Multi-heat-source networked heating collaborative optimization scheduling system and method based on blockchain

Abstract

The present invention discloses a multi-heat-source networked heating collaborative optimization scheduling system based on blockchain, comprising: a scheduling hardware layer, including heat sources, a multi-heat-source control center, and a wireless communication network; a scheduling blockchain layer, including data blocks, a chain structure, and a consensus algorithm, providing trustworthy and secure information services for the multi-heat-source networked collaborative scheduling system; a scheduling smart contract layer, including script codes, a smart contract programming environment, and a smart contract execution environment; the multi-heat-source networked collaborative scheduling algorithm is compiled into script codes and deployed on the blockchain system in the form of smart contracts, and after running in the execution environment, the optimal instruction for multi-heat-source networked collaborative scheduling is obtained, and then the multi-heat-source control center node sends the optimal scheduling instruction to each heat source node, and each node receives the optimal scheduling instruction. The present invention realizes a good fit with the multi-heat-source networked heating collaborative scheduling through blockchain technology, providing safe and efficient services for multi-heat-source networked scheduling.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent heating, and particularly relates to a multi-source networked heating collaborative optimization scheduling system and method based on blockchain. Background Art

[0002] Multi-source networked heating means that two or more heat sources jointly form a heating system to supply heat to users. The core content is: on the premise of ensuring the heating quality of users, the heat supply of each heat source can be freely scheduled as needed. Different from the operation scheduling of a single heat source, the hydraulic and thermal processes of multi-source networked operation are quite complex, and the difficulty of operation scheduling increases exponentially.

[0003] Blockchain is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm. The emergence of blockchain technology and its combination with the traditional heating system provide new ideas for the development of the heating system. However, there is currently little research on applying blockchain technology to the collaborative optimization scheduling of multi-source networked heating. How to achieve a good fit between blockchain technology and the collaborative scheduling of multi-source networked heating to provide safe and efficient services for multi-source networked scheduling is a difficult problem that needs to be solved urgently.

[0004] Based on the above technical problems, it is necessary to design a new multi-source networked heating collaborative optimization scheduling system and method based on blockchain. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a multi-source networked heating collaborative optimization scheduling system and method based on blockchain, which can achieve a good fit between blockchain technology and the collaborative scheduling of multi-source networked heating and provide safe and efficient services for multi-source networked scheduling.

[0006] To solve the above technical problem, the technical solution of the present invention is:

[0007] The present invention provides a multi-source networked heating collaborative optimization scheduling system based on blockchain, which includes:

[0008] A scheduling hardware layer, the scheduling hardware layer at least includes heat sources, a multi-source control center, and a wireless communication network. The multi-source control center sends multi-source networked collaborative scheduling instructions and receives instruction responses and execution results from multiple heat sources;

[0009] A scheduling blockchain layer, the scheduling blockchain layer provides reliable and secure information services for the multi-source networked collaborative scheduling system. The scheduling blockchain layer at least includes data blocks, a chain structure, and a consensus algorithm. The data blocks are connected in sequence to form a chain structure, and each data block is provided with encrypted data;

[0010] The dispatching smart contract layer provides a development platform and an operating environment for the collaborative dispatching of multiple heat sources. The dispatching smart contract layer at least includes script code, a smart contract programming environment, and a smart contract execution environment;

[0011] The dispatching application layer performs collaborative optimization dispatching of multiple heat sources by encapsulating the collaborative dispatching of multiple heat sources into an application scenario of the blockchain. The dispatching application layer at least includes a collaborative dispatching algorithm for multiple heat sources and application software; taking the multi-heat-source control center and multiple heat sources as nodes, each node is interconnected through a wireless communication network, and a blockchain system is composed of a multi-heat-source control center node, heat source nodes, and data blocks. The blockchain system enables each node to reach an agreement according to a consensus algorithm. The collaborative dispatching algorithm for multiple heat sources is compiled into script code and deployed on the blockchain system in the form of a smart contract, and after running in the execution environment, the optimal instruction for the collaborative dispatching of multiple heat sources is obtained. Then, the multi-heat-source control center node sends the optimal dispatching instruction to each heat source node, and each node receives the optimal dispatching instruction and automatically executes the corresponding strategy according to the conditions designed in the smart contract.

[0012] Furthermore, the data blocks are connected in sequence to form a chain structure, and each data block is provided with cryptographic data, including:

[0013] The data related to the collaborative dispatching of multiple heat sources is packaged in the form of blocks, and the blocks are sequentially connected in the form of a linked list according to the time sequence to form a blockchain; each block stores the information of the blockchain system for a period of time, and is composed of a block header and a set of data records. The block header includes information indicating the identity of the block, a proof that the block is reasonably generated, the hash value of the previous block, and the Merkle root value; the block is used for the storage of data related to the collaborative dispatching of multiple heat sources and the management of the blockchain. After receiving the block, the node verifies and executes the information in the block through an encryption algorithm, and all operations are securely stored in the transaction log; the data records in the block at least include heat source type, heat source location, heat source capacity, heating load quota, and fuel price.

[0014] Furthermore, the consensus algorithm adopted by the blockchain system is the PBFT Practical Byzantine Fault Tolerance algorithm. The consensus algorithm is used for the receiving consensus process of nodes. First, it verifies whether the instruction information of the dispatching scheme is sent by the multi-heat-source control center. After verification, each heat source node conducts a consensus on the feasibility of the dispatching scheme. If the scheme meets the constraint conditions, it will be broadcast, and at the same time, it waits to receive the verification results broadcast by more than 2 / 3 of the nodes. If the verification fails, it will not be broadcast. When more than 2 / 3 of the nodes broadcast that their own verification is passed, all nodes reach a consensus, then the verification results will be broadcast, and the instruction information of the dispatching scheme will be executed.

[0015] Furthermore, the multi-heat-source networking collaborative scheduling algorithm is compiled into script code and deployed on the blockchain system in the form of a smart contract, and runs in the execution environment. Each node receives the optimal instruction for heat-source networking collaborative scheduling and automatically executes the corresponding policy according to the conditions designed in the smart contract, specifically including:

[0016] The multi-heat-source networking collaborative scheduling algorithm writes a smart contract program based on the rotation time of the scheduling as the pre-designed trigger condition and the iterative calculation rules of the economic scheduling objective function and the environmental scheduling objective function as the pre-designed trigger rules, and deploys it on the blockchain system in the form of script code. At the beginning of each scheduling cycle, the blockchain system automatically executes the scheduling process and can calculate the scheduling instruction value according to the scheduling algorithm. Each node receives the optimal instruction for heat-source networking collaborative scheduling and automatically executes the corresponding policy according to the conditions designed in the smart contract;

[0017] Among them, the economic scheduling objective function is expressed as:

[0018]

[0019] Among them, K is the number of heat sources participating in the multi-heat-source combined scheduling; T is the scheduling cycle; C k is the power generation power of heat source k; P ek is the on-grid electricity price of heat source k; D k is the heating load of heat source k; P hk is the heating income of heat source k; f k is the fuel consumption of heat source k; E k is the fuel price used by heat source k;

[0020] The environmental scheduling objective function is expressed as:

[0021]

[0022] Among them, Q em,k,j is the mass of the j-th type of pollutant emitted by heat source k per unit mass of fuel used; E q,j is the pollution equivalent value of the j-th type of pollutant; J is the category of pollutants.

[0023] Further, the smart contract program includes a security verification program, an initialization program, a data reading and writing program, and a multi-heat-source networked collaborative scheduling iterative calculation program; the security verification program checks constraint conditions, and only after the security verification passes can the scheduling instruction value be sent to each heat source, and the constraint conditions at least include: thermal-electric load balance constraint and heat supply network transmission and distribution capacity constraint; the initialization program initializes the state of the node by designing an initialization program when the blockchain system is started and before the smart contract is called, and the ledger does not include any valid blockchain data and the current state of the node; the data reading and writing program reads the parameters required by the multi-heat-source networked collaborative scheduling algorithm from the blockchain or stores the calculated scheduling results into the blockchain; the multi-heat-source networked collaborative scheduling iterative calculation program performs scheduling iterative calculations according to the established economic scheduling objective function, environmental scheduling objective function, and set corresponding operation constraint conditions.

[0024] The present invention also proposes a multi-heat-source networked heating collaborative optimization scheduling method based on blockchain, and the multi-heat-source networked heating collaborative optimization scheduling method includes:

[0025] Establish a blockchain system with multiple heat sources and a multi-heat-source control center as nodes; the multiple heat sources and the multi-heat-source control center are interconnected through a wireless communication network;

[0026] Connect the multi-heat-source networked collaborative scheduling related data obtained by the blockchain system in the form of data blocks in sequence to form a chain structure, and make the data of each node consistent according to the consensus algorithm; the password data and interaction data of each block are set in the data block;

[0027] Compile the multi-heat-source networked collaborative scheduling algorithm into script code and deploy it on the blockchain system in the form of a smart contract, and obtain the optimal instruction for multi-heat-source networked collaborative scheduling after running in the set smart contract execution environment;

[0028] The multi-heat-source control center node sends the optimal scheduling instruction to each heat source node, each node receives the optimal scheduling instruction, and after automatically executing the corresponding policy according to the conditions designed by the smart contract, returns the instruction response and execution result of the multiple heat sources to the multi-heat-source control center.

[0029] Further, the multi-heat-source networked collaborative scheduling related data is packaged in the form of blocks, and the blocks are sequentially connected in the form of a linked list according to the time sequence to form a blockchain; each block stores the information of the blockchain system for a period of time, and consists of a block header and a group of data records. The block header includes information indicating the identity of the block, a proof that the block is reasonably generated, the hash value of the previous block, and the Merkle root value; the data records in the block at least include heat source type, heat source location, heat source capacity, heating load quota, and fuel price;

[0030] After the block is packaged, the packager uses its own private key to digitally sign the block and broadcasts the block to the blockchain system. After receiving the block, the nodes in the blockchain system first query their own ledgers to confirm whether they have ever received the block. If they have, they discard the block; otherwise, they use digital signature technology to verify the legality of the block. After passing the verification, they proceed with the transmission of subsequent information.

[0031] Furthermore, when a heat source node in the multi-source networked heating system wants to join the blockchain system, each heat source node has a unique identity identifier for identity authentication when joining the blockchain system. After passing the authentication, it participates in the multi-source networked collaborative scheduling.

[0032] The implementation process of the heat source node for identity authentication and participation in multi-source networked collaborative scheduling includes:

[0033] All heat source nodes send their own identity identifiers to the blockchain system for identity verification. If the verification passes, the heat source nodes are added to the blockchain system; otherwise, the identity identifiers are resubmitted.

[0034] After each heat source node joins the blockchain system, it accesses the system data, uses chained encrypted blocks to verify and store the scheduling operation data, broadcasts and publishes information. The heat source control center forms an economic scheduling objective function, an environmental scheduling objective function and constraint conditions based on the published information, and performs optimization calculations by calling the smart contract program to generate a scheduling plan. The blockchain system uses the consensus algorithm mechanism to verify whether the scheduling plan meets the constraints of each node. If it passes the verification, the optimization calculation of the scheduling plan is performed based on the data submitted and verified by each heat source node; otherwise, the data is resubmitted for optimization calculation.

[0035] Furthermore, the multi-source networked collaborative scheduling algorithm is compiled into script code and deployed on the blockchain system in the form of a smart contract. After running in the set smart contract execution environment, the optimal instruction for multi-source networked collaborative scheduling is obtained, specifically including:

[0036] The multi-source networked collaborative scheduling algorithm writes the smart contract program according to the rotation time of the scheduling as the pre-designed trigger condition and the iterative calculation rules of the economic scheduling objective function and the environmental scheduling objective function as the pre-designed trigger rules, and deploys it on the blockchain system in the form of script code. At the beginning of each scheduling cycle, the blockchain system automatically executes the scheduling process and can calculate the scheduling instruction value according to the scheduling algorithm.

[0037] Among them, the intelligent contract program includes a security verification program, an initialization program, a data reading and writing program, and a multi-heat-source networked collaborative scheduling iterative calculation program; the security verification program is to check the constraint conditions, and the scheduling instruction value can be sent to each heat source only after the security verification passes. The constraint conditions at least include: thermoelectric load balance constraint and heat supply network transmission and distribution capacity constraint; the initialization program is to initialize the state of the node by designing an initialization program when the blockchain system starts and before the intelligent contract is called. At this time, the ledger does not include any valid blockchain data and the current state of the node; the data reading and writing program is to read the parameters required by the multi-heat-source networked collaborative scheduling algorithm from the blockchain or store the calculated scheduling results into the blockchain; the multi-heat-source networked collaborative scheduling iterative calculation program is to perform scheduling iterative calculation according to the established economic scheduling objective function, environmental scheduling objective function and the set corresponding operation constraint conditions.

[0038] The economic scheduling objective function is expressed as:

[0039]

[0040] Among them, K is the number of heat sources participating in the multi-heat-source combined scheduling; T is the scheduling period; C k is the power generation of heat source k; P ek is the on-grid electricity price of heat source k; D k is the heating load of heat source k; P hk is the heating income of heat source k; f k is the fuel consumption of heat source k; E k is the fuel price used by heat source k;

[0041] The environmental scheduling objective function is expressed as:

[0042]

[0043] Among them, Q em,k,j is the mass of the j-th type of pollutant emitted by heat source k per unit mass of fuel used; E q,j is the pollution equivalent value of the j-th type of pollutant.

[0044] Furthermore, an improved satin bowerbird optimization algorithm is used to solve the multi-objective function including the economic scheduling objective function and the environmental scheduling objective function.

[0045] The improved satin bowerbird optimization algorithm includes: improvement in population initialization, where the population is initialized using an elite opposition-based learning strategy. In the initialization stage, an initial population is randomly generated in the search space, and at the same time, a dynamic opposition population is generated. The initial population and the population after its dynamic opposition learning are compared, and the bowerbirds with better fitness are selected to form the initial population; improvement in position update. For the points that cross the boundary during the search process, they are re-initialized within the search interval, and the opposition point search method is adopted, and the better points are retained through a competition mechanism.

[0046] The beneficial effects of the present invention are:

[0047] The present invention establishes a multi-heat-source networked heating system scheduling blockchain architecture including a scheduling hardware layer, a scheduling blockchain layer, a scheduling smart contract layer, and a scheduling application layer. Based on the immutable feature of the blockchain, it realizes the traceability of the multi-heat-source networked collaborative scheduling process. By using a consensus algorithm and a smart contract program, a scheduling algorithm for the multi-heat-source networked heating system is established, combining blockchain technology with multi-heat-source networked collaborative scheduling, improving the participation degree, scheduling efficiency, and reliability of each node. At the same time, through blockchain technology, using a consensus algorithm, encryption algorithm, and secure data storage, it can ensure the security of data interaction, prevent data leakage and tampering, and can use cryptographic encryption algorithms to verify the legal identities of nodes and blocks.

[0048] Other features and advantages will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0049] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0051] Figure 1 It is a schematic structural diagram of a multi-heat-source networked heating collaborative scheduling system based on blockchain of the present invention;

[0052] Figure 2 It is a schematic diagram of the blockchain data structure of the present invention;

[0053] Figure 3This is a schematic diagram of the dispatching principle of the multi-heat-source networked heating system based on blockchain in the present invention. Specific implementation manners

[0054] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] Embodiment 1

[0056] Figure 1 This is a schematic diagram of the structure of a multi-heat-source networked heating collaborative dispatching system based on blockchain involved in the present invention.

[0057] Figure 2 This is a schematic diagram of the blockchain data structure involved in the present invention.

[0058] Figure 3 This is a schematic diagram of the dispatching principle of the multi-heat-source networked heating system based on blockchain involved in the present invention.

[0059] As Figures 1 - 3 shown, Embodiment 1 of the present invention provides a multi-heat-source networked heating collaborative optimization dispatching system based on blockchain, which includes:

[0060] A dispatching hardware layer, where the dispatching hardware layer at least includes heat sources, a multi-heat-source control center and a wireless communication network, and the multi-heat-source control center sends multi-heat-source networked collaborative dispatching instructions and receives instruction responses and execution results of multiple heat sources;

[0061] A dispatching blockchain layer, where the dispatching blockchain layer provides trustworthy and secure information services for the multi-heat-source networked collaborative dispatching system, and the dispatching blockchain layer at least includes data blocks, a chain structure and a consensus algorithm, and the data blocks are connected in sequence to form a chain structure, and each data block is provided with encrypted data;

[0062] A dispatching smart contract layer, where the dispatching smart contract layer provides a development platform and an operating environment for the multi-heat-source networked collaborative dispatching, and the dispatching smart contract layer at least includes script code, a smart contract programming environment and a smart contract execution environment;

[0063] Dispatch application layer. The dispatch application layer performs collaborative optimization dispatch for multi-heat-source networking by encapsulating the collaborative dispatch of multi-heat-source networking into an application scenario of blockchain. The dispatch application layer at least includes a collaborative dispatch algorithm for multi-heat-source networking and application software. Taking the multi-heat-source control center and multiple heat sources as nodes, each node is interconnected through a wireless communication network. A blockchain system is composed of a multi-heat-source control center node, heat source nodes, and data blocks. The blockchain system enables each node to reach an agreement according to a consensus algorithm. The collaborative dispatch algorithm for multi-heat-source networking is compiled into script code and deployed on the blockchain system in the form of a smart contract. After running in the execution environment, the optimal instruction for collaborative dispatch of multi-heat-source networking is obtained. Then, the multi-heat-source control center node sends the optimal dispatch instruction to each heat source node. Each node receives the optimal dispatch instruction and automatically executes the corresponding strategy according to the conditions designed in the smart contract. Figure 3 The blockchain nodes (1 - N) shown in the figure are the heat source nodes, and the instruction values (1 - N) of the nodes in the figure are the instruction values of each heat source node.

[0064] In this embodiment, the data blocks are connected in sequence to form a chain structure, and each data block is provided with cryptographic data, including:

[0065] The relevant data for collaborative dispatch of multi-heat-source networking are packaged in the form of blocks, and the blocks are connected in sequence in the form of a linked list according to the time sequence to form a blockchain. Each block stores the information of the blockchain system for a period of time and consists of a block header and a set of data records. The block header includes information indicating the identity of the block, a proof that the block is reasonably generated, the hash value of the previous block, and the Merkle root value. The block is used for the storage of relevant data for collaborative dispatch of multi-heat-source networking and the management of the blockchain. After receiving the block, the node verifies and executes the information in the block through an encryption algorithm, and all operations are securely stored in the transaction log. The data records in the block at least include heat source type, heat source location, heat source capacity, heating load quota, and fuel price.

[0066] In this embodiment, the consensus algorithm adopted by the blockchain system is the PBFT Practical Byzantine Fault Tolerance algorithm. The consensus algorithm is used for the consensus process of node reception. First, it verifies whether the instruction information of the dispatch plan is sent by the multi-heat-source control center. After verification, each heat source node conducts consensus on the feasibility of the dispatch plan. If the plan meets the constraint conditions, it broadcasts, and at the same time waits to receive the verification results broadcast by more than 2 / 3 of the nodes. If the verification fails, it does not broadcast. When more than 2 / 3 of the nodes broadcast that their own verification is passed, all nodes reach a consensus, then broadcast the verification results, and execute the instruction information of the dispatch plan.

[0067] In this embodiment, the multi-heat-source networked collaborative scheduling algorithm is compiled into script code and deployed on the blockchain system in the form of a smart contract, and runs in the execution environment. Each node receives the optimal instruction for heat-source networked collaborative scheduling and automatically executes the corresponding policy according to the conditions designed in the smart contract, specifically including:

[0068] The multi-heat-source networked collaborative scheduling algorithm writes a smart contract program based on the rotation time of the scheduling as the pre-designed trigger condition and the iterative calculation rules of the economic scheduling objective function and the environmental scheduling objective function as the pre-designed trigger rules, and deploys it on the blockchain system in the form of script code. At the beginning of each scheduling cycle, the blockchain system automatically executes the scheduling process and can calculate the scheduling instruction value according to the scheduling algorithm. Each node receives the optimal instruction for heat-source networked collaborative scheduling and automatically executes the corresponding policy according to the conditions designed in the smart contract;

[0069] Among them, the economic scheduling objective function is expressed as:

[0070]

[0071] Among them, K is the number of heat sources participating in the multi-heat-source combined scheduling; T is the scheduling cycle; C k is the power generation of heat source k; P ek is the on-grid electricity price of heat source k; D k is the heating load of heat source k; P hk is the heating income of heat source k; f k is the fuel consumption of heat source k; E k is the fuel price used by heat source k;

[0072] The environmental scheduling objective function is expressed as:

[0073]

[0074] Among them, Q em,k,j is the mass of the j-th type of pollutant emitted by heat source k per unit mass of fuel used; E q,j is the pollution equivalent value of the j-th type of pollutant; J is the category of pollutants.

[0075] In this embodiment, the smart contract program includes a security verification program, an initialization program, a data reading and writing program, and a multi-heat-source networked collaborative scheduling iterative calculation program; the security verification program is to check the constraint conditions, and the scheduling instruction value can be sent to each heat source only after the security verification passes. The constraint conditions at least include: thermoelectric load balance constraint and heat supply network transmission and distribution capacity constraint; the initialization program is to initialize the state of the node by designing an initialization program when the blockchain system is started and before the smart contract is called. At this time, the ledger does not include any valid blockchain data and the current state of the node; the data reading and writing program is to read the parameters required by the multi-heat-source networked collaborative scheduling algorithm from the blockchain or store the calculated scheduling results into the blockchain; the multi-heat-source networked collaborative scheduling iterative calculation program is to perform scheduling iterative calculation according to the established economic scheduling objective function, environmental scheduling objective function and the set corresponding operation constraint conditions.

[0076] Embodiment 2

[0077] This Embodiment 2 proposes a multi-heat-source networked heating collaborative optimization scheduling method based on blockchain. The multi-heat-source networked heating collaborative optimization scheduling method includes:

[0078] Establish a blockchain system with multiple heat sources and a multi-heat-source control center as nodes; the multiple heat sources and the multi-heat-source control center are connected to each other through a wireless communication network;

[0079] Connect the multi-heat-source networked collaborative scheduling related data obtained by the blockchain system in the form of data blocks in sequence to form a chain structure, and make the data of each node consistent according to the consensus algorithm; the password data and interaction data of each block are set in the data block;

[0080] Compile the multi-heat-source networked collaborative scheduling algorithm into script code and deploy it on the blockchain system in the form of a smart contract, and obtain the optimal instruction for multi-heat-source networked collaborative scheduling after running in the set smart contract execution environment;

[0081] The multi-heat-source control center node sends the optimal scheduling instruction to each heat source node. Each node receives the optimal scheduling instruction, and after automatically executing the corresponding policy according to the conditions designed by the smart contract, returns the instruction response and execution results of the multiple heat sources to the multi-heat-source control center.

[0082] In this embodiment, the data related to the collaborative scheduling of multiple heat sources in the network is packaged in the form of blocks, and the blocks are sequentially connected in chronological order in the form of a linked list to form a blockchain. Each block stores the information of the blockchain system for a period of time, and consists of a block header and a set of data records. The block header includes information indicating the identity of the block, a proof that the block is reasonably generated, the hash value of the previous block, and the Merkle root value. The data records in the block at least include heat source type, heat source location, heat source capacity, heating load quota, and fuel price.

[0083] Among them, after the block is packaged, the block is digitally signed using the private key of the packager itself and broadcast to the blockchain system. After receiving the block, the nodes in the blockchain system first query their own ledgers to confirm whether they have ever received the block. If they have received it, the block is discarded; otherwise, the digital signature technology is used to verify the legality of the block, and after the verification passes, the subsequent information is transmitted.

[0084] It should be noted that the blockchain system will perform verification each time it reads the scheduling parameters, and at the same time, a network attack resistance algorithm is designed in the smart contract. And the nodes encrypt the data sent through the blockchain system using the asymmetric encryption algorithm. Without the corresponding private key, the attacker cannot decrypt the data, preventing data leakage and tampering caused by network attacks. The blockchain system iteratively calculates the collaborative scheduling instruction value for the multi-heat-source networked heating in the smart contract according to the collected information, and then transmits the process of this operation to other nodes in the form of blocks to modify the ledger data stored locally. When the attacker tampers with the data of a few nodes, the system will restore the data through the majority of normal nodes to ensure the data security during the communication process.

[0085] In this embodiment, when a heat source node in the multi-heat-source networked heating system wants to join the blockchain system, each heat source node is provided with a unique identity identifier for identity authentication when joining the blockchain system, and participates in the collaborative scheduling of the multi-heat-source network after the authentication passes.

[0086] The implementation process of the heat source node for identity authentication and participation in the collaborative scheduling of the multi-heat-source network includes:

[0087] All heat source nodes send their own identity identifiers to the blockchain system for identity verification. If the verification passes, the heat source nodes are added to the blockchain system; otherwise, the identity identifiers are resubmitted.

[0088] After each heat source node joins the blockchain system, it accesses the system data, verifies and stores the scheduling operation data using chained encrypted blocks, broadcasts and publishes information. The heat source control center forms an economic scheduling objective function, an environmental scheduling objective function, and constraint conditions based on the published information, and performs optimization calculations by calling the smart contract program to generate a scheduling plan. The blockchain system uses the consensus algorithm mechanism to verify whether the scheduling plan meets the constraints of each node. If it passes the verification, the optimization calculation of the scheduling plan is performed using the data submitted and verified by each heat source node; otherwise, the data is resubmitted for optimization calculation.

[0089] It should be noted that the operation mechanism of the blockchain is as follows: First step, each node broadcasts the data sent to all participants in the system. Second step, the node that receives the data checks the information recorded in the block data to determine whether the data is consistent and credible. If the consistency check passes, the consensus algorithm is used to verify the legality of the new block. Finally, the data that passes through the consensus algorithm process is stored in the accounting node. The whole network nodes start to receive the new block, and the random hash value of the new block will be regarded as the latest hash value. The new block will be connected to the previous block and extended. One of the reasons why the blockchain ensures the security, credibility, and difficulty of tampering of data is that the blockchain adopts the mechanism of data encryption verification signature of asymmetric encryption algorithm and the chain structure based on cryptography principles. In the data encryption verification signature mechanism, the blockchain system proves that a piece of data is sent from a certain node through a digital signature, that is, the private key in the traditional sense, and then uses the Hash algorithm based on cryptography principles to transform the data, that is, to transform data of any length into an irreversible and fixed-length character digital string. The consensus algorithm is the basis for the blockchain system to efficiently achieve data consistency.

[0090] The communication between each node obtains the information of adjacent nodes. By analyzing the functional characteristics of each node, the parameters affecting the scheduling, etc., the optimal scheduling instruction value of each heat source can be obtained. However, the prerequisite for obtaining the optimal value is that the communication topology used by each node remains fixed and the total scheduling instruction in the system needs to be consistent. In the multi-heat-source collaborative scheduling based on the blockchain, the system can quickly perform consistency verification on the scheduling data through the Merkle tree, improving the operation efficiency of the scheduling. One of the reasons is that the block header in the blockchain system using the Merkle tree only needs to contain the root hash value instead of encapsulating all the data, shortening the block encapsulation time.

[0091] In this embodiment, the multi-heat-source networking collaborative scheduling algorithm is compiled into script code and deployed on the blockchain system in the form of a smart contract, and the optimal instruction for multi-heat-source networking collaborative scheduling is obtained after running in the set smart contract execution environment, specifically including:

[0092] The multi-heat-source networked collaborative scheduling algorithm writes a smart contract program based on the rotation time of the scheduling as a pre-designed trigger condition and the iterative calculation rules of the economic scheduling objective function and the environmental scheduling objective function as pre-designed trigger rules, and deploys it on the blockchain system in the form of script code. At the beginning of each scheduling cycle, the blockchain system automatically executes the scheduling process and can calculate the scheduling instruction value according to the scheduling algorithm;

[0093] Among them, the smart contract program includes a security verification program, an initialization program, a data reading and writing program, and a multi-heat-source networked collaborative scheduling iterative calculation program; the security verification program is to check the constraint conditions, and the scheduling instruction value can be sent to each heat source only after the security verification passes. The constraint conditions at least include: thermoelectric load balance constraint and heat supply network transmission and distribution capacity constraint; the initialization program is to initialize the state of the node by designing the initialization program when the blockchain system starts and before the smart contract is called, and the ledger does not include any valid blockchain data and the current state of the node; the data reading and writing program is to read the parameters required by the multi-heat-source networked collaborative scheduling algorithm from the blockchain or store the calculated scheduling results into the blockchain; the multi-heat-source networked collaborative scheduling iterative calculation program is to perform scheduling iterative calculations according to the established economic scheduling objective function, environmental scheduling objective function and the set corresponding operation constraint conditions;

[0094] The economic scheduling objective function is expressed as:

[0095]

[0096] Among them, K is the number of heat sources participating in the multi-heat-source combined scheduling; T is the scheduling cycle; C k is the power generation of heat source k; P ek is the on-grid electricity price of heat source k; D k is the heating load of heat source k; P hk is the heating income of heat source k; f k is the fuel consumption of heat source k; E k is the fuel price used by heat source k;

[0097] The environmental scheduling objective function is expressed as:

[0098]

[0099] Among them, Q em,k,j is the mass of the j-th type of pollutant emitted by heat source k per unit mass of fuel used; E q,j is the pollution equivalent value of the j-th type of pollutant.

[0100] It should be noted that blockchain is essentially a secure database existing in the form of a ledger, and the part that realizes the rewriting of the blockchain ledger state and data processing is the smart contract. The smart contract is essentially a protocol built on computer technology for actively or passively processing data. Smart contracts also have characteristics such as distributed storage and being difficult to tamper with. Since the smart contract is a programmable program module, complex blockchain applications such as system scheduling can be achieved by presetting the trigger conditions and rules of the smart contract in advance. The smart contract within the blockchain system can be regarded as a signed contract agreement. When the data submitted by the nodes within the system reaches the pre-designed execution conditions, the blockchain system will trigger and execute the corresponding operations. During the operation of the blockchain system, the system will detect the execution status and conditions of the smart contract in real time throughout the process.

[0101] In this embodiment, an improved satin bowerbird optimization algorithm is used to solve the multi-objective function including the economic dispatch objective function and the environmental dispatch objective function;

[0102] The improved satin bowerbird optimization algorithm includes: improvement of population initialization. The population is initialized using the strategy based on elite opposition-based learning. In the initialization stage, an initial population is randomly generated in the search space, and at the same time, a dynamic opposition population is generated. The initial population and the population after its dynamic opposition learning are compared, and the bowerbird nests with better fitness are selected to form the initial population; improvement of position update. For the points that cross the boundary during the search process, they are re-initialized within the search interval, and the opposition point search method is adopted, and the better points are retained through the competition mechanism.

[0103] In practical applications, the multi-objective genetic algorithm is used to set weights for the multi-objective function respectively, and the multi-objective function is transformed into a single-objective function; for the multi-objective optimization problem, its solution is usually a set of non-dominated solutions, that is, the Pareto solution set. The objective functions corresponding to all non-dominated solutions constitute the non-dominated optimal objective domain of the multi-objective optimization problem, also known as the Pareto front. Considering that only a series of Pareto optimal solution sets can be obtained through the Pareto front, therefore, after using the multi-objective genetic algorithm to find the Pareto front, weights are set for each objective function of the multi-heat-source networked heating collaborative scheduling model respectively, and the multi-objective function is transformed into a single-objective function, where the weight is used to represent the importance degree of each objective function.

[0104] It should be noted that the satin bowerbird optimization algorithm mainly refers to the behavior of male satin bowerbirds building a bower (courtship pavilion) by using dead branches and thin branches, and decorating the surrounding environment to attract female birds. At the same time, before choosing a mating partner and returning to its bower, the female bird will visit several bowers built by other male birds along the way to select a more attractive bower. For male satin bowerbirds, they build their courtship pavilions through their natural instincts and imitation of other male bowerbirds. Based on the imitation of the courtship process of satin bowerbirds, the satin bowerbird optimization algorithm (SBO) integrates dynamic step size and mutation operation while establishing a position update mechanism, and has excellent performance in optimization. The present invention adopts an elite opposition-based learning strategy to initialize the population. In the initialization stage, both the current solution and its dynamically opposed learning solution are searched, and the better solution is used as the initial solution to eliminate blindness and search in parallel within the solution space; the diversity of the population is expanded, and the search efficiency of the algorithm is improved.

[0105] In several embodiments provided in the present application, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the drawings show the possible architectures, functions, and operations of systems, methods, and computer program products according to multiple embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0106] In addition, each functional module in various embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0107] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods according to various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0108] Taking the ideal embodiments of the present invention described above as an inspiration, through the above description, relevant staff can completely make various changes and modifications without departing from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A multi-heat-source networked heating collaborative optimization scheduling system based on blockchain, characterized in that, It includes: A scheduling hardware layer, which at least includes heat sources, a multi-heat-source control center, and a wireless communication network. The multi-heat-source control center sends multi-heat-source networking collaborative scheduling instructions and receives instruction responses and execution results from multiple heat sources; A scheduling blockchain layer, which provides information services for the multi-heat-source networking collaborative scheduling system. The scheduling blockchain layer at least includes data blocks, a chain structure, and a consensus algorithm. The data blocks are connected in sequence to form a chain structure, and each data block is provided with encrypted data; A scheduling smart contract layer, which provides a development platform and an operating environment for multi-heat-source networking collaborative scheduling. The scheduling smart contract layer at least includes script code, a smart contract programming environment, and a smart contract execution environment; A scheduling application layer, which performs multi-heat-source networking collaborative optimal scheduling by encapsulating multi-heat-source networking collaborative scheduling into an application scenario of the blockchain. The scheduling application layer at least includes a multi-heat-source networking collaborative scheduling algorithm and application software. The multi-heat-source control center and multiple heat sources are used as nodes, and each node is connected to each other through a wireless communication network. A blockchain system is composed of a multi-heat-source control center node, heat source nodes, and data blocks. The blockchain system makes each node reach an agreement according to the consensus algorithm. The multi-heat-source networking collaborative scheduling algorithm is compiled into script code and deployed on the blockchain system in the form of a smart contract, and after running in the execution environment, the optimal instruction for multi-heat-source networking collaborative scheduling is obtained. Then, the multi-heat-source control center node sends the optimal scheduling instruction to each heat source node, and each node receives the optimal scheduling instruction and automatically executes the corresponding strategy according to the conditions designed by the smart contract; Automatically execute the corresponding strategy according to the conditions designed by the smart contract, specifically including: The multi-heat-source networking collaborative scheduling algorithm is to write a smart contract program according to the rotation time of scheduling as a pre-designed trigger condition and the iterative calculation rules of the economic scheduling objective function and the environmental scheduling objective function as pre-designed trigger rules, and deploy it on the blockchain system in the form of script code. At the beginning of each scheduling cycle, the blockchain system automatically executes the scheduling process and can calculate the scheduling instruction value according to the scheduling algorithm. Each node receives the optimal instruction for heat source networking collaborative scheduling and automatically executes the corresponding strategy according to the conditions designed by the smart contract; The economic scheduling objective function is expressed as: Among them, K is the number of heat sources participating in the combined dispatching of multiple heat sources; T is the dispatching period; C k is the power generation of heat source k; P ek is the on-grid electricity price of heat source k; D k is the heating load of heat source k; P hk is the heating income of heat source k; f k is the fuel consumption of heat source k; E k is the fuel price used by heat source k; The environmental scheduling objective function is expressed as: where Q em,k,j is the mass of the j-th type of pollutant emitted per unit mass of fuel used by the heat source k; E q,j is the pollution equivalent value of the j-th type of pollutant; J is the category of pollutants.

2. The multi-heat-source networked heating collaborative optimization scheduling system according to claim 1, wherein The data blocks are connected in sequence to form a chain structure, and each data block is provided with encrypted data, including: The data related to multi-heat-source networking collaborative scheduling is packaged in the form of blocks, and the blocks are sequentially connected in the form of a linked list according to the time sequence to form a blockchain; Each block stores the information of the blockchain system for a period of time, and is composed of a block header and a set of data records. The block header includes information indicating the identity of the block, a proof that the block is reasonably generated, the hash value of the previous block, and the Merkle root value; The block is used for storing data related to the collaborative scheduling of multiple heat sources and the management of the blockchain. After receiving the block, the node verifies and executes the information in the block through an encryption algorithm, and all operations are securely stored in the transaction log. The data records in the block at least include heat source type, heat source location, heat source capacity, heating load quota, and fuel price.

3. The multi-heat-source networked heating collaborative optimization scheduling system according to claim 1, wherein The consensus algorithm adopted by the blockchain system is the PBFT Practical Byzantine Fault Tolerance algorithm. The consensus algorithm is used for the receiving consensus process of nodes. First, it verifies whether the instruction information of the scheduling scheme is sent by the multi-heat-source control center. After passing the verification, each heat source node reaches a consensus on the feasibility of the scheduling scheme. If the scheme meets the constraint conditions, it will be broadcast, and at the same time, it waits to receive the verification results broadcast by more than 2 / 3 of the nodes. If the verification fails, it will not be broadcast. When more than 2 / 3 of the nodes broadcast that their own verification has passed, all nodes reach a consensus, then broadcast the verification results, and execute the instruction information of the scheduling scheme.

4. The multi-heat-source networked heating collaborative optimization scheduling system according to claim 1, characterized in that: The intelligent contract program includes a security verification program, an initialization program, a data reading and writing program, and a multi-heat-source networked collaborative scheduling iterative calculation program; The security verification program checks the constraint conditions. After the security verification passes, the scheduling instruction value can be sent to each heat source. The constraint conditions at least include: thermoelectric load balance constraint and heating pipe network transmission and distribution capacity constraint; The initialization program is after the blockchain system is started and before the intelligent contract is called. The ledger does not include any valid blockchain data and the current state of the node. The state of the node is initialized by designing the initialization program; The data reading and writing program reads the parameters required by the multi-heat-source networked collaborative scheduling algorithm from the blockchain or stores the calculated scheduling results into the blockchain; The multi-heat-source networked collaborative scheduling iterative calculation program performs scheduling iterative calculations according to the established economic scheduling objective function, environmental scheduling objective function, and the set corresponding operation constraint conditions.

5. A collaborative optimal scheduling method for multi-heat-source networked heating based on blockchain, the collaborative optimal scheduling method for multi-heat-source networked heating based on blockchain is applied to the multi-heat-source networked heating collaborative optimal scheduling system according to any one of claims 1 to 4, and is characterized in that, The multi-heat-source networked heating collaborative optimization scheduling method includes: Establish a blockchain system with multiple heat sources and a multi-heat-source control center as nodes; the multiple heat sources and the multi-heat-source control center are interconnected through a wireless communication network; The multi-heat-source networked collaborative scheduling related data obtained by the blockchain system is connected in sequence in the form of data blocks to form a chain structure, and the data of each node is made consistent according to the consensus algorithm; the password data and interaction data of each block are set in the data block; Compile the multi-heat-source networked collaborative scheduling algorithm into script code and deploy it on the blockchain system in the form of an intelligent contract, and obtain the optimal instruction for multi-heat-source networked collaborative scheduling after running in the set intelligent contract execution environment; The multi-heat-source control center node sends the optimal scheduling instruction to each heat source node. Each node receives the optimal scheduling instruction, and after automatically executing the corresponding strategy according to the conditions designed by the intelligent contract, it returns the instruction response and execution results of multiple heat sources to the multi-heat-source control center.

6. The multi-heat-source networked heating collaborative optimization scheduling method according to claim 5, wherein The multi-objective function including the economic dispatch objective function and the environmental dispatch objective function is solved by using an improved satin bowerbird optimization algorithm; The improved satin bowerbird optimization algorithm includes: improvement of population initialization. The population is initialized by using an elite opposition-based learning strategy. In the initialization stage, an initial population is randomly generated in the search space, and at the same time, a dynamic opposition population is generated. The initial population and the dynamic opposition population are compared, and the bowerbirds with better fitness are selected to form the initial population; Improvement of position update. For the points that cross the boundary during the search process, they are re-initialized in the search interval, and the opposition point search method is adopted to retain the better points through a competition mechanism.

Images