CN-122026532-A - Hierarchical zoning multisource collaborative adaptive optimization management and control method, system, equipment and medium for flexible power distribution network

CN122026532ACN 122026532 ACN122026532 ACN 122026532ACN-122026532-A

Abstract

The invention discloses a layered partition multi-source collaborative self-adaptive optimization management and control method, a system, equipment and a medium of a flexible power distribution network, which belong to the technical field of operation and control of power systems and comprise the steps of dynamically generating and reconstructing an elastic autonomous region based on real-time electric coupling degree, establishing a bidirectional constraint interaction mechanism between daily and real-time rolling optimization layers, introducing prospective equipment action cost, realizing autonomous power distribution of equipment in the region by adopting a distributed collaborative algorithm based on self-adaptive virtual impedance, screening high-reliability user side resources through multidimensional credit evaluation and differential excitation, and generating a robust scheduling plan by adopting hybrid modeling and two-stage random optimization. The invention solves the problem of cooperative control of the strong uncertainty of the source load and the double sides of the power distribution network under the access of high-proportion new energy, realizes the transition from passive response to active prevention and from centralized control to distributed cooperation, and effectively improves the digestion capability, operation safety and economy of the power distribution network.

Inventors

PAN SHUCHANG
YAN YANYAN
Ji jiao
LU JIAMIN
LI HUIHUA
BAI XUE
YANG QIHONG

Assignees

上海浦源科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. A layered partition multi-source collaborative self-adaptive optimization management and control method for a flexible power distribution network is characterized by comprising the following steps of, Based on real-time measurement data, dynamically calculating the electric coupling strength among the nodes of the power distribution network, generating an elastic autonomous area, and determining a control boundary; establishing a decision mechanism of rolling optimization in the elastic autonomous region, and generating a collaborative optimization instruction of a full time scale; The collaborative optimization instruction is subjected to power distribution and execution on the equipment side through a distributed collaborative algorithm; screening a high-user polymer in the collaborative optimization instruction through an interaction mechanism and issuing a differential excitation strategy; and in the rolling optimization decision mechanism, performing mixed modeling of uncertainty decisions to generate a management and control plan.
2. The method for hierarchical zoning multisource collaborative adaptive optimization management and control of a flexible power distribution network according to claim 1, wherein the generating an elastic autonomous region comprises: Collecting whole network real-time data at all nodes of a power distribution network, calculating a sensitivity matrix of voltage of each node to injection power, traversing all nodes, and generating a whole network electric coupling degree matrix at the current moment; Dividing an initial elastic autonomous area which is currently effective, and obtaining the actual net power of all distributed power supplies in the area; and when the absolute value of the real-time net power fluctuation value of any area is continuously smaller than a preset threshold value, judging that all area monitoring is stable, and keeping the existing subarea.
3. The method for hierarchical zoning multisource collaborative adaptive optimization management and control of a flexible power distribution network according to claim 2, wherein the generating an elastic autonomous region further comprises: When the absolute value of the real-time net power fluctuation value of any region is larger than or equal to a preset threshold value, judging that the current region triggers reconstruction; Selecting a node with the largest net power fluctuation contribution in a trigger reconstruction area, and aggregating nodes with the electric coupling degree higher than a set strong coupling threshold value based on the whole network electric coupling degree matrix to form a new node set; and carrying out safety verification on the new node set, and when the verification passes, generating a new elastic autonomous area and updating the whole-network logic control partition map and the area attribute information.
4. A flexible distribution network layered partition multisource collaborative adaptive optimization management and control method according to claim 3, wherein the generating collaborative optimization instructions in full time scale comprises: establishing a real-time control layer, wherein the aim is to minimize the total running cost of the system; the intra-day optimization layer outputs a resource scheduling plan to the real-time control layer; and the real-time control layer performs rolling optimization based on the daily optimization layer output plan and outputs a collaborative optimization instruction of the equipment side.
5. The method for hierarchical zoning multisource collaborative adaptive optimization management and control of a flexible power distribution network according to claim 4, wherein the power distribution and execution performed by the equipment side comprises the following steps: receiving the collaborative optimization instruction by a device side positioned in the same elastic autonomous region; Calculating a self-adaptive virtual impedance value based on a real-time adjustable power range and a health state of the equipment side; the equipment side exchanges self-proposed power allocation rate information with the corresponding communication neighbor, and iteratively updates self-power allocation rate by combining the corresponding self-adaptive virtual impedance value; and after the iteration process is converged, calculating the power adjustment quantity which is required to be executed according to the finally determined power distribution rate, and feeding back the executed state to the real-time control layer.
6. The method for hierarchical zoning multisource collaborative adaptive optimization management and control of a flexible power distribution network according to claim 5, wherein the steps of screening high-user polymers and issuing differentiated excitation strategies comprise: generating an interactive offer according to the load regulation requirement generated by the optimization decision, and distributing the interactive offer to a user side resource aggregator; Receiving the adjustment capacity and the expected price declared by the aggregator, calling the dynamic credit file of the aggregator, and dividing the credit level of the aggregator in response to the performance data in the dynamic credit file; Screening the aggregators according to the order of the credit level from high to low and the declared price from low to high in the same level until the accumulated capacity meets the load regulation requirement; setting incentive coefficients for aggregators with different credit levels, determining settlement unit price based on the incentive coefficients and the declared prices, and issuing a final dispatching instruction to the selected aggregators.
7. The method for hierarchical zoning multisource collaborative adaptive optimization management and control of a flexible power distribution network according to claim 6, wherein the generating a management and control plan comprises: extracting credit file data of a user side resource aggregator, mapping the credit file data into an adjustment coefficient, and decomposing adjustment capacity declared by the aggregator into trusted capacity and uncertain capacity; Performing two-stage decision random optimization including a first-stage decision and a second-stage decision; And in a second stage of the two-stage decision random optimization, taking the minimum expected total cost as an objective function, setting constraint conditions, solving the objective function of the second stage, and outputting a robustness management and control plan.
8. The flexible power distribution network layered partition multi-source collaborative self-adaptive optimization management and control system is applied to the flexible power distribution network layered partition multi-source collaborative self-adaptive optimization management and control method according to any one of claims 1-7, and is characterized by comprising a boundary determination module, an instruction generation module, a device side execution module, a user side execution module and a management and control module; The boundary determining module dynamically calculates the electric coupling strength among the nodes of the power distribution network based on real-time measurement data, generates an elastic autonomous area and determines a control boundary; The instruction generation module establishes a rolling optimization decision mechanism in the elastic autonomous region to generate a collaborative optimization instruction of full time scale; The device side execution module distributes and executes the power of the collaborative optimization instruction on the device side through a distributed collaborative algorithm; The user side execution module screens the high user polymer through an interaction mechanism by the collaborative optimization instruction and issues a differential excitation strategy; and the control module performs mixed modeling of uncertainty decision in the rolling optimization decision mechanism to generate a control plan.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of a flexible distribution network layered partition multisource collaborative adaptive optimization management and control method according to any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of a flexible distribution network hierarchical zoning multisource collaborative adaptive optimization management and control method according to any of claims 1 to 7.

Description

Hierarchical zoning multisource collaborative adaptive optimization management and control method, system, equipment and medium for flexible power distribution network Technical Field The invention relates to the technical field of operation and control of power systems, in particular to a hierarchical zoning multi-source collaborative self-adaptive optimization management and control method, system, equipment and medium for a flexible power distribution network. Background Along with the continuous rising of the permeability of distributed energy sources, flexible loads and energy storage equipment in a power distribution network, look back to technology development paths, early focuses are mainly focused on grid connection and maximum power tracking of a single distributed power supply, and later, a centralized distribution network management system is taken as a core, and overall economy and safety are attempted to be comprehensively achieved by constructing a complex mathematical optimization model. In recent years, to cope with computation and communication pressure caused by mass device access, hierarchical and partitioned collaborative architecture forms a main research flow, such as a multi-agent system, a virtual power plant aggregation technology, and a "cloud-side-end" collaborative computing framework. Meanwhile, methods capable of rolling process uncertainties such as model predictive control are also widely introduced. It can be said that the technical exploration of the layer-by-layer progression jointly constructs the foundation stone for the optimal control of the current flexible power distribution network, and the goal is to improve the economical efficiency, the toughness and the new energy consumption capability. However, when the prior art framework is put into a practical high dynamic, high uncertainty environment for inspection, a troublesome problem is found. First, there is a conflict between partition stiffness and run dynamics. Most of the existing partitioning methods are based on static topology or historical data, once the power of the source fluctuates severely in a certain area, the fixed boundary cannot be adjusted in time, local instability and diffusion are easy to cause, and finally the local instability and the local instability are forced to be undermined by an upper layer system, so that the cost is high. Furthermore, it is a disjoint of different time scale optimization decisions. The instructions are always issued layer by layer in one direction in the traditional day-real-time scheduling. When the daily optimization layer is planning, the latest accurate running state feedback of the real-time layer can not be obtained, only a conservative constraint condition can be adopted, and in order to quickly track the target, the real-time layer possibly ignores the accumulated loss caused by frequent actions of the equipment, buries hidden danger of shortening the service life of the equipment, and further, how to enable mass distributed equipment to work cooperatively. The centralized optimization calculation is heavy in burden, and the simple distributed peer-to-peer coordination does not consider the difference of the adjustment capability and the health state among the devices, so that the result is either unreasonable or unreasonable. Therefore, the key point of cracking the current bottleneck and releasing the full potential of the flexible power distribution network is realized by a set of self-adaptive collaborative management and control method which can dynamically reconstruct the autonomous region, optimize the inter-layer bidirectional nourishing, give consideration to the equipment difference and the health state and accurately excite the users based on the credit. Disclosure of Invention The present invention has been made in view of the above-described problems. Therefore, the invention aims to solve the problems of low operation efficiency, high safety risk, difficult coordination and the like caused by strong uncertainty of source load and load on two sides, complex and changeable network power flow, mass and scattered control objects when the traditional operation control method of the power distribution network is faced to the access of a high-proportion distributed power supply and a flexible load. In order to solve the technical problems, the invention provides a layered partition multi-source collaborative self-adaptive optimization management and control method of a flexible power distribution network, which comprises the following steps of, The method comprises the steps of dynamically calculating electric coupling strength among nodes of a power distribution network based on real-time measurement data, generating an elastic autonomous region, determining a control boundary, establishing a rolling optimization decision mechanism in the elastic autonomous region, generating a collaborative optimization instruction of a full time scale, distributing a