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CN-122026627-A - Automatic micro-energy network reconstruction and energy supply stable control system

CN122026627ACN 122026627 ACN122026627 ACN 122026627ACN-122026627-A

Abstract

The invention relates to an automatic micro-energy network reconstruction and energy supply stable control system which comprises a multi-dimensional situation sensing module, a dynamic topology reconstruction module, a stability prediction module and a multi-mode stability evaluation module, wherein the multi-dimensional situation sensing module is used for collecting running state data, environment prediction data and grid-connected point interaction data of all nodes in a micro-energy network in real time, the dynamic topology reconstruction module is used for constructing a dynamic edge weight map for representing energy interaction potential among the nodes based on the running state data and generating a plurality of candidate reconstruction topologies by carrying out community discovery clustering on the dynamic edge weight map, and the stability prediction module is used for constructing a multi-mode stability evaluation model according to the environment prediction data, the grid-connected point interaction data and the candidate reconstruction topologies, and outputting a power angle stability margin and a frequency safety margin of each candidate reconstruction topology in a preset prediction time domain.

Inventors

  • ZHU YUEYANG

Assignees

  • 辰鳗科技集团有限公司

Dates

Publication Date
20260512
Application Date
20260414

Claims (9)

  1. 1. An automated micro-grid reconstruction and energy stabilization control system, comprising: The multidimensional situation awareness module is used for acquiring running state data, environment prediction data and grid-connected point interaction data of each node in the micro energy network in real time; the dynamic topology reconstruction module is used for constructing a dynamic edge weight map representing energy interaction potential among nodes based on the running state data, and generating a plurality of candidate reconstruction topologies by performing community discovery and clustering on the dynamic edge weight map; the stability prediction module is used for constructing a multi-mode stability evaluation model according to the environment prediction data, the grid-connected point interaction data and the candidate reconstruction topologies, and outputting a power angle stability margin and a frequency safety margin of each candidate reconstruction topology in a preset prediction time domain by the multi-mode stability evaluation model; The collaborative optimization decision module is used for constructing a mixed integer nonlinear programming model which takes the minimum comprehensive operation cost of the system as a target and takes the power angle stability margin and the frequency safety margin as dynamic constraints, and solving to obtain an optimal reconstruction topology and a corresponding reconstruction execution time sequence; the flexible reconfiguration execution module is used for controlling the cooperative action of the solid-state switch and the power electronic transformer according to the reconfiguration execution time sequence and switching the current topology to the optimal reconfiguration topology; and the layered stability control adjusting module is used for carrying out multi-time scale power redistribution by dynamically adjusting virtual inertia and damping coefficient of the virtual synchronous machine based on the electric quantity deviation monitored in real time in the topology reconstruction process.
  2. 2. The automated micro energy network reconfiguration and energy stabilization control system of claim 1, wherein the dynamic topology reconfiguration module comprises: the edge weight dynamic calculation unit is used for acquiring node voltage amplitude values, phase angle differences and line transmission power in the running state data and constructing a dynamic edge weight map; in the dynamic edge weight map, the dynamic edge weight between two nodes is obtained by processing first data, wherein the first data comprises an inter-node power transmission potential index, an inter-node electrical distance and a real-time load rate of a feeder line to which the nodes belong.
  3. 3. The automated micro energy grid reconstruction and energy stabilization control system of claim 2, wherein the stability prediction module comprises: The multi-mode stability evaluation unit is used for constructing a state space equation for each candidate reconstruction topology, taking an illumination intensity prediction sequence and a wind speed prediction sequence in environment prediction data as disturbance input quantity, and acquiring a power angle rocking curve and a frequency response curve of the system when encountering the maximum probability disturbance through time domain simulation; The power angle stability margin is obtained by carrying out numerical integration processing on a power angle rocking curve, and specifically comprises the steps of obtaining a power angle difference of a synchronous generator set relative to the center of inertia of a system, taking a difference value of a virtual internal potential phase of a grid-built converter relative to the center of inertia of the system as an equivalent power angle, integrating absolute values of the power angle differences of various power supplies within a preset time window, and taking the reciprocal of an integration result as the power angle stability margin; The frequency safety margin is obtained by carrying out extremum searching and time positioning processing on a frequency response curve, specifically, obtaining the absolute value of the deviation between the lowest point of the system frequency and the rated frequency and the adjustment time required by the frequency to be restored to the preset safety boundary from the disturbance occurrence time, and obtaining the frequency safety margin by taking the reciprocal after carrying out weighted summation on the absolute value of the deviation and the adjustment time.
  4. 4. The automated micro-grid reconstruction and energy stabilization control system of claim 3, wherein the collaborative optimization decision-making module comprises: The dynamic constraint conversion unit is used for constructing a mixed integer nonlinear programming model aiming at minimizing the comprehensive running cost of the system, and an objective function of the mixed integer nonlinear programming model comprises the power generation cost of each distributed power supply, the switching action cost of each connecting wire and a punishment item reflecting the satisfaction degree of the stability constraint; the mixed integer nonlinear programming solving unit is used for solving the mixed integer nonlinear programming model based on a mixed solving strategy combining a branch-and-bound method and an interior point method and outputting an optimal reconstruction topology and a binary time sequence matrix representing the action sequence of each solid switch; The objective function of the mixed integer nonlinear programming model is obtained by processing third data, and the third data comprises the power generation cost of each distributed power supply, the switching action cost of each connecting line, and soft constraint penalty terms of the power angle stability margin and the frequency safety margin.
  5. 5. The automated micro-grid reconstruction and energy stabilization control system of claim 4, wherein the flexible reconstruction execution module comprises: The transient process smoothing unit is used for identifying a critical switching sequence needing to be subjected to switching-on and switching-off operation in the reconstruction execution time sequence; Before executing the switching-off operation, the transient process smoothing unit is configured to send a feedforward compensation signal to the layered stability control adjustment module, wherein the feedforward compensation signal is used for instructing the layered stability control adjustment module to increase virtual inertia of a distributed power supply connected with a feeder line to be switched off in advance so as to inhibit power impact at the moment of switching-off; the virtual inertia increment in the feedforward compensation signal is obtained by processing fourth data, wherein the fourth data comprises the current transmission power of a feeder line to be disconnected, the equivalent inertia of the system and the preset execution time of the disconnection operation; The equivalent inertia of the system is obtained by weighting calculation according to inertia constants and rated capacity of each distributed power supply in the running state data; The virtual inertia increment is used for providing additional inertia support at the moment of disconnection to balance the power shortage, and the calculation process is deduced based on the power balance principle.
  6. 6. The automated micro-grid reconstruction and energy stabilization control system of claim 5, wherein the layered stability control adjustment module comprises: a primary adjustment unit for responding to instantaneous deviation of the system frequency and the voltage in a millisecond time scale based on droop control; the secondary adjusting unit is used for adjusting the active power set values of the distributed power supplies in a second time scale based on model predictive control so as to eliminate steady-state deviation after primary adjustment; The parameter dynamic adapting unit is respectively connected with the primary adjusting unit and the secondary adjusting unit, and is used for receiving the optimal reconstruction topology output by the collaborative optimization decision-making module, dynamically adjusting the sagging coefficient in the primary adjusting unit and the predicted time domain length in the secondary adjusting unit according to the access node position and the residual capacity of each distributed power supply in the optimal reconstruction topology, and the access node position is represented by the bus node number connected with the distributed power supply in the micro energy network topology; The parameter dynamic adapting unit is further used for presetting basic inertia values of the grid-formed converters and synchronization coefficients of the virtual synchronous machines, wherein the basic inertia values are initial virtual inertia set values of the grid-formed converters when dynamic adjustment is not performed, the basic inertia values are preset according to system capacity grades and voltage grades of the micro energy networks or are determined according to the functional positioning of the converters in the micro energy networks in a preset proportion range, the synchronization coefficients of the virtual synchronous machines are parameters representing synchronization capability between the virtual synchronous machines and a power grid, and the synchronization coefficients are obtained by multiplying the ratio of short circuit capacity of grid connection points of the converters to rated capacity of the system by rated angular frequency of the system.
  7. 7. The automated micro energy grid reconstruction and energy stabilization control system of claim 6, wherein the parameter dynamic adaptation unit comprises: The virtual inertia cooperative configuration subunit is used for carrying out online setting on the virtual inertia of each distributed power supply through a virtual synchronous machine control algorithm of the grid-built converter according to the equivalent inertia level of the system under the optimal reconstruction topology; The virtual inertia of the grid-built converter is obtained by processing second data, wherein the second data comprises rated capacity of the converter, electric distance from a converter node to a disturbance center node under optimal reconstruction topology and real-time frequency change rate of a system; The electrical distance is obtained by calculating the equivalent impedance modulus between the converter node and the disturbance center node.
  8. 8. The automated micro energy grid reconstruction and energy stabilization control system of claim 7, wherein the parameter dynamic adaptation unit further comprises: The damping coefficient dynamic setting subunit is used for cooperating with the virtual inertia cooperative configuration subunit to set the damping coefficient of each grid-built converter in real time based on the system damping ratio requirement under the optimal reconstruction topology; the damping coefficient of the grid-built converter is obtained by processing fifth data, wherein the fifth data comprises the virtual inertia currently set by the converter, the expected damping ratio of the system and the equivalent electrical distance from the node of the converter to the power fluctuation center of the system; The expected damping ratio of the system is preset according to the running mode of the micro energy network, wherein the preset value in the grid-connected running mode is lower than the preset value in the island running mode, so that the damping demand difference between the main network support and the autonomous regulation in island during grid connection is reflected; the system power fluctuation center calculates the absolute value of the active power change rate of each node in real time, and selects the node with the largest change rate absolute value for determination; The equivalent electrical distance is obtained by calculating an equivalent impedance modulus between the converter node and the center of the system power fluctuation.
  9. 9. The system for reconstructing and stabilizing energy supply of an automatic micro-energy network according to claim 8, wherein a closed loop feedback structure is formed between the collaborative optimization decision-making module and the layered stability control adjusting module; The collaborative optimization decision module is also used for sending the network parameters corresponding to the optimal reconstruction topology to the parameter dynamic adaptation unit of the layered stability control adjustment module after the flexible reconstruction execution module completes the topology switching; The layered stability control adjusting module is further used for feeding back the real-time adjustable capacity upper limit of each distributed power supply and the updated system equivalent inertia and equivalent damping ratio to the collaborative optimization decision module after the collaborative configuration of the virtual inertia and the damping coefficient is completed so as to update the initial state and the constraint boundary of the next round of reconstruction decision and form a reconstruction-control collaborative rolling optimization mechanism; in the constraint boundary of the next round of reconstruction decision, a power angle stability margin threshold and a frequency safety margin threshold are respectively obtained by processing sixth data, wherein the sixth data comprises equivalent inertia, equivalent damping ratio and disturbance intensity index in a prediction time domain of current round feedback; The disturbance intensity index is obtained by carrying out variance normalization processing on an illumination intensity prediction sequence and a wind speed prediction sequence in environment prediction data; The calculation process of the power angle stability margin threshold and the frequency safety margin threshold adopts a saturated power function form to ensure that the threshold is kept in a preset reasonable interval, and the reasonable interval is preset according to the micro-energy network stable operation regulation.

Description

Automatic micro-energy network reconstruction and energy supply stable control system Technical Field The invention relates to the field of control systems, in particular to an automatic micro-energy network reconstruction and energy supply stable control system. Background The micro energy network is used as an important carrier for large-scale utilization of distributed energy, a synchronous generator set, a network-structured converter and other power supply types and power electronic equipment are integrated, the micro energy network plays a key role in new energy consumption and energy cascade utilization, but is influenced by environmental disturbance, dynamic change of working conditions and self equipment characteristics in actual operation, and topology reconstruction and energy supply stable control face a plurality of technical problems, so that the technical background is formed; the stability of the micro energy network is predicted without fully considering different operation characteristics of a synchronous generator set and a grid-built converter, environmental disturbance such as illumination, wind speed and the like is not brought into an evaluation system, a quantitative margin calculation method is lacked in stability indexes, evaluation results are not accurate, reliable stability constraint basis is difficult to provide for reconstruction decisions, the reconstruction optimization decision of the micro energy network is often single to pursue operation economy or stability, the cooperative balance of the two is not realized, a rigid processing mode is mainly adopted for the stability constraint, the suitability of solving strategies is poor, meanwhile, accurate reconstruction execution time sequence design is lacked, the engineering executable of decision results is low, the power impact is easily caused by the on-off operation in the topological reconstruction execution process, effective smoothing measures are lacked in the transient process, the continuity and the safety of the energy supply of the micro energy network are easily influenced by large fluctuation of electric quantity, a fixed parameter adjustment mode is mainly adopted in the stability control of the micro energy network, a multi-time scale adjustment system is not constructed, and virtual inertia is realized, in addition, the topology reconstruction decision and the stable control link of the existing micro energy network are in an open-loop running mode, data intercommunication and closed-loop feedback are absent between the topology reconstruction decision and the stable control link, a rolling optimization mechanism is absent, the stable constraint threshold is mostly static preset, dynamic adjustment cannot be carried out according to the real-time inertia, the damping characteristic and the environmental disturbance intensity of the system, the self-adaption capacity and the robustness of the system to the working condition change are poor, the whole flow collaborative optimization of the reconstruction decision and the stable control is difficult to realize, the economical efficiency, the stability and the automation level of the integral operation of the micro energy network are insufficient, and the energy supply stable control requirement under the complex working condition cannot be met. Disclosure of Invention Aiming at the defects in the prior art, the invention provides an automatic micro-energy network reconstruction and energy supply stable control system, which comprises the following components: The multidimensional situation awareness module is used for acquiring running state data, environment prediction data and grid-connected point interaction data of each node in the micro energy network in real time; the dynamic topology reconstruction module is connected with the multidimensional situation awareness module and is used for constructing a dynamic edge weight map for representing energy interaction potential among nodes based on the running state data, and generating a plurality of candidate reconstruction topologies by carrying out community discovery and clustering on the dynamic edge weight map; The stability prediction module is respectively connected with the multidimensional situation awareness module and the dynamic topology reconstruction module and is used for constructing a multi-mode stability assessment model according to environment prediction data, grid-connected point interaction data and candidate reconstruction topologies, and outputting a power angle stability margin and a frequency safety margin of each candidate reconstruction topology in a preset prediction time domain by the multi-mode stability assessment model; The flexible reconfiguration execution module is connected with the collaborative optimization decision module and is used for controlling the collaborative action of the solid-state switch and the power electronic transformer according to the reconfiguration execu