CN-122026388-A - Collaborative control method, system, equipment and storage medium for multi-micro-grid connection

CN122026388ACN 122026388 ACN122026388 ACN 122026388ACN-122026388-A

Abstract

The invention relates to the technical field of grid connection control, and discloses a cooperative control method, a system, equipment and a storage medium for grid connection of multiple micro-grids, which comprise the steps of acquiring multidimensional synchronous operation data of multiple micro-grid clusters and generating a real-time dynamic cluster energy flow map; according to the real-time dynamic cluster energy flow map, a multi-main-body non-cooperative game model is built, each micro-grid is used as a game main body, grid-connected power is used as a strategy space, cluster risk cost is minimized to be an objective function, the multi-main-body non-cooperative game model is solved to obtain a cooperative grid-connected power target instruction, grid-connected control time sequence is generated according to the cooperative grid-connected power target instruction, and each micro-grid is driven to execute active grid-connected operation under the grid-connected control time sequence, so that the cooperative grid connection of the multi-micro-grid cluster to the main network is realized. The invention can realize smooth and efficient collaborative grid connection and power distribution optimization of the multi-micro-grid cluster, and effectively improve the electric energy quality and operation safety of the power grid.

Inventors

YANG JIANYOU
HU CHANGHONG
LIN ZE
BAO CHENGDUN
Lin Guanou
RUAN ZONGREN
LIU JINYUAN
QU HEZUO
ZHU QIWEI
CHEN YANG
YANG JIAN
WANG QIANGHONG
CHEN MENGXIANG
HUANG CHAODONG
WANG YIXIN
ZHANG ZHESHEN
SUN JINGLIAO
XIANG YEJUN
XI HONGLEI
YU KAI

Assignees

国网浙江省电力有限公司温州供电公司
国网浙江省电力有限公司苍南县供电公司

Dates

Publication Date: 20260512
Application Date: 20260408

Claims (10)

1. The cooperative control method for the grid connection of the multiple micro-grids is characterized by comprising the following steps of: Acquiring multidimensional synchronous operation data of a multi-micro-grid cluster, acquiring an internal coupling relation and a power distribution state of the multi-micro-grid cluster according to the multidimensional synchronous operation data, and generating a real-time dynamic cluster energy flow map; According to the real-time dynamic cluster energy flow map, a multi-main-body non-cooperative game model is established, each micro-grid is used as a game main body in the multi-main-body non-cooperative game model, grid-connected power is used as a strategy space in each game main body, and cluster risk cost is minimized as an objective function; solving the multi-main-body non-cooperative game model to obtain a cooperative grid-connected power target instruction; Generating a grid-connected control time sequence according to the cooperative grid-connected power target instruction, and driving each micro-grid to execute active grid-connected operation under the grid-connected control time sequence so as to realize cooperative grid connection of the multi-micro-grid cluster to the main network.
2. The collaborative control method for multi-micro grid integration according to claim 1, wherein the step of obtaining the internal coupling relation and the power distribution state of the multi-micro grid cluster according to the multi-dimensional synchronous operation data and generating a real-time dynamic cluster energy flow map comprises the steps of: performing alignment processing on the multidimensional synchronous operation data based on the high-precision clock signal to generate a synchronous data stream; extracting the real-time power state of each micro-grid and the connection relation between the micro-grids from the synchronous data stream to generate basic data of nodes and edges; Constructing a graph model which takes a micro-grid as a node and a power exchange path as an edge according to the basic data of the node and the edge; And dynamically updating node attributes and edge weights in the graph model according to the real-time power state to generate a real-time dynamic cluster energy flow graph.
3. The collaborative control method for multi-microgrid grid-connected according to claim 1, wherein the step of establishing a multi-subject non-collaborative gaming model according to the real-time dynamic cluster energy flow map comprises: Taking each micro-grid in the real-time dynamic cluster energy flow map as a game main body, and taking grid-connected power as a strategy space of each game main body, wherein the grid-connected power comprises grid-connected active power and grid-connected reactive power; Taking the total grid-connected risk cost under a specific strategy as a cluster risk cost, and constructing an objective function of each game main body with the minimum of the cluster risk cost, wherein the cluster risk cost comprises a cluster penalty cost, a control effort cost and an energy utilization efficiency item; The cluster punishment cost is obtained by carrying out safety evaluation on power grid operation under different strategy combinations through a global topological view provided by the real-time dynamic cluster energy flow graph spectrum, the control effort cost is obtained by calculating physical stress generated by responding to a grid-connected instruction by internal resources of the micro-grid, and the energy utilization efficiency item is obtained by calculating the absorption degree of the micro-grid to distributed energy sources.
4. The collaborative control method for multi-microgrid grid-tie according to claim 1, wherein the step of generating a grid-tie control sequence according to the collaborative grid-tie power target instruction comprises: driving each micro-grid to perform power pre-adjustment according to the collaborative grid-connected power target instruction, and generating a to-be-grid-connected station state; According to the real-time dynamic cluster energy flow map, an optimal synchronization window meeting the voltage, frequency and phase angle synchronization conditions is identified; and generating a closing instruction of the grid-connected switch in the optimal synchronization window, and forming a grid-connected control time sequence together with the state of the station to be grid-connected.
5. The cooperative control method of multi-microgrid grid connection according to claim 3, further comprising, after the step of executing an active grid connection operation under a grid connection control timing for the and driving each of the microgrids: Transient data in the grid-connected operation process are collected, and the execution deviation of each micro-grid to the collaborative grid-connected power target instruction is estimated; generating control execution trust of each micro-grid according to the execution deviation; taking the control execution trust degree as a feedback parameter, and dynamically correcting the cluster risk cost of the multi-main-body non-cooperative game model at the current moment; And generating an objective function of the multi-subject non-cooperative game model at the next moment according to the corrected cluster risk cost.
6. The collaborative control method for multi-microgrid grid connection according to claim 5, wherein the step of generating control execution trust for each microgrid according to the execution bias comprises: comparing the execution deviation of each micro-grid with a preset power deviation threshold value, and performing piecewise nonlinear mapping on the execution deviation according to a comparison result to obtain a trust degree score at the current moment; and carrying out weighted summation on the trust degree score at the current moment and the control execution trust degree at the previous moment to obtain the control execution trust degree at the current moment.
7. The collaborative control method for multi-microgrid grid-connected according to claim 5, wherein the step of dynamically correcting cluster risk costs in a multi-subject non-cooperative game model using the control execution confidence as a feedback parameter comprises: according to the control execution trust degree, adjusting a weight coefficient of cluster punishment cost in the cluster risk cost of each micro-grid, and generating a dynamic feedback additional risk item; And merging the dynamic feedback additional risk items to the cluster risk cost with the adjusted weight coefficient to obtain corrected cluster risk cost.
8. A coordinated control system for grid-tie of multiple micro-grids, comprising: The energy flow graph spectrum construction module is used for acquiring multidimensional synchronous operation data of the multi-micro grid cluster, obtaining an internal coupling relation and a power distribution state of the multi-micro grid cluster according to the multidimensional synchronous operation data, and generating a real-time dynamic cluster energy flow graph; The game model building module is used for building a multi-main-body non-cooperative game model according to the real-time dynamic cluster energy flow map, wherein each micro-grid is used as a game main body in the multi-main-body non-cooperative game model, grid-connected power is used as a strategy space in each game main body, and cluster risk cost is minimized as an objective function; The grid-connected instruction generation module is used for solving the multi-main-body non-cooperative game model to obtain a cooperative grid-connected power target instruction; And the grid-connected instruction execution module is used for generating a grid-connected control time sequence according to the cooperative grid-connected power target instruction and driving each micro-grid to execute active grid-connected operation under the grid-connected control time sequence so as to realize cooperative grid connection of the multi-micro-grid clusters to the main network.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.

Description

Collaborative control method, system, equipment and storage medium for multi-micro-grid connection Technical Field The invention relates to the technical field of grid connection control, in particular to a cooperative control method, a system, equipment and a storage medium for multi-micro grid connection. Background The micro-grid is a small power generation and distribution system consisting of a distributed power supply, an energy storage device, an energy conversion device, a load, a monitoring and protecting device and the like, and is an important component of the intelligent grid. With the widespread access of distributed energy sources, a multi-microgrid cluster consisting of a plurality of geographically adjacent microgrids interconnected has become a common grid modality. How to realize safe and efficient collaborative grid connection between a multi-micro-grid cluster and a main grid is an important subject faced by the current grid control field. In the prior art, a control method for grid connection of multiple micro-grids is mainly divided into centralized control and distributed control. Centralized control typically relies on a central controller to collect all microgrid information and make a unified decision, while enabling global optimization, high requirements for communication and single point failure risk. And the distributed control is used for downloading decision weights to all the micro-grids, and all the micro-grids carry out autonomous decision according to local information and limited neighbor communication, so that the flexibility is improved, but the globally optimal control effect is difficult to achieve. Disclosure of Invention In order to solve the technical problems, the invention provides a cooperative control method, a system, equipment and a storage medium for multi-micro grid connection, which can realize smooth and efficient cooperative grid connection and power distribution optimization of a multi-micro grid cluster, thereby improving the safety and stability of grid operation. In a first aspect, the present invention provides a coordinated control method for grid connection of multiple micro-grids, where the method includes: Acquiring multidimensional synchronous operation data of a multi-micro-grid cluster, acquiring an internal coupling relation and a power distribution state of the multi-micro-grid cluster according to the multidimensional synchronous operation data, and generating a real-time dynamic cluster energy flow map; According to the real-time dynamic cluster energy flow map, a multi-main-body non-cooperative game model is established, each micro-grid is used as a game main body in the multi-main-body non-cooperative game model, grid-connected power is used as a strategy space in each game main body, and cluster risk cost is minimized as an objective function; solving the multi-main-body non-cooperative game model to obtain a cooperative grid-connected power target instruction; Generating a grid-connected control time sequence according to the cooperative grid-connected power target instruction, and driving each micro-grid to execute active grid-connected operation under the grid-connected control time sequence so as to realize cooperative grid connection of the multi-micro-grid cluster to the main network. Further, the step of obtaining the internal coupling relation and the power distribution state of the multi-micro grid cluster according to the multi-dimensional synchronous operation data and generating the real-time dynamic cluster energy flow map comprises the following steps: performing alignment processing on the multidimensional synchronous operation data based on the high-precision clock signal to generate a synchronous data stream; extracting the real-time power state of each micro-grid and the connection relation between the micro-grids from the synchronous data stream to generate basic data of nodes and edges; Constructing a graph model which takes a micro-grid as a node and a power exchange path as an edge according to the basic data of the node and the edge; And dynamically updating node attributes and edge weights in the graph model according to the real-time power state to generate a real-time dynamic cluster energy flow graph. Further, the step of establishing a multi-main-body non-cooperative game model according to the real-time dynamic cluster energy flow map comprises the following steps: Taking each micro-grid in the real-time dynamic cluster energy flow map as a game main body, and taking grid-connected power as a strategy space of each game main body, wherein the grid-connected power comprises grid-connected active power and grid-connected reactive power; Taking the total grid-connected risk cost under a specific strategy as a cluster risk cost, and constructing an objective function of each game main body with the minimum of the cluster risk cost, wherein the cluster risk cost comprises a cluster penalty cost, a control effort