CN115423291A - Adjustable load demand response transaction method and computer equipment - Google Patents
Adjustable load demand response transaction method and computer equipment Download PDFInfo
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Abstract
The invention relates to a demand response transaction method and computer equipment capable of adjusting load, wherein the method comprises the steps of formulating a demand response transaction strategy before market declaration, obtaining transaction declaration data of all market main bodies according to the demand response transaction strategy and uploading the transaction declaration data to a dispatching center, and carrying out market clearing operation on the transaction declaration data by the dispatching center to form a clearing result; after the market is cleared, the trading center issues clearing results to each market main body, the cloud server in the market main bodies decomposes load response scheduling instructions to obtain decomposition instructions, and demand response instructions are adjusted based on the decomposition instructions and real-time data so as to regulate and control power consumption of electric equipment on a user side in real time. The invention provides a load demand response transaction cooperative framework consisting of three levels, namely an end side, an edge server and a cloud server, so that real-time data acquired by a user side can be directly and systematically regulated and demand response market transaction, and response excitation and optimal configuration of demand response resources are realized.
Description
Technical Field
The invention belongs to the technical field of electric power market trading, and particularly relates to an adjustable load demand response trading method and computer equipment.
Background
With the increase of the renewable energy grid-connected proportion, two changes exist in the positioning of a user side in a power system. One is functional role transition: the user side is an important ring, and the role of the user side is changed from a single consumer to the role of participating in the production, consumption and management of energy. The other is market participation role transition: the functional transformation of the user side promotes the establishment of market mechanisms such as demand response and the like, the user side resources can actively provide demand response service and obtain market benefits, and the situations that the user side has low market participation degree and single transaction variety and passively receives market signals in the past are changed.
In the related technology, most of the user side resources have small capacity, low elasticity level, dispersed distribution, strong randomness and poor controllability, and are often difficult to meet the minimum requirement of directly participating in system regulation and control and demand response market trading.
Disclosure of Invention
In view of this, the present invention provides an adjustable load demand response transaction method and a computer device to overcome the deficiencies of the prior art, so as to solve the problem that the user side in the prior art is difficult to satisfy the minimum requirement for directly participating in system regulation and control and demand response market transaction.
In order to achieve the purpose, the invention adopts the following technical scheme: an adjustable load demand response transaction method is applied to a market main body and comprises the following steps:
before market declaration, formulating a demand response transaction strategy, obtaining transaction declaration data of all market main bodies according to the demand response transaction strategy and uploading the transaction declaration data to a dispatching center, and carrying out market clearing operation on the transaction declaration data by the dispatching center to form a clearing result;
after the market is cleared, the trading center issues clearing results to each market main body, the cloud server in each market main body decomposes the load response scheduling instruction to obtain a decomposition instruction, and the demand response instruction is adjusted based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment on the user side.
Further, the formulating a demand response transaction policy, obtaining transaction declaration data of all market subjects according to the demand response transaction policy, and uploading the transaction declaration data to a scheduling center, and the scheduling center performing a market clearing operation on the transaction declaration data to form a clearing result, includes:
the method comprises the steps that a cloud server of a market main body obtains market release information from a trading center, and the market release information is combined with weather forecast data, primary energy price forecast data and pre-stored historical clearing prices to obtain market forecast prices;
a user side of a market main body collects real-time data through a sensor group;
an edge server of the market main body draws up a demand response declaration according to the market release information and the market forecast price;
the edge server is further used for constructing a demand response adjustment capability model according to the real-time data, obtaining power load forecast according to pre-stored historical power consumption data, checking the demand response declaration for the first time based on the power load forecast and the demand response adjustment capability model, and uploading the demand response declaration to the cloud server after the first check is passed;
the cloud server is further used for conducting second checking on the received demand response declaration, optimizing the demand response declaration passing the second checking according to the power utilization characteristics and the complementary characteristics of the user to obtain the optimized demand response declaration, obtaining a demand response transaction strategy according to the optimized demand response declaration by adopting a polymerization algorithm, obtaining transaction declaration data and uploading the transaction declaration data to a dispatching center, and the dispatching center conducting market clearing operation on the transaction declaration data to form a clearing result.
Further, the trading center issues the clearing result to each market main body, and the cloud server in the market main body decomposes the load response scheduling instruction and obtains the decomposition instruction, adjusts the demand response instruction based on the decomposition instruction and the real-time data to carry out real-time power utilization regulation and control on the power consumption equipment of the user side, and includes:
the cloud server of the market main body receives a clearing result of the trading center, determines a load response scheduling instruction according to the clearing result, and decomposes the load response scheduling instruction based on the declared demand of each user to obtain a decomposition instruction;
a user side of the market main body collects real-time data through a sensor group;
the edge server of the market main body adjusts the demand response instruction based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment at the user side;
the edge server is also used for acquiring the total demand response quantity of the user;
and the cloud server determines settlement of the demand response transaction according to the demands and clearing results of the users.
Further, the method also comprises the following steps:
the method comprises the steps that an edge server clears a user transaction result according to the implementation operation condition of electric equipment on a user side to obtain clearing data, generates a digital certificate description file corresponding to the clearing data according to the clearing data, and generates a hash value according to the digital certificate description file; and sending a chain loading request to the cloud server, writing chain loading information into a block chain, wherein the chain loading information comprises the hash value, and after the chain loading is successful, taking the digital certificate description file and the hash value thereof as a unique data source for the cloud server to perform user demand response expense settlement.
Further, the writing the uplink information into the block chain includes:
the edge server uses a private key to carry out digital signature, uses a public key of the authentication node to carry out information encryption, and broadcasts an uplink authentication request to other nodes in the block chain;
each authentication node acquires an uplink request from the message queue and calls an intelligent contract to perform data authentication, and the authentication content comprises the following steps: using the private key of the authentication node to decrypt data, and checking the completeness of the settlement data format and the rationality of transaction logic; decrypting by using the public key of the edge server, and verifying that the transaction data is from the edge server and is not tampered;
each authentication node sends an authentication result to a packaging node;
after acquiring the authentication state and the calculation result returned by each authentication node, the packaging node performs consistency verification, wherein the consensus mechanism is that more than half of the authentication pass replies of the nodes are received, and more than half of the resource evaluation calculation result data are consistent;
for the transaction data passing the consistency verification, putting the transaction data into a packaging queue to wait for agglomeration;
when the number of the caking reaches the caking threshold value, the packing node submits the block to the submitting node through the message middleware; wherein the blocking threshold comprises a block size and a time threshold;
after the submitting node finishes the uplink task of the previous block, the submitting node acquires a block to be uplink from the message middleware, and the submitting node takes the hash value of the latest block on the current block chain as the head data of the block to be uplink, so that the uplink task of the block is finished;
and when the submitting node finishes the uplink task, executing an intelligent contract to perform user demand response income calculation, and synchronizing the user account data and the account book to each authentication and packaging node.
Further, the uplink information is subjected to asymmetric encryption and digital signature, the edge server encrypts the information by using a public key of the authentication node and then sends the information to each authentication node, and each authentication node decrypts the information by using a preset private key to verify the reasonability of the data;
when sending data, the edge server uses the private key to carry out digital signature, and the authentication node uses the public key of the edge server to decrypt the information.
Further, a user side of the market main body collects real-time data through a sensor group, and the real-time data sends the real-time power and environment measurement data to the edge server at a first preset frequency;
and the edge server transmits a 96-point predicted power utilization curve, a 96-point demand response regulating capacity range curve and a checked 96-point demand response reporting volume price curve to the cloud server at a second preset frequency, and stores real-time measurement data, production plan data and demand response reporting original data to a database in the edge server.
Further, after receiving the real-time data collected by the user side, the edge server adopts an abnormal identification algorithm to preprocess the real-time data and eliminate abnormal data;
the real-time data comprises distributed power supply electricity consumption data, intelligent household appliance electricity consumption data, electric automobile electricity consumption data, cold and heat load real-time temperature data and environment monitoring data
Further, the user-side electric device includes:
distributed power supply, intelligent household electrical appliances and electric automobile.
An embodiment of the present application provides a computer device, including: a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the adjustable load demand response transaction method provided by any of the embodiments described above.
By adopting the technical scheme, the invention can achieve the following beneficial effects:
the invention provides an adjustable load demand response transaction method and computer equipment, which are applied to market bodies, wherein before market declaration, a demand response transaction strategy is formulated, transaction declaration data of all the market bodies are obtained according to the demand response transaction strategy and uploaded to a dispatching center, and the dispatching center performs market clearing operation on the transaction declaration data to form a clearing result; after the market is cleared, the trading center issues clearing results to each market main body, the cloud server in each market main body decomposes the load response scheduling instruction to obtain a decomposition instruction, and the demand response instruction is adjusted based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment on the user side.
In addition, the method and the device adopt the edge computing technology to store and communicate mass user data, combine hierarchical computing tasks and data storage of the demand response transaction service, reduce cloud computing pressure and improve data processing efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram illustrating the steps of an adjustable load demand response transaction method according to the present invention;
FIG. 2 is a schematic flow diagram of the hierarchical traffic flow of the load demand response transaction system of the present invention;
FIG. 3 is a flow chart of the hierarchical data flow accompanying the business process of the present invention;
FIG. 4 is a block link point deployment diagram of the present invention;
FIG. 5 is a diagram of a hardware architecture of an implementation environment of the adjustable load demand response transaction method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It should be apparent that the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
In the related art, when the resource at the user side of the aggregator agent participates in the demand response transaction, the capability foundation with the following three layers is needed: resource layer: the method has the advantages that the method has a data acquisition and regulation basis with various terminal types and a computing resource basis; and (4) a service layer: the method has the capability of resource aggregation and instruction decomposition, and supports the participation of distributed resources in market trading; ecological layer: creating a mutual-trust, fair and safe transaction environment and attracting massive and various terminal resources.
According to the adjustable load demand response transaction method and system, the storage and communication of mass user data are achieved by adopting the edge computing technology, and the data processing efficiency is improved while the cloud computing pressure is reduced by combining the hierarchical computing task and the data storage of the demand response transaction service. And taking the data on the chain as a unique trusted data source to calculate the user demand response income, thereby realizing the optimal configuration of response incentive and demand response resources. The invention carries out identity authentication, settlement authentication and storage by means of the block chain technology, and provides a fair, safe, efficient and mutually trusted ecological network for transaction business while protecting the privacy data of the end side.
A specific adjustable load demand response transaction method and computer apparatus provided in the embodiments of the present application will be described with reference to the accompanying drawings.
As shown in fig. 1 and fig. 2, the adjustable load demand response transaction method provided in the embodiment of the present application is applied to a market subject, and the adjustable load demand response transaction method includes:
s101, before market declaration, formulating a demand response transaction strategy, obtaining transaction declaration data of all market main bodies according to the demand response transaction strategy and uploading the transaction declaration data to a dispatching center, and carrying out market clearing operation on the transaction declaration data by the dispatching center to form a clearing result;
s102, after the market is cleared, the trading center issues clearing results to each market main body, a cloud server in each market main body decomposes a load response scheduling instruction to obtain a decomposition instruction, and the demand response instruction is adjusted based on the decomposition instruction and real-time data so as to regulate and control power utilization of power utilization equipment on a user side in real time.
In some embodiments, as shown in fig. 3, the formulating a demand response transaction policy, obtaining transaction declaration data of all market subjects according to the demand response transaction policy, and uploading the transaction declaration data to a scheduling center, where the scheduling center performs a market clearing operation on the transaction declaration data to form a clearing result, includes:
the method comprises the steps that a cloud server of a market main body obtains market release information from a trading center, and the market forecast price is obtained by combining weather forecast data, primary energy price forecast data and pre-stored historical clearing prices;
a user side of a market main body collects real-time data through a sensor group;
the edge server of the market main body obtains a demand response declaration according to the market release information and the market forecast price;
the edge server is further used for constructing a demand response adjustment capability model according to the real-time data, obtaining power load forecast according to pre-stored historical power consumption data, checking the demand response declaration for the first time based on the power load forecast and the demand response adjustment capability model, and uploading the demand response declaration to the cloud server after the first check is passed;
the cloud server is further used for conducting second checking on the received demand response declaration, optimizing the demand response declaration passing the second checking according to the power utilization characteristics and the complementary characteristics of the user to obtain the optimized demand response declaration, obtaining a demand response transaction strategy according to the optimized demand response declaration by adopting a polymerization algorithm, obtaining transaction declaration data and uploading the transaction declaration data to a dispatching center, and the dispatching center conducting market clearing operation on the transaction declaration data to form a clearing result.
As shown in fig. 3, the trading center issues the clearing result to each market main body, the cloud server in the market main body decomposes the load response scheduling instruction to obtain a decomposition instruction, and adjusts the demand response instruction based on the decomposition instruction and the real-time data so as to perform real-time power utilization regulation and control on the power utilization equipment at the user side, including:
the cloud server of the market main body receives a clearing result of the trading center, determines a load response scheduling instruction according to the clearing result, and decomposes the load response scheduling instruction based on the declared demand of each user to obtain a decomposition instruction;
a user side of a market main body collects real-time data through a sensor group;
the edge server of the market main body adjusts the demand response instruction based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment at the user side;
the edge server is also used for acquiring the total demand response quantity of the user;
and the cloud server determines the settlement of the demand response transaction according to the demands and clearing results of all the users.
The user end side sensor collects data including real-time power utilization data of a distributed power supply, intelligent household appliances and an electric automobile, and real-time temperature data of cold and heat loads, environment monitoring data and the like. And a light-weight data anomaly identification algorithm and an integrated energy modeling algorithm taking electricity as a core are carried on the edge side, and the data are standardized and preprocessed in time. Meanwhile, the edge side can be used for storing historical operation and power utilization data of the equipment, caching key data, timely acquiring production plan power utilization data of the equipment, matching with an intelligent algorithm, realizing power utilization load prediction of the equipment, modeling of demand response regulation capacity and formulation of demand response declaration strategies, reducing data communication traffic and relieving data storage and calculation pressure of a cloud server.
Specifically, the cloud server accesses weather forecast data and primary energy price forecast data, and combines multi-node historical market clearing data stored by the cloud server to forecast the demand response market clearing price of each declaration node. The electricity consumption data acquisition equipment sends real-time electricity and environment measurement data to the edge server at a frequency of 5 minutes/time. The edge server uses the historical electricity consumption data, the real-time measurement data and the production plan data of the terminal user to complete the electricity consumption load prediction of each service unit; a standardized power demand response turndown capability modeling is performed. And the edge server completes the formulation of a user demand response declaration strategy by combining the power consumption load prediction, the demand response adjustment capability and the market price prediction issued by the cloud server. The edge server carries out local data distribution, transmits a 96-point predicted power utilization curve, a 96-point demand response regulating capacity range curve and a checked 96-point demand response reporting volume price curve with time intervals of every 15 minutes to the cloud server, and stores real-time measurement data, production plan data and demand response reporting original data to an edge server database. And the cloud server calls an optimized aggregation algorithm according to the demand response declaration, the adjusting capacity and the power load data transmitted by the edge server to finish the price declaration.
In some embodiments, as shown in fig. 4, the edge server performs clearing of the transaction result of the user according to the implementation operation condition of the electric device on the user side to obtain clearing data, generates a digital certificate description file corresponding to the clearing data according to the clearing data, and generates a hash value according to the digital certificate description file; and sending a chain loading request to the cloud server, writing chain loading information into a block chain, wherein the chain loading information comprises the hash value, and after the chain loading is successful, taking the digital certificate description file and the hash value thereof as a unique data source for the cloud server to perform user demand response expense settlement.
It should be noted that the blockchain technique used in the present application is composed of four features of digital identity, intelligent contract, data encryption, and data encryption.
The digital identity features are mainly expressed as follows: when a user joins the aggregator demand response transaction platform, a digital certificate is acquired from a platform authority, and the digital certificate encapsulates the digital identity, member authority and the like of the terminal equipment. Before the digital certificate is authorized, access test and control test are required to be carried out on each device of a user, and the edge server is guaranteed to have data access capacity, the edge side resources are controllable at the edge, and the edge side resources can respond. After the digital certificate is authorized, the member service providers in the block chain network add the member authority of the client trusted by the member service providers into the member list, and the communication between each block chain network and the nodes needs to be authenticated by the member service providers. The block chain has good identity anonymity, and an attacker is prevented from directly obtaining the private data through the block chain address.
The intelligent contract features are mainly expressed as follows: by means of the intelligent contracts, key computing processes are programmed, once a data uplink request is initiated, the intelligent contracts are automatically executed, manual intervention cannot be achieved, and the intelligent contracts are mandatory, once the intelligent contracts are successfully deployed, the intelligent contracts are operated according to design codes, and can be viewed by anyone, and the intelligent contracts have high transparency. The characteristics of the two aspects enable the calculation result of the intelligent contract to have high credibility.
In the demand response transaction business, the calculation of the demand response income of the user is one of the core business links, and is the guarantee of the fundamental benefits of the user participating in the market, and influences the market participation willingness of each user. Therefore, the user demand response income calculation flow is written into the intelligent contract, and after the edge server initiates the bill uplink application, the data, the declaration data and the execution data are decomposed according to the instruction, and the automatic calculation of the intelligent contract is executed. If the execution result of the market user deviates from the decomposition instruction or other default behaviors are generated, synchronizing the execution result into each distributed account book, thereby influencing the market declaration of the next demand response service.
The data encryption characteristics are mainly expressed as: and carrying out asymmetric encryption and digital signature on the data to be uplinked, enhancing the data transmission security between nodes and preventing the data from being tampered or forging information. The edge server encrypts the information by using the public key of the authentication node and then sends the information to each authentication node, and each authentication node decrypts the information by using the private key of the authentication node to verify the rationality of the data. When the data is sent, the edge server uses the private key to carry out digital signature, and the authentication node uses the public key of the edge server to decrypt the information, so that the received file can be ensured not to be tampered, and the identity of a sender can also be ensured.
The data uplink is characterized by: after the demand response transaction is executed, the edge server clears the account according to the decomposition instruction and the operation data, and initiates a data uplink request. In order to improve the data storage and calculation efficiency, only the transaction settlement data are stored in an uplink. Through the data authentication and chaining process of the chained data structure and the distributed nodes, the possibility of tampering the existing account book data and the user income calculation result is greatly reduced.
Specifically, the data authentication and uplink procedure for writing uplink information into a block chain includes:
after clearing the transaction result of the user and sending out the data uplink clearing request, the following processing needs to be performed on the data:
the edge server uses a private key to carry out digital signature, uses a public key of the authentication node to carry out information encryption, and broadcasts an uplink authentication request to other nodes in the block chain;
each authentication node acquires an uplink request from the message queue and calls an intelligent contract to perform data authentication, and the authentication content comprises the following steps: using the private key of the authentication node to decrypt data, and checking the completeness of the settlement data format and the rationality of transaction logic; decrypting by using the public key of the edge server, and verifying that the transaction data comes from the edge server and is not tampered;
each authentication node sends an authentication result to a packaging node;
after the packaging node acquires the authentication state and the evaluation calculation result returned by each node, consistency verification is carried out, and the default consensus mechanism is as follows: receiving authentication passing replies of more than half of nodes, wherein more than half of resource evaluation calculation result data are consistent;
for the transaction data passing the consistency verification, putting the transaction data into a packing queue to wait for agglomeration; after the blocking threshold is reached, the block size and the time threshold are commonly included, and the packing node submits the block to the submitting node through message middleware;
after the submitting node completes the uplink task of the previous block, the submitting node acquires the block to be uplink from the message middleware, and the submitting node takes the hash value of the latest block on the current block chain as the head data of the block to be uplink, so as to complete the uplink task of the block.
And when the submitting node finishes the uplink task, executing an intelligent contract to evaluate the load response dominance degree, and synchronizing the user account data and the account book to each authentication and packaging node together.
In some embodiments, the uplink information is subjected to asymmetric encryption and digital signature, the edge server encrypts the information by using a public key of the authentication node and then sends the information to each authentication node, and each authentication node decrypts the information by using a preset private key to verify the reasonability of the data;
when sending data, the edge server uses the private key to carry out digital signature, and the authentication node uses the public key of the edge server to decrypt the information.
The application provides a computer device comprising: a memory 1 and a processor 2, and may further include a network interface 3, wherein the memory 1 stores computer programs, and the memory 1 may include volatile memory in a computer readable medium, random Access Memory (RAM), and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM). The computer device stores an operating system 4, and the memory 1 is an example of a computer-readable medium. The computer program, when executed by the processor 2, causes the processor 2 to perform an adjustable load demand response transaction method, the arrangement shown in fig. 5 being a block diagram of only a portion of the arrangement relevant to the present solution and not constituting a limitation of the computer apparatus to which the present solution applies, a particular computer apparatus may include more or fewer components than shown in the drawings, or combine certain components, or have a different arrangement of components.
In one embodiment, the adjustable load demand response transaction method provided herein may be implemented in the form of a computer program that is executable on a computer device such as that shown in fig. 5.
In some embodiments, the computer program, when executed by the processor 2, causes the processor 2 to perform the steps of: before market declaration, formulating a demand response transaction strategy, obtaining transaction declaration data of all market main bodies according to the demand response transaction strategy and uploading the transaction declaration data to a dispatching center, and carrying out market clearing operation on the transaction declaration data by the dispatching center to form a clearing result; after the market is cleared, the trading center issues clearing results to each market main body, a cloud server in each market main body decomposes a load response scheduling instruction to obtain a decomposition instruction, and the demand response instruction is adjusted based on the decomposition instruction and real-time data so as to regulate and control the real-time power utilization of the power utilization equipment on the user side.
In summary, the present invention provides an adjustable load demand response transaction method and a computer device, where the method includes, before market declaration, formulating a demand response transaction policy, obtaining transaction declaration data of all market subjects according to the demand response transaction policy, and uploading the transaction declaration data to a scheduling center, where the scheduling center performs a market clearing operation on the transaction declaration data to form a clearing result; after the market is cleared, the trading center issues clearing results to each market main body, the cloud server in each market main body decomposes the load response scheduling instruction to obtain a decomposition instruction, and the demand response instruction is adjusted based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment on the user side. The invention provides a load demand response transaction cooperative framework longitudinally composed of three levels, namely an end side, an edge server and a cloud server, so that real-time data acquired by a user side can directly participate in system regulation and control and demand response market transaction, and optimal configuration of response excitation and demand response resources is realized.
It is understood that the embodiments of the method provided above correspond to the embodiments of the computer device described above, and corresponding specific contents may be referred to each other, which is not described herein again.
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, 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.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An adjustable load demand response transaction method is characterized by being applied to a market main body; the adjustable load demand response transaction method comprises the following steps:
before market declaration, formulating a demand response transaction strategy, obtaining transaction declaration data of all market main bodies according to the demand response transaction strategy and uploading the transaction declaration data to a dispatching center, and carrying out market clearing operation on the transaction declaration data by the dispatching center to form a clearing result;
after the market is cleared, the trading center issues clearing results to each market main body, the cloud server in each market main body decomposes the load response scheduling instruction to obtain a decomposition instruction, and the demand response instruction is adjusted based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment on the user side.
2. The method according to claim 1, wherein the formulating a demand response transaction policy, obtaining transaction declaration data of all market subjects according to the demand response transaction policy and uploading the transaction declaration data to a scheduling center, and the scheduling center performing a market clearing operation on the transaction declaration data to form a clearing result, comprises:
the method comprises the steps that a cloud server of a market main body obtains market release information from a trading center, and the market forecast price is obtained by combining weather forecast data, primary energy price forecast data and pre-stored historical clearing prices;
a user side of the market main body collects real-time data through a sensor group;
an edge server of the market main body draws up a demand response declaration according to the market release information and the market forecast price;
the edge server is further used for constructing a demand response adjustment capability model according to the real-time data, obtaining power load prediction according to pre-stored historical power consumption data, performing first check on the demand response declaration based on the power load prediction and the demand response adjustment capability model, and uploading the demand response declaration to the cloud server after the first check is passed;
the cloud server is further used for conducting second checking on the received demand response declaration, optimizing the demand response declaration passing the second checking according to the power utilization characteristics and the complementary characteristics of the user to obtain the optimized demand response declaration, obtaining a demand response transaction strategy according to the optimized demand response declaration by adopting a polymerization algorithm, obtaining transaction declaration data and uploading the transaction declaration data to a dispatching center, and the dispatching center conducting market clearing operation on the transaction declaration data to form a clearing result.
3. The method according to claim 1, wherein the trading center issues the clearing result to each market subject, a cloud server in the market subject decomposes a load response scheduling instruction to obtain a decomposition instruction, and adjusts a demand response instruction based on the decomposition instruction and real-time data to perform real-time power utilization regulation and control on the power utilization equipment on the user side, including:
the cloud server of the market main body receives a clearing result of the trading center, determines a load response scheduling instruction according to the clearing result, and decomposes the load response scheduling instruction based on the declared demand of each user to obtain a decomposition instruction;
a user side of the market main body collects real-time data through a sensor group;
the edge server of the market main body adjusts the demand response instruction based on the decomposition instruction and the real-time data so as to regulate and control the real-time power utilization of the power utilization equipment at the user side;
the edge server is also used for acquiring the total demand response quantity of the user;
and the cloud server determines settlement of the demand response transaction according to the demands and clearing results of the users.
4. The method of claim 3, further comprising:
the method comprises the steps that an edge server clears a user transaction result according to the implementation operation condition of electric equipment on a user side to obtain clearing data, generates a digital certificate description file corresponding to the clearing data according to the clearing data, and generates a hash value according to the digital certificate description file; and sending a chain-up request to the cloud server, writing chain-up information into a block chain, wherein the chain-up information comprises the hash value, and after the chain-up is successful, taking the digital certificate description file and the hash value thereof as a unique data source for the cloud server to settle the user demand response cost.
5. The method of claim 4, wherein writing uplink information into the block chain comprises:
the edge server uses a private key to carry out digital signature, uses a public key of the authentication node to carry out information encryption, and broadcasts an uplink authentication request to other nodes in the block chain;
each authentication node acquires an uplink request from the message queue and calls an intelligent contract to perform data authentication, wherein the authentication content comprises the following steps: using the private key of the authentication node to decrypt data, and checking the completeness of the settlement data format and the rationality of transaction logic; decrypting by using the public key of the edge server, and verifying that the transaction data comes from the edge server and is not tampered;
each authentication node sends an authentication result to a packaging node;
after acquiring the authentication state and the calculation result returned by each authentication node, the packaging node performs consistency verification, wherein the consensus mechanism is that more than half of the authentication pass replies of the nodes are received, and more than half of the resource evaluation calculation result data are consistent;
for the transaction data passing the consistency verification, putting the transaction data into a packaging queue to wait for agglomeration;
when the number of the caking reaches the caking threshold value, the packing node submits the block to the submitting node through the message middleware; wherein the blocking threshold comprises a block size and a time threshold;
after the submitting node finishes the uplink task of the previous block, the submitting node acquires a block to be uplink from the message middleware, and the submitting node takes the hash value of the latest block on the current block chain as the head data of the block to be uplink, so that the uplink task of the block is finished;
and when the submitting node finishes the uplink task, executing an intelligent contract to calculate the user demand response income, and synchronizing the user account data and the account book to each authentication and packaging node together.
6. The method of claim 5,
the uplink information is subjected to asymmetric encryption and digital signature, the edge server encrypts the information by using a public key of the authentication node and then sends the information to each authentication node, and each authentication node decrypts the information by using a preset private key to verify the reasonability of the data;
when sending data, the edge server uses the private key to carry out digital signature, and the authentication node uses the public key of the edge server to decrypt the information.
7. The method of claim 6,
a user side of a market main body collects real-time data through a sensor group, and the real-time data sends real-time electric power and environment measurement data to an edge server at a first preset frequency;
and the edge server transmits a 96-point predicted power utilization curve, a 96-point demand response regulating capacity range curve and a checked 96-point demand response reporting volume price curve to the cloud server at a second preset frequency, and stores real-time measurement data, production plan data and demand response reporting original data to a database in the edge server.
8. The method according to claim 2 or 3,
after receiving real-time data collected by a user side, an edge server adopts an abnormal identification algorithm to preprocess the real-time data and eliminates abnormal data;
the real-time data comprises distributed power supply electricity consumption data, intelligent household appliance electricity consumption data, electric automobile electricity consumption data, cold and heat load real-time temperature data and environment monitoring data.
9. The method of claim 2, wherein the user-side powered device comprises:
distributed power supply, intelligent household electrical appliances and electric automobile.
10. A computer device, comprising: a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the adjustable load demand response transaction method of any one of claims 1 to 9.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116544941A (en) * | 2023-04-28 | 2023-08-04 | 中国南方电网有限责任公司 | Distributed energy reporting strategy regulation and control system and method based on cloud edge cooperative architecture |
| CN117273557A (en) * | 2023-11-20 | 2023-12-22 | 杭州轻舟科技有限公司 | User virtual power plant operation method based on light-EMS, electronic equipment and medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116544941A (en) * | 2023-04-28 | 2023-08-04 | 中国南方电网有限责任公司 | Distributed energy reporting strategy regulation and control system and method based on cloud edge cooperative architecture |
| CN116544941B (en) * | 2023-04-28 | 2023-12-08 | 中国南方电网有限责任公司 | Distributed energy reporting strategy regulation and control system and method based on cloud edge cooperative architecture |
| CN117273557A (en) * | 2023-11-20 | 2023-12-22 | 杭州轻舟科技有限公司 | User virtual power plant operation method based on light-EMS, electronic equipment and medium |
| CN117273557B (en) * | 2023-11-20 | 2024-04-19 | 杭州轻舟科技有限公司 | User virtual power plant operation method based on light-EMS, electronic equipment and medium |
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