Anti-misoperation method based on digital twinning of space-time state chain

Abstract

The application discloses a misoperation prevention method based on digital twinning of space-time state chain, and relates to the technical field of intelligent management and control, comprising the following steps: constructing a digital twin of a power system and synchronizing the state of a physical device in real time; based on the synchronized virtual device state, constructing a dynamic space-time state chain, which is a chained data structure that sequentially connects key state nodes of a system and adds state change trend information to each key state node, used to continuously depict the space-time evolution of the state of the power system; mapping a to-be-executed operation instruction into a disturbance to the space-time state chain to generate a post-disturbance state chain; and determining the compliance of the to-be-executed operation instruction based on the post-disturbance state chain. The application realizes dynamic depiction of the state of a power grid device and forward reasoning of operation consequences, solves the technical problems of lagging judgment and strong locality of traditional misoperation prevention methods in dynamic scenarios, and significantly improves the reliability of operation safety management and control of new power systems.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent management and control, more specifically, the present application relates to a method for preventing misoperation based on digital twinning of space-time state chain. BACKGROUND

[0002] In the process of power system operation and dispatch, preventing misoperation is an important link to ensure the safety of power grid, equipment and personal safety. With the continuous complication of power grid structure and the continuous improvement of operation automation level, the logical association, spatial coupling and operation chain between devices are becoming more and more complex, and the traditional misoperation prevention system relying on static rule table or fixed locking logic has been difficult to meet the requirements of real-time, accuracy and dynamic adaptability of modern power grid. At present, some substations and dispatching control systems have begun to introduce digital twinning technology to build a virtual-real mapping operation environment, realize the visualization monitoring and auxiliary decision of device state and operation process.

[0003] However, the misoperation prevention logic of the existing misoperation prevention method is still based on static topology and pre-set rules, which lacks the description of the continuous evolution relationship of the state of power grid equipment in the time and space dimensions, and it is difficult to accurately judge the legality of the operation in the dynamic running scene. At the same time, there is a lack of deep linkage mechanism between the misoperation prevention system and the digital twinning model, which cannot pre-check and path verify the operation instruction through virtual-real collaborative mode, resulting in the problems of lag and locality in misoperation prevention, which is difficult to meet the demand of high credible operation safety management and control of new power system. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a misoperation prevention method based on digital twinning of space-time state chain, which maps the operation instruction into state chain disturbance and generates the disturbed state chain by constructing dynamic space-time state chain, and judges the operation compliance accordingly, solving the problems of lag and locality caused by the traditional misoperation prevention system relying on static rules.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0006] The misoperation prevention method based on digital twinning of space-time state chain comprises the following steps: constructing a digital twin of power system and synchronizing the state of physical device in real time; based on the synchronized virtual device state, constructing a dynamic space-time state chain, the space-time state chain is a chained data structure which connects the key state nodes of the system in time sequence and adds state change trend information to each key state node, used to continuously describe the space-time evolution of power system state; mapping the to-be-executed operation instruction into the disturbance of the space-time state chain to generate the disturbed state chain; based on the disturbed state chain, judging the compliance of the to-be-executed operation instruction.

[0007] In a preferred embodiment, the real-time synchronization of the physical device state is specifically: constructing a state observation vector based on multiple source state quantities, and performing time series and spatial registration to generate a state projection vector consistent with the coordinate system of the digital twin model; calculating the projection residual between the state projection vector and the pre-acquired virtual device state vector; constructing a correction function to dynamically correct the projection residual to obtain a consistent solution of the virtual and real states; updating the virtual device state in the digital twin model according to the consistent solution to complete the synchronization of the virtual and real states.

[0008] In a preferred embodiment, the construction of the correction function is specifically: calculating the fluctuation covariance matrix of each state quantity at different time scales based on the historical virtual and real state deviation sequence; establishing a dynamic correction function composed of a time drift term and a topological correlation term as a constraint based on the fluctuation covariance matrix, wherein the time drift term is used to correct the phase deviation caused by sampling delay, and the topological correlation term is used to constrain the state consistency between adjacent electrical devices; in each synchronization period, the weight coefficient of the correction function is dynamically adjusted to achieve an optimal balance between the virtual and real deviation convergence rate and the state smoothness.

[0009] In a preferred embodiment, the construction of the dynamic space-time state chain is specifically: based on the digital twin state after virtual and real synchronization, calculating the comprehensive deviation index of the state from the stable operation reference state; when the change rate of the comprehensive deviation index exceeds the trigger threshold dynamically calculated based on historical data, defining the current system state as a key state node; based on all key state nodes, optimizing a virtual evolution path in the state space that connects the key state nodes and has the most smooth overall state potential energy change; connecting the key state nodes on the virtual evolution path, and attaching state change trend information of each key state node on the path to form a dynamic space-time state chain.

[0010] In a preferred embodiment, the optimization of a virtual evolution path in the state space that connects the key state nodes and has the most smooth overall state potential energy change is specifically: taking the key state nodes as boundary conditions of the path, solving a trajectory in the state space that satisfies the power system dynamic equation constraint and has the minimum system state potential energy functional integral, and taking the trajectory as the virtual evolution path.

[0011] In a preferred embodiment, the solving of a trajectory that satisfies the power system dynamic equation constraint and has the minimum system state potential energy functional integral includes: constructing an association matrix with the key state nodes as vertices and the state potential energy difference and time interval between nodes as weights; based on the association matrix, establishing an optimization problem with the minimum system state potential energy functional integral as the objective; solving the optimization problem under the condition of satisfying the power system dynamic equation constraint to obtain the virtual evolution path.

[0012] In a preferred embodiment, the mapping of the to-be-executed operation instruction to the perturbation of the space-time state chain generates a post-perturbation state chain, specifically: the to-be-executed operation instruction is mapped to a directional state perturbation acting on the target node in the space-time state chain; based on the state evolution trend information of each node in the space-time state chain, the space-time propagation path of the directional state perturbation is deduced to obtain a perturbation space-time distribution; the perturbation space-time distribution is superimposed with the steady-state field of the current space-time state chain to construct a synthetic state field after perturbation; based on the energy distribution of the synthetic state field and the state continuity constraint, the post-perturbation state chain is reconstructed and output.

[0013] In a preferred embodiment, the reconstruction and output of the post-perturbation state chain are specifically: the potential energy gradient of the synthetic state field is calculated, and searching is performed along the direction of the potential energy gradient to generate a main evolution path and an alternative path; the state variables of the main evolution path and the alternative path are subjected to continuity checking, and the paths with mutations or oscillations are removed; the potential energy curvature is calculated on the paths that pass the checking, and the nodes with negative curvature are marked as high-risk nodes; the main evolution path is taken as a skeleton, the high-risk node information is embedded, and the post-perturbation state chain is packaged and output.

[0014] In a preferred embodiment, the judgment of the compliance of the to-be-executed operation instruction based on the post-perturbation state chain is specifically: whether the main evolution path of the post-perturbation state chain has a structural variation due to the perturbation of the operation instruction is checked; the structural variation includes the appearance of a new high-risk node, irreversible deviation of the original state evolution trend, or degradation of the potential energy convergence characteristics of the state chain; whether the operation instruction is compliant is determined according to whether the structural variation occurs.

[0015] The system of the anti-misoperation method based on digital twinning of a space-time state chain includes: a digital twinning synchronization module for constructing a digital twin of a power system and synchronizing the state of a physical device in real time; a space-time state chain module for constructing a dynamic space-time state chain based on the synchronized virtual device state; a perturbation deduction module for mapping a to-be-executed operation instruction to a perturbation of the space-time state chain to generate a post-perturbation state chain; and a compliance judgment module for judging the compliance of the to-be-executed operation instruction based on the post-perturbation state chain.

[0016] The application can analyze and evaluate the potential influence of the operation on the overall operation of the system in real time before the operation is executed, realize the pre-judgment of the operation legality, accurately identify the operation instructions that may cause system instability or safety conflicts, and effectively reduce the probability of misoperation, thereby significantly improving the real-time performance and accuracy of the misoperation prevention of the power system. At the same time, by mapping the to-be-executed operation to the time-space state chain and generating a disturbed state chain, the application can analyze the device state changes, system dynamic fluctuations and potential risk areas caused by the operation, realize virtual-real collaborative protection across devices and time dimensions, and adaptively evaluate the influence of the operation on the system safety in the dynamic operation scene of the power grid, provide global and continuous safety judgment ability, and thus ensure that the power system can still maintain a high-trust and high-reliable operation safety control level under complex operation conditions. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 FIG. 1 is a flowchart of the misoperation prevention method based on the digital twin of the time-space state chain of the application;

[0018] Figure 2 FIG. 1 is a flowchart of the misoperation prevention method based on the digital twin of the time-space state chain of the application;

[0019] Figure 3 FIG. 1 is a flowchart of the misoperation prevention method based on the digital twin of the time-space state chain of the application; DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0021] Embodiment 1, Figure 1 The misoperation prevention method based on the digital twin of the time-space state chain of the application is given, including the following steps:

[0022] S1, constructing a digital twin of a power system and synchronizing a physical device state in real time;

[0023] In this embodiment, the real-time synchronization of the physical device state is specifically:

[0024] First, select key equipment from the anti-misoperation control area: circuit breaker, disconnecting switch, bus, current transformer, transformer, etc. Assign a unique identifier to each device , establish a virtual device state vector for each device , and initialize it through historical monitoring data and device rated parameters. Build a matrix according to the electrical connection relationship between devices , where:

[0025]

[0026] Construct the device state evolution equation, which is:

[0027]

[0028] where, , indicates the dispatching command, load fluctuation, environmental disturbance, The parameters are obtained by fitting and inverse solving the historical data to ensure the nonlinear and time-varying characteristics.

[0029] Based on the multi-source state quantity (including voltage, current, temperature, vibration, switch position signal, etc.) from the monitoring end, construct the state observation vector , and perform time series and spatial registration to generate the state projection vector consistent with the coordinate system of the digital twin model , calculate the projection residual between the state projection vector and the pre-acquired virtual device state vector , which is:

[0030]

[0031] where, indicates the difference between the state projection vector and the virtual device state vector at time .

[0032] The virtual device state vector is used to represent the running state of the i-th device in the digital twin at time t.

[0033] The construction of the correction function is as follows:

[0034] Save the projection residual of the previous time steps in chronological order, i.e. form the historical virtual-real state deviation sequence , which is used to describe the evolution of the deviation between the virtual device state and the physical device observation state in the digital twin in the past several time steps, which is:

[0035]

[0036] Based on historical virtual and real state deviation sequence Multi-scale statistical methods are used to calculate device i at different time scales. The fluctuation covariance matrix under the given conditions, specifically, for each scale ( First, the historical virtual-real state deviation sequence is aggregated by window using the sliding window weighted average method, specifically:

[0037]

[0038] in, For device i in time scale Below, the aggregated projection residual of the k-th window, This indicates that the summation is performed on all sample points within the window. For window weight function, This represents the projected residual of device i at time (k+u). Index of the window's starting position. This represents the number of samples obtainable through the sliding window.

[0039] By aggregating the historical virtual-real state deviation sequences by window, an aggregated sequence is obtained. Calculate the mean of the aggregated sequence:

[0040]

[0041] The fluctuation covariance matrix The calculation method is as follows:

[0042]

[0043] To enhance numerical stability and invertibility, the fluctuation covariance matrix is ​​adjusted. By applying shrinkage regularization, the final fluctuation covariance matrix is ​​obtained. :

[0044]

[0045] in, Time scale The coefficient of contraction (scalar) under the given conditions. , representing the strength of the contraction towards the target matrix. To shrink the target matrix, a simple structure is usually chosen to ensure robustness, such as a diagonal matrix (each element being the variance of the corresponding variable) or an identity matrix multiplied by the average variance.

[0046] A dynamic correction function composed of a time drift term and a topology correlation term is established with the wave covariance matrix as a constraint, specifically as follows:

[0047]

[0048] wherein, is a dynamic correction function value of the i-th device at time t, is a projection residual of the i-th device at time t, is a time drift weight coefficient of the i-th device at time t, is a time drift term of the i-th device at time t, is a topology constraint weight coefficient of the i-th device at time t, is a topology coupling coefficient of the device i and the device j at time t, is a neighborhood set of the device i, and respectively represent a virtual device state vector of the i-th device and a virtual device state vector of the j-th device at time t.

[0049] wherein, the time drift term is used to correct the phase deviation caused by sampling delay, and the topology correlation term is used to constrain the state consistency between electrically adjacent devices;

[0050] In each synchronization cycle, the time drift weight coefficient and the topology constraint weight coefficient are dynamically adjusted according to the virtual-real state deviation convergence rate and the state smoothness, specifically, if the deviation converges too slowly, the may be appropriately increased to speed up the drift correction; if the state changes too much oscillation, the may be appropriately increased to enhance the topology constraint, so as to achieve an optimal balance between the convergence rate and the state smoothness.

[0051] The dynamic correction function is applied to the current projection residual to obtain a constrained consistent virtual device state correction, to obtain a constrained consistent solution of the virtual-real state, to update the virtual device state in the digital twin model according to the constrained consistent solution, and to complete the virtual-real state synchronization.

[0052] The virtual-real state synchronization method of the application realizes a technical leap from traditional open-loop writing to closed-loop adaptive calibration through the dynamic correction function and the multi-source data registration mechanism, effectively solves the model distortion problem caused by the space-time inconsistency of data; by fusing the two-dimensional information of time drift correction and topology correlation constraint, the timing accuracy is ensured while the system fault tolerance is enhanced, so that the digital twin can automatically adapt to the dynamic operation condition of the power grid, and an optimal balance is achieved between the virtual-real deviation convergence rate and the state smoothness, thereby providing a high-fidelity and strong-robustness data basis for subsequent false judgment prevention.

[0053] S2, based on the synchronized virtual device state, constructs a dynamic spatiotemporal state chain;

[0054] In this embodiment, the construction of the dynamic spatiotemporal state chain specifically refers to:

[0055] Based on the state of the digital twin after virtual-real synchronization, the system state at the current moment is obtained. Calculate its relationship with the stable operating reference state. Comprehensive deviation index :

[0056]

[0057] When the rate of change of the comprehensive deviation index exceeds the trigger threshold dynamically calculated based on historical data, the current system state is defined as a critical state node. Based on all critical state nodes, an association matrix is ​​constructed with the critical state nodes as vertices and weighted by the state potential difference and time interval between nodes:

[0058]

[0059] in, Let be the potential energy difference between nodes i and j. For time intervals, This is the time weighting coefficient.

[0060] Based on the aforementioned correlation matrix, an optimization problem is established with the objective of minimizing the functional integral of the system state potential energy. This optimization problem is then solved while satisfying the constraints of the power system dynamic equations.

[0061]

[0062] in, The system state potential energy functional is represented by the following: These are candidate trajectories.

[0063] Solving the above problem to obtain the path with the smoothest potential energy change is the virtual evolution path. .

[0064] Virtual evolution path The key state nodes are connected in series, and information on the state change trend of each key state node along the path is attached to form a dynamic spatiotemporal state chain.

[0065] This invention's method for constructing a spatiotemporal state chain achieves a technological breakthrough in extracting continuous evolutionary patterns from discrete state records through a dynamic triggering mechanism and physical constraint path optimization. Specifically, it employs a trigger threshold dynamically calculated based on historical data to intelligently capture key state nodes, effectively overcoming the shortcomings of traditional fixed-period sampling, such as insensitivity to capturing rapid transient processes or redundancy in recording steady-state processes. By solving for the minimum action path that satisfies the constraints of the power system's dynamic equations, the principle of minimum energy in physics is introduced into the state chain construction, ensuring that the generated virtual evolutionary path is not only mathematically smooth but also conforms to the actual physical laws of the power grid. This constructs a spatiotemporal state chain that truly reflects the system's inherent evolutionary trend, providing a physically reliable dynamic model foundation for accurately predicting operational consequences.

[0066] S3, map the operation instruction to be executed as a perturbation of the spatiotemporal state chain, and generate a perturbed state chain;

[0067] In this embodiment, the step of mapping the operation instruction to be executed as a perturbation to the spatiotemporal state chain to generate a perturbed state chain specifically involves:

[0068] Operation instructions to be executed The mapping is a directional state perturbation acting on the target node in the spatiotemporal state chain, specifically:

[0069]

[0070] in, Indicates that the action is applied to the target node. The state disturbance quantity. The sensitivity matrix is ​​obtained from historical control response data or a power flow linearization model. The characteristic vector representing the operation command (such as the change in control variable, voltage setpoint offset, etc.).

[0071] After the disturbance, the local state of the system changes as follows:

[0072]

[0073] To characterize the propagation effect of this local disturbance along the spatiotemporal state chain, a disturbance propagation equation is defined based on the state evolution trend information of each node in the spatiotemporal state chain, and the spatiotemporal propagation path of the directional state disturbance is deduced:

[0074]

[0075]

[0076] in, Let i be the state response propagation matrix from node i to node i+1. is a local damping matrix, reflecting the decay ability of the system to the disturbance, is an interval of time between nodes, represents the change of the disturbance after the transmission at the space-time node i+1.

[0077] After the propagation of the space-time state chain, the space-time distribution of the disturbance is obtained.

[0078] The space-time distribution of the disturbance is superimposed on the steady-state field of the current space-time state chain to construct a synthetic state field after the disturbance, and the potential energy distribution of the synthetic state field is further calculated. According to the potential energy distribution of the synthetic state field, search along the direction of potential energy gradient descent, and generate the main evolution path and several alternative paths through gradient descent iteration. In order to ensure the continuity of the state chain, the smoothness of the state variable of all paths is checked. If the change rate difference of adjacent nodes is greater than the state continuity threshold, the path is removed. The state continuity threshold is determined according to the experience of system dynamic characteristics. The potential energy curvature is calculated on the path that passes the check, and the node with negative potential energy curvature is marked as a high-risk node. The high-risk node represents that there is an unstable trend of potential energy or a reversal of evolution direction. Take the main evolution path as the skeleton, embed the high-risk node information, and package the output state chain after the disturbance.

[0079] The present application realizes the transformation of operation consequence prediction from single path simulation to multi-dimensional risk situation assessment by introducing state field disturbance mapping and potential energy topology analysis mechanism. Specifically, the operation instruction is mapped to a directional state disturbance and its propagation is deduced in the space-time state chain, which realizes the accurate simulation of the operation chain effect; by superimposing the disturbance field and the steady-state field to construct the synthetic state field, and reconstructing the state chain under the energy distribution and continuity constraint, it is ensured that the prediction result not only conforms to the physical law but also contains complete space-time information; especially through the potential energy gradient tracking and curvature analysis, the potential instability risk area can be automatically identified, and the final state chain after the disturbance not only contains the most possible evolution path, but also integrates multi-level risk information, thereby providing a panoramic decision basis with prediction accuracy and risk assessment depth for operation compliance judgment.

[0080] S4, based on the state chain after the disturbance, judging the compliance of the operation instruction to be executed.

[0081] In this embodiment, based on the state chain after the disturbance, the compliance of the operation instruction to be executed is judged, specifically:

[0082] Check whether the main evolution path of the state chain after the disturbance has structural variation due to the disturbance of the operation instruction, the structural variation includes the appearance of a new high-risk node, the irreversible deviation of the original state evolution trend, or the degradation of the potential energy convergence characteristics of the state chain. If any of the above three conditions occurs, it is preliminarily determined that the operation instruction may cause non-steady-state evolution or misoperation risk.

[0083] To avoid misjudgment and ambiguous boundaries, a risk judgment function is further defined based on the evolution data of the state chain after disturbance:

[0084]

[0085] wherein, is the risk function value, is the potential energy stability weight coefficient, is the state consistency weight coefficient, is the potential energy curvature, is the state evolution trend vector before disturbance, is the state evolution trend vector after disturbance, , are the start and end time of the space-time state chain respectively.

[0086] A risk threshold is constructed based on historical safety samples, if the risk function value is less than the risk threshold, it is determined that the operation instruction is compliant, if the risk function value is greater than the risk threshold, it is determined that the operation instruction is not compliant.

[0087] The present application realizes the conversion of the anti-misjudgment from the parameter overrun check to the system dynamic characteristic evaluation through the structural variation detection mechanism. Unlike the traditional method which only focuses on whether a single parameter exceeds a static threshold, the present application can identify the potential risk of the operation from the system evolution mechanism level by comprehensively analyzing three types of structural variation characteristics, i.e. whether a new high-risk node is introduced after disturbance, whether the trend is irreversibly deviated, and whether the potential energy convergence characteristics are degraded. This judgment method based on system dynamic characteristics can not only find the immediate explicit risk, but also can early warn the potential and gradual safety degradation process, so as to realize the deep intelligent evaluation of the operation compliance, and greatly improve the foresight and reliability of the power grid safety protection.

[0088] Embodiment 2, Figure 2 The present application gives a system of the anti-misoperation method of digital twin based on space-time state chain of the present application, comprising:

[0089] A digital twin synchronization module is used to construct the digital twin of the power system, and to synchronize the physical device state in real time;

[0090] A space-time state chain module is used to construct a dynamic space-time state chain based on the synchronized virtual device state, the space-time state chain is a chained data structure which sequentially connects the system key state nodes in time and attaches state change trend information to each key state node, and is used to continuously depict the space-time evolution of the power system state;

[0091] A disturbance deduction module is used to map the to-be-executed operation instruction into a disturbance to the space-time state chain, and to generate a state chain after disturbance;

[0092] A compliance determination module is configured to determine compliance of the operation instruction to be executed based on the perturbed state chain.

[0093] The above formulas are all dimensionless values calculated, and the formulas are obtained by collecting a large amount of data to simulate a formula of the most recent real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0094] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product.

[0095] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0096] In addition, each functional module in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0097] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0098] Finally: the above is only the preferred embodiment of the present application, and is not used to limit the present application, any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for preventing misoperation based on digital twinning of spatiotemporal state chains, characterized in that, The method comprises the following steps: constructing a digital twin of the power system and synchronizing the physical device states in real time; based on the synchronized virtual device states, constructing a dynamic space-time state chain, specifically: calculating a comprehensive deviation index of the virtual device states and the stable operation benchmark state, when the change rate of the index exceeds a trigger threshold dynamically calculated based on historical data, defining the current system state as a key state node; based on all key state nodes, taking the key state nodes as boundary conditions of the path, solving a trajectory in the state space that meets the power system dynamic equation constraint and has the minimum system state potential functional integral, taking the trajectory as a virtual evolution path; concatenating the key state nodes on the virtual evolution path and adding state change trend information of each key state node on the path to form a dynamic space-time state chain; the solving of the trajectory comprises: constructing a correlation matrix with the key state nodes as vertices and the state potential difference and time interval between the nodes as weights; based on the correlation matrix, establishing an optimization problem with the minimum system state potential functional integral as the target; solving the optimization problem under the condition of meeting the power system dynamic equation constraint to obtain the virtual evolution path; mapping the to-be-executed operation instruction to a disturbance to the space-time state chain to generate a post-disturbance state chain; based on the post-disturbance state chain, determining the compliance of the to-be-executed operation instruction.

2. The anti-misoperation method based on spatiotemporal state chain digital twinning according to claim 1, characterized in that, The real-time synchronization of the physical device states specifically comprises: constructing a state observation vector based on multiple source state quantities and performing time series and spatial registration to generate a state projection vector consistent with the coordinate system of the digital twin model; calculating the projection residual between the state projection vector and a pre-acquired virtual device state vector; constructing a correction function to dynamically correct the projection residual to obtain a constraint consistent solution of the virtual and real states; updating the virtual device state in the digital twin model according to the constraint consistent solution to complete the synchronization of the virtual and real states.

3. The anti-misoperation method based on spatiotemporal state chain digital twinning according to claim 2, characterized in that, The construction of the correction function specifically comprises: based on a historical virtual and real state deviation sequence, calculating the fluctuation covariance matrix of each state quantity at different time scales; establishing a dynamic correction function composed of a time drift term and a topological correlation term as a constraint, wherein the time drift term is used to correct the phase deviation caused by sampling delay, and the topological correlation term is used to constrain the state consistency between electrically adjacent devices; in each synchronization period, dynamically adjusting the weight coefficient of the correction function to achieve an optimal balance between the virtual and real deviation convergence rate and the state smoothness.

4. The anti-misoperation method based on the digital twinning of the space-time state chain according to claim 3, characterized in that, The mapping of the to-be-executed operation instruction to a disturbance to the space-time state chain to generate a post-disturbance state chain specifically comprises: mapping the to-be-executed operation instruction to a directional state disturbance acting on a target node in the space-time state chain; based on the state evolution trend information of each node in the space-time state chain, deducing the space-time propagation path of the directional state disturbance to obtain a disturbance space-time distribution; superimposing the disturbance space-time distribution and the steady state field of the current space-time state chain to construct a synthesized state field after disturbance; based on the energy distribution and state continuity constraint of the synthesized state field, reconstructing and outputting the post-disturbance state chain.

5. The anti-misoperation method based on spatiotemporal state chain digital twinning according to claim 4, characterized in that, The reconstruction and output of the post-disturbance state chain specifically comprise: The potential energy gradient of the synthetic state field is calculated, a search is performed in the direction of the potential energy gradient, a main evolution path and an alternative path are generated; The state variables of the main evolution path and the alternative path are continuously checked, and the paths with mutations or oscillations are removed; The potential energy curvature of the paths passing the check is calculated, and the nodes with negative curvature are marked as high-risk nodes; The main evolution path is taken as a skeleton, high-risk node information is embedded, and an output post-disturbance state chain is packaged.

6. The anti-misoperation method based on spatiotemporal state chain digital twinning according to claim 5, characterized in that, Based on the post-disturbance state chain, the compliance of the operation instruction to be executed is determined, specifically: Check whether the main evolution path of the post-disturbance state chain has structural variation due to the disturbance of the operation instruction; The structural variation includes the appearance of a new high-risk node, irreversible deviation of the original state evolution trend, or degradation of the potential energy convergence characteristics of the state chain; According to whether the structural variation is generated, it is determined whether the operation instruction is compliant.

7. A system for a misoperation prevention method using a spatiotemporal state chain-based digital twin according to any one of claims 1 to 6, characterized in that, It includes: A digital twin synchronization module for constructing a digital twin of a power system and synchronizing the state of a physical device in real time; A space-time state chain module for constructing a dynamic space-time state chain based on the synchronized virtual device state, the space-time state chain being a chained data structure sequentially connecting system key state nodes in time and attaching state change trend information to each key state node, for continuously depicting the space-time evolution of the power system state; A disturbance reasoning module for mapping the operation instruction to be executed to a disturbance to the space-time state chain, generating a post-disturbance state chain; A compliance determination module for determining the compliance of the operation instruction to be executed based on the post-disturbance state chain.

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