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CN-121984135-A - Collaborative operation system for regional multi-micro-grid cluster

CN121984135ACN 121984135 ACN121984135 ACN 121984135ACN-121984135-A

Abstract

The invention discloses a collaborative operation system for regional multi-micro grid clusters, which relates to the technical field of power system dispatching and control and comprises an asynchronous perception fusion module, a prediction difference modeling module and a control and calculation module, wherein the asynchronous perception fusion module is used for carrying out asynchronous receiving and time axis reconstruction on operation state data reported by a plurality of micro grid nodes, determining a trust level based on a communication link state and data integrity, carrying out weighted combination according to the trust level in the same time window to form a unified state view, and the prediction difference modeling module is used for extracting state change characteristics among the micro grid nodes based on the state view, determining state offset information and historical change boundaries thereof and taking the state offset information and the historical change boundaries as numerical constraints of dispatching calculation. The system provided by the invention realizes time axis reconstruction on the basis of asynchronous data reception through the asynchronous perception fusion module, and dynamically evaluates the credibility level of each piece of data by combining the state of a communication link and the data integrity, so as to perform weighted fusion in a unified time window.

Inventors

  • TONG XIANG
  • ZHANG SHIHAO
  • ZHENG HAO

Assignees

  • 广州统力新能源有限公司

Dates

Publication Date
20260505
Application Date
20260409

Claims (9)

  1. 1. A regional multi-microgrid cluster-oriented co-operating system, comprising: the asynchronous perception fusion module is used for carrying out asynchronous receiving and time axis reconstruction on running state data reported by a plurality of micro grid nodes, determining a credibility level based on the state of a communication link and the data integrity, and carrying out weighting and merging according to the credibility level in the same time window to form a unified state view; the prediction difference modeling module extracts state change characteristics among the micro grid nodes based on the state view, determines state offset information and historical change boundaries thereof, and serves as numerical constraint of scheduling calculation; the tolerance scheduling calculation module is used for constructing a scheduling target based on the state view and the numerical constraint, executing joint scheduling calculation of the multiple micro grid nodes and generating a scheduling result meeting the offset condition; the response matching driving module is used for determining numerical value difference and adjusting a scheduling instruction according to the scheduling result and combining the response capability of the energy storage equipment so as to enable the scheduling instruction to meet the dynamic response requirement of the energy storage equipment; and the feedback correction module is used for collecting actual operation data of each micro-grid node after executing the scheduling instruction, comparing the actual operation data with the scheduling result, and correcting relevant processing rules or parameters in the asynchronous perception fusion module and the predictive difference modeling module according to the actual operation data.
  2. 2. The collaborative operation system for a regional multi-microgrid cluster according to claim 1, wherein the working steps of the asynchronous awareness fusion module include: Receiving running state data reported by a plurality of micro-grid nodes, and recording a time stamp carried by each piece of data and a corresponding node identifier; performing time axis reconstruction on asynchronously received running state data according to the time stamp, uniformly mapping all the data into the same global time reference axis, and constructing a standardized time window interval; Evaluating the delay condition of the communication link corresponding to each running state data and the integrity of the data field, and calculating the credibility level of the data based on a preset weight factor; And in the time window, weighting and combining the corresponding numerical values according to the credibility level of each running state data to generate a unified state view with dynamic difference reconciliation capability so as to improve the accuracy and adaptability of data fusion under the unstable condition of the link.
  3. 3. The collaborative operation system for a regional multi-micro grid cluster according to claim 2, wherein the asynchronous perceptual fusion module comprises the following steps when performing state data weighted fusion: Establishing a credible level mapping table of the running state data of a plurality of micro grid nodes, wherein the mapping table is generated by joint evaluation based on three indexes of communication delay, data packet retransmission times and data field integrity; aiming at running state data reported by a plurality of micro grid nodes in the same time window, using scores in a trusted class mapping table as weights, and executing numerical weighting calculation on similar state parameters; In the merging process, introducing an offset compensation factor based on a trusted level, and executing weight down-conversion and numerical value inhibition processing on data exceeding a set deviation threshold value with other data values in the same time window so as to reduce the duty ratio of abnormal state data in a weighted merging result; And generating a unified state view, and outputting a structured state set with credible level notes for a subsequent state modeling module for tolerance calculation and feedback closed-loop control of the scheduling system.
  4. 4. The regional multi-microgrid cluster-oriented co-operation system according to claim 1, wherein the predictive differential modeling module, when generating state offset information, comprises the steps of: Based on the unified state view output by the asynchronous perception fusion module, carrying out sliding scheduling period segmentation processing on the running state data of a plurality of micro grid nodes in a plurality of scheduling periods, and carrying out weighted sliding average operation on the running state parameters of the same type in each scheduling period to generate a state reference sequence of each micro grid node; In each scheduling period, performing difference operation on state reference sequences of different micro-grid nodes item by item to construct a state difference set between micro-grid node pairs; Dividing the state difference value in the state difference set into a plurality of continuous numerical value intervals, counting the occurrence frequency of the state difference value in each numerical value interval, marking the numerical value interval with the occurrence frequency higher than a preset frequency threshold as a first frequency interval, marking the rest numerical value intervals as a second frequency interval, assigning a first weighting factor to the state difference value in the first frequency interval, assigning a second weighting factor to the state difference value in the second frequency interval, applying the first weighting factor to the state difference value in the first frequency interval, applying the second weighting factor to the state difference value in the second frequency interval, and performing weighting processing on all the state difference values to generate a weighted state difference matrix; Performing time sequence expansion on the weighted state difference matrix along the dispatching cycle direction, calculating the change amplitude of the state difference values of the same micro grid node pairs in adjacent dispatching cycles, marking a state difference change section with the change amplitude higher than a set change rate threshold as a first change section, marking a state difference change section with the change amplitude not higher than the change rate threshold as a second change section, performing weighted accumulation operation on the state difference values in the first change section to generate a first accumulation result, and performing weighted accumulation operation on the state difference values in the second change section to generate a second accumulation result; Based on a preset fusion scale factor, the first accumulation result and the second accumulation result are linearly combined to generate a combined offset sequence, normalization processing is performed on the combined offset sequence, and the combined offset sequence is output as state offset information between micro grid nodes.
  5. 5. The regional multi-microgrid cluster-oriented co-operation system according to claim 4, wherein said predictive differential modeling module, when generating a historical change boundary of state offset information, comprises the steps of: acquiring state offset information in a plurality of continuous scheduling periods, and constructing a state offset evolution sequence according to a time sequence; Performing fixed span interval division processing on the state offset evolution sequence, namely dividing the numerical range of the state offset information into a plurality of continuous numerical intervals with equal intervals according to set numerical intervals, and respectively counting the occurrence frequency of the state offset information in each numerical interval; marking a numerical value interval with occurrence frequency higher than a preset minimum frequency threshold as a high-frequency interval, performing weighted moving average operation on state offset information in each high-frequency interval, and simultaneously calculating sample standard deviation in each interval; identifying a high-frequency section with a sample standard deviation lower than a preset standard deviation threshold as an offset stable section; And respectively extracting the maximum value and the minimum value of the state offset information in the offset stable section, taking the maximum value and the minimum value as an upper boundary and a lower boundary of the state offset information, taking the upper boundary and the lower boundary as numerical constraints, and writing the numerical constraints into a tolerance scheduling calculation module for limiting the value range of the micro-grid node scheduling variable.
  6. 6. The regional multi-microgrid cluster-oriented co-operation system according to claim 1, wherein the tolerance schedule calculation module, when generating a schedule result satisfying an offset condition, comprises: Determining a target power value of each micro grid node in a current dispatching cycle based on a state view output by an asynchronous perception fusion module, taking a history change boundary output by a prediction difference modeling module as an adjustable upper limit and an adjustable lower limit of power adjustment quantity of each micro grid node, and constructing an interval dispatching parameter structure based on the upper limit and the lower limit and the target power value in the state view to serve as numerical constraint in dispatching calculation; Converting the state offset information into a scheduling offset constraint item, wherein the scheduling offset constraint item is used for describing the allowable offset amplitude of each micro-grid node scheduling value relative to the corresponding node state in the state view, and taking the scheduling offset constraint item and the compartmentalized scheduling parameter structure together as constraint input of joint scheduling; Executing a multi-node joint scheduling solving process in a feasible region defined by an adjustable upper limit, an adjustable lower limit and a scheduling offset constraint item, taking a minimized global scheduling offset and node load matching error as a joint optimization target, and generating a group of candidate joint scheduling schemes meeting power balance constraint and energy storage equipment operation constraint; respectively calculating the corresponding global scheduling offset, node load matching error and power change rate in a scheduling period for the candidate joint scheduling scheme, and comprehensively evaluating and sequencing the three indexes based on preset evaluation weights; And selecting the candidate joint scheduling scheme with the optimal score from the sequencing results as a scheduling result meeting the offset condition, and outputting the scheduling result to a response matching driving module for execution.
  7. 7. The regional multi-microgrid cluster-oriented co-operating system of claim 6, wherein the offset conditions comprise: Constructing a scheduling offset constraint item based on the state offset information output by the prediction difference modeling module, wherein the scheduling offset constraint item is used for describing the deviation degree of each micro-grid node target scheduling value relative to the corresponding running state value in the unified state view; setting an adjustable upper limit and an adjustable lower limit of a scheduling variable for each micro-grid node based on a historical change boundary output by the prediction difference modeling module, and forming a boundary constraint item for limiting an absolute value range of a scheduling result; in the joint scheduling calculation process, a scheduling offset constraint item and a boundary constraint item are introduced simultaneously, and a relative offset limit and an absolute value range limit are applied to a scheduling result so as to generate the scheduling result meeting an offset condition.
  8. 8. The regional multi-microgrid cluster-oriented co-operation system according to claim 1, wherein the response matching driver module when adjusting the scheduling instructions to meet the dynamic response requirements of the energy storage devices comprises the steps of: collecting operation capacity parameters of a plurality of energy storage devices, wherein the operation capacity parameters comprise maximum charge and discharge power, charge and discharge rate, minimum response time delay and response lag time, and carrying out standardized processing on the parameters for representing the response capacity characteristics of the energy storage devices; The scheduling result output by the tolerance scheduling calculation module is compared with the response capability characteristic item by item, the difference quantity of each energy storage device in the aspects of power amplitude, response time and scheduling persistence is calculated, and a response difference set for describing the difference relation between the scheduling result and the response capability is formed; And according to the response difference set, performing power amplitude limiting adjustment, scheduling instruction time axis offset processing and scheduling duration compression or stretching operation according to the corresponding difference quantity for each energy storage device, and outputting a scheduling instruction meeting the dynamic response requirement of the energy storage device.
  9. 9. The regional multi-microgrid cluster-oriented co-operation system according to claim 1, wherein the feedback correction module, when correcting the processing rules or parameters in the asynchronous perceptual fusion module and the predictive differential modeling module, comprises the following steps: Acquiring actual running state data of each micro-grid node in a plurality of continuous scheduling periods, carrying out difference calculation on the actual running state data and corresponding scheduling results, and constructing a state deviation sequence; Based on the state deviation sequences and the communication quality indexes of the nodes, respectively executing moving average processing on the state deviation sequences of each node, dividing the processing result by the communication quality index value of the corresponding node, and then normalizing the processing results of all the nodes to construct an error correction factor vector; And simultaneously extracting the average value of the error correction factor vector, and respectively updating the cycle window width parameter of the sliding scheduling cycle process in the predictive difference modeling module and the minimum frequency threshold parameter for fixed span interval division by taking the average value as the correction factor so as to improve the precision of scheduling modeling and fusion analysis.

Description

Collaborative operation system for regional multi-micro-grid cluster Technical Field The invention relates to the technical field of power system dispatching and control, in particular to a cooperative operation system for regional multi-micro-grid clusters. Background With the continuous development of distributed energy technology and smart grid technology, the micro-grid is used as an independent energy system integrating transmission, distribution and use, plays an important role in regional energy supply, clean energy access, load response and the like, and gradually becomes an important component for constructing a novel power system for a multi-micro-grid cluster deployed in a larger geographic region, has the characteristics of complex topological structure, asynchronous running state, various communication links and the like, and realizes cooperative running and unified scheduling among a plurality of micro-grids under the background, thereby becoming an important target for improving the overall running efficiency and the system toughness; The existing micro-grid scheduling-oriented research is mostly focused on load optimization and energy management in a single micro-grid, and part of schemes are mainly based on synchronous assumption, but neglect time deviation and link fluctuation existing in operation state acquisition, in practical application, because of the problems of unstable communication, incomplete state data and the like, a system often cannot obtain reliable operation information of all nodes at a unified time point, so that a scheduling model input has deviation to influence scheduling precision and system stability, and therefore, how to realize reliable, dynamic and adjustable joint scheduling under the condition of asynchronous state perception forms an important challenge of the current technology; In order to solve the problems, a few fault tolerance scheduling methods based on asynchronous data fusion and dynamic adjustment are developed in recent years, the stability of a scheduling system is attempted to be improved by introducing a reliability evaluation, weighted fusion or feedback correction mechanism, the methods show good adaptability in specific scenes, but most of the methods still lack complete closed loop design from data perception, state modeling, scheduling solution to feedback correction, and active control and evolution management on scheduling offset are difficult to realize, so that the invention provides a collaborative operation system for a regional multi-micro-grid cluster. Disclosure of Invention The invention aims to provide a cooperative operation system for a regional multi-micro-grid cluster, which aims to solve the problems in the background art. The invention can be realized by the following technical scheme that the collaborative operation system for the regional multi-micro-grid cluster comprises: The asynchronous perception fusion module is used for asynchronously receiving the operation state data from the plurality of micro grid nodes, carrying out unified time axis reconstruction on the reporting time of each operation state data, determining a credible grade for each operation state data according to the state of a communication link and the data integrity, and carrying out weighted combination on the operation state data from different micro grid nodes in the same time window according to the credible grade to form a unified state view; The prediction difference modeling module extracts state change characteristics among the micro grid nodes based on the state view, determines state offset information among different micro grid nodes, determines upper and lower boundary ranges of state values based on historical state change trend, takes the state offset information and the upper and lower boundary ranges as adjustable value constraints in scheduling calculation, and limits the change range of scheduling variables of each micro grid node; The tolerance scheduling calculation module is used for constructing a scheduling target based on the state view, the state offset information and the upper and lower boundary ranges, executing joint scheduling calculation of the multi-micro grid nodes according to the defined numerical constraint, generating a scheduling result meeting the state numerical offset condition, and giving out a corresponding execution range of the scheduling result; The response matching driving module is used for determining the numerical value difference between the scheduling result and the response capability of the energy storage equipment according to the scheduling result and combining the operation parameters of the energy storage equipment, and adjusting the output time sequence and the power amplitude of the scheduling instruction according to the numerical value difference so that the adjusted scheduling instruction meets the dynamic response requirement of the energy storage equipment; The feedback correction modu