sharing information of the sharing block.
Step S1 of the control method includes:
the identity verification module performs identity verification on the acquired power grid updating data of the power system by using a preset data linked list;
if the verification is passed through the identity verification module, the nonlinear hash coding module is updated, the characteristic data of the power grid updating data of the power system is used as the input of a pre-established neural network model, and a first hash value of the power grid updating data of the power system is obtained, otherwise, the power grid updating data of the power system is obtained again;
the data updating module acquires the Hamming distance between the first Hash value and the Hash value in the updating block Hash table, if the Hamming distance is smaller than a preset threshold value, the data updating module records updating information corresponding to the Hash value in the updating block Hash table and sends power grid updating data of the power system and the first Hash value of the power grid updating data to the storage block, and if the Hamming distance is not smaller than the preset threshold value, the data updating module adds the first Hash value to the updating block Hash table and records the updating information corresponding to the first Hash value;
step S2 includes:
the power grid dispatching rule verification module verifies whether the power grid parameters of the power grid updating data of the power system provided by the obtained updating block conform to preset power grid dispatching rules or not;
if the characteristic data of the power grid updating data of the power system provided by the obtained updating block is used as the input of a pre-established neural network model, acquiring a second hash value of the power grid updating data of the power system provided by the obtained updating block, and otherwise, re-acquiring the power grid updating data of the power system provided by the updating block;
the storage data verification module verifies whether the second hash value is the same as the first hash value of the power grid updating data of the power system provided by the obtained updating block, if so, the storage data verification module transfers to the storage data module, and if not, the storage data verification module obtains the power grid updating data of the power system provided by the updating block again;
the storage data module acquires the Hamming distance between the second Hash value and the Hash value in the storage block Hash table, if the Hamming distance is smaller than a preset threshold value, storage information corresponding to the Hash value in the storage block Hash table is recorded, the data stored in the storage block and the second Hash value of the data are sent to a backup block, power grid data and the Hash value needed by a user are sent to the shared block, and if not, the second Hash value is added to the storage block Hash table, and the storage information corresponding to the second Hash value is recorded;
if the data required by the user and stored in the storage block is lost, the data backed up in the backup block is restored to the storage block.
Step S3 includes:
the backup non-linear Hash coding module takes the acquired characteristic data of the data stored in the storage block as the input of a pre-established neural network model, and acquires a third Hash value of the acquired data stored in the storage block;
the backup data verification module verifies whether the third hash value is the same as the second hash value of the acquired data stored in the storage block, if so, the backup data verification module transfers to the backup data module, otherwise, the data stored in the storage block is acquired again;
the backup data module acquires the Hamming distance between the third Hash value and the Hash value in the backup block Hash table, if the Hamming distance is smaller than a preset threshold value, the backup information corresponding to the Hash value in the backup block Hash table is recorded, otherwise, the third Hash value is added into the backup block Hash table, and the backup information corresponding to the third Hash value is recorded;
step S4 includes:
when a user request is received, the shared interface module calls power grid data required by a user from the storage block according to the user request, and the shared non-linear Hash coding module takes the acquired feature data of the power grid data required by the user, provided by the storage block, as the input of a pre-established neural network model, and acquires a fourth Hash value of the power grid data required by the user, provided by the acquired storage block;
the shared data verification module verifies whether the fourth hash value is the same as the acquired third hash value of the power grid data required by the user and provided by the storage block, if so, the shared data verification module transfers to the shared data module, and otherwise, the power grid data required by the user and provided by the storage block is acquired again;
the shared data module obtains the Hamming distance between the fourth Hash value and the Hash value in the Hash table of the shared data module, if the Hamming distance is smaller than a preset threshold value, shared information corresponding to the Hash value in the Hash table of the shared data module is recorded, otherwise, the fourth Hash value is added into the Hash table of the shared block, and shared information corresponding to the fourth Hash value is recorded;
and the sharing interface module transmits the power grid data required by the user and provided by the storage block to the user.
In summary, according to the block chain control system and the control method for the power grid dispatching system provided by the invention, historical information of interaction between the power system and the power grid dispatching system is recorded by controlling the update block, the sharing block, the storage block and the backup block, so that the problem that the historical information, data update or abnormal sharing cannot be inquired in the prior art is solved; the problem of data loss in the prior art is solved by backing up the power grid data of the power system through the backup blocks.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (7)
1. A block chain control system facing a power grid dispatching system is characterized in that a block chain comprises an updating block, a storage block, a backup block and a shared block, and the system comprises a storage module, an updating module, a shared module and a backup module;
the updating module is used for acquiring power grid updating data of the power system, recording updating information of the updating block and sending the power grid updating data of the power system to the storage block;
the storage module is used for acquiring and storing the power grid updating data provided by the updating block, recording the storage information of the storage block and sending the power grid updating data stored in the storage block to the backup block; the shared block is also used for sending data required by the user to the shared block according to the user request;
the backup module is used for backing up the data stored in the storage block and recording the backup information of the backup block;
and the sharing module is used for calling data required by the user from the storage block according to the user request, sending the data to the user and recording the sharing information of the sharing block.
2. The system of claim 1, wherein the update module comprises:
the identity authentication module is used for performing identity authentication on the acquired power grid updating data of the power system by using a preset data linked list;
the updating nonlinear hash coding module is used for acquiring a first hash value of the power grid updating data of the power system by taking the characteristic data of the power grid updating data of the power system as the input of a pre-established neural network model if the identity authentication is passed, or else, acquiring the power grid updating data of the power system again;
the data updating module is used for acquiring the Hamming distance between the first Hash value and the Hash value in the updating block Hash table, recording updating information corresponding to the Hash value in the updating block Hash table if the Hamming distance is smaller than a preset threshold value, and sending the power grid updating data of the power system and the first Hash value thereof to the storage block, or adding the first Hash value to the updating block Hash table and recording the updating information corresponding to the first Hash value;
the characteristic data comprises a collecting node timestamp, a collecting node information abstract and a collecting node identity; the preset data linked list comprises the number of collection nodes of the power grid data of the power system, a collection node timestamp, a collection node information abstract and a collection node identity.
3. The system of claim 1, wherein the storage module comprises:
the power grid dispatching rule verification module is used for verifying whether the power grid parameters of the power grid updating data of the power system provided by the obtained updating block conform to preset power grid dispatching rules or not;
the storage nonlinear hash coding module is used for acquiring a second hash value of the power grid updating data of the power system provided by the acquired updating block by taking the acquired characteristic data of the power grid updating data of the power system provided by the updating block as the input of a pre-established neural network model if the storage nonlinear hash coding module passes the verification of the power grid scheduling rule verification module, or else, acquiring the power grid updating data of the power system provided by the updating block again;
the storage data verification module is used for verifying whether the second hash value is the same as the first hash value of the power grid updating data of the power system provided by the obtained updating block, if so, the storage data module is switched to, and otherwise, the power grid updating data of the power system provided by the updating block is obtained again;
the storage data module is used for acquiring the hamming distance between the second hash value and the hash value in the storage block hash table, recording storage information corresponding to the hash value in the storage block hash table if the hamming distance is smaller than a preset threshold value, sending the data stored in the storage block and the second hash value thereof to the backup block, sending the power grid data and the hash value thereof required by a user to the shared block, and otherwise, adding the second hash value to the storage block hash table and recording the storage information corresponding to the second hash value;
and the storage information comprises the acquired power grid updating data of the power system provided by the updating block.
4. The system of claim 1, wherein the backup module comprises:
the backup nonlinear hash coding module is used for taking the acquired characteristic data of the data stored in the storage block as the input of a pre-established neural network model and acquiring a third hash value of the data stored in the acquired storage block;
the backup data verification module is used for verifying whether the third hash value is the same as the second hash value of the acquired data stored in the storage block, if so, the backup data module is switched to, and otherwise, the data stored in the storage block is acquired again;
the backup data module is used for acquiring the Hamming distance between the third Hash value and the Hash value in the backup block Hash table, if the Hamming distance is smaller than a preset threshold value, recording backup information corresponding to the Hash value in the backup block Hash table, otherwise, adding the third Hash value into the backup block Hash table, and recording the backup information corresponding to the third Hash value;
and the backup information comprises the data stored in the acquired storage blocks.
5. The system of claim 1, wherein the sharing module comprises:
the shared nonlinear hash coding module is used for taking the acquired characteristic data of the power grid data required by the user and provided by the storage block as the input of a pre-established neural network model and acquiring a fourth hash value of the power grid data required by the user and provided by the acquired storage block;
the shared data verification module is used for verifying whether the fourth hash value is the same as the acquired third hash value of the power grid data required by the user and provided by the storage block, if so, the shared data module is switched to, and otherwise, the power grid data required by the user and provided by the storage block is acquired again;
the shared data module is used for acquiring the Hamming distance between the fourth Hash value and the Hash value in the Hash table of the shared data module, if the Hamming distance is smaller than a preset threshold value, recording shared information corresponding to the Hash value in the Hash table of the shared data module, otherwise, adding the fourth Hash value into the Hash table of the shared block, and recording the shared information corresponding to the fourth Hash value;
and the shared interface module is used for calling the power grid data required by the user from the storage block and sending the power grid data to the user.
6. The system of any one of claims 2-5, wherein the pre-established neural network model obtaining process comprises:
obtaining a hash value of characteristic data of the historical power grid data by using a hash algorithm;
and training the initial neural network model by taking the characteristic data of the historical power grid data as input layer training sample data of the initial neural network model and taking the hash value of the characteristic data of the historical power grid data as output layer training sample data of the initial neural network model, and acquiring the pre-established neural network model.
7. A block chain control method for a power grid dispatching system is characterized by comprising the following steps:
the updating module acquires power grid updating data of the power system, records updating information of an updating block and sends the power grid updating data of the power system to a storage block;
the storage module acquires and stores power grid updating data provided by the updating block, records storage information of the storage block, sends the data stored in the storage block to the backup block, and sends data required by a user to the sharing block;
the backup module backs up the data stored in the storage block and records backup information of the backup block;
the sharing module calls data required by the user from the storage block according to the user request, sends the data required by the user and provided by the storage block to the user, and records sharing information of the sharing block.
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