CN-122001024-A - Block chain-based intelligent power system resource allocation method and system

CN122001024ACN 122001024 ACN122001024 ACN 122001024ACN-122001024-A

Abstract

The invention provides an intelligent configuration method and system for power system resources based on block chains, which relates to the technical field of power system resource configuration, and comprises the steps of obtaining equipment resources and demand data to construct a topology layer, calculating a matching weight identification combination relationship to form an extended matching set, and detecting conflict through the space-time index, resolving the conflict by utilizing a game propagation diagram to generate a correlation diagram, performing electric partition verification, distributing to blockchain verification, and finally executing resource allocation through intelligent contracts. The invention can realize the accurate and efficient configuration of the power resources, improve the running reliability of the system and reduce the configuration cost.

Inventors

KOU FENG
JIANG YI
WEN JUAN
WEI ZE

Assignees

北京冠宇信息科技股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260225

Claims (10)

1. The intelligent allocation method for the power system resources based on the block chain is characterized by comprising the following steps: acquiring power resource data and transaction demand data of each device of a power system, and constructing resource nodes and demand nodes; Forming a resource supply topology layer by connecting the resource nodes through cooperative edges, forming a demand intention topology layer by connecting the demand nodes through dependent edges, calculating interlayer mapping weights based on supply-demand matching degree and space-time constraint, identifying a resource demand combination relation transferred by multiple hops, and generating an expansion matching relation set; Detecting resource competition conflict of the matching relation set in the space-time dimension by using a time interval tree and a space partition index, constructing a game propagation diagram according to the demand urgency and the resource scarcity to carry out iterative propagation conflict resolution, and generating a resource space-time correlation diagram; Dividing an electrical decoupling partition and verifying power balance between resource adjustment and load change based on the resource space-time correlation map, packaging feasible operation into a sub-decision unit, distributing the sub-decision unit to a block chain link point verification trend constraint, and generating a resource allocation scheme through double-round consensus voting; and packaging the resource allocation scheme into an intelligent contract, writing the intelligent contract into a blockchain, and automatically triggering the resource allocation to execute actions through the intelligent contract.
2. The method of claim 1, wherein forming the resource nodes into a resource supply topology layer by cooperative edge connection, forming the demand nodes into a demand intention topology layer by dependent edge connection, calculating interlayer mapping weights based on supply-demand matching and space-time constraints, identifying resource demand combination relationships of multi-hop transfer, and generating an extended matching relationship set, comprises: Extracting the output capacity and the geographic position of each resource node from the power resource data, calculating the product of the capacity complementation degree and the distance attenuation factor between any two resource nodes, and establishing a cooperative edge between the resource nodes with the cooperative weight greater than a cooperative threshold value as a cooperative weight to obtain a resource supply topology layer; Based on transaction demand data, extracting a time window and a resource type of each demand node, calculating the similarity of the time window overlapping rate and the resource type between the demand nodes and the preamble demand nodes, carrying out weighted summation to obtain a dependent weight, and establishing a dependent edge between the demand nodes with the dependent weight greater than a dependent threshold value to obtain a demand intention topology layer; Calculating the fitting degree of a power supply power curve of a resource node and a power consumption load curve of a demand node to obtain a supply-demand matching degree, and obtaining an interlayer mapping weight through self-adaptive weighted fusion by combining a constraint value of geographic coverage overlapping degree and time response overlapping degree; And identifying an initial demand node from the demand intention topology layer, performing multi-hop traversal along a dependent edge, selecting a resource node by combining the interlayer mapping weight and the cooperative edge, recording the matching relation between each demand node and a resource node sequence to generate a resource demand, and summarizing multi-hop traversal paths to form a matching relation set.
3. The method of claim 1, wherein detecting resource competition conflicts for the set of matching relationships in the space-time dimension using a time interval tree and a spatial partition index, and constructing a game propagation graph for iterative propagation resolution conflicts according to demand urgency and resource scarcity, generating a resource space-time correlation graph, comprises: Mapping the time characteristic of each matching relation in the extended matching relation set to a time interval tree, marking the interval node occupied by the time interval tree, mapping the space characteristic to a space partition index, marking the partition unit occupied by the space characteristic, and identifying the matching relation pair with space-time competition and constructing a conflict relation set by inquiring the interval node with overlapping and the partition unit with overlapping; aiming at each matching relation in the conflict relation set, calculating an initial game weight based on demand urgency and resource scarcity, constructing a game propagation diagram, identifying a multi-level transmitted indirect conflict relation by tracking a conflict propagation path, performing decremental correction on the initial game weight of the indirect conflict relation, and generating a path corrected game weight distribution; And executing an iterative game process in the game propagation diagram, calculating game benefits by the conflict nodes in each iteration according to the game weights of the conflict nodes and the game weights of the adjacent conflict nodes, marking the nodes with the game benefits lower than the exit threshold as invalid states, releasing occupied resources, reversely distributing the released resources to the nodes with high game benefits according to the propagation path, terminating the iteration when the game benefits of all the nodes are stable or reach the maximum iteration times, and constructing the reserved matching relationship as a resource space-time correlation diagram.
4. A method according to claim 3, wherein for each matching relationship in the set of conflict relationships, calculating initial gaming weights and constructing a gaming propagation graph based on demand urgency and resource rarity, identifying multi-pass indirect conflict relationships by tracking conflict propagation paths, comprising: For each matching relation in the conflict relation set, extracting an aging attenuation parameter of a demand node as demand urgency, and a supply-demand ratio parameter of a resource node as resource scarcity, counting the number of conflict sides of each matching relation with other matching relations in the conflict relation set, calculating a competition strength correction coefficient according to the number of conflict sides, and multiplying the competition strength correction coefficient with the weighted sum of the demand urgency and the resource scarcity to obtain an initial game weight; And constructing a game propagation graph by taking each matching relation in the conflict relation set as a node and taking the conflict relation as an edge, assigning the initial game weight to the corresponding node as a node state, traversing from any node in the game propagation graph, recording the traversed node sequence to form a propagation path set, identifying the node which is connected with the most edge and bears as a path target node for the propagation path with the path length larger than a direct conflict threshold, calculating a medium number centrality measurement value, and marking the relation between a path starting point and a path ending point as the indirect conflict relation of multistage transmission when the medium number centrality measurement value exceeds the centrality threshold.
5. The method of claim 1, wherein partitioning the electrical decoupling partitions and verifying power balance of resource adjustment and load variation based on the resource spatiotemporal correlation map encapsulates feasible operations into sub-decision units, distributes to block link point verification power flow constraints, generates a resource allocation scheme by double round consensus voting, comprising: Calculating the electric coupling strength between the resource nodes and the demand nodes and dividing a plurality of electric decoupling partitions based on the resource space-time correlation map, extracting the power generation adjustment quantity of the resource nodes and the load variation quantity of the demand nodes, performing power balance verification, identifying the transmission capacity limit of the communication branch between the partitions, marking the electric decoupling partitions which do not pass the power balance verification as the partitions to be adjusted, and re-dividing the new electric decoupling partitions to perform the power balance verification; The method comprises the steps of packaging the intra-partition resource allocation operation passing through power balance verification into sub-decision units, calculating the power flow increment generated on a connecting branch by the sub-decision units by using a direct current power flow model, and distributing the sub-decision units and the influence parameters to block chain nodes as power grid influence parameters; Each block chain link point verifies whether the increment of the power flow meets the transmission capacity limit and generates a partition verification message, performs first-round consensus voting through a Bayesian fault-tolerant protocol, marks sub-decision units with the number exceeding a fault-tolerant threshold as partition feasible units, extracts corresponding influence parameters, marks sub-decision units which do not pass through the voting as units to be regulated and returns to a game propagation diagram for re-digestion; And superposing the power flow increment on the same contact branch to obtain the whole network power flow distribution, initiating a second round of consensus voting to verify whether all transmission capacity limits are met, eliminating part of the partition feasible units according to the descending order of the influence parameters if the verification fails, re-verifying, and integrating the partition feasible units passing the verification to generate a resource allocation scheme.
6. The method of claim 5, wherein calculating the electrical coupling strength between the resource node and the demand node and dividing a plurality of electrical decoupling partitions based on the resource space-time correlation map, extracting the power generation adjustment amount of the resource node and the load variation amount of the demand node, performing power balance verification, and identifying the transmission capacity limit of the inter-partition connection leg, comprises: Extracting the geographic position and supply-demand matching relation of each node from the resource space-time correlation diagram, calculating the electrical distance between each resource node and each demand node according to the geographic position, and calculating the electrical coupling strength between the nodes by combining the power transmission paths in the supply-demand matching relation; clustering and decomposing the resource nodes and the demand nodes based on the electric coupling strength to obtain a plurality of electric decoupling partitions, identifying branches connected with different electric decoupling partitions, marking the branches as connecting branches, and extracting rated transmission power of the connecting branches as transmission capacity limit; In each electric decoupling partition, determining node pairing combinations according to supply-demand matching relations to obtain resource allocation operation, extracting resource power generation adjustment quantity and demand load change quantity, calculating power deviation of the node pairing combinations and accumulating to obtain partition power unbalance quantity, and establishing a partition power balance check equation; And when the partition power unbalance is smaller than the balance error threshold, extracting a contact branch set corresponding to the electrically decoupled partition passing the power balance verification, and storing the transmission capacity limit and the partition identification binding of the contact branch set as a partition constraint mapping table as an input condition of a sub-decision unit.
7. The method of claim 1, wherein encapsulating the resource allocation scheme as a smart contract and writing to a blockchain, automatically triggering a resource allocation execution action by the smart contract, comprises: According to the resource allocation scheme, a multi-stage trigger structure comprising a contract life cycle state machine is constructed, the multi-stage trigger structure comprises a resource scheduling instruction sequence, an execution state feedback signal and an exception handling rule, and the multi-stage trigger structure and the state machine trigger condition are bound into an event-driven intelligent contract; Broadcasting the intelligent contracts to block chain link points, establishing call link diagrams among contracts based on node time sequence dependency relations in the resource allocation scheme, performing contract executable verification on the call link diagrams by adopting a hierarchical progressive verification mechanism, and writing the intelligent contracts into a block chain after verification is passed; Monitoring a triggering condition defined in the intelligent contract, converting the resource scheduling instruction sequence into a resource allocation execution action according to the hierarchical sequence of the calling link diagram when the triggering condition is met, and writing the execution result state back to a blockchain; when the execution fails or the timeout does not respond, an exception handling rule of the intelligent contract is triggered, and an exception record writing block chain is generated.
8. A blockchain-based power system resource intelligent allocation system for implementing the method of any of claims 1-7, comprising: The first unit is used for acquiring power resource data and transaction demand data of all equipment of the power system and constructing resource nodes and demand nodes; The second unit is used for connecting the resource nodes through cooperative edges to form a resource supply topology layer, connecting the demand nodes through dependent edges to form a demand intention topology layer, calculating interlayer mapping weights based on supply-demand matching degree and space-time constraint, identifying a multi-hop transmitted resource demand combination relation, and generating an expanded matching relation set; The third unit is used for detecting resource competition conflict of the matching relation set in the space-time dimension by utilizing a time interval tree and a space partition index, constructing a game propagation diagram according to the demand urgency and the resource scarcity to carry out iterative propagation conflict resolution, and generating a resource space-time correlation diagram; A fourth unit, configured to divide an electrical decoupling partition and verify power balance between resource adjustment and load change based on the resource space-time correlation map, package feasible operations into sub-decision units, distribute the sub-decision units to block link point verification power flow constraints, and generate a resource allocation scheme through double-round consensus voting; and a fifth unit, configured to package the resource allocation scheme into an intelligent contract and write the intelligent contract into a blockchain, and automatically trigger the resource allocation to execute an action through the intelligent contract.
9. An electronic device, comprising: A processor; A memory for storing processor-executable instructions; Wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 7.

Description

Block chain-based intelligent power system resource allocation method and system Technical Field The invention relates to the technical field of power system resource allocation, in particular to an intelligent power system resource allocation method and system based on a block chain. Background With the rapid development of energy internet and smart grid, power system resource allocation faces new challenges of diversification, distribution and dynamics. The power system resources comprise power generation resources, energy storage resources, demand side response resources and the like, and efficient configuration of the resources in time and space is a key for guaranteeing the economy and stability of the power system. Traditional power resource allocation mainly depends on a centralized scheduling system, and load requirements are met through unified planning and scheduling. In recent years, with the large-scale access of renewable energy sources, the rapid growth of distributed resources, and the advancement of power market, the power system resource allocation mode is transitioning from centralized to distributed. The block chain technology provides a new idea for intelligent configuration of power system resources due to the characteristics of decentralization, non-tampering, traceability and the like. The blockchain can ensure fairness and fairness of power transaction, and realize efficient allocation of resources, so that the blockchain becomes an important technical means for innovation of a power system. Disclosure of Invention The embodiment of the invention provides an intelligent power system resource allocation method and system based on a block chain, which can solve the problems in the prior art. In a first aspect of an embodiment of the present invention, an intelligent allocation method for power system resources based on blockchain is provided, including: acquiring power resource data and transaction demand data of each device of a power system, and constructing resource nodes and demand nodes; Forming a resource supply topology layer by connecting the resource nodes through cooperative edges, forming a demand intention topology layer by connecting the demand nodes through dependent edges, calculating interlayer mapping weights based on supply-demand matching degree and space-time constraint, identifying a resource demand combination relation transferred by multiple hops, and generating an expansion matching relation set; Detecting resource competition conflict of the matching relation set in the space-time dimension by using a time interval tree and a space partition index, constructing a game propagation diagram according to the demand urgency and the resource scarcity to carry out iterative propagation conflict resolution, and generating a resource space-time correlation diagram; Dividing an electrical decoupling partition and verifying power balance between resource adjustment and load change based on the resource space-time correlation map, packaging feasible operation into a sub-decision unit, distributing the sub-decision unit to a block chain link point verification trend constraint, and generating a resource allocation scheme through double-round consensus voting; and packaging the resource allocation scheme into an intelligent contract, writing the intelligent contract into a blockchain, and automatically triggering the resource allocation to execute actions through the intelligent contract. Forming a resource supply topology layer by connecting the resource nodes through cooperative edges, forming a demand intention topology layer by connecting the demand nodes through dependent edges, calculating interlayer mapping weights based on supply-demand matching degree and space-time constraint, identifying a resource demand combination relation of multi-hop transfer, and generating an expansion matching relation set, wherein the method comprises the following steps: Extracting the output capacity and the geographic position of each resource node from the power resource data, calculating the product of the capacity complementation degree and the distance attenuation factor between any two resource nodes, and establishing a cooperative edge between the resource nodes with the cooperative weight greater than a cooperative threshold value as a cooperative weight to obtain a resource supply topology layer; Based on transaction demand data, extracting a time window and a resource type of each demand node, calculating the similarity of the time window overlapping rate and the resource type between the demand nodes and the preamble demand nodes, carrying out weighted summation to obtain a dependent weight, and establishing a dependent edge between the demand nodes with the dependent weight greater than a dependent threshold value to obtain a demand intention topology layer; Calculating the fitting degree of a power supply power curve of a resource node and a power consumption load curve of