CN-122026419-A - Digital twinning-based power voltage simulation and adjustment method and system

CN122026419ACN 122026419 ACN122026419 ACN 122026419ACN-122026419-A

Abstract

The invention relates to the technical field of digital twin simulation, in particular to a power voltage simulation and adjustment method and system based on digital twin, which comprises the following steps: the method comprises the steps of collecting power node operation data to construct a real-time voltage state vector, generating a dynamic impedance coupling matrix based on a node topological relation, inputting a virtual load disturbance sequence into the matrix to calculate a virtual voltage response track, and generating a reactive compensation instruction based on Euclidean distance deviation of the track and a standard curve. According to the invention, by constructing the dynamic impedance coupling matrix, the nonlinear time-varying characteristic of the power grid topology is accurately mapped, the problem of the traditional static model parameter updating hysteresis is solved, and by calculating the virtual voltage response track and generating the reactive compensation instruction, the advanced prediction and accurate adjustment of the voltage fluctuation are realized, the interference of complex load change on the power grid stability is effectively eliminated, and the voltage quality and the operation reliability of the power system are obviously improved.

Inventors

JIANG JUN
ZHAN YE
ZHENG PEI
LIU RUOHAN
Mu Derong
ZHU MING
ZHANG SONGWEI
Ke Yizhu

Assignees

云南八冶新能源科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260416

Claims (10)

1. The power voltage simulation and adjustment method based on digital twinning is characterized by comprising the following steps of: s1, acquiring voltage amplitude and phase data through synchronous phasor measurement devices distributed on key nodes of a power grid, mapping the voltage amplitude and phase data to a Hilbert space, constructing a real-time voltage state vector, and extracting a power grid topological connection structure defining a physical connection relation at the current moment; S2, constructing a dynamic impedance coupling matrix based on the real-time voltage state vector and the power grid topological connection structure in a digital twin simulation environment, calculating a sensitivity coefficient for describing the electrical association strength between nodes by using a recursive least square algorithm, and updating the dynamic impedance coupling matrix reflecting a nonlinear mapping relation in real time by using the sensitivity coefficient; s3, generating a virtual load disturbance sequence obeying normal distribution, inputting the virtual load disturbance sequence into the dynamic impedance coupling matrix for iterative operation, simulating node voltage change trend under different load working conditions, and calculating a virtual voltage response track covering future time window information; And S4, calculating the Euclidean distance deviation between the virtual voltage response track and a preset ideal voltage standard curve, reversely solving a reactive compensation instruction for minimizing voltage fluctuation through a particle swarm optimization logic based on the Euclidean distance deviation, and transmitting the reactive compensation instruction to a flexible alternating current transmission device.
2. The digital twin based power voltage simulation and regulation method according to claim 1, wherein the step S1 is specifically: s11, acquiring an original voltage amplitude sequence and an original voltage phase sequence of a key node of a power grid in real time at a millisecond sampling frequency through the synchronous phasor measurement device, denoising original data by using a Kalman filtering algorithm, and generating a reference voltage amplitude and a reference voltage phase with high signal-to-noise ratio; S12, performing Hilbert transformation on the reference voltage amplitude and the reference voltage phase to construct an analytic signal, mapping the analytic signal to a complex domain Hilbert space, and establishing the real-time voltage state vector capable of representing the instantaneous electric characteristics of the whole network by combining the complex voltage signals of all nodes; and S13, reading switch state signals of all the circuit breakers and isolating switches in the power grid in real time, identifying electrical connectivity among all the nodes based on graph theory logic, constructing an adjacency matrix describing physical connection relations among the nodes, and defining the adjacency matrix as the power grid topological connection structure.
3. The digital twin based power voltage simulation and regulation method according to claim 1, wherein the step S2 is specifically: S21, acquiring a topological connection structure of the real-time voltage state vector and the power grid, initializing a jacobian matrix based on a physical circuit law, and taking an inverse matrix of the jacobian matrix as the dynamic impedance coupling matrix at the initial moment; s22, setting a forgetting factor and a covariance matrix initial value, taking the node voltage variation at the current moment as an output vector, taking the variation of node injection power as an input vector, and performing loop iteration calculation on the partial derivative of voltage to power variation by using a recursive least square algorithm to generate the sensitivity coefficient representing voltage fluctuation sensitivity; And S23, carrying out weighted correction on the impedance matrix element at the last moment by utilizing the newly generated sensitivity coefficient, and eliminating model distortion caused by linearization errors, thereby establishing the dynamic impedance coupling matrix capable of following the time-varying characteristic of the power grid operation condition in real time.
4. The digital twin based power voltage simulation and regulation method according to claim 1, wherein the step S3 is specifically: S31, setting a mean value and a standard deviation according to statistical characteristics of historical load data, generating a series of random power fluctuation values conforming to a normal distribution rule by adopting a Monte Carlo method, and combining the random power fluctuation values conforming to the normal distribution rule to form the virtual load disturbance sequence simulating future load uncertainty; S32, inputting the virtual load disturbance sequence into the dynamic impedance coupling matrix as excitation, deducing voltage response values of each node under different disturbance excitation through matrix multiplication operation, and generating a plurality of groups of voltage prediction time sequences according to time step sequence arrangement; and S33, carrying out weighted average processing on the multiple groups of voltage prediction time sequences to eliminate random error interference, extracting voltage change envelope curves of all nodes in a future preset time window, and constructing the virtual voltage response track containing time domain and space domain information.
5. The digital twin based power voltage simulation and regulation method according to claim 1, wherein the step S4 is specifically: s41, acquiring the virtual voltage response track and the ideal voltage standard curve, calculating the sum of squares of differences of the virtual voltage response track and the ideal voltage standard curve at each corresponding time point, and performing squaring operation to generate the Euclidean distance deviation capable of quantitatively evaluating the voltage deviation degree; S42, establishing a particle swarm search space containing reactive power output values, setting the Euclidean distance deviation as an optimization target of an fitness function, initializing a position vector and a speed vector of a particle swarm, and searching a global optimal position with minimum fitness function value through iterative updating; And S43, analyzing the reactive power value corresponding to the global optimal position, converting the reactive power value into a control code executable by equipment, and generating the reactive compensation instruction for driving the flexible alternating current transmission device to act.
6. The digital twin based power voltage simulation and adjustment method according to claim 3, wherein the calculation process of the sensitivity coefficient specifically comprises: The estimated parameter vector and the covariance matrix at the last moment are obtained, and the current gain matrix and the estimated parameter vector are updated and calculated by combining the current input vector by using the following formula: ; And ; Wherein, the Representative time of day Is used for the gain matrix of the (c), Representative time of day Is used for the co-variance matrix of (a), Representative time of day Is used to determine the vector of the input data, Representing a forgetting factor for adjusting the weight of the historical data, Representative time of day The sensitivity coefficient after the update is used, Representative time of day The system of (a) actually observes the output value.
7. The digital twinning-based power voltage simulation and adjustment method according to claim 5, wherein the process of iteratively updating the search for the global optimal position specifically comprises: Acquiring the current individual extremum of each particle and the global extremum of the whole population, and updating the speed vector and the position vector of the particle according to a preset inertia weight factor and a preset learning factor by using the following formula: ; And ; Wherein, the Represents the first The particles are at the first The velocity vector at the time of the iteration, Representing inertial weighting factors that maintain the inertia of the particle motion, And A learning factor representing the flight steps of the adjusting particles to the individual extremum and the global extremum, And Representing a random number ranging from 0 to 1, Represents the first The historic individual optimal positions of the individual particles, Representing the global optimal position of the population, Represents the first The particles are at the first Position vector at the time of iteration.
8. The digital twinning-based power voltage simulation and adjustment method according to claim 2, wherein the process of establishing the real-time voltage state vector specifically comprises: And acquiring analysis signal module values and phase angles of all the monitoring nodes, arranging analysis signals of all the nodes into a column vector form according to the node numbering sequence, expanding the column vector into a high-dimensional tensor structure by utilizing a Cronecker product, and embedding a time stamp mark into the tensor structure so as to establish the real-time voltage state vector with space-time correlation characteristics.
9. The digital twinning-based power voltage simulation and adjustment method according to claim 4, wherein the generating process of the virtual load disturbance sequence specifically comprises: And obtaining a typical daily load curve in a power grid historical operation database, fitting probability density function parameters of load fluctuation by using a maximum likelihood estimation method, constructing a Gaussian white noise generator based on a mean value and a variance parameter obtained by fitting, and generating random disturbance components superimposed on a reference load curve, thereby generating the virtual load disturbance sequence in a combined way.
10. A digital twin based power voltage simulation and regulation system for implementing the digital twin based power voltage simulation and regulation method of any one of claims 1-9, the system comprising: the data acquisition and topology reconstruction module is used for acquiring voltage amplitude and phase data through synchronous phasor measurement devices distributed on key nodes of the power grid, mapping the voltage amplitude and phase data to a Hilbert space, constructing a real-time voltage state vector, and extracting a power grid topology connection structure defining a physical connection relationship at the current moment; The dynamic impedance modeling and updating module is used for constructing the dynamic impedance coupling matrix based on the real-time voltage state vector and the power grid topological connection structure in a digital twin simulation environment, calculating a sensitivity coefficient for describing the electrical association strength between nodes by using a recursive least square algorithm, and updating the dynamic impedance coupling matrix reflecting the nonlinear mapping relation in real time by using the sensitivity coefficient; The virtual simulation and track prediction module is used for generating the virtual load disturbance sequence obeying normal distribution, inputting the virtual load disturbance sequence into the dynamic impedance coupling matrix for iterative operation, simulating the node voltage change trend under different load working conditions, and calculating a virtual voltage response track covering future time window information; and the optimization decision and instruction execution module is used for calculating the Euclidean distance deviation between the virtual voltage response track and a preset ideal voltage standard curve, solving a reactive compensation instruction for minimizing voltage fluctuation reversely through a particle swarm optimization logic based on the Euclidean distance deviation, and sending the reactive compensation instruction to the flexible alternating current transmission device.

Description

Digital twinning-based power voltage simulation and adjustment method and system Technical Field The invention relates to the technical field of digital twin simulation, in particular to a power voltage simulation and adjustment method and system based on digital twin. Background The technical field of digital twin simulation relates to mapping, predicting and optimizing the full life cycle of a physical entity by utilizing a high-fidelity digital model, and constructs a virtual space capable of reflecting the dynamic evolution rule of a physical object by fusing multi-physical-field data and real-time perception information, thereby realizing state monitoring and closed-loop control of a complex industrial system. The traditional digital twin-based power voltage simulation and adjustment method is mainly based on static network topology model built offline to perform power flow calculation, a fixed voltage deviation threshold is set as a basis for triggering adjustment, the nonlinear dynamic impedance change generated by random abrupt change of load of a power grid in actual operation is ignored by the operation mode based on idealized steady state assumption, so that the coupling relation between nodes cannot be perceived in real time when the power grid faces complex working conditions, the calculated adjustment strategy is prone to serious time lag and error accumulation, instantaneous fluctuation of voltage is difficult to accurately stabilize on a millisecond time scale, and linkage voltage out-of-limit faults are extremely easy to cause. Disclosure of Invention The invention aims to solve the defects in the prior art, and provides a digital twinning-based power voltage simulation and adjustment method and system. In order to achieve the above purpose, the invention adopts the following technical scheme that the power voltage simulation and adjustment method based on digital twin comprises the following steps: s1, acquiring voltage amplitude and phase data through synchronous phasor measurement devices distributed on key nodes of a power grid, mapping the voltage amplitude and phase data to a Hilbert space, constructing a real-time voltage state vector, and extracting a power grid topological connection structure defining a physical connection relation at the current moment; S2, constructing a dynamic impedance coupling matrix based on a real-time voltage state vector and a power grid topological connection structure in a digital twin simulation environment, calculating a sensitivity coefficient for describing the electrical correlation strength between nodes by using a recursive least square algorithm, and updating the dynamic impedance coupling matrix reflecting the nonlinear mapping relation in real time by using the sensitivity coefficient; s3, generating a virtual load disturbance sequence obeying normal distribution, inputting the virtual load disturbance sequence into a dynamic impedance coupling matrix for iterative operation, simulating node voltage change trend under different load working conditions, and calculating a virtual voltage response track covering future time window information; And S4, calculating Euclidean distance deviation between the virtual voltage response track and a preset ideal voltage standard curve, reversely solving a reactive compensation instruction for minimizing voltage fluctuation through particle swarm optimization logic based on the Euclidean distance deviation, and transmitting the reactive compensation instruction to the flexible alternating current transmission device. As a further scheme of the invention, the step S1 specifically comprises the following steps: S11, acquiring an original voltage amplitude sequence and an original voltage phase sequence of a key node of a power grid in real time at a millisecond sampling frequency through a synchronous phasor measurement device, denoising original data by using a Kalman filtering algorithm, and generating a reference voltage amplitude and a reference voltage phase with high signal-to-noise ratio; S12, performing Hilbert transformation on the reference voltage amplitude and the reference voltage phase to construct an analytic signal, mapping the analytic signal to a complex domain Hilbert space, and establishing a real-time voltage state vector capable of representing the instantaneous electric characteristics of the whole network by combining the complex voltage signals of all nodes; and S13, reading switch state signals of all the circuit breakers and isolating switches in the power grid in real time, identifying electrical connectivity among all the nodes based on graph theory logic, constructing an adjacency matrix describing physical connection relations among the nodes, and defining the adjacency matrix as a power grid topological connection structure. As a further scheme of the invention, the step of S2 is specifically as follows: S21, acquiring a real-time voltage state vector and a power grid topologi