CN-122026513-A - Hybrid power supply method and system for electric energy router

CN122026513ACN 122026513 ACN122026513 ACN 122026513ACN-122026513-A

Abstract

The invention belongs to the technical field of power systems and automation thereof, and discloses a hybrid power supply method and system of an electric energy router, comprising the steps of acquiring equipment multi-source data, instantiating independent regularized energy agents for each equipment, generating static semantic tags and dynamic state tags, constructing and broadcasting corresponding three-dimensional energy contracts by combining a local behavior rule set; setting up a distributed negotiation market, generating a deterministic scheduling instruction set by matching contracts with matching rules, converting the deterministic scheduling instruction set into control commands, driving equipment to execute power exchange, monitoring feedback of an execution result, injecting temporary rules into the distributed negotiation market when preset conditions are triggered, synchronizing a linkage double-circulation active immunization mechanism to optimize a power supply link, recovering multi-dimensional operation data, generating an operation data set by structuring, generating parameter optimization suggestions by analyzing preset diagnosis rules, adjusting corresponding parameters, and synchronously updating the double-circulation active immunization mechanism to form a closed-loop iterative hybrid power supply system.

Inventors

YANG BO
WANG WEIJIAN
JIANG HUA
FU XIN
ZHANG CHAOBIN
TONG JIAJUN

Assignees

奥为科技(南京)有限公司

Dates

Publication Date: 20260512
Application Date: 20260114

Claims (10)

1. The hybrid power supply method for the electric energy router is characterized by comprising the following steps of: S1, acquiring multi-source data of equipment, instantiating independent regularized energy agents for each piece of equipment, generating static semantic tags and dynamic state tags, integrating to obtain a regularized energy agent set, and further constructing and broadcasting corresponding three-dimensional energy contracts by combining a local behavior rule set; s2, building a distributed negotiation market based on a regularized energy agent set and corresponding three-dimensional energy contracts, and generating a deterministic scheduling instruction set through three-layer deterministic matching rule matching contracts; S3, based on a deterministic scheduling instruction set, converting a scheduling instruction into a control command through each regularized energy agent to drive equipment to execute power exchange, continuously monitoring feedback of actual execution results of the equipment, injecting temporary rules into a distributed negotiation market when a preset condition is triggered, and optimizing a power supply link by a synchronous linkage double-circulation active immune mechanism; S4, based on the feedback of the actual execution result of the equipment and the optimized power supply link, recovering multidimensional operation data, and generating an operation data set through structuring; and S5, analyzing and generating parameter optimization suggestions through preset diagnosis rules based on the operation data set, adjusting corresponding parameters, and synchronously updating a dual-cycle active immunization mechanism to form a closed-loop iterative hybrid power supply system.
2. The method for hybrid power supply of an electrical energy router according to claim 1, wherein the means for generating the static semantic label and the dynamic state label and integrating the static semantic label and the dynamic state label to obtain the regularized energy agent set comprises: synchronously acquiring electrical quantity data, state quantity data, environment data and demand data of each device to form multi-source data of the device; based on the collected multi-source data, independently instantiating a regularized energy agent with data processing and label generating capabilities for each device, and establishing a binding relation between physical devices and virtual agents; generating rules according to preset labels by each regularized energy agent, generating static semantic labels of inherent attributes of curing equipment, and updating dynamic state labels of running states in real time; And integrating all the regularized energy agents and corresponding labels to form a regularized energy agent set.
3. The power router hybrid power supply method of claim 2, wherein the manner in which the corresponding three-dimensional energy contracts are constructed and broadcast in conjunction with the local behavior rule set comprises: each regularized energy agent invokes self labels and presets a local behavior rule set, sequentially constructs terms of space dimension, time dimension and attribute dimension, forms a standardized three-dimensional energy contract, and synchronously broadcasts to the ready state distributed negotiation market.
4. The power router hybrid power supply method as claimed in claim 3, wherein the way of building a distributed negotiation market comprises: After the ready state distributed negotiation market receives the broadcasted three-dimensional energy contracts, associating the regularized energy proxy set, and executing proxy identity verification and contract legitimacy verification; Taking the verified proxy contracts as contracts to be matched, classifying and displaying the proxy types and the contract types, constructing a structured contract pool, and synchronously loading matching rule parameters adapting to the current scene from a preset matching rule base to form a dynamic initialized distributed negotiation market.
5. The power router hybrid power supply method of claim 4, wherein the means for generating a deterministic scheduling instruction set comprises: Based on contracts to be matched in the contract pool, according to parameters of three deterministic matching rules of matched safety filtering, space-time arbitration and economic preference, candidate contracts are screened through a safety filtering layer, then the time sequence compatibility of the candidate contracts is matched through a space-time arbitration layer, and finally the optimal contract combination is obtained through an economic preference layer; Based on the optimal contract combination, an independent scheduling instruction is generated for each pair of matched power source agents and load agents and distributed to the corresponding regularized energy agents as a deterministic scheduling instruction set.
6. The method of claim 5, wherein the means for converting the scheduling instruction into a control command and the driving device performs power switching comprises: after each regularized energy agent receives the distributed deterministic scheduling instruction set, according to the difference between the power supply equipment and the load equipment, the scheduling instruction is disassembled into a control command which is matched with the bottom-layer power electronic converter, and the physical equipment is driven to execute power exchange; the regularized energy agent synchronizes the execution result of the real-time monitoring device, feeds back the execution result to the distributed negotiation market, and synchronously updates the self dynamic state label.
7. The method of power router hybrid power supply of claim 6, wherein the means for optimizing the power supply link comprises: Monitoring the feedback execution result in real time, and judging the current risk level by combining a quantization threshold value and a risk grading and researching judgment logic; If the risk level meets the preset condition, judging that the power supply risk exists, switching a corresponding operation mode according to the risk level, and injecting temporary constraint rules into the distributed negotiation market and the regularized energy agent; And a synchronous linkage double-circulation active immunization mechanism is used for regulating and controlling a power supply link with power supply risk through link topology adjustment and load and power supply collaborative optimization.
8. The power router hybrid power supply method of claim 7, wherein the means for generating the operational data set comprises: based on the optimized power supply link, the full recovery acquisition equipment execution class, the power supply link class, the toughness regulation class and the contract and market class data form multidimensional operation data; And constructing a structured data set according to four dimensions of equipment operation, link state, toughness regulation and control and contract life cycle, and establishing a cross-dimension association relationship to form a structured operation data set.
9. The power router hybrid power supply method of claim 8, wherein the generating parameter optimization suggestions by pre-set diagnostic rule analysis, adjusting the corresponding parameters comprises: Based on the operation data set, carrying out parameter optimization analysis on three-dimensional energy contracts, a double-circulation active immune mechanism and contract matching through a preset diagnosis rule, and generating and sequencing parameter optimization suggestions according to priorities; and then parameter adjustment and mechanism iteration are executed according to the priority, and the parameters are synchronously updated to a distributed negotiation market, a double-circulation active immunization mechanism and a regularized energy agent.
10. The power router hybrid power supply system, implemented based on the power router hybrid power supply method according to claims 1 to 9, is characterized by comprising: The agent construction and contract generation unit is used for acquiring equipment multi-source data, instantiating independent regularized energy agents for each equipment, generating static semantic tags and dynamic state tags, integrating to obtain a regularized energy agent set, and further constructing and broadcasting corresponding three-dimensional energy contracts by combining a local behavior rule set; the distributed market matching and instruction generation unit is used for constructing a distributed negotiation market based on the regularized energy agent set and the corresponding three-dimensional energy contracts, and generating a deterministic scheduling instruction set through three-layer deterministic matching rule matching contracts; the instruction execution and state feedback unit is used for converting a scheduling instruction into a control command through each regularized energy agent based on a deterministic scheduling instruction set and driving the equipment to execute power exchange, continuously monitoring feedback of an actual execution result of the equipment, injecting a temporary rule into a distributed negotiation market when a preset condition is triggered, and optimizing a power supply link by a synchronous linkage double-circulation active immunization mechanism; The multi-dimensional data recovery and structuring unit is used for recovering multi-dimensional operation data based on the feedback of the actual execution result of the equipment and the optimized power supply link, and generating an operation data set through structuring; And the parameter optimization and mechanism iteration unit is used for analyzing and generating parameter optimization suggestions through preset diagnosis rules based on the operation data set, adjusting corresponding parameters, and synchronously updating the dual-cycle active immunization mechanism to form a closed-loop iterative hybrid power supply system.

Description

Hybrid power supply method and system for electric energy router Technical Field The invention relates to the technical field of power systems and automation thereof, in particular to a hybrid power supply method and system for an electric energy router. Background The new energy transformation promotes large-scale access of multiple devices such as photovoltaics, energy storage and the like, and the electric energy router is used as a hybrid power supply core hub to realize multi-source energy collaborative scheduling. Under the condition, the problems of mismatching of source load and space, poor equipment cooperativity and insufficient power supply toughness are outstanding, the traditional centralized control is difficult to adapt to the dynamic change of distributed energy, and a data driving optimization mechanism is lacked, so that the power supply safety, economy and toughness are difficult to be compatible. The existing electric energy router hybrid power supply scheme still has some limitations that equipment is cooperated with the centralized control, flexibility is poor, random output of a distributed power supply and dynamic requirements of loads are difficult to adapt, contract matching rules are simple, only power matching is considered, safety, time sequence and cost cannot be considered, toughness regulation is passive, after faults are remedied, response to equipment deviation and link abnormality is delayed, and core load power supply guaranteeing capability is weak. Disclosure of Invention In order to overcome the defects in the prior art, the invention provides the following technical scheme that the electric energy router hybrid power supply method comprises the following steps: S1, acquiring multi-source data of equipment, instantiating independent regularized energy agents for each piece of equipment, generating static semantic tags and dynamic state tags, integrating to obtain a regularized energy agent set, and further constructing and broadcasting corresponding three-dimensional energy contracts by combining a local behavior rule set; s2, building a distributed negotiation market based on a regularized energy agent set and corresponding three-dimensional energy contracts, and generating a deterministic scheduling instruction set through three-layer deterministic matching rule matching contracts; S3, based on a deterministic scheduling instruction set, converting a scheduling instruction into a control command through each regularized energy agent to drive equipment to execute power exchange, continuously monitoring feedback of actual execution results of the equipment, injecting temporary rules into a distributed negotiation market when a preset condition is triggered, and optimizing a power supply link by a synchronous linkage double-circulation active immune mechanism; S4, based on the feedback of the actual execution result of the equipment and the optimized power supply link, recovering multidimensional operation data, and generating an operation data set through structuring; and S5, analyzing and generating parameter optimization suggestions through preset diagnosis rules based on the operation data set, adjusting corresponding parameters, and synchronously updating a dual-cycle active immunization mechanism to form a closed-loop iterative hybrid power supply system. Further, the method for generating the static semantic tag and the dynamic state tag and integrating the static semantic tag and the dynamic state tag to obtain the regularized energy agent set includes: synchronously acquiring electrical quantity data, state quantity data, environment data and demand data of each device to form multi-source data of the device; based on the collected multi-source data, independently instantiating a regularized energy agent with data processing and label generating capabilities for each device, and establishing a binding relation between physical devices and virtual agents; generating rules according to preset labels by each regularized energy agent, generating static semantic labels of inherent attributes of curing equipment, and updating dynamic state labels of running states in real time; And integrating all the regularized energy agents and corresponding labels to form a regularized energy agent set. Further, the manner in which the corresponding three-dimensional energy contract is constructed and broadcast in conjunction with the local behavior rule set includes: each regularized energy agent invokes self labels and presets a local behavior rule set, sequentially constructs terms of space dimension, time dimension and attribute dimension, forms a standardized three-dimensional energy contract, and synchronously broadcasts to the ready state distributed negotiation market. Further, the method for setting up the distributed negotiation market comprises the following steps: After the ready state distributed negotiation market receives the broadcasted three-dimensional energy co